Its a stormy holiday weekend, and youve just received the last notification you want in the busiest travel week of the year: The first leg of your flight is significantly delayed. You might expect this means youll be sitting on hold with airline customer service for half an hour. But this time, the process looks a little different: You have a brief text exchange with the airlines AI chatbot, which quickly assesses your situation and places you in a priority queue. Shortly after, a human agent takes over, confirms the details, and gets you rebooked on an earlier flight so you can make your connection. Youll be home in time to enjoy moms pot roast. DOWNLOAD THE REPORT Generative AI is becoming a key component of business operations and customer service interactions today. According to Salesforce research, three out of five workers (61%) either currently use or plan to use generative AI in their roles. A full 68% of these employees are confident that the technologywhich can churn out text, video, image, and audio content almost instantaneouslywill enable them to provide more enriching customer experiences. But the technology isnt a complete solutionor a replacement for human workers. Sixty percent of the surveyed employees believe that human oversight is indispensable for effective and trustworthy generative AI. Generative AI enables people and increases efficiencies in business operations, but using it to empower employees will make all the difference. Its full business value will only be achieved when it is used thoughtfully to blend with human empathy, ingenuity, and emotional intelligence. Generative AI pilots across industries Though the technology is still nascent, many generative AI use cases are starting to emerge. In sales and marketing, generative AI can assist with creating targeted ad content, identifying leads, upselling, cross-selling, and providing real-time sales analytics. When used for internal functions like IT, HR, and finance, generative AI can improve help-desk services, simplify recruitment processes, generate job descriptions, assist with onboarding and exit processes, and even write code. Download the full report. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Reviews editorial staff.

A live agent spends hours each week manually documenting routine interactions. Another combs through multiple knowledge bases to find the right solution, scrambling to piece it together while the customer waits on hold. A third types out the same response theyve written dozens of times before. These repetitive tasks can be draining, leaving less time for meaningful customer interactionsbut generative AI is changing this reality. By automating routine workflows, AI augments the efforts of live agents, freeing them to do what they do best: solving complex problems and applying human understanding and empathy to help customers during critical situations. DOWNLOAD THE REPORT Enterprises are trying to rush to figure out how to implement or incorporate generative AI into their business to gain efficiencies, says Will Fritcher, deputy chief client officer at TP. But instead of viewing AI as a way to reduce expenses, they should really be looking at it through the lens of enhancing the customer experience and driving value. Doing this requires solving two intertwined challenges: empowering live agents by automating routine tasks and ensuring AI outputs remain accurate, reliable, and precise. And the key to both these goals? Striking the right balance between technological innovation and human judgment. A key role in customer support Generative AIs potential impact on customer support is twofold: Customers stand to benefit from faster, more consistent service for simple requests, while also receiving undivided human attention for complex, emotionally charged situations. For employees, eliminating repetitive tasks boosts job satisfaction and reduces burnout.The tech can also be used to streamline customer support workflows and enhance service quality in various ways, including:Automated routine inquiries: AI systems handle straightforward customer requests, like resetting passwords or checking account balances. Real-time assistance: During interactions, AI pulls up contextually relevant resources, suggests responses, and guides live agents to solutions faster. Fritcher notes that TP is relying on many of these capabilities in its customer support solutions. For instance, AI-powered coaching marries AI-driven metrics with human expertise to provide feedback on 100% of customer interactions, rather than the traditional 2% to 4% that was monitored pre-generative AI.Call summaries: By automatically documenting customer interactions, AI saves live agents valuable time that can be reinvested in customer care. Download the full report. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Reviews editorial staff.

David Dewan came up with this solution (which Richard Lipesalso found on Wikipedia): Let N be any integer not divisible by 2 or 5. Consider repunits R1 = 1, R2 = 11, R3 = 111, , RN+1 and their residues modulo N. There are at most N different residues, so the set of N+1 residues modulo N must contain at least one repeat. Assume RA mod N and RB mod N with B>A are the same. Then (RB RA) mod N = (RB-A10A) mod N = 0. Since N and 10 are relatively prime, N divides RB-A. S/O4. Frank offers this sudoku problem: Many readers tackled it successfully. For anyone who got stuck, heres the answer key: Ten years ago I was doing what is now called AI, Richard Marks 58 writes. He noted that trying all possible iterations of a sudoku problem will tie up your Cray for a week. So I personally wrote the rules and coded this little AI program that solves any sudoko by the time you have released the Solve It button. Since I wrote the program from scratch, I guess you can say I solved S/O4. S/O6. On behalf of the MIT Chess Club, Justin Zhou 25 asked how White can play and mate in two (see below). Frank Model 63 says there are two cases to consider: when Black can castle, and when Black cannot. If Black can castle, then Blacks last move had to be Pc7-c5. In this case White can take en passant, Pb5-c6. If Black castles, then White plays Pb7#. If Black can castle, but makes some other move, then White plays Rf8#. If Black cannot castle, then White plays Ke6. Black cannot escape mate on the next move when White plays Rf8#. Steve Gordon noted that this problem illustrates the three special chess moves. The following was adapted from his analysis with his algebraic chess notation. Black last moved either a king, rook, or c5. If c5, then 1. bxc6 (en passant a.k.a e. p.). If Black can still castle queenside (1. Kc8 & Rd8, a.k.a O-O-O), then 2. b7#. If Black cannot, its king is still trapped on rank 8, so after any black move, 2. Rf8#. If Black last moved a king or rook, en passant is not possible for White, but Black cant castle either, so 1. Ke6 also traps the black king on rank 8, and after any Black move, 2. Rf8#. Note: To create this puzzle, the white bishop on g7 resulted from an underpromotion on h8.

Ready for a fresh set of puzzles? Click here for the January/February Puzzle Corner, brought to you with a special Mystery Hunt twist by guest editor Dan Katz 03.This column includes solutions to three September/October 24 problems. Find solutions to the other three problems here.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. The next generation of neural networks could live in hardware Networks programmed directly into computer chip hardware can identify images faster, and use much less energy, than the traditional neural networks that underpin most modern AI systems. Thats according to work presented at a leading machine learning conference in Vancouver last week. Neural networks, from GPT-4 to Stable Diffusion, are built by wiring together perceptrons, which are highly simplified simulations of the neurons in our brains. In very large numbers, perceptrons are powerful, but they also consume enormous volumes of energy. Part of the trouble is that perceptrons are just software abstractionsrunning a perceptron network on a GPU requires translating that network into the language of hardware, which takes time and energy. Building a network directly from hardware components does away with a lot of those costs. And one day, they could even be built directly into chips used in smartphones and other devices. Read the full story. Grace Huckins Drugs like Ozempic now make up 5% of prescriptions in the US Whats new? US doctors write billions of prescriptions each year. During 2024, though, one type of drug stood outwonder drugs known as GLP-1 agonists. As of September, one of every 20 prescriptions written for adults was for one of these drugs, according to the health data company Truveta. The big picture: According to the data, people who get prescriptions for these drugs are younger, whiter, and more likely to be female. In fact, women are twice as likely as men to get a prescription. Yet not everyone whos prescribed the drugs ends up taking them. In fact, half the new prescriptions for obesity are going unfilled. Read the full story. Antonio Regalado Why childhood vaccines are a public health success story Childhood vaccination is a success story. In the 50 years since the World Health Organization launched its ambitious global childhood vaccination program, vaccines are estimated to have averted 154 million deaths. That number includes 146 million children under the age of five. But concerns around vaccines endure. Especially, it seems, among the individuals Donald Trump has picked as his choices to lead US health agencies from January. So lets take a look at their claims, and where the evidence really stands on childhood vaccines. Read the full story. Jessica Hamzelou This story is from The Checkup, our weekly health and biotech newsletter. Sign up to receive it in your inbox every Thursday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Elon Musk is the shadow president of the United States The billionaire pressured Republicans into impeding a spending bill, despite lacking an official government role. (WP $)+ He posted about the bill more than 100 times on Wednesday alone (NBC News)+ but those posts were generally misleading or outright false. (Rolling Stone $)+ Lawmakers arent thrilled about Musks interference. (NYT $)2 Amazon workers are striking during the Christmas rush The walkouts could delay the delivery of parcels across the US. (WSJ $)+ Amazon is refusing to recognize the workers labor union. (WP $)3 The US is growing increasingly wary of Nvidias overseas sales spree Officials worry the chipmakers deals could end up empowering its adversaries. (NYT $)+ US-based venture firms have pledged to avoid taking funding from China. (WP $)+ Custom chipmaker Broadcoms stock is surging right now. (Insider $)4 Dozens of families are suing Snap over teen overdoses They allege Snapchat helped dealers to sell deadly counterfeit drugs to their children. (Bloomberg $)5 Ukraines drone footage will be used to train AI models The country has collected 228 years worth of data during its conflict with Russia. (Reuters)+ An overnight drone attack set fire to a refinery in south Russia. (Bloomberg $)+ Meet the radio-obsessed civilian shaping Ukraines drone defense. (MIT Technology Review)6 Jailbreaking AI models can be as simple as TyPiNg LiKe ThIsAnd the methods are simple to automate, too. (404 Media) + Text-to-image AI models can be tricked into generating disturbing images. (MIT Technology Review) 7 Indias answer to Silicon Valley is under immense pressureBengalurus rapid expansion is pushing the citys infrastructure to the absolute limit. (Insider $) + Indias gig economy is focusing on 10-minute deliveries. (Bloomberg $)+ How Indian health-care workers use WhatsApp to save pregnant women. (MIT Technology Review)8 Whats next for AI gadgets?Consumers werent overly enamored with them in 2024. (Fast Company $) 9 The man who claimed to have created bitcoin has been sentenced Craig Wright has been given a one-year suspended sentence after refusing to stop suing developers. (The Guardian)+ Hell face jail if he continues claiming he really is the mysterious Satoshi Nakamoto. (BBC)10 Online returns arent what they used to be Retailers are fed up, and so are customers. (The Atlantic $)Quote of the day You guys scared the life out of a lot of people. Geno, an Arizona resident, tells Amazon workers that their delivery drones are making his neighbors uneasy amid the drone panic gripping the US, the New York Times reports. The big story Bright LEDs could spell the end of dark skies August 2022 Scientists have known for years that light pollution is growing and can harm both humans and wildlife. In people, increased exposure to light at night disrupts sleep cycles and has been linked to cancer and cardiovascular disease, while wildlife suffers from interruption to their reproductive patterns, and increased danger. Astronomers, policymakers, and lighting professionals are all working to find ways to reduce light pollution. Many of them advocate installing light-emitting diodes, or LEDs, in outdoor fixtures such as city streetlights, mainly for their ability to direct light to a targeted area. But the high initial investment and durability of modern LEDs mean cities need to get the transition right the first time or potentially face decades of consequences. Read the full story. Shel Evergreen We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + How the Black diaspora celebrates Christmas across the world, featuring Motown tunes and a tasty saltfish salad.+ We love you Pamela Anderson!+ Test your science knowledge with this fiendish quiz of the year.+ Lets look ahead to just some of the exciting films coming out next year, from Bridget Jones to the bonkers-sounding Mickey 17.

This article first appeared in The Checkup,MIT Technology Reviewsweekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,sign up here. Later today, around 10 minutes after this email lands in your inbox, Ill be holding my four-year-old daughter tight as she receives her booster dose of the MMR vaccine. This shot should protect her from a trio of nasty infectionsinfections that can lead to meningitis, blindness, and hearing loss. I feel lucky to be offered it. This year marks the 50-year anniversary of an ambitious global childhood vaccination program. The Expanded Programme on Immunization was launched by the World Health Organization in 1974 with the goal of getting lifesaving vaccines to all the children on the planet. Vaccines are estimated to have averted 154 million deaths since the launch of the EPI. That number includes 146 million children under the age of five. Vaccination efforts are estimated to have reduced infant mortality by 40%, and to have contributed an extra 10 billion years of healthy life among the global population. Childhood vaccination is a success story. But concerns around vaccines endure. Especially, it seems, among the individuals Donald Trump has picked as his choices to lead US health agencies from January. This week, lets take a look at their claims, and where the evidence really stands on childhood vaccines. WHO, along with health agencies around the world, recommends a suite of vaccinations for babies and young children. Some, such as the BCG vaccine, which offers some protection against tuberculosis, are recommended from birth. Others, like the vaccines for pertussis, diphtheria, tetanus, and whooping cough, which are often administered in a single shot, are introduced at eight weeks. Other vaccinations and booster doses follow. The idea is to protect babies as soon as possible, says Kaja Abbas of the London School of Hygiene & Tropical Medicine in the UK and Nagasaki University in Japan. The full vaccine schedule will depend on what infections pose the greatest risks and will vary by country. In the US, the recommended schedule is determined by the Centers for Disease Control and Prevention, and individual states can opt to set vaccine mandates or allow various exemptions. Some scientists are concerned about how these rules might change in January, when Donald Trump makes his return to the White House. Trump has already listed his picks for top government officials, including those meant to lead the countrys health agencies. These individuals must be confirmed by the Senate before they can assume these roles, but it appears that Trump intends to surround himself with vaccine skeptics. For starters, Trump has selected Robert F. Kennedy Jr. as his pick to lead the Department of Health and Human Services. Kennedy, who has long been a prominent anti-vaxxer, has a track record of spreading false information about vaccines. In 2005, he published an error-laden article in Salon and Rolling Stone linking thimerosalan antifungal preservative that was previously used in vaccines but phased out in the US by 2001to neurological disorders in children. (That article was eventually deleted in 2011. I regret we didnt move on this more quickly, as evidence continued to emerge debunking the vaccines and autism link, wrote Joan Walsh, Salons editor at large at the time.) Kennedy hasnt let up since. In 2015, he made outrageous comments about childhood vaccinations at a screening of a film that linked thimerosal to autism. They get the shot, that night they have a fever of a hundred and three, they go to sleep, and three months later their brain is gone, Kennedy said, as reported by the Sacramento Bee. This is a holocaust, what this is doing to our country. Aaron Siri, the lawyer who has been helping Kennedy pick health officials for the upcoming Trump administration, has petitioned the government to pause the distribution of multiple vaccines and to revoke approval of the polio vaccine entirely. And Dave Weldon, Trumps pick to direct the CDC, also has a history of vaccine skepticism. He has championed the disproven link between thimerosal and autism. These arguments arent new. The MMR vaccine in particular has been subject to debate, controversy, and conspiracy theories for decades. All the way back in 1998, a British doctor, Andrew Wakefield, published a paper suggesting a link between the vaccine and autism in children. The study has since been debunkedmultiple times overand Wakefield was found to have unethically subjected children to invasive and unnecessary procedures. The paper was retracted 12 years after it was published, and the UKs General Medical Council found Wakefield guilty of serious professional misconduct. He was struck off the medical register and is no longer allowed to practice medicine in the UK. (He continues to peddle false information, though, and directed the 2016 film Vaxxed, which Weldon appeared in.) So its remarkable that his study still seems to be affecting public opinion. A recent Pew Research Center survey suggests that four in 10 US adults worry that not all vaccines are necessary, and while most Americans think the benefits outweigh any risks, some are still concerned about side effects. Views among Republicans in particular seem to have shifted over the years. In 2019, 82% supported school-based vaccine requirements. That figure dropped to 70% in 2023. The problem is that we need more than 70% of children to be vaccinated to reach herd immunitythe level needed to protect communities. For a super-contagious infection like measles, 95% of the population needs to be vaccinated, according to WHO. If [coverage drops to] 80%, we should expect outbreaks, says Abbas. And thats exactly what is happening. In 2023, only 83% of children got their first dose of a measles vaccine through routine health services. Nearly 35 million children are thought to have either partial protection from the disease or none at all. And over the last five years, there have been measles outbreaks in 103 countries. Polio vaccinesthe ones whose approval Siri sought to revokehave also played a vital role in protecting children, in this case from a devastating infection that can cause paralysis. People were so afraid of polio in the 30s, 40s, and 50s here in the United States, says William Moss, an epidemiologist at Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. When the trial results of [the first] vaccine were announced in the United States, people were dancing in the streets. That vaccine was licensed in the US in 1955. By 1994, polio was considered eliminated in North and South America. Today, wild forms of the virus have been eradicated in all but two countries. But the polio vaccine story is not straightforward. There are two types of polio vaccine: an injected type that includes a dead form of the virus, and an oral version that includes live virus. This virus can be shed in feces, and in places with poor sanitation, it can spread. It can also undergo genetic changes to create a form of the virus that can cause paralysis. Although this is rare, it does happenand today there are more cases of vaccine-derived polio than wild-type polio. It is worth noting that since 2000, more than 10 billion doses of the oral polio vaccine have been administered to almost 3 billion children. It is estimated that more than 13 million cases of polio have been prevented through these efforts. But there have been just under 760 cases of vaccine-derived polio. We could prevent these cases by switching to the injected vaccine, which wealthy countries have already done. But thats not easy in countries with fewer resources and those trying to reach children in remote rural areas or war zones. Even the MMR vaccine is not entirely risk-free. Some people will experience minor side effects, and severe allergic reactions, while rare, can occur. And neither vaccine offers 100% protection against disease. No vaccine does. Even if you vaccinate 100% [of the population], I dont think well be able to attain herd immunity for polio, says Abbas. Its important to acknowledge these limitations. While there are some small risks, though, they are far outweighed by the millions of lives being saved. [People] often underestimate the risk of the disease and overestimate the risk of the vaccine, says Moss. In some ways, vaccines have become a victim of their own success. Most of todays parents fortunately have never seen the tragedy caused by vaccine-preventable diseases such as measles encephalitis, congenital rubella syndrome, and individuals crippled by polio, says Kimberly Thompson, president of Kid Risk, a nonprofit that conducts research on health risks to children. With some individuals benefiting from the propagation of scary messages about vaccines and the proliferation of social media providing reinforcement, its no surprise that fears may endure. But most Americans recognize the benefits of vaccines and choose to get their children immunized, she adds. Now, that is a sentiment I can relate to. Now read the rest of The Checkup Read more from MIT Technology Review's archive A couple of years ago, the polio virus was detected in wastewater in London, where I live. I immediately got my daughter (who was only one year old then!) vaccinated. Measles outbreaks continue to spring up in places where vaccination rates drop. Researchers hope that searching for traces of the virus in wastewater could help them develop early warning systems. Last year, the researchers whose work paved the way for the development of mRNA vaccines were awarded the Nobel Prize. Now, scientists are hoping to use the same technology to treat and vaccinate against a host of diseases. Most vaccines work by priming the immune system to respond to a pathogen. Scientists are also working on inverse vaccines that teach the immune system to stand down. They might help treat autoimmune disorders. From around the web A person in the US is the first in the country to have become severely ill after being infected with the bird flu virus, the US Centers for Disease Control and Prevention shared on December 18. The case was confirmed on December 13. The person was exposed to sick and dead birds in backyard flocks in Louisiana. (CDC) Gavin Newsom, the governor of California, declared a state of emergency as the bird flu virus moved from the Central Valley to Southern California dairy herds. Since August, 645 herds have been reported to be infected with the virus. (LA Times) Pharmacy benefit managers control access to prescription drugs for most Americans. These middlemen were paid billions of dollars by drug companies to allow the free flow of opioids during the USs deadly addiction epidemic, an investigation has revealed. (New York Times) Weight-loss drugs like Ozempic have emerged as blockbuster medicines over the past couple of years. Were learning that they may have benefits beyond weight loss. Might they also protect organ function or treat kidney disease? (Nature Medicine) Doctors and scientists have been attempting head transplants on animals for decades. Can they do it in people? Watch this delightful cartoon to learn more about the early head transplant attempts. (Aeon)

Networks programmed directly into computer chip hardware can identify images faster, and use much less energy, than the traditional neural networks that underpin most modern AI systems. Thats according to work presented at a leading machine learning conference in Vancouver last week. Neural networks, from GPT-4 to Stable Diffusion, are built by wiring together perceptrons, which are highly simplified simulations of the neurons in our brains. In very large numbers, perceptrons are powerful, but they also consume enormous volumes of energyso much that Microsoft has penned a deal that will reopen Three Mile Island to power its AI advancements. Part of the trouble is that perceptrons are just software abstractionsrunning a perceptron network on a GPU requires translating that network into the language of hardware, which takes time and energy. Building a network directly from hardware components does away with a lot of those costs. One day, they could even be built directly into chips used in smartphones and other devices, dramatically reducing the need to send data to and from servers. Felix Petersen, who did this work as a postdoctoral researcher at Stanford University, has a strategy for making that happen. He designed networks composed of logic gates, which are some of the basic building blocks of computer chips. Made up of a few transistors apiece, logic gates accept two bits1s or 0sas inputs and, according to a rule determined by their specific pattern of transistors, output a single bit. Just like perceptrons, logic gates can be chained up into networks. And running logic-gate networks is cheap, fast, and easy: in his talk at the Neural Information Processing Systems (NeurIPS) conference, Petersen said that they consume less energy than perceptron networks by a factor of hundreds of thousands. Logic-gate networks dont perform nearly as well as traditional neural networks on tasks like image labeling. But the approachs speed and efficiency make it promising, according to Zhiru Zhang, a professor of electrical and computer engineering at Cornell University. If we can close the gap, then this could potentially open up a lot of possibilities on this edge of machine learning, he says. Petersen didnt go looking for ways to build energy-efficient AI networks. He came to logic gates through an interest in differentiable relaxations, or strategies for wrangling certain classes of mathematical problems into a form that calculus can solve. It really started off as a mathematical and methodological curiosity, he says. Backpropagation, the training algorithm that made the deep-learning revolution possible, was an obvious use case for this approach. Because backpropagation runs on calculus, it cant be used directly to train logic-gate networks. Logic gates only work with 0s and 1s, and calculus demands answers about all the fractions in between. Petersen devised a way to relax logic-gate networks enough for backpropagation by creating functions that work like logic gates on 0s and 1s but also give answers for intermediate values. He ran simulated networks with those gates through training and then converted the relaxed logic-gate network back into something that he could implement in computer hardware. One challenge with this approach is that training the relaxed networks is tough. Each node in the network could end up as any one of 16 different logic gates, and the 16 probabilities associated with each of those gates must be kept track of and continually adjusted. That takes a huge amount of time and energyduring his NeurIPS talk, Petersen said that training his networks takes hundreds of times longer than training conventional neural networks on GPUs. At universities, which cant afford to amass hundreds of thousands of GPUs, that amount of GPU time can be tough to swingPetersen developed these networks, in collaboration with his colleagues, at Stanford University and the University of Konstanz. It definitely makes the research tremendously hard, he says. Once the network has been trained, though, things get way, way cheaper. Petersen compared his logic-gate networks with a cohort of other ultra-efficient networks, such as binary neural networks, which use simplified perceptrons that can process only binary values. The logic-gate networks did just as well as these other efficient methods at classifying images in the CIFAR-10 data set, which includes 10 different categories of low-resolution pictures, from frog to truck. It achieved this with fewer than a tenth of the logic gates required by those other methods, and in less than a thousandth of the time. Petersen tested his networks using programmable computer chips called FPGAs, which can be used to emulate many different potential patterns of logic gates; implementing the networks in non-programmable ASIC chips would reduce costs even further, because programmable chips need to use more components in order to achieve their flexibility. Farinaz Koushanfar, a professor of electrical and computer engineering at the University of California, San Diego, says she isnt convinced that logic-gate networks will be able to perform when faced with more realistic problems. Its a cute idea, but Im not sure how well it scales, she says. She notes that the logic-gate networks can only be trained approximately, via the relaxation strategy, and approximations can fail. That hasnt caused issues yet, but Koushanfar says that it could prove more problematic as the networks grow. Nevertheless, Petersen is ambitious. He plans to continue pushing the abilities of his logic-gate networks, and he hopes, eventually, to create what he calls a hardware foundation model. A powerful, general-purpose logic-gate network for vision could be mass-produced directly on computer chips, and those chips could be integrated into devices like personal phones and computers. That could reap enormous energy benefits, Petersen says. If those networks could effectively reconstruct photos and videos from low-resolution information, for example, then far less data would need to be sent between servers and personal devices. Petersen acknowledges that logic-gate networks will never compete with traditional neural networks on performance, but that isnt his goal. Making something that works, and that is as efficient as possible, should be enough. It wont be the best model, he says. But it should be the cheapest.

US doctors write billions of prescriptions each year. During 2024, though, one type of drug stood outwonder drugs known as GLP-1 agonists. As of September, one of every 20 prescriptions written for adults was for one of these drugs, according to the health data company Truveta. The drugs, which include Wegovy, Mounjaro, and Victoza, are used to treat diabetes, since they help generate insulin. But their popularity exploded after scientists determined the drugs tell your brain youre not hungry. Without those hunger cues, people find they can lose 10% of their body weight, or even more. During 2024, the drugs popularity hit an all-time high, according to Tricia Rodriguez, a principal applied scientist at Truveta, which studies medical records of 120 million Americans, or about a third of the population. Among adults, 5.4% of all prescriptions in September 2024 were for GLP-1s, Rodriguez says. That is up from 3.5% a year earlier, in 2023, and 1% at the start of 2021. According to Truvetas data, people who get prescriptions for these drugs are younger, whiter, and more likely to be female. In fact, women are twice as likely as men to get a prescription. Yet not everyone whos prescribed the drugs ends up taking them. In fact, Rodriguez says, half the new prescriptions for obesity are going unfilled. Thats very unusual, she says, and could be due to shortages or sticker shock over the cost of the treatment. Many insurers don t cover weight-loss drugs, and the out-of-pocket price can be $1,300 a month, according to USA Today. For most medications, prescribing rates and dispensing rates are pretty much identical, says Rodriguez. But for GLP-1s, we see this gap, which is really unique. It's suggestive that people are really interested in getting these medications, but for whatever reason, they are not always able to. It also means the number of people taking these drugs could go highermaybe much higherif insurers would pay. I don't think that we are at the saturation point, or necessarily nearing the saturation point, says Rodriguez, noting that around 70% of Americans are overweight or obese. Use of the drugs may also grow dramatically if new applications are found. Companies are already exploring whether they can treat addiction, or even Alzheimers. Many of the clues about those potential uses are coming directly out of peoples medical records. Because so many people are on the drugs, it means researchers like Rodriguez have a gold mine to sift through for signs of how use of the drugs is affecting other health problems. Because we have so many patients that are on these medications, you're certainly likely to have a good number that also have all of these other conditions, she says. One of the things we're excited about is: How can real-world data help accelerate how quickly we can understand those? Here are some of the new uses of GLP-1 drugs that are being explored, based on hints from real-world patient records. Alzheimers disease This year, researchers poking through records of a million people found that taking semaglutide (sold as Wegovy and Ozempic) was associated with a 40% to 70% lower chance of an Alzheimers diagnosis. It's still a guess why the drugs might be helping (or whether they really do), but large international studies are underway to follow up on the lead. Doctors are recruiting people with early Alzheimers in more than 30 countries who will take either a placebo or semaglutide for two years. Then well see how much their dementia has progressed. Addiction The anecdotes are everywhere: A person on a weight-loss drug finds hunger isnt the only craving that seems to stop. Those are the types of clues Eli Lillys CEO, David Ricks, says his company will pursue next year, testing whether its GLP-1 drug, tirzepatide (called Mounjaro for diabetes treatment, and Zepbound for weight loss), could help with addiction to alcohol, nicotine, and other things we dont think about [as being] connected to weight. In comments he made in December, Ricks said the drugs might be anti-hedonicsmeaning they counteract our hedonistic pursuit of pleasure, be it from food, alcohol, or drugs. A study this year mining digital health records found that opioid addicts taking the drugs were about half as likely to have had an overdose. Sleep apnea This idea goes back a ways, including to a 2015 case study of a 260-pound man with diabetes and sleep apnea. When he went on the drug liraglutide, doctors noticed that his sleeping improved. In sleep apnea, a person gasps for air at nightits annoying and, with time, causes health problems. This year, Eli Lilly published a study in the New England Journal of Medicine on its drugtirzepatide , finding that it caused a 50% decrease in breathing interruption in overweight patients with sleep apnea. Longevity This year, the U.S. Food and Drug Administration approved Wegovy as a cardiovascular medicine, after researchers showed the drugs could reduce heart attack and stroke in overweight people. But that wasnt all. The study, involving 17,000 people, found that the drug reduced the overall chance someone would die for any reason (known as all-cause mortality) by 19%. That now has aging researchers paying attention. This year they named Wegovy, and drugs like it, among their the top four candidates for a general life-extension drug.

A healthy heart beats at a steady rate, between 60 and 100 times a minute. Thats not the case for all of us, Im reminded, as I look inside a cardboard box containing around 20 plastic heartseach a replica of a real human one. The hearts, which previously sat on a shelf in a lab in West London, were generated from MRI and CT scans of people being treated for heart conditions at Hammersmith Hospital next door. Steven Niederer, a biomedical engineer at the Alan Turing Institute and Imperial College London, created them on a 3D printer in his office. One of the hearts, printed in red recycled plastic, looks as I imagine a heart to look. It just about fits in my hand, and the chambers have the same dimensions as the ones you might see in a textbook. Perhaps it helps that its red. The others look enormous to me. One in particular, printed in black plastic, seems more than twice the size of the red one. As I find out later, the person who had the heart it was modeled on suffered from heart failure. The plastic organs are just for educational purposes. Niederer is more interested in creating detailed replicas of peoples hearts using computers. These digital twins are the same size and shape as the real thing. They work in the same way. But they exist only virtually. Scientists can do virtual surgery on these virtual hearts, figuring out the best course of action for a patients condition. After decades of research, models like these are now entering clinical trials and starting to be used for patient care. Virtual replicas of many other organs are also being developed. Engineers are working on digital twins of peoples brains, guts, livers, nervous systems, and more. Theyre creating virtual replicas of peoples faces, which could be used to try out surgeries or analyze facial features, and testing drugs on digital cancers. The eventual goal is to create digital versions of our bodiescomputer copies that could help researchers and doctors figure out our risk of developing various diseases and determine which treatments might work best. Theyd be our own personal guinea pigs for testing out medicines before we subject our real bodies to them. To engineers like Niederer, its a tantalizing prospect very much within reach. Several pilot studies have been completed, and larger trials are underway. Those in the field expect digital twins based on organs to become a part of clinical care within the next five to 10 years, aiding diagnosis and surgical decision-making. Further down the line, well even be able to run clinical trials on synthetic patientsvirtual bodies created using real data. But the budding technology will need to be developed carefully. Some worry about who will own this highly personalized data and how it could be used. Others fear for patient autonomywith an uncomplicated virtual record to consult, will doctors eventually bypass the patients themselves? And some simply feel a visceral repulsion at the idea of attempts to re-create humans in silico. People will say I dont want you copying me, says Wahbi El-Bouri, who is working on digital-twin technologies. They feel its a part of them that youve taken. Getting digital Digital twins are well established in other realms of engineering; for example, they have long been used to model machinery and infrastructure. The term may have become a marketing buzzword lately, but for those working on health applications, it means something very specific. We can think of a digital twin as having three separate components, says El-Bouri, a biomedical engineer at the University of Liverpool in the UK. The first is the thing being modeled. That might be a jet engine or a bridge, or it could be a persons heart. Essentially, its what we want to test or study. The second component is the digital replica of that object, which can be created by taking lots of measurements from the real thing and entering them into a computer. For a heart, that might mean blood pressure recordings as well as MRI and CT scans. The third is new data thats fed into the model. A true digital twin should be updated in real timefor example, with information collected from wearable sensors, if its a model of someones heart. Taking measurements of airplanes and bridges is one thing. Its much harder to get a continuous data feed from a person, especially when you need details about the inner functions of the heart or brain. And the information transfer should run both ways. Just as sensors can deliver data from a persons heart, the computer can model potential outcomes to make predictions and feed them back to a patient or health-care provider. A medical team might want to predict how a person will respond to a drug, for example, or test various surgical procedures on a digital model before operating in real life. By this definition, pretty much any smart device that tracks some aspect of your health could be considered a kind of rudimentary digital twin. You could say that an Apple Watch fulfills the definition of a digital twin in an unexciting way, says Niederer. It tells you if youre in atrial fibrillation or not. But the kind of digital twin that researchers like Niederer are working on is far more intricate and detailed. It could provide specific guidance on which disease risks a person faces, what medicines might be most effective, or how any surgeries should proceed. Were not quite there yet. Taking measurements of airplanes and bridges is one thing. Its much harder to get a continuous data feed from a person, especially when you need details about the inner functions of the heart or brain, says Niederer. As things stand, engineers are technically creating patient-specific models based on previously collected hospital and research data, which is not continually updated. The most advanced medical digital twins are those built to match human hearts. These were the first to be attempted, partly because the heart is essentially a pumpa device familiar to engineersand partly because heart disease is responsible for so much ill health and death, says El-Bouri. Now, advances in imaging technology and computer processing power are enabling researchers to mimic the organ with the level of fidelity that clinical applications require. Building a heart The first step to building a digital heart is to collect images of the real thing. Each team will have its own slightly different approach, but generally, they all start with MRI and CT scans of a persons heart. These can be entered into computer software to create a 3D movie. Some scans will also highlight any areas of damaged tissue, which might disrupt the way the electrical pulses that control heart muscle contraction travel through the organ. The next step is to break this 3D model down into tiny chunks. Engineers use the term computational mesh to describe the result; it can look like an image of the heart made up of thousands of 3D pieces. Each segment represents a small collection of cells and can be assigned properties based on how well they are expected to propagate an electrical impulse. Its all equations, says Natalia Trayanova, a biomedical engineering professor based at Johns Hopkins University in Baltimore, Maryland. This computer model of the human heart show how electrical signals pass through heart tissue. The model was created by Marina Strocchi, who works with Steven Niederer at Imperial College London.COURTESY OF MARINA STROCCHI As things stand, these properties involve some approximation. Engineers will guess how well each bit of heart works by extrapolating from previous studies of human hearts or past research on the disease the person has. The end result is a beating, pumping model of a real heart. When we have that model, you can poke it and prod it and see under what circumstances stuff will happen, says Trayanova. Her digital twins are already being trialed to help people with atrial fibrillation, a fairly common condition that can trigger an irregular heartbeattoo fast or all over the place. One treatment option is to burn off the bits of heart tissue responsible for the disrupted rhythm. Its usually left to a surgical team to figure out which bits to target. For Trayanova, the pokes and prods are designed to help surgeons with that decision. Scans might highlight a few regions of damaged or scarred tissue. Her team can then construct a digital twin to help locate the underlying source of the damage. In total, the tool will likely suggest two or three regions to destroythough in rare instances, it has shown many more, says Trayanova: They just have to trust us. So far, 59 people have been through the trial. More are planned. In cases like these, the models dont always need to be continually updated, Trayanova says. A heart surgeon might need to run simulations only to know where to implant a device, for example. Once that operation is over, no more data might be needed, she says. Quasi patients At his lab on the campus of Hammersmith Hospital in London, Niederer has also been building virtual hearts. He is exploring whether his models could be used to find the best place to implant pacemakers. His approach is similar to Trayanovas, but his models also incorporate ECG data from patients. These recordings give a sense of how electrical pulses pass through the heart tissue, he says. So far, Niederer and his colleagues have published a small trial in which models of 10 patients hearts were evaluated by doctors but not used to inform surgical decisions. Still, Niederer is already getting requests from device manufacturers to run virtual tests of their products. A couple have asked him to choose places where their battery-operated pacemaker devices can sit without bumping into heart tissue, he says. Not only can Niederer and his colleagues run this test virtually, but they can do it for hearts of various different sizes. The team can test the device in hundreds of potential locations, within hundreds of different virtual hearts. And we can do it in a week, he adds. This is an example of what scientists call in silico trialsclinical trials run on a computer. In some cases, its not just the trials that are digital. The volunteers are, too. El-Bouri and his colleagues are working on ways to create synthetic participants for their clinical trials. The team starts with data collected from real people and uses this to create all-new digital organs with a mishmash of characteristics from the real volunteers. These in silico trials could be especially useful for helping us figure out the best treatments for pregnant peoplea group that is notoriously excluded from many clinical trials. Specifically, one of El-Bouris interests is stroke, a medical emergency in which clots or bleeds prevent blood flow in parts of the brain. For their research, he and his colleagues model the brain, along with the blood vessels that feed it. You could create lots and lots of different shapes and sizes of these brains based on patient data, says El-Bouri. Once he and his team create a group of synthetic patient brains, they can test how these clots might change the flow of blood or oxygen, or how and where brain tissue is affected. They can test the impact of certain drugs, or see what might happen if a stent is used to remove the blockage. For another project, El-Bouri is creating synthetic retinas. From a starting point of 100 or so retinal scans from real people, his team can generate 200 or more synthetic eyes, just like that, he says. The trick is to figure out the math behind the distribution of blood vessels and re-create it through a set of algorithms. Now he is hoping to use those synthetic eyes in drug trialsamong other things, to find the best treatment doses for people with age-related macular degeneration, a common condition that can lead to blindness. These in silico trials could be especially useful for helping us figure out the best treatments for pregnant peoplea group that is notoriously excluded from many clinical trials. Thats for fear that an experimental treatment might harm a fetus, says Michelle Oyen, a professor of biomedical engineering at Wayne State University in Detroit. Oyen is creating digital twins of pregnancy. Its a challenge to get the information needed to feed the models; during pregnancy, people are generally advised to avoid scans or invasive investigations they dont need. Were much more limited in terms of the data that we can get, she says. Her team does make use of ultrasound images, including a form of ultrasound that allows the team to measure blood flow. From those images, they can see how blood flow in the uterus and the placenta, the organ that supports a fetus, might be linked to the fetuss growth and development, for example. For now, Oyen and her colleagues arent creating models of the fetuses themselvestheyre focusing on the fetal environment, which includes the placenta and uterus. A baby needs a healthy, functioning placenta in order to survive; if the organ starts to fail, stillbirth can be the tragic outcome. Oyen is working on ways to monitor the placenta in real time during pregnancy. These readings could be fed back to a digital twin. If she can find a way to tell when the placenta is failing, doctors might be able to intervene to save the baby, she says. I think this is a game changer for pregnancy research, she adds, because this basically gives us ways of doing research in pregnancy that [carries a minimal] risk of harm to the fetus or of harm to the mother. In another project, the team is looking at the impact of cesarean section scars on pregnancies. When a baby is delivered by C-section, surgeons cut through multiple layers of tissue in the abdomen, including the uterus. Scars that dont heal well become weak spots in the uterus, potentially causing problems for future pregnancies. By modeling these scars in digital twins, Oyen hopes to be able to simulate how future pregnancies might pan out, and determine if or when specialist care might be called for. Eventually, Oyen wants to create a full virtual replica of the pregnant uterus, fetus and all. But were not there yetwere decades behind the cardiovascular people, she says. Thats pregnancy research in a nutshell, she adds. Were always decades behind. Twinning Its all very well to generate virtual body parts, but the human body functions as a whole. Thats why the grand plan for digital twins involves replicas of entire people. Long term, the whole body would be fantastic, says El-Bouri. It may not be all that far off, either. Various research teams are already building models of the heart, brain, lungs, kidneys, liver, musculoskeletal system, blood vessels, immune system, eye, ear, and more. If we were to take every research group that works on digital twins across the world at the moment, I think you could put [a body] together, says El-Bouri. I think theres even someone working on the tongue, he adds. The challenge is bringing together all the various researchers, with the different approaches and different code involved in creating and using their models, says El-Bouri. Everything exists, he says. Its just putting it together thats going to be the issue. In theory, such whole-body twins could revolutionize health care. Trayanova envisions a future in which a digital twin is just another part of a persons medical recordone that a doctor can use to decide on a course of treatment. Technically, if someone tried really hard, they might be able to piece back who someone is through scans and twins of organs. Wahbi El-Bouri But El-Bouri says he receives mixed reactions to the idea. Some people think its really exciting and really cool, he says. But hes also met people who are strongly opposed to the idea of having a virtual copy of themselves exist on a computer somewhere: They dont want any part of that. Researchers need to make more of an effort to engage with the public to find out how people feel about the technology, he says. There are also concerns over patient autonomy. If a doctor has access to a patients digital twin and can use it to guide decisions about medical care, where does the patients own input come into the equation? Some of those working to create digital twins point out that the models could reveal whether patients have taken their daily meds or what theyve eaten that week. Will clinicians eventually come to see digital twins as a more reliable source of information than peoples self-reporting? Doctors should not be allowed to bypass patients and just ask the machine, says Matthias Braun, a social ethicist at the University of Bonn in Germany. There would be no informed consent, which would infringe on autonomy and maybe cause harm, he says. After all, we are not machines with broken parts. Two individuals with the same diagnosis can have very different experiences and lead very different lives. However, there are cases in which patients are not able to make decisions about their own treatmentfor example, if they are unconscious. In those cases, clinicians try to find a proxysomeone authorized to make decisions on the patients behalf. A digital psychological twin, trained on a persons medical data and digital footprint, could potentially act as a better surrogate than, for example, a relative who doesnt know the persons preferences, he says. If using digital twins in patient care is problematic, in silico trials can also raise issues. Jantina de Vries, an ethicist at the University of Cape Town, points out that the data used to create digital twins and synthetic quasi patients will come from people who can be scanned, measured, and monitored. This group is unlikely to include many of those living on the African continent, who wont have ready access to those technologies. The problem of data scarcity directly translates into technologies that are not geared to think about diverse bodies, she says. De Vries thinks the data should belong to the public in order to ensure that as many people benefit from digital-twin technologies as possible. Every record should be anonymized and kept within a public database that researchers around the world can access and make use of, she says. The people who participate in Trayanovas trials explicitly give me consent to know their data, and to know who they are [everything] about them, she says. The people taking part in Niederers research also provide consent for their data to be used by the medical and research teams. But while clinicians have access to all medical data, researchers access only anonymized or pseudonymized data, Niederer says. In some cases, researchers will also ask participants to consent to sharing their fully anonymized data in public repositories. This is the only data that companies are able to access, he adds: We do not share [our] data sets outside of the research or medical teams, and we do not share them with companies. El-Bouri thinks that patients should receive some form of compensation in exchange for sharing their health data. Perhaps they should get preferential access to medications and devices based on that data, he suggests. At any rate, [full] anonymization is tricky, particularly if youre taking patient scans to develop twins, he says. Technically, if someone tried really hard, they might be able to piece back who someone is through scans and twins of organs. When I looked at those anonymous plastic hearts, stored in a cardboard box tucked away on a shelf in the corner of an office, they felt completely divorced from the people whose real, beating hearts they were modeled on. But digital twins seem different somehow. Theyre animated replicas, digital copies that certainly appear to have some sort of life. People often think, Oh, this is just a simulation, says El-Bouri. But its a digital representation of an individual.

This article is from The Spark, MIT Technology Reviews weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here. The vibes in the climate world this year have largely been less than great. Global greenhouse-gas emissions hit a new high, reaching 37.4 billion metric tons in 2024. This year is also on track to be the warmest on record, with temperatures through September hitting 1.54 C (2.77 F) above preindustrial levels. Global climate talks fell flat, and disasters from wildfires to hurricanes are being made worse by climate change. But among all that (very real) negative news, there was some good, too: We saw progress cutting back on the most polluting fossil fuels, cheaper and better technologies for combating climate change, and a continuous global effort to address the problem. As we near the end of 2024, lets take a moment to look back on some of the bright spots. Were kicking coal to the curb One of my favorite climate moments from this year happened in the UK. The country has historically relied heavily on coal as an electricity sourceas of 1990, coal met about 65% of its electricity demand. But on September 30, 2024, the last coal plant in the nation shut down. Renewables are stepping in to fill the gap. Wind farms in the UK are on track to produce more electricity this year than coal and gas plants together. The moment was a symbolic one, and it also reflects the very real progress thats happening around the world in inching away from this polluting fossil fuel. In the US, coal made up around 50% of the electricity supply four decades ago. In 2023, that share was roughly 16%. We should see coal use plateau and potentially begin to fall by the end of the decade, according to the International Energy Agency. Progress needs to happen faster, though, and it needs to happen in countries like China, where energy demand is increasing. Theres also growing concern about what increasing energy demand from data centers, including those used to power AI, will mean for efforts to shut off old coal plants. Batteries just keep getting cheaper Lithium-ion battery packs are cheaper than ever in 2024, with prices dropping 20% this year to $115 per kilowatt-hour, according to data from BloombergNEF. Thats the biggest drop since 2017. Batteries are a central technology for addressing climate change. They power the electric vehicles were relying on to help clean up the transportation sector and play an increasingly important role for the grid, since they can store energy from inconsistently available renewables like wind and solar. Since EVs are still more expensive upfront than their gas-powered counterparts in most of the world, cheaper batteries are great news for efforts to get more people to take the leap to electric. And its hard to overstate how quickly battery prices have plummeted. Batteries were twice as expensive in 2017 as they are today. Just 10 years ago, prices were six times what they are in 2024. To be fair, theres been mixed news in the EV world this yeara slowdown in demand growth for EVs is actually one of the factors helping battery prices hit record lows. EV sales are still growing around the world, but at a slower pace than they were in 2023. China is the biggest EV market in the world by far, making up three-quarters of global registrations in 2024 as of October. Climate tech is still busy and bustling Looking back at the energy and climate stories we published this year, I cant help but feel at least a little bit optimistic about whats coming next. Some groups are looking to the natural world to address the climate crisis; this year, I covered a company working to grow microbes in massive bioreactors to help supplement our food sources, as well as researchers who are looking to plants to help mine the metals we need to fight climate change. Others hope to tweak biologymy colleague James Temple spoke with Jennifer Doudna about the potential for CRISPR, the gene-editing technology she pioneered. Companies are deploying air-conditioning systems that can act like batteries, storing up energy for when its needed. The US Department of Energy is investing in projects that aim to concentrate heat from the sun and use it to power the grid or industrial processes. I spoke to a startup looking to make hydropower technology thats safer for fish, and another building magnets using cheap, widely available materials. And in October we published our 2024 list of 15 Climate Tech Companies to Watch, which featured everything from a startup using AI to detect wildfires to a company giving supplements to cattle to help cut emissions from their burps. Climate change represents a massive challenge for the world, and were entering an especially uncertain time. Well be covering it all, the good and the bad. Thanks for being here this year, and Im looking forward to bringing you all the climate tech news you need in 2025. Now read the rest of The Spark Related reading If you need a dash of innovation and positivity in your life, might I recommend taking a gander at our list of 15 Climate Tech Companies to Watch? Whats more inspiring than young people working on the worlds most important problems? Our 2024 class of 35 Innovators Under 35 is sure to spread some cheer. If youre needing even more innovation, why not look back at our 10 Breakthrough Technologies? Exascale computers certainly help me put things in perspective. And get excited, because our 2025 list is coming very, very soon. NICO ORTEGA Another thing This year was filled with some exciting moments in technology, but there were also some failures. Here are a few of the worst technology flops of 2024. Check it out to see why voluntary carbon markets made the list and learn all about AI slop. And one more Youve almost certainly heard that energy demand from AI is huge, and only expected to explode in the coming years. A new preprint study aimed to quantify just how bad things are, and the researchers found that data centers accounted for over 4% of electricity consumption in the US between September 2023 and August 2024. And the carbon intensity of the power thats used is nearly 50% higher than the national average. Get all the details in the latest story from my colleague James ODonnell. Keeping up with climate Geothermal energy provides about 1% of global electricity today, but If things go well, the tech could meet up to 15% of global power demand growth through 2050. (Axios) Renting an EV over the holidays? This is a great guide for first-time EV drivers, including helpful tips about how to handle charging. (Bloomberg) Commonwealth Fusion Systems chose Virginia as the site for its first commercial fusion power plant. The company says the 400-megawatt plant will come online in the early 2030s. (Heatmap) I recently visited Commonwealths first demonstration site in Massachusetts. Its basically still a hole in the ground. (MIT Technology Review)The US Department of Energys Loan Programs Office just committed $15 billion to a California utility. Its the largest-ever commitment from the office. (New York Times) The US EPA will grant California the right to ban gas-powered cars by 2035. The agency has to give the state a waiver to set its own rules. (Washington Post) We can expect a legal battle, though. The incoming Trump administration is recommending major changes to cut off support for EVs and charging. (Reuters)China dominates the world of lithium-ion batteries. Some startups in the US and Europe argue that rather than playing catch-up, the rest of the world should focus on alternative chemistries like lithium-sulfur and sodium-ion batteries. (Canary Media)

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Digital twins of human organs are here. Theyre set to transform medical treatment. Steven Niederer, a biomedical engineer at the Alan Turing Institute and Imperial College London, has a cardboard box filled with 3D-printed hearts. Each of them is modeled on the real heart of a person with heart failure, but Niederer is more interested in creating detailed replicas of peoples hearts using computers. These digital twins are the same size and shape as the real thing. They work in the same way. But they exist only virtually. Scientists can do virtual surgery on these virtual hearts, figuring out the best course of action for a patients condition.After decades of research, models like these are now entering clinical trials and starting to be used for patient care. The eventual goal is to create digital versions of our bodiescomputer copies that could help researchers and doctors figure out our risk of developing various diseases and determine which treatments might work best.But the budding technology will need to be developed very carefully. Read the full story to learn why.Jessica Hamzelou This story is from the forthcoming magazine edition of MIT Technology Review, set to go live on January 6its all about the exciting breakthroughs happening in the world right now. If you dont already, subscribe to receive future copies. This is where the data to build AI comes from AI is all about data. Reams and reams of data are needed to train algorithms to do what we want, and what goes into the AI models determines what comes out. But heres the problem: AI developers and researchers dont really know much about the sources of the data they are using. The Data Provenance Initiative, a group of over 50 researchers from both academia and industry, wanted to fix that. They wanted to know, very simply: Where does the data to build AI come from? Their findings, shared exclusively with MIT Technology Review, show a worrying trend: AI's data practices risk concentrating power overwhelmingly in the hands of a few dominant technology companies. Read the full story.Melissa Heikkil Three pieces of good news on climate change in 2024 The vibes in the climate world this year have largely been less than great. Global greenhouse-gas emissions hit a new high, and this year is also on track to be the warmest on record. Global climate talks fell flat, and disasters from wildfires to hurricanes are being made worse by climate change. But among all that (very real) negative news, there was some good, too: We saw progress cutting back on the most polluting fossil fuels, cheaper and better technologies for combating climate change, and a continuous global effort to address the problem. So as we near the end of 2024, lets take a moment to look back on some of the bright spots. Casey Crownhart This story is from The Spark, our weekly climate and energy newsletter. Sign up to receive it in your inbox every Wednesday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 The US Supreme Court will hear TikToks appeal against its ban Its agreed to hear the companys arguments on January 10. (FT $)+ A ruling could follow shortly afterwards. (WP $)+ Heres how a couple of the most likely scenarios could play out. (The Information $)2 Amazons telehealth clinic is being sued Philip Tong died shortly after a virtual appointment last year. His family wants answers. (WP $)+ The legal case accuses the health provider of negligently failing to care for Tong. (LA Times $)3 The Boeing Starliner astronauts are still stuck in space Their return to Earth has been pushed back yet again, this time to March 2025. (WP $)+ Theyve been living on the ISS since June. (The Guardian)4 Dangerous disordered eating content is rife on XThe platforms content moderation has become so lax, harmful communities are thriving unchecked. (The Atlantic $)5 People are shining lasers at planes flying over New York Amid the local drone panic, pilots are struggling with the unwelcome intrusions. (404 Media)+ Dont be surprised if other similar drone panics crop up in the future. (Vox)6 How Google Street View helped to solve a missing-person caseAfter its cars captured a man hunched over a large white bag in a car trunk. (NYT $) + Google Maps is still the biggest, but these startups are fast gaining traction. (Fast Company $)7 Why you shouldnt remove fluoride from your drinking waterUnless you desperately want to jeopardize your dental health. (WSJ $) + Its not the first time concerns around fluoride have surfaced. (NYT $) 8 The old internet is slowly disappearingWhat does that mean for our collective cultural understanding? (The Verge) + How to fix the internet. (MIT Technology Review)9 Europeans just love balcony solar panelsTheyre simple to install and can help to keep electricity bills down. (The Guardian) + How to store energy for leaner times. (Knowable Magazine)+ Advanced solar panels still need to pass the test of time. (MIT Technology Review)10 You can now call ChatGPT on the phone Theres nowhere left to hide. (Bloomberg $)Quote of the day I dont think that work is suitable for human beings. James Irungu, a former Facebook content moderator, reflects on the horrific material he encountered in the job, the Guardian reports. The big story Future space food could be made from astronaut breath May 2023 The future of space food could be as simpleand weirdas a protein shake made with astronaut breath or a burger made from fungus. For decades, astronauts have relied mostly on pre-packaged food during their forays off our planet. With missions beyond Earth orbit in sight, a NASA-led competition is hoping to change all that and usher in a new era of sustainable space food. To solve the problem of feeding astronauts on long-duration missions, NASA asked companies to propose novel ways to develop sustainable foods for future missions. Around 200 rose to the challengecreating nutritious (and outlandish) culinary creations in the process. Read the full story. Jonathan O'Callaghan We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + These optical illusion bird sculptures are a sight to be seen. + Dont blame me if you end up wanting to eat this Bche de Nol in one sitting.+ Casio watches are 50 years oldand cooler than ever.+ Do you fly naked? (No, not like that..)

Business applications powered by AI are revolutionizing customer experiences, accelerating the speed of business, and driving employee productivity. In fact, according to research firm Frost & Sullivans 2024 Global State of AI report, 89% of organizations believe AI and machine learning will help them grow revenue, boost operational efficiency, and improve customer experience. Take for example, Vodafone. The telecommunications company is using a suite ofAzure AI services, such as Azure OpenAI Service,to deliver real-time, hyper-personalized experiences across all of its customer touchpoints, including its digital chatbot TOBi. By leveraging AI to increase customer satisfaction, Naga Surendran, senior director of product marketing for Azure Application Services at Microsoft, says Vodafone has managed to resolve 70% of its first-stage inquiries through AI-powered digital channels. It has also boosted the productivity of support agents by providing them with access to AI capabilities that mirror those of Microsoft Copilot, an AI-powered productivity tool. The result is a 20-point increase in net promotor score, he says. These benefits are whats driving AI infusion into every business process and application. Yet realizing measurable business value from AI-powered applications requires a new game plan. Legacy application architectures simply arent capable of meeting the high demands of AI-enhanced applications. Rather, the time is now for organizations to modernize their infrastructure, processes, and application architectures using cloud native technologies to stay competitive. The time is now for modernization Todays organizations exist in an era of geopolitical shifts, growing competition, supply chain disruptions, and evolving consumer preferences. AI applications can help by supporting innovation, but only if they have the flexibility to scale when needed. Fortunately, by modernizing applications, organizations can achieve the agile development, scalability, and fast compute performance needed to support rapid innovation and accelerate the delivery of AI applications. David Harmon, director of software development for AMD says companies, really want to make sure that they can migrate their current [environment] and take advantage of all the hardware changes as much as possible. The result is not only a reduction in the overall development lifecycle of new applications but a speedy response to changing world circumstances. Beyond building and deploying intelligent apps quickly, modernizing applications, data, and infrastructure can significantly improve customer experience. Consider, for example, Coles, an Australian supermarket thatinvested in modernization andis using data and AI to deliver dynamic e-commerce experiences to its customers both online and in-store. With Azure DevOps, Coles has shifted from monthly to weekly deployments of applications while, at the same time, reducing build times by hours. Whats more, by aggregating views of customers across multiple channels, Coles has been able to deliver more personalized customer experiences. In fact, according to a 2024 CMSWire Insights report, there is a significant rise in the use of AI across the digital customer experience toolset, with 55% of organizations now using it to some degree, and more beginning their journey. But even the most carefully designed applications are vulnerable to cybersecurity attacks. If given the opportunity, bad actors can extract sensitive information from machine learning models or maliciously infuse AI systems with corrupt data. AI applications are now interacting with your core organizational data, says Surendran. Having the right guard rails is important to make sure the data is secure and built on a platform that enables you to do that. The good news is modern cloud based architectures can deliver robust security, data governance, and AI guardrails like content safety to protect AI applications from security threats and ensure compliance with industry standards. The answer to AI innovation New challenges, from demanding customers to ill-intentioned hackers, call for a new approach to modernizing applications. You have to have the right underlying application architecture to be able to keep up with the market and bring applications faster to market, says Surendran. Not having that foundation can slow you down. Enter cloud native architecture. As organizations increasingly adopt AI to accelerate innovation and stay competitive, there is a growing urgency to rethink how applications are built and deployed in the cloud. By adopting cloud native architectures, Linux, and open source software, organizations can better facilitate AI adoption and create a flexible platform purpose built for AI and optimized for the cloud. Harmon explains that open source software creates options, And the overall open source ecosystem just thrives on that. It allows new technologies to come into play. Application modernization also ensures optimal performance, scale, and security for AI applications. Thats because modernization goes beyond just lifting and shifting application workloads to cloud virtual machines. Rather, a cloud native architecture is inherently designed to provide developers with the following features: The flexibility to scale to meet evolving needs Better access to the data needed to drive intelligent apps Access to the right tools and services to build and deploy intelligent applications easily Security embedded into an application to protect sensitive data Together, these cloud capabilities ensure organizations derive the greatest value from their AI applications. At the end of the day, everything is about performance and security, says Harmon. Cloud is no exception. Whats more, Surendran notes that when you leverage a cloud platform for modernization, organizations can gain access to AI models faster and get to market faster with building AI-powered applications. These are the factors driving the modernization journey. Best practices in play For all the benefits of application modernization, there are steps organizations must take to ensure both technological and operational success. They are: Train employees for speed. As modern infrastructure accelerates the development and deployment of AI-powered applications, developers must be prepared to work faster and smarter than ever. For this reason, Surendran warns, Employees must be skilled in modern application development practices to support the digital business needs. This includes developing expertise in working with loosely coupled microservices to build scalable and flexible application and AI integration. Start with an assessment. Large enterprises are likely to have hundreds of applications, if not thousands, says Surendran. As a result, organizations must take the time to evaluate their application landscape before embarking on a modernization journey. Starting with an assessment is super important, continues Surendran. Understanding, taking inventory of the different applications, which team is using what, and what this application is driving from a business process perspective is critical. Focus on quick wins. Modernization is a huge, long-term transformation in how companies build, deliver, and support applications. Most businesses are still learning and developing the right strategy to support innovation. For this reason, Surendran recommends focusing on quick wins while also working on a larger application estate transformation. You have to show a return on investment for your organization and business leaders, he says. For example, modernize some apps quickly with re-platforming and then infuse them with AI capabilities. Partner up. Modernization can be daunting, says Surendran. Selecting the right strategy, process, and platform to support innovation is only the first step. Organizations must also bring on the right set of partners to help them go through change management and the execution of this complex project. Address all layers of security. Organizations must be unrelenting when it comes to protecting their data. According to Surendran, this means adopting a multi-layer approach to security that includes: security by design, in which products and services are developed from the get-go with security in mind; security by default, in which protections exist at every layer and interaction where data exists; and security by ongoing operations, which means using the right tools and dashboards to govern applications throughout their lifecycle. A look to the future Most organizations are already aware of the need for application modernization. But with the arrival of AI comes the startling revelation that modernization efforts must be done right, and that AI applications must be built and deployed for greater business impact. Adopting a cloud native architecture can help by serving as a platform for enhanced performance, scalability, security, and ongoing innovation. As soon as you modernize your infrastructure with a cloud platform, you have access to these rapid innovations in AI models, says Surendran. Its about being able to continuously innovate with AI. Read more about how toaccelerate app and data estate readiness for AI innovationwithMicrosoft AzureandAMD. ExploreLinux on Azure. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Reviews editorial staff.

A small songbird soars above Ithaca, New York, on a September night. He is one of 4 billion birds, a great annual river of feathered migration across North America. Midair, he lets out what ornithologists call a nocturnal flight call to communicate with his flock. Its the briefest of signals, barely 50 milliseconds long, emitted in the woods in the middle of the night. But humans have caught it nevertheless, with a microphone topped by a focusing funnel. Moments later, software called BirdVoxDetect, the result of a collaboration between New York University, the Cornell Lab of Ornithology, and cole Centrale de Nantes, identifies the bird and classifies it to the species level. Biologists like Cornells Andrew Farnsworth had long dreamed of snooping on birds this way. In a warming world increasingly full of human infrastructure that can be deadly to them, like glass skyscrapers and power lines, migratory birds are facing many existential threats. Scientists rely on a combination of methods to track the timing and location of their migrations, but each has shortcomings. Doppler radar, with the weather filtered out, can detect the total biomass of birds in the air, but it cant break that total down by species. GPS tags on individual birds and careful observations by citizen-scientist birders help fill in that gap, but tagging birds at scale is an expensive and invasive proposition. And theres another key problem: Most birds migrate at night, when its more difficult to identify them visually and while most birders are in bed. For over a century, acoustic monitoring has hovered tantalizingly out of reach as a method that would solve ornithologists woes. In the late 1800s, scientists realized that migratory birds made species-specific nocturnal flight callsacoustic fingerprints. When microphones became commercially available in the 1950s, scientists began recording birds at night. Farnsworth led some of this acoustic ecology research in the 1990s. But even then it was challenging to spot the short calls, some of which are at the edge of the frequency range humans can hear. Scientists ended up with thousands of tapes they had to scour in real time while looking at spectrograms that visualize audio. Though digital technology made recording easier, the perpetual problem, Farnsworth says, was that it became increasingly easy to collect an enormous amount of audio data, but increasingly difficult to analyze even some of it. Then Farnsworth met Juan Pablo Bello, director of NYUs Music and Audio Research Lab. Fresh off a project using machine learning to identify sources of urban noise pollution in New York City, Bello agreed to take on the problem of nocturnal flight calls. He put together a team including the French machine-listening expert Vincent Lostanlen, and in 2015, the BirdVox project was born to automate the process. Everyone was like, Eventually, when this nut is cracked, this is going to be a super-rich source of information, Farnsworth says. But in the beginning, Lostanlen recalls, there was not even a hint that this was doable. It seemed unimaginable that machine learning could approach the listening abilities of experts like Farnsworth. Andrew is our hero, says Bello. The whole thing that we want to imitate with computers is Andrew. They started by training BirdVoxDetect, a neural network, to ignore faults like low buzzes caused by rainwater damage to microphones. Then they trained the system to detect flight calls, which differ between (and even within) species and can easily be confused with the chirp of a car alarm or a spring peeper. The challenge, Lostanlen says, was similar to the one a smart speaker faces when listening for its unique wake word, except in this case the distance from the target noise to the microphone is far greater (which means much more background noise to compensate for). And, of course, the scientists couldnt choose a unique sound like Alexa or Hey Google for their trigger. For birds, we dont really make that choice. Charles Darwin made that choice for us, he jokes. Luckily, they had a lot of training data to work withFarnsworths team had hand-annotated thousands of hours of recordings collected by the microphones in Ithaca. With BirdVoxDetect trained to detect flight calls, another difficult task lay ahead: teaching it to classify the detected calls by species, which few expert birders can do by ear. To deal with uncertainty, and because there is not training data for every species, they decided on a hierarchical system. For example, for a given call, BirdVoxDetect might be able to identify the birds order and family, even if its not sure about the speciesjust as a birder might at least identify a call as that of a warbler, whether yellow-rumped or chestnut-sided. In training, the neural network was penalized less when it mixed up birds that were closer on the taxonomical tree. Last August, capping off eight years of research, the team published a paper detailing BirdVoxDetects machine-learning algorithms. They also released the software as a free, open-source product for ornithologists to use and adapt. In a test on a full season of migration recordings totaling 6,671 hours, the neural network detected 233,124 flight calls. In a 2022 study in the Journal of Applied Ecology, the team that tested BirdVoxDetect found acoustic data as effective as radar for estimating total biomass. BirdVoxDetect works on a subset of North American migratory songbirds. But through few-shot learning, it can be trained to detect other, similar birds with just a few training examples. Its like learning a language similar to one you already speak, Bello says. With cheap microphones, the system could be expanded to places around the world without birders or Doppler radar, even in vastly different recording conditions. If you go to a bioacoustics conference and you talk to a number of people, they all have different use cases, says Lostanlen. The next step for bioacoustics, he says, is to create a foundation model, like the ones scientists are working on for natural-language processing and image and video analysis, that would be reconfigurable for any specieseven beyond birds. That way, scientists wont have to build a new BirdVoxDetect for every animal they want to study. The BirdVox project is now complete, but scientists are already building on its algorithms and approach. Benjamin Van Doren, a migration biologist at the University of Illinois Urbana-Champaign who worked on BirdVox, is using Nighthawk, a new user-friendly neural network based on both BirdVoxDetect and the popular birdsong ID app Merlin, to study birds migrating over Chicago and elsewhere in North and South America. And Dan Mennill, who runs a bioacoustics lab at the University of Windsor, says hes excited to try Nighthawk on flight calls his team currently hand-annotates after theyre recorded by microphones on the Canadian side of the Great Lakes. One weakness of acoustic monitoring is that unlike radar, a single microphone cant detect the altitude of a bird overhead or the direction in which it is moving. Mennills lab is experimenting with an array of eight microphones that can triangulate to solve that problem. Sifting through recordings has been slow. But with Nighthawk, the analysis will speed dramatically. With birds and other migratory animals under threat, Mennill says, BirdVoxDetect came at just the right time. Knowing exactly which birds are flying over in real time can help scientists keep tabs on how species are doing and where theyre going. That can inform practical conservation efforts like Lights Out initiatives that encourage skyscrapers to go dark at night to prevent bird collisions. Bioacoustics is the future of migration research, and were really just getting to the stage where we have the right tools, he says. This ushers us into a new era. Christian Elliott is a science and environmental reporter based in Illinois.

AI is all about data. Reams and reams of data are needed to train algorithms to do what we want, and what goes into the AI models determines what comes out. But heres the problem: AI developers and researchers dont really know much about the sources of the data they are using. AIs data collection practices are immature compared with the sophistication of AI model development. Massive data sets often lack clear information about what is in them and where it came from. The Data Provenance Initiative, a group of over 50 researchers from both academia and industry, wanted to fix that. They wanted to know, very simply: Where does the data to build AI come from? They audited nearly 4,000 public data sets spanning over 600 languages, 67 countries, and three decades. The data came from 800 unique sources and nearly 700 organizations. Their findings, shared exclusively with MIT Technology Review, show a worrying trend: AI's data practices risk concentrating power overwhelmingly in the hands of a few dominant technology companies. In the early 2010s, data sets came from a variety of sources, says Shayne Longpre, a researcher at MIT who is part of the project. It came not just from encyclopedias and the web, but also from sources such as parliamentary transcripts, earning calls, and weather reports. Back then, AI data sets were specifically curated and collected from different sources to suit individual tasks, Longpre says. Then transformers, the architecture underpinning language models, were invented in 2017, and the AI sector started seeing performance get better the bigger the models and data sets were. Today, most AI data sets are built by indiscriminately hoovering material from the internet. Since 2018, the web has been the dominant source for data sets used in all media, such as audio, images, and video, and a gap between scraped data and more curated data sets has emerged and widened. In foundation model development, nothing seems to matter more for the capabilities than the scale and heterogeneity of the data and the web, says Longpre. The need for scale has also boosted the use of synthetic data massively. The past few years have also seen the rise of multimodal generative AI models, which can generate videos and images. Like large language models, they need as much data as possible, and the best source for that has become YouTube. For video models, as you can see in this chart, over 70% of data for both speech and image data sets comes from one source. This could be a boon for Alphabet, Googles parent company, which owns YouTube. Whereas text is distributed across the web and controlled by many different websites and platforms, video data is extremely concentrated in one platform. It gives a huge concentration of power over a lot of the most important data on the web to one company, says Longpre. And because Google is also developing its own AI models, its massive advantage also raises questions about how the company will make this data available for competitors, says Sarah Myers West, the coexecutive director at the AI Now Institute. Its important to think about data not as though its sort of this naturally occurring resource, but its something that is created through particular processes, says Myers West. If the data sets on which most of the AI that were interacting with reflect the intentions and the design of big, profit-motivated corporationsthats reshaping the infrastructures of our world in ways that reflect the interests of those big corporations, she says. This monoculture also raises questions about how accurately the human experience is portrayed in the data set and what kinds of models we are building, says Sara Hooker, the vice president of research at the technology company Cohere, who is also part of the Data Provenance Initiative. People upload videos to YouTube with a particular audience in mind, and the way people act in those videos is often intended for very specific effect. Does [the data] capture all the nuances of humanity and all the ways that we exist? says Hooker. Hidden restrictions AI companies dont usually share what data they used to train their models. One reason is that they want to protect their competitive edge. The other is that because of the complicated and opaque way data sets are bundled, packaged, and distributed, they likely dont even know where all the data came from. They also probably dont have complete information about any constraints on how that data is supposed to be used or shared. The researchers at the Data Provenance Initiative found that data sets often have restrictive licenses or terms attached to them, which should limit their use for commercial purposes, for example. This lack of consistency across the data lineage makes it very hard for developers to make the right choice about what data to use, says Hooker. It also makes it almost impossible to be completely certain you havent trained your model on copyrighted data, adds Longpre. More recently, companies such as OpenAI and Google have struck exclusive data-sharing deals with publishers, major forums such as Reddit, and social media platforms on the web. But this becomes another way for them to concentrate their power. These exclusive contracts can partition the internet into various zones of who can get access to it and who cant, says Longpre. The trend benefits the biggest AI players, who can afford such deals, at the expense of researchers, nonprofits, and smaller companies, who will struggle to get access. The largest companies also have the best resources for crawling data sets. This is a new wave of asymmetric access that we havent seen to this extent on the open web, Longpre says. The West vs. the rest The data that is used to train AI models is also heavily skewed to the Western world. Over 90% of the data sets that the researchers analyzed came from Europe and North America, and fewer than 4% came from Africa. "These data sets are reflecting one part of our world and our culture, but completely omitting others," says Hooker. The dominance of the English language in training data is partly explained by the fact that the internet is still over 90% in English, and there are still a lot of places on Earth where theres really poor internet connection or none at all, says Giada Pistilli, principal ethicist at Hugging Face, who was not part of the research team. But another reason is convenience, she adds: Putting together data sets in other languages and taking other cultures into account requires conscious intention and a lot of work. The Western focus of these data sets becomes particularly clear with multimodal models. When an AI model is prompted for the sights and sounds of a wedding, for example, it might only be able to represent Western weddings, because thats all that it has been trained on, Hooker says. This reinforces biases and could lead to AI models that push a certain US-centric worldview, erasing other languages and cultures. We are using these models all over the world, and theres a massive discrepancy between the world were seeing and whats invisible to these models, Hooker says.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. AI is changing how we study bird migration In a warming world, migratory birds face many existential threats. Scientists rely on a combination of methods to track the timing and location of their migrations, but each has shortcomings. And theres another problem: Most birds migrate at night, when its more difficult to identify them visually and while most birders are in bed. For over a century, acoustic monitoring has hovered tantalizingly out of reach as a method that would solve ornithologists woes. Now, finally, machine-learning tools are unlocking a treasure trove of acoustic data for ecologists. Read the full story.Christian Elliot This story is from the forthcoming magazine edition of MIT Technology Review, set to go live on January 6its all about the exciting breakthroughs happening in the world right now. If you dont already, subscribe to receive a copy. A woman in the US is the third person to receive a gene-edited pig kidney Towana Looney, a 53-year-old woman from Alabama, has become the third living person to receive a kidney transplant from a gene-edited pig. Looney, who donated one of her kidneys to her mother back in 1999, developed kidney failure several years later following a pregnancy complication that caused high blood pressure. She started dialysis treatment in December of 2016 and was put on a waiting list for a kidney transplant soon after. But it was difficult to find a match. So Looneys doctors recommended the experimental pig organ as an alternative. After eight years on the waiting list, Looney was authorized to receive the kidney. Read the full story. Jessica Hamzelou Roundtables: The Worst Technology Failures of 2024 Each year, MIT Technology Review publishes a list of the worst technologies of the past 12 months. Antonio Regalado, our senior editor for biomedicine, sat down to discuss 2024s worst failures with our executive editor Niall Firth in a subscriber-exclusive online Roundtable event yesterday. Watch their conversation about what made the cut here, and to make sure you dont miss out in the future, subscribe!MIT Technology Review Narrated: Meet the radio-obsessed civilian shaping Ukraines drone defense Despite it being over 100 years old, radio technology is still critical in almost all aspects of modern warfareincluding in the drones that have come to dominate the Russia-Ukraine war. Serhii Flash Beskrestnov, who has been obsessed with radios since childhood, has become an unlikely hero of the conflict, sharing advice and intel. His work may determine the future of Ukraine, and wars far beyond it. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which were publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as its released.The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Conspiracy theories are still circulating about those mysterious drones What are they? And where have they come from? (NY Mag $)+ Authorities are attempting to quell public hysteria, but theories abound. (WP $)+ Realistically, theyre probably just standard drones out for a night-time flight. (AP News)2 AI poses a major threat to the power grid Thats according to the US industry watchdog, which is feeling the pressure. (FT $)+ AIs emissions are about to skyrocket even further. (MIT Technology Review)3 SpaceX and Elon Musk are under investigation US federal agencies are probing their repeated failures to comply with reporting rules. (NYT $)4 Nvidia has unveiled a tiny, affordable AI supercomputer Which is handy for roboticists looking to bypass connecting to remote data centers. (Gizmodo)+ While its not the companys most powerful device, its pretty speedy. (WSJ $)+ Microsoft is gobbling up more of Nvidias chips than anyone else. (FT $)+ Blacklisted Chinese AI chip firms gained access to cutting-edge UK tech. (The Guardian) 5 Bitcoins value is rocketing even higherThe industry continues to boom in the wake of Trumps election victory. (Bloomberg $) + So much so, luxury brands are weighing up accepting crypto payments. (Reuters)6 Hepatitis B is an extremely treatable diseaseSo why are so many people still dying from it? (New Yorker $) + Were starting to understand the mysterious surge of hepatitis in children. (MIT Technology Review)7 Earthbrieflyhad an extra second moon And scientists believe it originated from the actual moon we know and love. (New Scientist $) 8 The future of deep-sea miningA set of rules governing how we should do it is highly contentiousand up for debate.(Hakai Magazine) + These deep-sea potatoes could be the future of mining for renewable energy. (MIT Technology Review)9 Resist the temptation to outsource your Christmas shopping to a bot You never know what youll end up with. (Insider $)+ Its probably quicker to browse the web yourself. (WP $)10 Our snacks could soon be designed by AI Confectionary giant Mondelez is using the tech to tweak recipes and test new ones. (WSJ $)+ Forget cookiesthis creamy vegan cheese was made with AI. (MIT Technology Review) Quote of the day It takes a lot for an uber-wealthy, creative-type CEO, many of whom lean left, to suck it up and deal with Trump. But what choice do they have? A Washington lobbyist explains to the Financial Times why the steady stream of tech executives paying their respects to US President-elect Donald Trump shows no sign of slowing. The big story What does GPT-3 know about me? August 2022 One of the biggest stories in tech is the rise of large language models that produce text that reads like a human might have written it. These models power comes from being trained on troves of publicly available human-created text hoovered up from the internet. If youve posted anything even remotely personal in English on the internet, chances are your data might be part of some of the worlds most popular LLMs. Melissa Heikkil, MIT Technology Reviews AI reporter, wondered what data these models might have on herand how it could be misused. So she put OpenAIs GPT-3 to the test. Read about what she found.We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + 2024 was a seriously weird year, as evidenced by this completely bonkers list.+ Who knew Seal was such a grunge head?+ These Charli xcx Christmas mashups will haunt my dreams forever, and not in a good way.+ Next summer I feel the need to level up my sandcastle game.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. If you drove by one of the 2,990 data centers in the United States, youd probably think little more than Huh, thats a boring-looking building. You might not even notice it at all. However, these facilities underpin our entire digital world, and they are responsible for tons of greenhouse-gas emissions. New research shows just how much those emissions have skyrocketed during the AI boom. Since 2018, carbon emissions from data centers in the US have tripled, according to new research led by a team at the Harvard T.H. Chan School of Public Health. That puts data centers slightly below domestic commercial airlines as a source of this pollution. That leaves a big problem for the worlds leading AI companies, which are caught between pressure to meet their own sustainability goals and the relentless competition in AI thats leading them to build bigger models requiring tons of energy. The trend toward ever more energy-intensive new AI models, including video generators like OpenAIs Sora, will only send those numbers higher. A growing coalition of companies is looking toward nuclear energy as a way to power artificial intelligence. Meta announced on December 3 it was looking for nuclear partners, and Microsoft is working to restart the Three Mile Island nuclear plant by 2028. Amazon signed nuclear agreements in October. However, nuclear plants take ages to come online. And though public support has increased in recent years, and president-elect Donald Trump has signaled support, only a slight majority of Americans say they favor more nuclear plants to generate electricity. Though OpenAI CEO Sam Altman pitched the White House in September on an unprecedented effort to build more data centers, the AI industry is looking far beyond the United States. Countries in Southeast Asia, like Malaysia, Indonesia, Thailand, and Vietnam, are all courting AI companies, hoping to be their new data center hubs. In the meantime, AI companies will continue to use up power from their current sources, which are far from renewable. Since so many data centers are located in coal-producing regions, like Virginia, the carbon intensity of the energy they use is 48% higher than the national average. The researchers found that 95% of data centers in the US are built in places with sources of electricity that are dirtier than the national average. Read more about the new research here. Deeper Learning We saw a demo of the new AI system powering Andurils vision for war Were living through the first drone wars, but AI is poised to change the future of warfare even more drastically. I saw that firsthand during a visit to a test site in Southern California run by Anduril, the maker of AI-powered drones, autonomous submarines, and missiles. Anduril has built a way for the military to command much of its hardwarefrom drones to radars to unmanned fighter jetsfrom a single computer screen. Why it matters: Anduril, other companies in defense tech, and growing numbers of people within the Pentagon itself are increasingly adopting a new worldview: A future great power conflictmilitary jargon for a global war involving multiple countrieswill not be won by the entity with the most advanced drones or firepower, or even the cheapest firepower. It will be won by whoever can sort through and share information the fastest. The Pentagon is betting lots of energy and money that AIdespite its flaws and riskswill be what puts the US and its allies ahead in that fight. Read more here. Bits and Bytes Bluesky has an impersonator problem The platforms rise has brought with it a surge of crypto scammers, as my colleague Melissa Heikkil experienced firsthand. (MIT Technology Review) Techs elite make large donations to Trump ahead of his inauguration Leaders in Big Tech, who have been lambasted by Donald Trump, have made sizable donations to his inauguration committee. (The Washington Post) Inside the premiere of the first commercially streaming AI-generated movies The films, according to writer Jason Koebler, showed the telltale flaws of AI-generated video: dead eyes, vacant expressions, unnatural movements, and a reliance on voice-overs, since dialogue doesnt work well. The company behind the films is confident viewers will stomach them anyway. (404 Media) Meta asked Californias attorney general to stop OpenAI from becoming for-profit Meta now joins Elon Musk in alleging that OpenAI has improperly enjoyed the benefits of nonprofit status while developing its technology. (Wall Street Journal) How Silicon Valley is disrupting democracy Two books explore the price weve paid for handing over unprecedented power to Big Techand explain why its imperative we start taking it back. (MIT Technology Review)

They say you learn more from failure than success. If so, this is the story for you: MIT Technology Reviews annual roll call of the biggest flops, flimflams, and fiascos in all domains of technology. Some of the foul-ups were funny, like the "woke AI which got Google in trouble after it drew Black Nazis. Some caused lawsuits, like a computer error by CrowdStrike that left thousands of Delta passengers stranded. We also reaped failures among startups that raced to expand from 2020 to 2022, a period of ultra-low interest rates. But then the economic winds shifted. Money wasnt free anymore. The result? Bankruptcy and dissolution for companies whose ambitious technological projects, from vertical farms to carbon credits, hadnt yet turned a profit and might never do so. Read on. Woke AI blunder GOOGLE GEMINI VIA X.COM/END WOKENESS People worry about bias creeping into AI. But what if you add bias on purpose? Thanks to Google, we know where that leads: Black Vikings and female popes. Googles Gemini AI image feature, launched last February, had been tuned to zealously showcase diversity, damn the history books. Ask Google for a picture of German soldiers from World War II, and it would create a Benetton ad in Wehrmacht uniforms. Critics pounced and Google beat an embarrassed retreat. It paused Geminis ability to draw people and agreed its well-intentioned effort to be inclusive had missed the mark. The free version of Gemini still wont create images of people. But paid versions will. When we asked for an image of 12 CEOs of public biotech companies, the software produced a photographic-quality image of middle-aged white men. Less than ideal. But closer to the truth. More: Is Googles Gemini chatbot woke by accident, or by design? (The Economist), Gemini image generation got it wrong. We'll do better. (Google) Boeing Starliner THE BOEING COMPANY VIA NASA Boeing, we have a problem. And its your long-delayed reusable spaceship, the Starliner, which stranded NASA astronauts Sunita Suni Williams and Barry Butch Wilmore on the International Space Station. The June mission was meant to be a quick eight-day round trip to test Starliner before it embarked on longer missions. But, plagued by helium leaks and thruster problems, it had to come back empty. Now Butch and Suni wont return to Earth until 2025, when a craft from Boeing competitor SpaceX is scheduled to bring them home. Credit Boeing and NASA with putting safety first. But this wasnt Boeings only malfunction during 2024. The company began the year with a door blowing off one of its planes midflight, faced a worker strike, agreed to a major fine for misleading the government about the safety of its 737 Max airplane (which made our 2019 list of worst technologies), and saw its CEO step down in March. After the Starliner fiasco, Boeing fired the chief of its space and defense unit. At this critical juncture, our priority is to restore the trust of our customers and meet the high standards they expect of us to enable their critical missions around the world, Boeings new CEO, Kelly Ortberg, said in a memo. CrowdStrike outage MITTR / ENVATO The motto of the cybersecurity company CrowdStrike is We stop breaches. And its true: No one can breach your computer if you cant turn it on. Thats exactly what happened to many people on July 19, when thousands of Windows computers at airlines, TV stations, and hospitals started displaying the blue screen of death. The cause wasnt hackers or ransomware. Instead, those computers were stuck in a boot loop because of a bad update shipped by CrowdStrike itself. CEO George Kurtz jumped on X to say the issue had been identified as a defect in a single computer file. So who is liable? CrowdStrike customer Delta Airlines, which canceled 7,000 flights, is suing for $500 million. It alleges that the security firm caused a global catastrophe when it took uncertified and untested shortcuts. CrowdStrike countersued. It says Deltas management is to blame for its troubles and that the airline is due little more than a refund. More: Crowdstrike is working with customers(George Kurtz), How to fix a Windows PC affected by the global outage (MIT Technology Review), Delta Sues CrowdStrike Over July Operations Meltdown (WSJ) Vertical farms MITTR / ENVATO Grow lettuce in buildings using robots, hydroponics, and LED lights. Thats what Bowery, a vertical farming startup, raised over $700 million to do. But in November, Bowery went bust, making it the biggest startup failure of the year, according to the business analytics firm CB Insights. Bowery claimed that vertical farms were 100 times more productive per square foot than traditional farms, since racks of plants could be stacked 40 feet high. In reality, the companys lettuce was more expensive, and when a stubborn plant infection spread through its East Coast facilities, Bowery had trouble delivering the green stuff at any price. More: How a leaf-eating pathogen, failed deals brought down Bowery Farming (Pitchbook), Vertical farming "unicorn" Bowery to shut down (Axios) Exploding pagers MITTR / ADOBE STOCK They beeped, and then they blew up. Across Lebanon, fingers and faces were shredded in what was called Israels surprise opening blow in an all-out war to try to cripple Hezbollah. The deadly attack was diabolically clever. Israel set up shell companies that sold thousands of pagers packed with explosives to the Islamic faction, which was already worried that its phones were being spied on. A coup for Israels spies. But was it a war crime? A 1996 treaty prohibits intentionally manufacturing apparently harmless objects designed to explode. The New York Times says nine-year-old Fatima Abdullah died when her fathers booby-trapped beeper chimed and she raced to take it to him. More: Israel conducted Lebanon pager attack (Axios), A 9-Year-Old Girl Killed in Pager Attack Is Mourned in Lebanon (New York Times), Did Israel break international law? (Middle East Eye) 23andMe MITTR / ADOBE STOCK The company that pioneered direct-to-consumer gene testing is sinking fast. Its stock price is going toward zero, and a plan to create valuable drugs is kaput after that team got pink slips this November. 23andMe always had a celebrity aura, bathing in good press. Now, though, the press is all bad. Its a troubled company in the grip of a controlling founder, Anne Wojcicki, after its independent directors resigned en masse this September. Customers are starting to worry about whats going to happen to their DNA data if 23andMe goes under. 23andMe says it created the worlds largest crowdsourced platform for genetic research. Thats true. It just never figured out how to turn a profit. More: 23andMes fall from $6 billion to nearly $0 (Wall Street Journal), How todelete your 23andMe data (MIT Technology Review), 23andMe Financial Report, November 2024 (23andMe) AI slop AUTHOR UNKNOWN VIA WIKIMEDIA COMMONS Slop is the scraps and leftovers that pigs eat. AI slop is what you and I are increasingly consuming online now that people are flooding the internet with computer-generated text and pictures. AI slop is dubious, says the New York Times, and dadaist, according to Wired. Its frequently weird, like Shrimp Jesus (dont ask if you dont know), or deceptive, like the picture of a shivering girl in a rowboat, supposedly showing the US governments poor response to Hurricane Helene. AI slop is often entertaining. AI slop is usually a waste of your time. AI slop is not fact-checked. AI slop exists mostly to get clicks. AI slop is that blue-check account on X posting 10-part threads on how great AI isthreads that were written by AI. Most of all, AI slop is very, very common. This year, researchers claimed that about half the long posts on LinkedIn and Medium were partly AI-generated. More: First came Spam. Now, With A.I., Weve got Slop (New York Times), AI Slop Is Flooding Medium (Wired) Voluntary carbon markets MITTR / ENVATO Your business creates emissions that contribute to global warming. So why not pay to have some trees planted or buy a more efficient cookstove for someone in Central America? Then you could reach net-zero emissions and help save the planet. Neat idea, but good intentions aren't enough. This year the carbon marketplace Nori shut down, and so did Running Tide, a firm trying to sink carbon into the ocean. The problem is the voluntary carbon market is voluntary, Running Tides CEO wrote in a farewell post, citing a lack of demand. While companies like to blame low demand, it's not the only issue. Sketchy technology, questionable credits, and make-believe offsets have created a credibility problem in carbon markets. In October, US prosecutors charged two men in a $100 million scheme involving the sale of nonexistent emissions savings. More: The growing signs of trouble for global carbon markets (MIT Technology Review), Running Tides ill-fated adventure in ocean carbon removal (Canary Media), Ex-carbon offsetting boss charged in New York with multimillion-dollar fraud (The Guardian)

Recorded on December 17, 2024The Worst Technology Failures of 2024Speakers: Antonio Regalado, senior editor for biomedicine, and Niall Firth, executive editor.MIT Technology Review publishes an annual list of the worst technologies of the year. This year, The Worst Technology Failures of 2024 list was unveiled live by our editors. Hear fromMIT Technology Reviewexecutive editor Niall Firth and senior editor for biomedicine Antonio Regalado as they discuss each of the 8 items on this list.Related CoverageThe 8 worst technology failures of 2024The worst technology failures of 2023The worst technology of 2022

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. The 8 worst technology failures of 2024 They say you learn more from failure than success. If so, this is the story for you: MIT Technology Reviews annual roll call of the biggest flops, flimflams, and fiascos in all domains of technology. Some of the foul-ups were funny, like the "woke AI which got Google in trouble after it drew Black Nazis. Some caused lawsuits, like a computer error by CrowdStrike that left thousands of Delta passengers stranded. And we also reaped failures among startups that raced to expand from 2020 to 2022, a period of ultra-low interest rates. Check out what made our list of this years biggest technology failures. Antonio Regalado Antonio will be discussing this years worst failures with our executive editor Niall Firth in a subscriber-exclusive online Roundtable event today at 12.00 ET. Register here to make sure you dont miss outf you havent already, subscribe! AIs search for more energy is growing more urgent If you drove by one of the 2,990 data centers in the United States, youd probably think little more than Huh, thats a boring-looking building. You might not even notice it at all. However, these facilities underpin our entire digital world, and they are responsible for tons of greenhouse-gas emissions. New research shows just how much those emissions have skyrocketed during the AI boom. That leaves a big problem for the worlds leading AI companies, which are caught between pressure to meet their own sustainability goals and the relentless competition in AI thats leading them to build bigger models requiring tons of energy. And the trend toward ever more energy-intensive new AI models will only send those numbers higher. Read the full story.James O'Donnell This story originally appeared in The Algorithm, our weekly newsletter on AI. Sign up to receive it in your inbox every Monday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 TikTok has asked the US Supreme Court for a lifeline Its asked lawmakers to intervene before the proposed ban kicks in on January 19. (WP $)+ TikTok CEO Shou Zi Chew reportedly met with Donald Trump yesterday. (NBC News)+ Trump will take office the following day, on January 20. (WSJ $)+ Meanwhile, the EU is investigating TikToks role in Romanias election. (Politico)2 Waymos autonomous cars are heading to Tokyo In the first overseas venture for the firms vehicles. (The Verge)+ The cars will require human safety drivers initially. (CNBC)+ Whats next for robotaxis in 2024. (MIT Technology Review)3 Chinas tech workers are still keen to work in the US But securing the right to work there is much tougher than it used to be. (Rest of World)4 Digital license plates are vulnerable to hacking And theyre already legal to buy in multiple US states. (Wired $) 5 Were all slaves to the algorithmsFrom the mundane (Spotify) to the essential (housing applications.) (The Atlantic $) + How a group of tenants took on screening systemsand won. (The Guardian)+ The coming war on the hidden algorithms that trap people in poverty. (MIT Technology Review)6 How to build an undetectable submarine The race is on to stay hidden from the competition. (IEEE Spectrum)+ How underwater drones could shape a potential Taiwan-China conflict. (MIT Technology Review)7 How Empower became a viable rival to UberIts refusal to cooperate with authorities is straight out of Ubers early playbook. (NYT $) 8 Even airlines are using AirTags to find lost luggage Bloomberg $) + Heres how to keep tabs on your suitcase as you travel. (Forbes $)9 Youre reading your blood pressure all wrong Keep your feet flat on the floor and ditch your phone, for a start. (WSJ $)10 The rise and rise of the group chat Expressing yourself publicly on social media is so last year. (Insider $)+ How to fix the internet. (MIT Technology Review)Quote of the day Where are the adults in the room? Francesca Marano, a long-time contributor to WordPress, lambasts the platforms decision to require users to check a box reading Pineapple is delicious on pizza to log in, 404 Media reports. The big story Responsible AI has a burnout problem October 2022 Margaret Mitchell had been working at Google for two years before she realized she needed a break. Only after she spoke with a therapist did she understand the problem: she was burnt out. Mitchell, who now works as chief ethics scientist at the AI startup Hugging Face, is far from alone in her experience. Burnout is becoming increasingly common in responsible AI teams. All the practitioners MIT Technology Review interviewed spoke enthusiastically about their work: it is fueled by passion, a sense of urgency, and the satisfaction of building solutions for real problems. But that sense of mission can be overwhelming without the right support. Read the full story. Melissa Heikkil We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet 'em at me.) + This timelapse of a pine tree growing from a tiny pinecone is pretty special + Shaboozeys A Bar Song (Tipsy) is one of 2024s biggest hits. But why has it struck such a chord?+ All hail Londons campest Christmas tree!+ Stay vigilant, Oregons googly eye bandit has struck again

Towana Looney, a 53-year-old woman from Alabama, has become the third living person to receive a kidney transplant from a gene-edited pig. Looney, who donated one of her kidneys to her mother back in 1999, developed kidney failure several years later following a pregnancy complication that caused high blood pressure. She started dialysis treatment in December of 2016 and was put on a waiting list for a kidney transplant soon after, in early 2017. But it was difficult to find a match. So Looneys doctors recommended the experimental pig organ as an alternative. After eight years on the waiting list, Looney was authorized to receive the kidney under the US Food and Drug Administrations expanded access program, which allows people with serious or life-threatening conditions to try experimental treatments. The pig in question was developed by Revivicor, a United Therapeutics company. The companys technique involves making 10 gene edits to a pig cell. The edits are made to prevent too much organ growth, curb inflammation, and, importantly, stop the recipients immune system from rejecting the organ. The edited pig cell is then placed into a pig egg cell that has had its nucleus removed, and the egg is transferred to the uterus of a sow, which eventually gives birth to a gene-edited piglet. JOE CARROTTA FOR NYU LANGONE HEALTH In theory, once the piglet has grown, its organs can be used for human transplantation. Pig organs are similar in size to human ones, after all. A few years ago, David Bennett Sr. became the first person to receive a heart transplant from such a pig. He died two months after the operation, and the heart was later found to have been infected with a pig virus. Richard Slayman was the first person to get a gene-edited pig kidney, which he received in early 2024. He died two months after his surgery, although the hospital treating him said in a statement that it had no indication that it was the result of his recent transplant. In April, Lisa Pisano was reported to be the second person to receive such an organ. Pisano also received a heart pump alongside her kidney transplant. Her kidney failed because of an inadequate blood supply and was removed the following month. She died in July. Looney received her pig kidney during a seven-hour operation that took place at NYU Langone Health in New York City on November 25. The surgery was led by Jayme Locke of the US Health Resources & Services Administration and Robert Montgomery of the NYU Langone Transplant Institute. Looney was discharged from the hospital 11 days after her surgery, to an apartment in New York City. Shell stay in New York for another three months so she can check in with doctors at the hospital for evaluations. Its a blessing, Looney said in a statement. I feel like Ive been given another chance at life. I cannot wait to be able to travel again and spend more quality time with my family and grandchildren. Looneys doctors are hopeful that her kidney will last longer than those of her predecessors. For a start, Looney was in better health to begin withshe had chronic kidney disease and required dialysis, but unlike previous recipients, she was not close to death, Montgomery said in a briefing. He and his colleagues plan to start clinical trials within the next year. There is a huge unmet need for organs. In the US alone, there more than 100,000 people are waiting for one, and 17 people on the waiting list die every day. Researchers hope that gene-edited animals might provide a new source of organs for such individuals. Revivicor isnt the only company working on this. Rival company eGenesis, which has a different approach to gene editing, has used CRISPR to create pigs with around 70 gene edits. Transplant is one of the few therapies that can cure a complex disease overnight, yet there are too few organs to provide a cure for all in need, Locke said in a statement. The thought that we may now have a solution to the organ shortage crisis for others who have languished on our waiting lists invokes the most welcome of feelings: pure joy! Today, Looney is the only person living with a pig organ. I am full of energy. I got an appetite Ive never had in eight years, she said at a briefing. I can put my hand on this kidney and feel it buzzing. This story has been updated with additional information after a press briefing.

Last week, this space was all about OpenAIs 12 days of shipmas. This week, the spotlight is on Google, which has been speeding toward the holiday by shipping or announcing its own flurry of products and updates. The combination of stuff here is pretty monumental, not just for a single company, but I think because it speaks to the power of the technology industryeven if it does trigger a personal desire that we could do more to harness that power and put it to more noble uses. To start, last week Google Introduced Veo, a new video generation model, and Imagen 3, a new version of its image generation model.Then on Monday, Google announced a breakthrough in quantum computing with its Willow chip. The company claims the new machine is capable of a standard benchmark computation in under five minutes that would take one of todays fastest supercomputers 10 septillion (that is, 1025) years. you may recall that MIT Technology Review covered some of the Willow work after researchers posted a paper preprint in August. But this week marked the big media splash. It was a stunning update that had Silicon Valley abuzz. (Seriously, I have never gotten so many quantum computing pitches as in the past few days.) Google followed this on Wednesday with even more gifts: a Gemini 2 release, a Project Astra update, and even more news about forthcoming agents called Mariner, an agent that can browse the web, and Jules, a coding assistant. First: Gemini 2. Its impressive, with a lot of performance updates. But I have frankly grown a little inured by language-model performance updates to the point of apathy. Or at least near-apathy. I want to see them do something. So for me, the cooler update was second on the list: Project Astra, which comes across like an AI from a futuristic movie set. Google first showed a demo of Astra back in May at its developer conference, and it was the talk of the show. But, since demos offer companies chances to show off products at their most polished, it can be hard to tell whats real and whats just staged for the audience. Still, when my colleague Will Douglas Heaven recently got to try it out himself, live and unscripted, it largely lived up to the hype. Although he found it glitchy, he noted that those glitches can be easily corrected. He called the experience stunning and said it could be generative AIs killer app.On top of all this, Will notes that this week Google DeepMind CEO (the companys AI division) Demis Hassabis was in Sweden to receive his Nobel Prize. And what did you do with your week? Making all this even more impressive, the advances represented in Willow, Gemini, Astra, and Veo are ones that just a few years ago many, many people would have said were not possibleor at least not in this timeframe.A popular knock on the tech industry is that it has a tendency to over-promise and under-deliver. The phone in your pocket gives the lie to this. So too do the rides I took in Waymos self-driving cars this week. (Both of which arrived faster than Ubers estimated wait time. And honestly its not been that long since the mere ability to summon an Uber was cool!) And while quantum has a long way to go, the Willow announcement seems like an exceptional advance; if not a tipping point exactly, then at least a real waypoint on a long road. (For what its worth, Im still not totally sold on chatbots. They do offer novel ways of interacting with computers, and have revolutionized information retrieval. But whether they are beneficial for humanityespecially given energy debts, the use of copyrighted material in their training data, their perhaps insurmountable tendency to hallucinate, etc.is debatable, and certainly is being debated. But Im pretty floored by this weeks announcements from Google, as well as OpenAIfull stop.) And for all the necessary and overdue talk about reining in the power of Big Tech, the ability to hit significant new milestones on so many different fronts all at once is something that only a company with the resources of a Google (or Apple or Microsoft or Amazon or Meta or Baidu or whichever other behemoth) can do.All this said, I dont want us to buy more gadgets or spend more time looking at our screens. I dont want us to become more isolated physically, socializing with others only via our electronic devices. I dont want us to fill the air with carbon or our soil with e-waste. I do not think these things should be the price we pay to drive progress forward. Its indisputable that humanity would be better served if more of the tech industry was focused on ending poverty and hunger and disease and war. Yet every once in a while, in the ever-rising tide of hype and nonsense that pumps out of Silicon Valley, epitomized by the AI gold rush of the past couple of years, there are moments that make me sit back in awe and amazement at what people can achieve, and in which I become hopeful about our ability to actually solve our larger problemsif only because we can solve so many other dumber, but incredibly complicated ones. This week was one of those times for me. Now read the rest of The Debrief The News Robotaxi adoptionis hitting a tipping point. But also,GM is shutting down its Cruise robotaxi division. Hereshow to use OpenAIs new video editing toolSora. Blueskyhas an impersonator problem. The AI hype machine iscoming under government scrutiny. The Chat Every week, I talk to one of MIT Technology Reviews journalists to go behind the scenes of a story they are working on. This week, I hit up James ODonnell, who covers AI and hardware, about his story on how the startup defense contractorAnduril is bringing AI to the battlefield. Mat:James, you got a pretty up close look at something most people probably havent even thought about yet, which is how the future of AI-assisted warfare might look. What did you learn on that trip that you think will surprise people? James:Two things stand out. One, I think people would be surprised by the gulf between how technology has developed for the last 15 years for consumers versus the military. For consumers, weve gotten phones, computers, smart TVs and other technologies that generally do a pretty good job of talking to each other and sharing our data, even though theyre made by dozens of different manufacturers. Its called the internet of things. In the military, technology has developed in exactly the opposite way, and its putting them in a crisis. They have stealth aircraft all over the world, but communicating about a drone threat might be done with Powerpoints and a chat service reminiscent of AOL Instant Messenger. The second is just how much the Pentagon is now looking to AI to change all of this. New initiatives have surged in the current AI boom. They are spending on training new AI models to better detect threats, autonomous fighter jets, and intelligence platforms that use AI to find pertinent information. What I saw at Andurils test site in California is also a key piece of that. Using AI to connect to and control lots of different pieces of hardware, like drones and cameras and submarines, from a single platform. The amount being invested in AI is much smaller than for aircraft carriers and jets, but its growing. Mat:I was talking with a different startup defense contractor recently, who was talking to me about the difficulty of getting all these increasingly autonomous devices on the battlefield talking to each other in a coordinated way. Like Anduril, he was making the case that this has to be done at the edge, and that there is too much happening for human decision making to process. Do you think thats true? Why is that? James:So many in the defense space have pointed to the war in Ukraine as a sign that warfare is changing. Drones are cheaper and more capable than they ever were in the wars in the Middle East. Its why the Pentagon is spending $1 billion on the Replicator initiative to fieldthousands of cheap dronesby 2025. Its also looking to field more underwater drones as it plans for scenarios in which China may invade Taiwan. Once you get these systems, though, the problem is having all the devices communicate with one another securely. You need to play Air Traffic Control at the same time that youre pulling in satellite imagery and intelligence information, all in environments where communication links are vulnerable to attacks. Mat:I guess I still have a mental image of a control room somewhere, like you might see inDr. StrangeloveorWar Games(orStar Warsfor that matter) with a handful of humans directing things. Are those days over? James:I think a couple things will change. One, a single person in that control room will be responsible for a lot more than they are now. Rather than running just one camera or drone system manually, theyll command software that does it for them, for lots of different devices. The idea that the defense tech sector is pushing is to take them out of the mundane tasksrotating a camera around to look for threatsand instead put them in the drivers seat for decisions that only humans, not machines, can make. Mat:I know that critics of the industry push back on the idea of AI being empowered to make battlefield decisions, particularly when it comes to life and death, but it seems to me that we are increasingly creeping toward that and it seems perhaps inevitable. Whats your sense? James:This is painting with broad strokes, but I think the debates about military AI fall along similar lines to what we see for autonomous vehicles. You have proponents saying that driving is not a thing humans are particularly good at, and when they make mistakes, it takes lives. Others might agree conceptually, but debate at what point its appropriate to fully adopt fallible self-driving technology in the real world. How much better does it have to be than humans? In the military, the stakes are higher. Theres no question that AI is increasingly being used to sort through and surface information to decision-makers. Its finding patterns in data, translating information, and identifying possible threats. Proponents are outspoken that that will make warfare more precise and reduce casualties. What critics are concerned about is how far across that decision-making pipeline AI is going, and how much there is human oversight. I think where it leaves me is wanting transparency. When AI systems make mistakes, just like when human military commanders make mistakes, I think we deserve to know, and that transparency does not have to compromise national security. It tookyearsfor reporter Azmat Khan to piece together the mistakes made during drone strikes in the Middle East, because agencies were not forthcoming. That obfuscation absolutely cannot be the norm as we enter the age of military AI. Mat:Finally, did you have a chance to hit an In-N-Out burger while you were in California? James:Normally In-N-Out is a requisite stop for me in California, but ahead of my trip I heard lots of good things about the burgers at The Apple Pan in West LA, so I went there. To be honest, the fries were better, but for the burger I have to hand it to In-N-Out. The Recommendation A few weeks ago I suggestedCa7riel and Paco Amorosos appearance on NPR Tiny Desk. At the risk of this space becoming a Tiny Desk stan account, Im back again with another. I was completely floored byDoechiis Tiny Desk appearance last week. Its so full of talent and joy and style and power. I came away completely inspired and have basically had her music on repeat in Spotify ever since. If you are already a fan of her recorded music, you will love her live. If shes new to you, well, youre welcome. Go check it out. Oh, and dont worry: Im not planning to recommendBillie Eilishs new Tiny Desk concertin next weeks newsletter. Mostly because Im doing so now.

AIs emissions are about to skyrocket even further Its no secret that the current AI boom is using up immense amounts of energy. Now we have a better idea of how much. A new paper, from a team at the Harvard T.H. Chan School of Public Health, examined 78% of all data centers in the country in the US. These facilitiesessentially buildings filled to the brim with rows of serversare where AI models get trained, and they also get pinged every time we send a request through models like ChatGPT. They require huge amounts of energy both to power the servers and to keep them cool. Since 2018, carbon emissions from data centers in the US have tripled.Its difficult to put a number on how much AI in particular is responsible for this surge. But AIs share is certainly growing rapidly as nearly every segment of the economy attempts to adopt the technology. Read the full story. Googles big week was a flex for the power of big tech Google has been speeding toward the holiday by shipping or announcing a flurry of products and updates. The combination of stuff here is pretty monumental, not just for a single company, but I think because it speaks to the power of the technology industryeven if it does trigger a personal desire that we could do more to harness that power and put it to more noble uses.Read more here. This story originally appeared in The Debrief with Mat Honan, our weekly take on whats really going on behind the biggest tech headlines. The story is subscriber-only sonab a subscriptiontoo, if you havent already! Or you cansign upto the newsletter for free to get the next edition in your inbox on Friday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Mysterious drones have been spotted along the US east coast People are getting a bit freaked out, to say the least. (BBC) Although sometimes theyre just small planes, authorities say.(Wired) Trump says they should be shot down.(Politico) 2 TikTok could be gone from app stores by January 19 Last week, a US appeals court upheld a law forcing Bytedance to divest. (Reuters) The rationale behind the ban could open the door to other regulations that suppress speech.(Atlantic) Influencers are putting together their post-TikTok plans.(Business Insider) The long-shot plan to save TikTok. (Verge) The depressing truth about the coming ban.(MIT Technology Review) 3 Authorities in Serbia are using phone-cracking tools to install spyware Activists and journalists found their phone had been tampered with after a run-in with police. (404 Media) 4 Cellphone videos are fueling violence inside US schools Students are using phones to arrange, provoke and capture brawls in the corridors. (NYT) 5 AI search startup Perplexity says it will generate $10.5 million a month next year Its in talks to raise money at a $9 billion valuation. (The Information) AI search could break the web. (MIT Technology Review) 6 How Musks partnership with Trump could influence science Even if he cant cut as much as hed like, he still stands to make big changes. (Nature) Is deleting the IRS his worst idea yet?(Washington Post) The top cybersecurity agency is bracing for Trump. (Wired) Trumps win is a huge loss for the climate.(MIT Technology Review) 7 AI firms will scour the globe looking for cheap energy Low-cost power is an absolute priority. (Wired) Its an insatiably hungry industry.(Bloomberg) 8 Anthropics Claude is winning the chatbot battle for tech insiders Its not as big as ChatGPT, but it's got a special something that people like. (NYT) A new Character.ai chatbot for teens will no longer talk romance. (Verge) How to trust what a chatbot says.(MIT Technology Review) 9 The reaction to the UnitedHealthcare CEOs murder could prompt a reckoning Healthcares algorithmic decision-making turns us into numbers on a spreadsheets. (Vanity Fair) Luigi Mangione has to mean something. (Atlantic) 10 How Chinas satellite megaprojects are challenging Starlink Between them, Qianfan, Guo Wang and Honghu-3 could have as many satellites.(CNBC) Quote of the day Weve achieved peak data and therell be no more. OpenAIs cofounder and former chief scientist, Ilya Sutskever, tells the NeurIPS conference that the way AI models will be trained will have to change. The big story How to stop a state from sinkingApril 2024 In a 10-month span between 2020 and 2021, southwest Louisiana saw five climate-related disasters, including two destructive hurricanes. As if that wasnt bad enough, more storms are coming, and many areas are not prepared. But some government officials and state engineers are hoping there is an alternative: elevation. The $6.8 billion Southwest Coastal Louisiana Project is betting that raising residences by a few feet, coupled with extensive work to restore coastal boundary lands, will keep Louisianans in their communities. Ultimately, its something of a last-ditch effort to preserve this slice of coastline, even as some locals pick up and move inland and as formal plans for managed retreat become more popular in climate-vulnerable areas across the country and the rest of the world.Read the full story. Xander Peters We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas?Drop me a lineortweet 'em at me.)+ How to make the most of yourjigsaw puzzlestry them on hard mode. +Mr Tickleis a maniac who needs to be stopped.+ Asong about Christmasthat probably many of us can relate to, if were honest. + If the original Home Alone was wince-inducing in terms of injuries, thesequelis even more excruciating.+ The best crispy roast potatoes ever?Ill let you be the judge.

Last week, this space was all about OpenAIs 12 days of shipmas. This week, the spotlight is on Google, which has been speeding toward the holiday by shipping or announcing its own flurry of products and updates. The combination of stuff here is pretty monumental, not just for a single company, but I think because it speaks to the power of the technology industryeven if it does trigger a personal desire that we could do more to harness that power and put it to more noble uses. To start, last week Google Introduced Veo, a new video generation model, and Imagen 3, a new version of its image generation model.Then on Monday, Google announced a breakthrough in quantum computing with its Willow chip. The company claims the new machine is capable of a standard benchmark computation in under five minutes that would take one of todays fastest supercomputers 10 septillion (that is, 1025) years. you may recall that MIT Technology Review covered some of the Willow work after researchers posted a paper preprint in August. But this week marked the big media splash. It was a stunning update that had Silicon Valley abuzz. (Seriously, I have never gotten so many quantum computing pitches as in the past few days.) Google followed this on Wednesday with even more gifts: a Gemini 2 release, a Project Astra update, and even more news about forthcoming agents called Mariner, an agent that can browse the web, and Jules, a coding assistant. First: Gemini 2. Its impressive, with a lot of performance updates. But I have frankly grown a little inured by language-model performance updates to the point of apathy. Or at least near-apathy. I want to see them do something. So for me, the cooler update was second on the list: Project Astra, which comes across like an AI from a futuristic movie set. Google first showed a demo of Astra back in May at its developer conference, and it was the talk of the show. But, since demos offer companies chances to show off products at their most polished, it can be hard to tell whats real and whats just staged for the audience. Still, when my colleague Will Douglas Heaven recently got to try it out himself, live and unscripted, it largely lived up to the hype. Although he found it glitchy, he noted that those glitches can be easily corrected. He called the experience stunning and said it could be generative AIs killer app.On top of all this, Will notes that this week Google DeepMind CEO (the companys AI division) Demis Hassabis was in Sweden to receive his Nobel Prize. And what did you do with your week? Making all this even more impressive, the advances represented in Willow, Gemini, Astra, and Veo are ones that just a few years ago many, many people would have said were not possibleor at least not in this timeframe.A popular knock on the tech industry is that it has a tendency to over-promise and under-deliver. The phone in your pocket gives the lie to this. So too do the rides I took in Waymos self-driving cars this week. (Both of which arrived faster than Ubers estimated wait time. And honestly its not been that long since the mere ability to summon an Uber was cool!) And while quantum has a long way to go, the Willow announcement seems like an exceptional advance; if not a tipping point exactly, then at least a real waypoint on a long road. (For what its worth, Im still not totally sold on chatbots. They do offer novel ways of interacting with computers, and have revolutionized information retrieval. But whether they are beneficial for humanityespecially given energy debts, the use of copyrighted material in their training data, their perhaps insurmountable tendency to hallucinate, etc.is debatable, and certainly is being debated. But Im pretty floored by this weeks announcements from Google, as well as OpenAIfull stop.) And for all the necessary and overdue talk about reining in the power of Big Tech, the ability to hit significant new milestones on so many different fronts all at once is something that only a company with the resources of a Google (or Apple or Microsoft or Amazon or Meta or Baidu or whichever other behemoth) can do.All this said, I dont want us to buy more gadgets or spend more time looking at our screens. I dont want us to become more isolated physically, socializing with others only via our electronic devices. I dont want us to fill the air with carbon or our soil with e-waste. I do not think these things should be the price we pay to drive progress forward. Its indisputable that humanity would be better served if more of the tech industry was focused on ending poverty and hunger and disease and war. Yet every once in a while, in the ever-rising tide of hype and nonsense that pumps out of Silicon Valley, epitomized by the AI gold rush of the past couple of years, there are moments that make me sit back in awe and amazement at what people can achieve, and in which I become hopeful about our ability to actually solve our larger problemsif only because we can solve so many other dumber, but incredibly complicated ones. This week was one of those times for me. Now read the rest of The Debrief The News Robotaxi adoptionis hitting a tipping point. But also,GM is shutting down its Cruise robotaxi division. Hereshow to use OpenAIs new video editing toolSora. Blueskyhas an impersonator problem. The AI hype machine iscoming under government scrutiny. The Chat Every week, I talk to one of MIT Technology Reviews journalists to go behind the scenes of a story they are working on. This week, I hit up James ODonnell, who covers AI and hardware, about his story on how the startup defense contractorAnduril is bringing AI to the battlefield. Mat:James, you got a pretty up close look at something most people probably havent even thought about yet, which is how the future of AI-assisted warfare might look. What did you learn on that trip that you think will surprise people? James:Two things stand out. One, I think people would be surprised by the gulf between how technology has developed for the last 15 years for consumers versus the military. For consumers, weve gotten phones, computers, smart TVs and other technologies that generally do a pretty good job of talking to each other and sharing our data, even though theyre made by dozens of different manufacturers. Its called the internet of things. In the military, technology has developed in exactly the opposite way, and its putting them in a crisis. They have stealth aircraft all over the world, but communicating about a drone threat might be done with Powerpoints and a chat service reminiscent of AOL Instant Messenger. The second is just how much the Pentagon is now looking to AI to change all of this. New initiatives have surged in the current AI boom. They are spending on training new AI models to better detect threats, autonomous fighter jets, and intelligence platforms that use AI to find pertinent information. What I saw at Andurils test site in California is also a key piece of that. Using AI to connect to and control lots of different pieces of hardware, like drones and cameras and submarines, from a single platform. The amount being invested in AI is much smaller than for aircraft carriers and jets, but its growing. Mat:I was talking with a different startup defense contractor recently, who was talking to me about the difficulty of getting all these increasingly autonomous devices on the battlefield talking to each other in a coordinated way. Like Anduril, he was making the case that this has to be done at the edge, and that there is too much happening for human decision making to process. Do you think thats true? Why is that? James:So many in the defense space have pointed to the war in Ukraine as a sign that warfare is changing. Drones are cheaper and more capable than they ever were in the wars in the Middle East. Its why the Pentagon is spending $1 billion on the Replicator initiative to fieldthousands of cheap dronesby 2025. Its also looking to field more underwater drones as it plans for scenarios in which China may invade Taiwan. Once you get these systems, though, the problem is having all the devices communicate with one another securely. You need to play Air Traffic Control at the same time that youre pulling in satellite imagery and intelligence information, all in environments where communication links are vulnerable to attacks. Mat:I guess I still have a mental image of a control room somewhere, like you might see inDr. StrangeloveorWar Games(orStar Warsfor that matter) with a handful of humans directing things. Are those days over? James:I think a couple things will change. One, a single person in that control room will be responsible for a lot more than they are now. Rather than running just one camera or drone system manually, theyll command software that does it for them, for lots of different devices. The idea that the defense tech sector is pushing is to take them out of the mundane tasksrotating a camera around to look for threatsand instead put them in the drivers seat for decisions that only humans, not machines, can make. Mat:I know that critics of the industry push back on the idea of AI being empowered to make battlefield decisions, particularly when it comes to life and death, but it seems to me that we are increasingly creeping toward that and it seems perhaps inevitable. Whats your sense? James:This is painting with broad strokes, but I think the debates about military AI fall along similar lines to what we see for autonomous vehicles. You have proponents saying that driving is not a thing humans are particularly good at, and when they make mistakes, it takes lives. Others might agree conceptually, but debate at what point its appropriate to fully adopt fallible self-driving technology in the real world. How much better does it have to be than humans? In the military, the stakes are higher. Theres no question that AI is increasingly being used to sort through and surface information to decision-makers. Its finding patterns in data, translating information, and identifying possible threats. Proponents are outspoken that that will make warfare more precise and reduce casualties. What critics are concerned about is how far across that decision-making pipeline AI is going, and how much there is human oversight. I think where it leaves me is wanting transparency. When AI systems make mistakes, just like when human military commanders make mistakes, I think we deserve to know, and that transparency does not have to compromise national security. It tookyearsfor reporter Azmat Khan to piece together the mistakes made during drone strikes in the Middle East, because agencies were not forthcoming. That obfuscation absolutely cannot be the norm as we enter the age of military AI. Mat:Finally, did you have a chance to hit an In-N-Out burger while you were in California? James:Normally In-N-Out is a requisite stop for me in California, but ahead of my trip I heard lots of good things about the burgers at The Apple Pan in West LA, so I went there. To be honest, the fries were better, but for the burger I have to hand it to In-N-Out. The Recommendation A few weeks ago I suggestedCa7riel and Paco Amorosos appearance on NPR Tiny Desk. At the risk of this space becoming a Tiny Desk stan account, Im back again with another. I was completely floored byDoechiis Tiny Desk appearance last week. Its so full of talent and joy and style and power. I came away completely inspired and have basically had her music on repeat in Spotify ever since. If you are already a fan of her recorded music, you will love her live. If shes new to you, well, youre welcome. Go check it out. Oh, and dont worry: Im not planning to recommendBillie Eilishs new Tiny Desk concertin next weeks newsletter. Mostly because Im doing so now.

Like many others, I recently fled the social media platform X for Bluesky. In the process, I started following many of the people I followed on X. On Thanksgiving, I was delighted to see a private message from a fellow AI reporter, Will Knight from Wired. Or at least thats who I thought I was talking to. I became suspicious when the person claiming to be Knight mentioned being from Miami, when Knight is, in fact, from the UK. The account handle was almost identical to the real Will Knights handle, and the profile used his profile photo. Then more messages started to appear. Paris Marx, a prominent tech critic, slid into my DMs to ask me how I was doing. Things are going splendid over here, he replied to me. Then things got suspicious again. How are your trades going? fake-Marx asked me. This account was far more sophisticated than Knights; it had meticulously copied every single tweet and retweet from Marxs real page over the past few weeks. Both accounts were eventually deleted, but not before trying to get me to set up a crypto wallet and a cloud mining pool account. Knight and Marx confirmed to us that these accounts did not belong to them, and that they have been fighting impersonator accounts of themselves for weeks. They are not the only ones. The New York Times tech journalist Sheera Frankel and Molly White, a researcher and cryptocurrency critic, have also experienced people impersonating them on Bluesky, most likely to scam people. This tracks with research from Alexios Mantzarlis, the director of the Security, Trust, and Safety Initiative at Cornell Tech, who manually went through the top 500 Bluesky users by follower count and found that of the 305 accounts belonging to a named person, at least 74 had been impersonated by at least one other account. The platform has had to suddenly cater to an influx of millions of new users in recent months as people leave X in protest of Elon Musks takeover of the platform. Its user base has more than doubled since September, from 10 million users to over 20 million. This sudden wave of new usersand the inevitable scammersmeans Bluesky is still playing catch-up, says White. These accounts block me as soon as theyre created, so I dont initially see them, Marx says. Both Marx and White describe a frustrating pattern: When one account is taken down, another one pops up soon after. White says she had experienced a similar phenomenon on X and TikTok too. A way to prove that people are who they say they are would help. Before Musk took the reins of the platform, employees at X, previously known as Twitter, verified users such as journalists and politicians, and gave them a blue tick next to their handles so people knew they were dealing with credible news sources. After Musk took over, he scrapped the old verification system and offered blue ticks to all paying customers. The ongoing crypto-impersonation scams have raised calls for Bluesky to initiate something similar to Twitters original verification program. Some users, such as the investigative journalist Hunter Walker, have set up their own initiatives to verify journalists. However, users are currently limited in the ways they can verify themselves on the platform. By default, usernames on Bluesky end with the suffix bsky.social. The platform recommends that news organizations and high-profile people verify their identities by setting up their own websites as their usernames. For example, US senators have verified their accounts with the suffix senate.gov. But this technique isnt foolproof. For one, it doesnt actually verify peoples identityonly their affiliation with a particular website. Bluesky did not respond to MIT Technology Reviews requests for comment, but the companys safety team posted that the platform had updated its impersonation policy to be more aggressive and would remove impersonation and handle-squatting accounts. The company says it has also quadrupled its moderation team to take action on impersonation reports more quickly. But it seems to be struggling to keep up. We still have a large backlog of moderation reports due to the influx of new users as we shared previously, though we are making progress, the company continued. Blueskys decentralized nature makes kicking out impersonators a trickier problem to solve. Competitors such as X and Threads rely on centralized teams within the company who moderate unwanted content and behavior, such as impersonation. But Bluesky is built on the AT Protocol, a decentralized, open-source technology, which allows users more control over what kind of content they see and enables them to build communities around particular content. Most people sign up to Bluesky Social, the main social network, whose community guidelines ban impersonation. However, Bluesky Social is just one of the services or clients that people can use, and other services have their own moderation practices and terms. This approach means that until now, Bluesky itself hasnt needed an army of content moderators to weed out unwanted behaviors because it relies on this community-led approach, says Wayne Chang, the founder and CEO of SpruceID, a digital identity company. That might have to change. In order to make these apps work at all, you need some level of centralization, says Chang. Despite community guidelines, its hard to stop people from creating impersonation accounts, and Bluesky is engaged in a cat-and-mouse game trying to take suspicious accounts down. Cracking down on a problem such as impersonation is important because it poses a serious problem for the credibility of Bluesky, says Chang. Its a legitimate complaint as a Bluesky user that Hey, all those scammers are basically harassing me. You want your brand to be tarnished? Or is there something we can do about this? he says. A fix for this is urgently needed, because attackers might abuse Blueskys open-source code to create spam and disinformation campaigns at a much larger scale, says Francesco Pierri, an assistant professor at Politecnico di Milano who has researched Bluesky. His team found that the platform has seen a rise in suspicious accounts since it was made open to the public earlier this year. Bluesky acknowledges that its current practices are not enough. In a post, the company said it has received feedback that users want more ways to confirm their identities beyond domain verification, and it is exploring additional options to enhance account verification. In a livestream at the end of November, Bluesky CEO Jay Graber said the platform was considering becoming a verification provider, but because of its decentralized approach it would also allow others to offer their own user verification services. And [users] can choose to trust usthe Bluesky teams verificationor they could do their own. Or other people could do their own, Graber said. But at least Bluesky seems to have some willingness to actually moderate content on the platform, says White. I would love to see something a little bit more proactive that didnt require me to do all of this reporting, she adds. As for Marx, I just hope that no one truly falls for it and gets tricked into crypto scams, he says.

The internet loves a good neologism, especially if it can capture a purported vibe shift or explain a new trend. In 2013, the columnist Adrian Wooldridge coined a word that eventually did both. Writing for the Economist, he warned of the coming techlash, a revolt against Silicon Valleys rich and powerful fueled by the publics growing realization that these sovereigns of cyberspace werent the benevolent bright-future bringers they claimed to be. While Wooldridge didnt say precisely when this techlash would arrive, its clear today that a dramatic shift in public opinion toward Big Tech and its leaders did in fact happenand is arguably still happening. Say what you will about the legions of Elon Musk acolytes on X, but if an industry and its executives can bring together the likes of Elizabeth Warren and Lindsey Graham in shared condemnation, its definitely not winning many popularity contests. To be clear, there have always been critics of Silicon Valleys very real excesses and abuses. But for the better part of the last two decades, many of those voices of dissent were either written off as hopeless Luddites and haters of progress or drowned out by a louder and far more numerous group of techno-optimists. Today, those same critics (along with many new ones) have entered the fray once more, rearmed with popular Substacks, media columns, andincreasinglybook deals. Two of the more recent additions to the flourishing techlash genreRob Lalkas The Venture Alchemists: How Big Tech Turned Profits into Power and Marietje Schaakes The Tech Coup: How to Save Democracy from Silicon Valleyserve as excellent reminders of why it started in the first place. Together, the books chronicle the rise of an industry that is increasingly using its unprecedented wealth and power to undermine democracy, and they outline what we can do to start taking some of that power back. Lalka is a business professor at Tulane University, and The Venture Alchemists focuses on how a small group of entrepreneurs managed to transmute a handful of novel ideas and big bets into unprecedented wealth and influence. While the names of these demigods of disruption will likely be familiar to anyone with an internet connection and a passing interest in Silicon Valley, Lalka also begins his book with a page featuring their nine (mostly) young, (mostly) smiling faces. There are photos of the famous founders Mark Zuckerberg, Larry Page, and Sergey Brin; the VC funders Keith Rabois, Peter Thiel, and David Sacks; and a more motley trio made up of the disgraced former Uber CEO Travis Kalanick, the ardent eugenicist and reputed father of Silicon Valley Bill Shockley (who, it should be noted, died in 1989), and a former VC and the future vice president of the United States, JD Vance. To his credit, Lalka takes this medley of tech titans and uses their origin stories and interrelationships to explain how the so-called Silicon Valley mindset (mind virus?) became not just a fixture in Californias Santa Clara County but also the preeminent way of thinking about success and innovation across America. This approach to doing business, usually cloaked in a barrage of cringey innovation-speakdisrupt or be disrupted, move fast and break things, better to ask for forgiveness than permissioncan often mask a darker, more authoritarian ethos, according to Lalka. One of the nine entrepreneurs in the book, Peter Thiel, has written that I no longer believe that freedom and democracy are compatible and that competition [in business] is for losers. Many of the others think that all technological progress is inherently good and should be pursued at any cost and for its own sake. A few also believe that privacy is an antiquated concepteven an illusionand that their companies should be free to hoard and profit off our personal data. Most of all, though, Lalka argues, these men believe that their newfound power should be unconstrained by governments, regulators, or anyone else who might have the gall to impose some limitations. Where exactly did these beliefs come from? Lalka points to people like the late free-market economist Milton Friedman, who famously asserted that a companys only social responsibility is to increase profits, as well as to Ayn Rand, the author, philosopher, and hero to misunderstood teenage boys everywhere who tried to turn selfishness into a virtue. The Venture Alchemists: How Big Tech Turned Profits into PowerRob LalkaCOLUMBIA BUSINESS SCHOOL PUBLISHING, 2024 Its a somewhat reductive and not altogether original explanation of Silicon Valleys libertarian inclinations. What ultimately matters, though, is that many of these values were subsequently encoded into the DNA of the companies these men founded and fundedcompanies that today shape how we communicate with one another, how we share and consume news, and even how we think about our place in the world. The Venture Alchemists is strongest when its describing the early-stage antics and on-campus controversies that shaped these young entrepreneurs or, in many cases, simply reveal who theyve always been. Lalka is a thorough and tenacious researcher, as the books 135 pages of endnotes suggest. And while nearly all these stories have been told before in other books and articles, he still manages to provide new perspectives and insights from sources like college newspapers and leaked documents. One thing the book is particularly effective at is deflating the myth that these entrepreneurs were somehow gifted seers of (and investors in) a future the rest of us simply couldnt comprehend or predict. Sure, someone like Thiel made what turned out to be a savvy investment in Facebook early on, but he also made some very costly mistakes with that stake. As Lalka points out, Thiels Founders Fund dumped tens of millions of shares shortly after Facebook went public, and Thiel himself went from owning 2.5% of the company in 2012 to 0.000004% less than a decade later (around the same time Facebook hit its trillion-dollar valuation). Throw in his objectively terrible wagers in 2008, 2009, and beyond, when he effectively shorted what turned out to be one of the longest bull markets in world history, and you get the impression hes less oracle and more ideologue who happened to take some big risks that paid off. One of Lalkas favorite mantras throughout The Venture Alchemists is that words matter. Indeed, he uses a lot of these entrepreneurs own words to expose their hypocrisy, bullying, juvenile contrarianism, casual racism, andyesoutright greed and self-interest. It is not a flattering picture, to say the least. Unfortunately, instead of simply letting those words and deeds speak for themselves, Lalka often feels the need to interject with his own, frequently enjoining readers against finger-pointing or judging these men too harshly even after hes chronicled their many transgressions. Whether this is done to try to convey some sense of objectivity or simply to remind readers that these entrepreneurs are complex and complicated men making difficult decisions, it doesnt work. At all. For one thing, Lalka clearly has his own strong opinions about the behavior of these entrepreneursopinions he doesnt try to disguise. At one point in the book he suggests that Kalanicks alpha-male, dominance-at-any-cost approach to running Uber is almost, but not quite like rape, which is maybe not the comparison youd make if you wanted to seem like an arbiter of impartiality. And if he truly wants readers to come to a different conclusion about these men, he certainly doesnt provide many reasons for doing so. Simply telling us to judge less, and discern more seems worse than a cop-out. It comes across as almost, but not quite like victim-blamingas if were somehow just as culpable as they are for using their platforms and buying into their self-mythologizing. In many ways, Silicon Valley has become the antithesis of what its early pioneers set out to be. Marietje Schaake Equally frustrating is the crescendo of empty platitudes that ends the book. The technologies of the future must be pursued thoughtfully, ethically, and cautiously, Lalka says after spending 313 pages showing readers how these entrepreneurs have willfully ignored all three adverbs. What theyve built instead are massive wealth-creation machines that divide, distract, and spy on us. Maybe its just me, but that kind of behavior seems ripe not only for judgment, but also for action. So what exactly do you do with a group of men seemingly incapable of serious self-reflectionmen who believe unequivocally in their own greatness and who are comfortable making decisions on behalf of hundreds of millions of people who did not elect them, and who do not necessarily share their values? You regulate them, of course. Or at least you regulate the companies they run and fund. In Marietje Schaakes The Tech Coup, readers are presented with a road map for how such regulation might take shape, along with an eye-opening account of just how much power has already been ceded to these corporations over the past 20 years. There are companies like NSO Group, whose powerful Pegasus spyware tool has been sold to autocrats, who have in turn used it to crack down on dissent and monitor their critics. Billionaires are now effectively making national security decisions on behalf of the United States and using their social media companies to push right-wing agitprop and conspiracy theories, as Musk does with his Starlink satellites and X. Ride-sharing companies use their own apps as propaganda tools and funnel hundreds of millions of dollars into ballot initiatives to undo laws they dont like. The list goes on and on. According to Schaake, this outsize and largely unaccountable power is changing the fundamental ways that democracy works in the United States. In many ways, Silicon Valley has become the antithesis of what its early pioneers set out to be: from dismissing government to literally taking on equivalent functions; from lauding freedom of speech to becoming curators and speech regulators; and from criticizing government overreach and abuse to accelerating it through spyware tools and opaque algorithms, she writes. Schaake, whos a former member of the European Parliament and the current international policy director at Stanford Universitys Cyber Policy Center, is in many ways the perfect chronicler of Big Techs power grab. Beyond her clear expertise in the realms of governance and technology, shes also Dutch, which makes her immune to the distinctly American disease that seems to equate extreme wealth, and the power that comes with it, with virtue and intelligence. This resistance to the various reality-distortion fields emanating from Silicon Valley plays a pivotal role in her ability to see through the many justifications and self-serving solutions that come from tech leaders themselves. Schaake understands, for instance, that when someone like OpenAIs Sam Altman gets in front of Congress and begs for AI regulation, what hes really doing is asking Congress to create a kind of regulatory moat between his company and any other startups that might threaten it, not acting out of some genuine desire for accountability or governmental guardrails. The Tech Coup:How to Save Democracyfrom Silicon ValleyMarietje SchaakePRINCETON UNIVERSITY PRESS, 2024 Like Shoshana Zuboff, the author of The Age of Surveillance Capitalism, Schaake believes that the digital should live within democracys housethat is, technologies should be developed within the framework of democracy, not the other way around. To accomplish this realignment, she offers a range of solutions, from banning what she sees as clearly antidemocratic technologies (like face-recognition software and other spyware tools) to creating independent teams of expert advisors to members of Congress (who are often clearly out of their depth when attempting to understand technologies and business models). Predictably, all this renewed interest in regulation has inspired its own backlash in recent yearsa kind of tech revanchism, to borrow a phrase from the journalist James Hennessy. In addition to familiar attacks, such as trying to paint supporters of the techlash as somehow being antitechnology (theyre not), companies are also spending massive amounts of money to bolster their lobbying efforts. Some venture capitalists, like LinkedIn cofounder Reid Hoffman, who made big donations to the Kamala Harris presidential campaign, wanted to evict Federal Trade Commission chair Lina Khan, claiming that regulation is killing innovation (it isnt) and removing the incentives to start a company (its not). And then of course theres Musk, who now seems to be in a league of his own when it comes to how much influence he may exert over Donald Trump and the government that his companies have valuable contracts with. What all these claims of victimization and subsequent efforts to buy their way out of regulatory oversight miss is that theres actually a vast and fertile middle ground between simple techno-optimism and techno-skepticism. As the New Yorker contributor Cal Newport and others have noted, its entirely possible to support innovations that can significantly improve our lives without accepting that every popular invention is good or inevitable. Regulating Big Tech will be a crucial part of leveling the playing field and ensuring that the basic duties of a democracy can be fulfilled. But as both Lalka and Schaake suggest, another battle may prove even more difficult and contentious. This one involves undoing the flawed logic and cynical, self-serving philosophies that have led us to the point where we are now. What if we admitted that constant bacchanals of disruption are in fact not all that good for our planet or our brains? What if, instead of creative destruction, we started fetishizing stability, and in lieu of putting dents in the universe, we refocused our efforts on fixing whats already broken? What ifand hear me outwe admitted that technology might not be the solution to every problem we face as a society, and that while innovation and technological change can undoubtedly yield societal benefits, they dont have to be the only measures of economic success and quality of life? When ideas like these start to sound less like radical concepts and more like common sense, well know the techlash has finally achieved something truly revolutionary. Bryan Gardiner is a writer based in Oakland, California.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. How Silicon Valley is disrupting democracy The internet loves a good neologism, especially if it can capture a purported vibe shift or explain a new trend. In 2013, the columnist Adrian Wooldridge coined a word that eventually did both. Writing for the Economist, he warned of the coming techlash, a revolt against Silicon Valleys rich and powerful fueled by the publics growing realization that these sovereigns of cyberspace werent the benevolent bright-future bringers they claimed to be. While Wooldridge didnt say precisely when this techlash would arrive, its clear today that a dramatic shift in public opinion toward Big Tech and its leaders did in fact happenand is arguably still happening. Two new books serve as excellent reminders of why it started in the first place. Together, they chronicle the rise of an industry that is increasingly using its unprecedented wealth and power to undermine democracy, and they outline what we can do to start taking some of that power back. Read the full story.Bryan Gardiner This story is from the forthcoming magazine edition of MIT Technology Review, set to go live on January 6its all about the exciting breakthroughs happening in the world right now. If you dont already, subscribe to receive a copy. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Google has unveiled a new headset and smart glasses OS Android XR gives wearers hands-free control thanks to the firms Gemini chatbot. (The Verge)+ It also revealed a new Samsung-build headset called Project Moohan. (WP $)+ Googles hoping to learn from mistakes it made with Google Glass a decade ago. (Wired $)+ Its new Project Astra could be generative AIs killer app. (MIT Technology Review) 2 The US and UK are on a AI regulation collision course Donald Trumps approach to policing AI is in stark contrast to what the UK is planning. (FT $)+ The new US FTC chair favors a light regulatory touch. (Reuters)+ Hows AI self-regulation going? (MIT Technology Review)3 We dont quite know whats causing a global temperature spike But scientists agree that we should be worried. (New Yorker $)+ The average global temperature could drop slightly next year, though. (New Scientist $)+ Whos to blame for climate change? Its surprisingly complicated. (MIT Technology Review)4 Trumps administration is filling up with tech insiders More venture capitalists and officials are likely to join their ranks. (The Information $)+ These crypto kingpins will be keeping a close eye on proceedings. (FT $)5 What happened after West Virginia revoked access to obesity drugsTeachers and state workers struggled after a pilot drugs program was deemed too expensive. (The Atlantic $) + Weight-loss injections have taken over the internet. But what does this mean for people IRL? (MIT Technology Review)6 Would you buy a car from Amazon?The e-retail giant wants you to sidestep the dealership and purchase from it directly. (Wired $) + While its limited to Hyundai models, other manufacturers will follow. (Forbes $)7 Silicon Valleys perks culture is largely dead No more free massages or artisanal chocolate, sob. (NYT $)8 AI is teaching us more about the Berlin Walls murals From the kinds of paint used, to application techniques. (Ars Technica)9 For $69, you can invest in a rare stegosaurus skeleton The rare fossil is a pretty extreme example of an alternative investment. (Fast Company $)+ New Yorkers can swing by the American Museum of Natural History to see it. (AP News) 10 This New Jersey politician faked his Spotify Wrapped To hide his childrens results and make him appear a bigger Bruce Springsteen fan. (Billboard $)+ What would The Boss himself make of the controversy? (WP $)Quote of the day It could be far worse than any challenge weve previously encountered and far beyond our capacity to mitigate. Jack Szostak, a professor in the University of Chicagos chemistry department, tells the Financial Times about the unprecedented danger posed by synthetic bacteria. The big story A brief, weird history of brainwashing April 2024 On a spring day in 1959, war correspondent Edward Hunter testified before a US Senate subcommittee investigating the effect of Red China Communes on the United States. Hunter introduced them to a supposedly scientific system for changing peoples minds, even making them love things they once hated. Much of it was baseless, but Hunters sensational tales still became an important part of the disinformation that fueled a mind-control race, with the US government pumping millions of dollars into research on brain manipulation during the Cold War. But while the science never exactly panned out, residual beliefs fostered by this bizarre conflict continue to play a role in ideological and scientific debates to this day. Read the full story. Annalee Newitz We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Deep down in the depths of the Atacama Trench, a new crustacean has been discovered.+ Living in this picturesque Antarctic settlement comes with a catchyou have to have your appendix removed before you can move in.+ Just when you thought sweet potato couldnt get any better, it turns out it makes pretty tasty macaroons.+ If youre looking to introduce kids to the joy of sci-fi, these movies are a great place to start.

Its no secret that the current AI boom is using up immense amounts of energy. Now we have a better idea of how much. A new paper, from a team at the Harvard T.H. Chan School of Public Health, examined 2,132 data centers operating in the United States (78% of all facilities in the country). These facilitiesessentially buildings filled to the brim with rows of serversare where AI models get trained, and they also get pinged every time we send a request through models like ChatGPT. They require huge amounts of energy both to power the servers and to keep them cool. Since 2018, carbon emissions from data centers in the US have tripled. For the 12 months ending August 2024, data centers were responsible for 105 million metric tons of CO2, accounting for 2.18% of national emissions (for comparison, domestic commercial airlines are responsible for about 131 million metric tons). About 4.59% of all the energy used in the US goes toward data centers, a figure thats doubled since 2018. Its difficult to put a number on how much AI in particular, which has been booming since ChatGPT launched in November 2022, is responsible for this surge. Thats because data centers process lots of different types of datain addition to training or pinging AI models, they do everything from hosting websites to storing your photos in the cloud. However, the researchers say, AIs share is certainly growing rapidly as nearly every segment of the economy attempts to adopt the technology. Its a pretty big surge, says Eric Gimon, a senior fellow at the think tank Energy Innovation, who was not involved in the research. Theres a lot of breathless analysis about how quickly this exponential growth could go. But its still early days for the business in terms of figuring out efficiencies, or different kinds of chips. Notably, the sources for all this power are particularly dirty. Since so many data centers are located in coal-producing regions, like Virginia, the carbon intensity of the energy they use is 48% higher than the national average. The paper, which was published on arXiv and has not yet been peer-reviewed, found that 95% of data centers in the US are built in places with sources of electricity that are dirtier than the national average. There are causes other than simply being located in coal country, says Falco Bargagli-Stoffi, an author of the paper. Dirtier energy is available throughout the entire day, he says, and plenty of data centers require that to maintain peak operation 24-7. Renewable energy, like wind or solar, might not be as available. Political or tax incentives, and local pushback, can also affect where data centers get built. One key shift in AI right now means that the fields emissions are soon likely to skyrocket. AI models are rapidly moving from fairly simple text generators like ChatGPT toward highly complex image, video, and music generators. Until now, many of these multimodal models have been stuck in the research phase, but thats changing. OpenAI released its video generation model Sora to the public on December 9, and its website has been so flooded with traffic from people eager to test it out that it is still not functioning properly. Competing models, like Veo from Google and Movie Gen from Meta, have still not been released publicly, but if those companies follow OpenAIs lead as they have in the past, they might be soon. Music generation models from Suno and Udio are growing (despite lawsuits), and Nvidia released its own audio generator last month. Google is working on its Astra project, which will be a video-AI companion that can converse with you about your surroundings in real time. As we scale up to images and video, the data sizes increase exponentially, says Gianluca Guidi, a PhD student in artificial intelligence at University of Pisa and IMT Lucca, who is the papers lead author. Combine that with wider adoption, he says, and emissions will soon jump. One of the goals of the researchers was to build a more reliable way to get snapshots of just how much energy data centers are using. Thats been a more complicated task than you might expect, given that the data is dispersed across a number of sources and agencies. Theyve now built a portal that shows data center emissions across the country. The long-term goal of the data pipeline is to inform future regulatory efforts to curb emissions from data centers, which are predicted to grow enormously in the coming years. Theres going to be increased pressure, between the environmental and sustainability-conscious community and Big Tech, says Francesca Dominici, director of the Harvard Data Science Initiative and another coauthor. But my prediction is that there is not going to be regulation. Not in the next four years.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Googles new Project Astra could be generative AIs killer app Google DeepMind has announced an impressive grab bag of new products and prototypes that may just let it seize back its lead in the race to turn generative artificial intelligence into a mass-market concern. Top billing goes to Gemini 2.0the latest iteration of Google DeepMinds family of multimodal large language models, now redesigned around the ability to control agentsand a new version of Project Astra, the experimental everything app that the company teased at Google I/O in May. The margins between top-end models like Gemini 2.0 and those from rival labs like OpenAI and Anthropic are now slim. These days, advances in large language models are less about how good they are and more about what you can do with them. And thats where agents come in. MIT Technology Review got to try out Astra in a closed-door live demo last week. It gave us a hint at whats to come. Find out more in the full story. Will Douglas Heaven China banned exports of a few rare minerals to the US. Things could get messier. Casey Crownhart Ive thought more about gallium and germanium over the last week than I ever have before (and probably more than anyone ever should). China banned the export of those materials to the US last week and placed restrictions on others. The move is just the latest drama in escalating trade tensions between the two countries. While the new export bans could have significant economic consequences, this might be only the beginning. China is a powerhouse, and not just in those niche materialsits also a juggernaut in clean energy, and particularly in battery supply chains. So what comes next could have significant consequences for EVs and climate action more broadly. Read the full story.This story is from The Spark, our weekly climate and energy newsletter. Sign up to receive it in your inbox every Wednesday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Its looking pretty likely 2024 will be the hottest year on recordBut average temperatures are just one way of assessing our warming world. (New Scientist $) + The first few months of 2025 are likely to be hotter than average, too. (Reuters)+ The US is about to make a sharp turn on climate policy. (MIT Technology Review)2 Meta has donated $1 million to Trumps inaugural fund In an effort to strengthen their previously fractious relationship. (WSJ $)+ Mark Zuckerberg isnt the only tech figure seeking the President-elects ear. (Insider $) 3 How China secretly repatriates Uyghurs Even the United Nations is seemingly powerless to stop it. (WP $)+ Uyghurs outside China are traumatized. Now theyre starting to talk about it. (MIT Technology Review)4 How Big Tech decides when to scrub a users digital footprint Murder suspect Luigi Mangiones Instagram has been taken downbut his Goodreads hasnt. (NYT $)+ Why its dangerous to treat public online accounts as the full story. (NY Mag $)5 Russia-backed hackers targeted Ukraines military using criminal toolsWhich makes it even harder to work out who did it. (TechCrunch) 6 What Cruises exit means for the rest of the robotaxi industryAutomakers are becoming frustrated waiting for the technology to mature. (The Verge) + Cruise will focus on developing fully autonomous personal vehicles instead. (NYT $)7 Researching risky pathogens is extremely high stakes The potential for abuse has some researchers worried we shouldnt undertake it at all. (Undark Magazine)+ Meet the scientist at the center of the covid lab leak controversy. (MIT Technology Review)8 Altermagnetism could be computings next big thingIt would lead to faster, more reliable electronic devices. (FT $) 9 Why some people need so little sleep Gene mutations appear to hold at least some of the answers. (Knowable Magazine)+ Babies spend most of their time asleep. New technologies are beginning to reveal why. (MIT Technology Review)10 Inside the creeping normalization of AI movies The worlds largest TV manufacturer wants to make films for people too lazy to change the channel. (404 Media)+ Unsurprisingly, itll push targeted ads, too. (Ars Technica)+ How AI-generated video is changing film. (MIT Technology Review) Quote of the day "They've made him a martyr for all the troubles people have had with their own insurance companies." Felipe Rodriguez, an adjunct professor at the John Jay College of Criminal Justice in New York, explains why murder suspect Luigi Mangione is being lionized online to Reuters. The big story Why AI could eat quantum computings lunch November 2024 Tech companies have been funneling billions of dollars into quantum computers for years. The hope is that theyll be a game changer for fields as diverse as finance, drug discovery, and logistics. But while the field struggles with the realities of tricky quantum hardware, another challenger is making headway in some of these most promising use cases. AI is now being applied to fundamental physics, chemistry, and materials science in a way that suggests quantum computings purported home turf might not be so safe after all. Read the full story. Edd Gent We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Working life getting you down? These pictures of bygone office malaise will make you feel a whole lot better (or worsethanks Will!) + Gen Z are getting really into documenting their lives via digital cameras, apparently. + If you believe that Alan MacMasters invented the first electric bread toaster, Im sorry to inform you that youve fallen for an elaborate online hoax.+ The case for a better Turing test for AI-generated art.

The Intel 4004, the first commercial microprocessor, was released in 1971. With 2,300 transistors packed into 12mm2, it heralded a revolution in computing. A little over 50 years later, Apples M2 Ultra contains 134 billion transistors. The scale of progress is difficult to comprehend, but the evolution of semiconductors, driven for decades by Moores Law, has paved a path from the emergence of personal computing and the internet to todays AI revolution. But this pace of innovation is not guaranteed, and the next frontier of technological advancesfrom the future of AI to new computing paradigmswill only happen if we think differently. Atomic challenges The modern microchip stretches both the limits of physics and credulity. Such is the atomic precision, that a few atoms can decide the function of an entire chip. This marvel of engineering is the result of over 50 years of exponential scaling creating faster, smaller transistors. But we are reaching the physical limits of how small we can go, costs are increasing exponentially with complexity, and efficient power consumption is becoming increasingly difficult. In parallel, AI is demanding ever-more computing power. Data from Epoch AI indicates the amount of computing needed to develop AI is quickly outstripping Moores Law, doubling every six months in the deep learning era since 2010. These interlinked trends present challenges not just for the industry, but society as a whole. Without new semiconductor innovation, todays AI models and research will be starved of computational resources and struggle to scale and evolve. Key sectors like AI, autonomous vehicles, and advanced robotics will hit bottlenecks, and energy use from high-performance computing and AI will continue to soar. Materials intelligence At this inflection point, a complex, global ecosystemfrom foundries and designers to highly specialized equipment manufacturers and materials solutions providers like Merckis working together more closely than ever before to find the answers. All have a role to play, and the role of materials extends far, far beyond the silicon that makes up the wafer. Instead, materials intelligence is present in almost every stage of the chip production processwhether in chemical reactions to carve circuits at molecular scale (etching) or adding incredibly thin layers to a wafer (deposition) with atomic precision: a human hair is 25,000 times thicker than layers in leading edge nodes. Yes, materials provide a chips physical foundation and the substance of more powerful and compact components. But they are also integral to the advanced fabrication methods and novel chip designs that underpin the industrys rapid progress in recent decades. For this reason, materials science is taking on a heightened importance as we grapple with the limits of miniaturization. Advanced materials are needed more than ever for the industry to unlock the new designs and technologies capable of increasing chip efficiency, speed, and power. We are seeing novel chip architectures that embrace the third dimension and stack layers to optimize surface area usage while lowering energy consumption. The industry is harnessing advanced packaging techniques, where separate chiplets are fused with varying functions into a more efficient, powerful single chip. This is called heterogeneous integration. Materials are also allowing the industry to look beyond traditional compositions. Photonic chips, for example, harness light rather than electricity to transmit data. In all cases, our partners rely on us to discover materials never previously used in chips and guide their use at the atomic level. This, in turn, is fostering the necessary conditions for AI to flourish in the immediate future. New frontiers The next big leap will involve thinking differently. The future of technological progress will be defined by our ability to look beyond traditional computing. Answers to mounting concerns over energy efficiency, costs, and scalability will be found in ambitious new approaches inspired by biological processes or grounded in the principles of quantum mechanics. While still in its infancy, quantum computing promises processing power and efficiencies well beyond the capabilities of classical computers. Even if practical, scalable quantum systems remain a long way off, their development is dependent on the discovery and application of state-of-the-art materials. Similarly, emerging paradigms like neuromorphic computing, modelled on the human brain with architectures mimicking our own neural networks, could provide the firepower and energy-efficiency to unlock the next phase of AI development. Composed of a deeply complex web of artificial synapses and neurons, these chips would avoid traditional scalability roadblocks and the limitations of todays Von Neumann computers that separate memory and processing. Our biology consists of super complex, intertwined systems that have evolved by natural selection, but it can be inefficient; the human brain is capable of extraordinary feats of computational power, but it also requires sleep and careful upkeep. The most exciting step will be using advanced computeAI and quantumto finally understand and design systems inspired by biology. This combination will drive the power and ubiquity of next-generation computing and associated advances to human well-being. Until then, the insatiable demand for more computing power to drive AIs development poses difficult questions for an industry grappling with the fading of Moores Law and the constraints of physics. The race is on to produce more powerful, more efficient, and faster chips to progress AIs transformative potential in every area of our lives. Materials are playing a hidden, but increasingly crucial role in keeping pace, producing next-generation semiconductors and enabling the new computing paradigms that will deliver tomorrows technology. But materials sciences most important role is yet to come. Its true potential will be to take usand AIbeyond silicon into new frontiers and the realms of science fiction by harnessing the building blocks of biology. This content was produced by EMD Electronics. It was not written by MIT Technology Reviews editorial staff.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. Bluesky has an impersonator problem Melissa Heikkil Like many others, I recently joined Bluesky. On Thanksgiving, I was delighted to see a private message from a fellow AI reporter, Will Knight from Wired. Or at least thats who I thought I was talking to. I became suspicious when the person claiming to be Knight said they were from Miami, when Knight is, in fact, from the UK. The account handle was almost identical to the real Will Knights handle, and used his profile photo. Then more messages started to appear. Paris Marx, a prominent tech critic, slid into my DMs to ask me how I was doing. Both accounts were eventually deleted, but not before trying to get me to set up a crypto wallet and a cloud mining pool account. Knight and Marx confirmed to us these accounts did not belong to them, and that they have been fighting impersonator accounts of themselves for weeks. Theyre not alone. The platform has had to suddenly cater to an influx of millions of new users in recent months as people leave X in protest of Elon Musks takeover of the platform. But this sudden wave of new users and the inevitable scammers means Bluesky is still playing catch up. Read the full story. MIT Technology Review Narrated: ChatGPT is about to revolutionize the economy. We need to decide what that looks like. You can practically hear the shrieks from corner offices around the world: What is our ChatGPT play? How do we make money off this? Whether its based on hallucinatory beliefs or not, an AI gold rush has started to mine the anticipated business opportunities from generative AI models like ChatGPT. But while companies and executives see a clear chance to cash in, the likely impact of the technology on workers and the economy on the whole is far less obvious. This is our latest story to be turned into a MIT Technology Review Narrated podcast, which were publishing each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as its released.The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Cruise is exiting the robotaxi business Once one of the biggest players, it says it costs too much to develop the tech. (Bloomberg $)+ The news came as a shock to Cruise employees. (TechCrunch)2 Google asked the US government to kill Microsofts cloud deal with OpenAI It wants the opportunity to host the firms models itself. (The Information $)3 The season of coughs and sneezes is upon us Heres what will actually keep a cold at bayand what wont. (Vox)+ RFK Jrs alternative medicine movement is unlikely to help. (The Atlantic $)+ Flu season is comingand so is the risk of an all-new bird flu. (MIT Technology Review)4 Trumps new Commerce Secretary champions a stablecoin favored by criminalsTether regularly crops up in international criminal cases. (FT $) + The crypto industry is obsessed with debanking. (NBC News) 5 A Russian influence operation probably used AI voice generation modelsElevenLabs technology was highly likely to have been abused by the campaign. (TechCrunch) + How this grassroots effort could make AI voices more diverse. (MIT Technology Review)6 These satellites are designed to create solar eclipses on demandItll allow scientists to study the suns outer atmosphere. (WP $) 7 WhatsApp is for so much more than just messagingIts been repurposed by communities across the world. (Rest of World) + How Indian health-care workers use WhatsApp to save pregnant women. (MIT Technology Review)8 Paris is turning its parking spaces into tiny parks Cars are out, trees are in. (Fast Company $)9 How AI is shedding light on an ancient board gameOddly enough, they didnt come with instructions 4,500 years ago. (New Scientist $) 10 What a quarter-century of robotic dogs has taught us The Aibo is one of the few robots thats made it into homes worldwide. (IEEE Spectrum)+ Generative AI taught a robot dog to scramble around a new environment. (MIT Technology Review)Quote of the day In case it was unclear before, it is clear now: GM are a bunch of dummies. Kyle Vogt, founder of robotaxi firm Cruise, criticizes parent company General Motors decision to exit the industry in a post on X. The big story Inside NASAs bid to make spacecraft as small as possible October 2023 Since the 1970s, weve sent a lot of big things to Mars. But when NASA successfully sent twin Mars Cube One spacecraft, the size of cereal boxes, in November 2018, it was the first time wed ever sent something so small. Just making it this far heralded a new age in space exploration. NASA and the community of planetary science researchers caught a glimpse of a future long sought: a pathway to much more affordable space exploration using smaller, cheaper spacecraft. Read the full story. David W. Brown We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + This fascinating tool creates fake video game screenshots in the blink of an eyegive it a whirl.+ Where and how did the people of the submerged territory of Doggerland live before rising seas pushed them away thousands of years ago? Were getting closer to learning the answers.+ Home Alone is a surprisingly brutal movie, as these doctors can attest.+ Cats love boxes. But why?

Google DeepMind has announced an impressive grab bag of new products and prototypes that may just let it seize back its lead in the race to turn generative artificial intelligence into a mass-market concern. Top billing goes to Gemini 2.0the latest iteration of Google DeepMinds family of multimodal large language models, now redesigned around the ability to control agentsand a new version of Project Astra, the experimental everything app that the company teased at Google I/O in May. MIT Technology Review got to try out Astra in a closed-door live demo last week. It was a stunning experience, but theres a gulf between polished promo and live demo. Astra uses Gemini 2.0s built-in agent framework to answer questions and carry out tasks via text, speech, image, and video, calling up existing Google apps like Search, Maps, and Lens when it needs to. Its merging together some of the most powerful information retrieval systems of our time, says Bibo Xu, product manager for Astra. Gemini 2.0 and Astra are joined by Mariner, a new agent built on top of Gemini that can browse the web for you; Jules, a new Gemini-powered coding assistant; and Gemini for Games, an experimental assistant that you can chat to and ask for tips as you play video games. (And lets not forget that in the last week Google DeepMind also announced Veo, a new video generation model; Imagen 3, a new version of its image generation model; and Willow, a new kind of chip for quantum computers. Whew. Meanwhile, CEO Demis Hassabis was in Sweden yesterday receiving his Nobel Prize.) Google DeepMind claims that Gemini 2.0 is twice as fast as the previous version, Gemini 1.5, and outperforms it on a number of standard benchmarks, including MMLU-Pro, a large set of multiple-choice questions designed to test the abilities of large language models across a range of subjects, from math and physics to health, psychology, and philosophy. But the margins between top-end models like Gemini 2.0 and those from rival labs like OpenAI and Anthropic are now slim. These days, advances in large language models are less about how good they are and more about what you can do with them. And thats where agents come in. Hands on with Project Astra Last week I was taken through an unmarked door on an upper floor of a building in Londons Kings Cross district into a room with strong secret-project vibes. The word ASTRA was emblazoned in giant letters across one wall. Xus dog, Charlie, the projects de facto mascot, roamed between desks where researchers and engineers were busy building a product that Google is betting its future on. The pitch to my mum is that were building an AI that has eyes, ears, and a voice. It can be anywhere with you, and it can help you with anything youre doing says Greg Wayne, co-lead of the Astra team. Its not there yet, but thats the kind of vision. The official term for what Xu, Wayne, and their colleagues are building is universal assistant. Exactly what that means in practice, theyre still figuring out. At one end of the Astra room were two stage sets that the team uses for demonstrations: a drinks bar and a mocked-up art gallery. Xu took me to the bar first. A long time ago we hired a cocktail expert and we got them to instruct us to make cocktails, said Praveen Srinivasan, another co-lead. We recorded those conversations and used that to train our initial model. Xu opened a cookbook to a recipe for a chicken curry, pointed her phone at it, and woke up Astra. Ni hao, Bibo! said a female voice. Oh! Why are you speaking to me in Mandarin? Xu asked her phone. Can you speak to me in English, please? My apologies, Bibo. I was following a previous instruction to speak in Mandarin. I will now speak in English as you have requested. Astra remembers previous conversations, Xu told me. It also keeps track of the previous 10 minutes of video. (Theres a remarkable moment in the promo video that Google put out in May when Astra tells the person giving the demo where she had left her glasses, having spotted them on a desk a few seconds earlier. But I saw nothing like this in the live demo.) Back to the cookbook. Moving her phone camera over the page for a few seconds, Xu asked Astra to read the recipe and tell her what spices were in it. I recall the recipe mentioning a teaspoon of black peppercorns, a teaspoon of hot chili powder, and a cinnamon stick, it replied. I think youre missing a few, said Xu. Take another look. You are correctI apologize. I also see ground turmeric and curry leaves in the ingredients. Seeing this tech in action, two things hit you straight away. First, its glitchy and often needs correcting. Second, those glitches can be corrected with just a few spoken words. You simply interrupt the voice, repeat your instructions, and move on. It feels more like coaching a child than butting heads with broken software. Next Xu pointed her phone at a row of wine bottles and asked Astra to pick the one that would go best with the chicken curry. It went for a rioja and explained why. Xu asked how much a bottle would cost. Astra said it would need to use Search to look prices up online. A few seconds later it came back with its answer. We moved to the art gallery, and Xu showed Astra a number of screens with famous paintings on them: the Mona Lisa, Munchs The Scream, a Vermeer, a Seurat, and several others. Ni hao, Bibo! the voice said. Youre speaking to me in Mandarin again, Xu said. Try to speak to me in English, please. My apologies, I seem to have misunderstood. Yes, I will respond in English. (I should know better, but I could swear I heard the snark.) It was my turn. Xu handed me her phone. I tried to trip Astra up, but it was having none of it. I asked it what famous art gallery we were in, but it refused to hazard a guess. I asked why it had identified the paintings as replicas and it started to apologize for its mistake (Astra apologizes a lot). I was compelled to interrupt: No, noyoure right, its not a mistake. Youre correct to identify paintings on screens as fake paintings. I couldnt help feeling a bit bad: Id confused an app that exists only to please. When it works well, Astra is enthralling. The experience of striking up a conversation with your phone about whatever youre pointing it at feels fresh and seamless. In a media briefing yesterday, Google DeepMind shared a video showing off other uses: reading an email on your phones screen to find a door code (and then reminding you of that code later), pointing a phone at a passing bus and asking where it goes, quizzing it about a public artwork as you walk past. This could be generative AIs killer app. And yet theres a long way to go before most people get their hands on tech like this. Theres no mention of a release date. Google DeepMind has also shared videos of Astra working on a pair of smart glasses, but that tech is even further down the companys wish list. Mixing it up For now, researchers outside Google DeepMind are keeping a close eye on its progress. The way that things are being combined is impressive, says Maria Liakata, who works on large language models at Queen Mary University of London and the Alan Turing Institute. Its hard enough to do reasoning with language, but here you need to bring in images and more. Thats not trivial. Liakata is also impressed by Astras ability to recall things it has seen or heard. She works on what she calls long-range context, getting models to keep track of information that they have come across before. This is exciting, says Liakata. Even doing it in a single modality is exciting. But she admits that a lot of her assessment is guesswork. Multimodal reasoning is really cutting-edge, she says. But its very hard to know exactly where theyre at, because they havent said a lot about what is in the technology itself. For Bodhisattwa Majumder, a researcher who works on multimodal models and agents at the Allen Institute for AI, thats a key concern. We absolutely dont know how Google is doing it, he says. He notes that if Google were to be a little more open about what it is building, it would help consumers understand the limitations of the tech they could soon be holding in their hands. They need to know how these systems work, he says. You want a user to be able to see what the system has learned about you, to correct mistakes, or to remove things you want to keep private. Liakata is also worried about the implications for privacy, pointing out that people could be monitored without their consent. I think there are things I'm excited about and things that I'm concerned about, she says. There's something about your phone becoming your eyestheres something unnerving about it. The impact these products will have on society is so big that it should be taken more seriously, she says. But its become a race between the companies. Its problematic, especially since we dont have any agreement on how to evaluate this technology. Google DeepMind says it takes a long, hard look at privacy, security, and safety for all its new products. Its tech will be tested by teams of trusted users for months before it hits the public. Obviously, weve got to think about misuse. Weve got to think about, you know, what happens when things go wrong, says Dawn Bloxwich, director of responsible development and innovation at Google DeepMind. Theres huge potential. The productivity gains are huge. But it is also risky. No team of testers can anticipate all the ways that people will use and misuse new technology. So whats the plan for when the inevitable happens? Companies need to design products that can be recalled or switched off just in case, says Bloxwich: If we need to make changes quickly or pull something back, then we can do that.

One afternoon in late November, I visited a weapons test site in the foothills east of San Clemente, California, operated by Anduril, a maker of AI-powered drones and missiles that recently announced a partnership with OpenAI. I went there to witness a new system its expanding today, which allows external parties to tap into its software and share data in order to speed up decision-making on the battlefield. If it works as planned over the course of a new three-year contract with the Pentagon, it could embed AI more deeply into the theater of war than ever before. Near the sites command center, which looked out over desert scrubs and sage, sat pieces of Andurils hardware suite that have helped the company earn its $14 billion valuation. There was Sentry, a security tower of cameras and sensors currently deployed at both US military bases and the US-Mexico border, and advanced radars. Multiple drones, including an eerily quiet model called Ghost, sat ready to be deployed. What I was there to watch, though, was a different kind of weapon, displayed on two large television screens positioned at the test sites command station. I was here to examine the pitch being made by Anduril, other companies in defense tech, and growing numbers of people within the Pentagon itself: A future great power conflictmilitary jargon for a global war involving competition between multiple countrieswill not be won by the entity with the most advanced drones or firepower, or even the cheapest firepower. It will be won by whoever can sort through and share information the fastest. And that will have to be done at the edge where threats arise, not necessarily at a command post in Washington. A desert drone test Youre going to need to really empower lower levels to make decisions, to understand whats going on, and to fight, Anduril CEO Brian Schimpf says. That is a different paradigm than today. Currently, information flows poorly among people on the battlefield and decision-makers higher up the chain. To show how the new tech will fix that, Anduril walked me through an exercise demonstrating how its system would take down an incoming drone threatening a base of the US military or its allies (the scenario at the center of Andurils new partnership with OpenAI). It began with a truck in the distance, driving toward the base. The AI-powered Sentry tower automatically recognized the object as a possible threat, highlighting it as a dot on one of the screens. Andurils software, called Lattice, sent a notification asking the human operator if he would like to send a Ghost drone to monitor. After a click of his mouse, the drone piloted itself autonomously toward the truck, as information on its location gathered by the Sentry was sent to the drone by the software. The truck disappeared behind some hills, so the Sentry tower camera that was initially trained on it lost contact. But the surveillance drone had already identified it, so its location stayed visible on the screen. We watched as someone in the truck got out and launched a drone, which Lattice again labeled as a threat. It asked the operator if hed like to send a second attack drone, which then piloted autonomously and locked onto the threatening drone. With one click, it could be instructed to fly into it fast enough to take it down. (We stopped short here, since Anduril isnt allowed to actually take down drones at this test site.) The entire operation could have been managed by one person with a mouse and computer. Anduril is building on these capabilities further by expanding Lattice Mesh, a software suite that allows other companies to tap into Andurils software and share data, the company announced today. More than 10 companies are now building their hardware into the systemeverything from autonomous submarines to self-driving trucksand Anduril has released a software development kit to help them do so. Military personnel operating hardware can then publish their own data to the network and subscribe to receive data feeds from other sensors in a secure environment. On December 3, the Pentagons Chief Digital and AI Office awarded a three-year contract to Anduril for Mesh. Andurils offering will also join forces with Maven, a program operated by the defense data giant Palantir that fuses information from different sources, like satellites and geolocation data. Its the project that led Google employees in 2018 to protest against working in warfare. Anduril and Palantir announced on December 6 that the military will be able to use the Maven and Lattice systems together. The militarys AI ambitions The aim is to make Andurils software indispensable to decision-makers. It also represents a massive expansion of how the military is currently using AI. You might think the US Department of Defense, advanced as it is, would already have this level of hardware connectivity. We have some semblance of it in our daily lives, where phones, smart TVs, laptops, and other devices can talk to each other and share information. But for the most part, the Pentagon is behind. Theres so much information in this battle space, particularly with the growth of drones, cameras, and other types of remote sensors, where folks are just sopping up tons of information, says Zak Kallenborn, a warfare analyst who works with the Center for Strategic and International Studies. Sorting through to find the most important information is a challenge. There might be something in there, but theres so much of it that we cant just set a human down and to deal with it, he says. Right now, humans also have to translate between systems made by different manufacturers. One soldier might have to manually rotate a camera to look around a base and see if theres a drone threat, and then manually send information about that drone to another soldier operating the weapon to take it down. Those instructions might be shared via a low-tech messenger appone on par with AOL Instant Messenger. That takes time. Its a problem the Pentagon is attempting to solve through its Joint All-Domain Command and Control plan, among other initiatives. For a long time, weve known that our military systems dont interoperate, says Chris Brose, former staff director of the Senate Armed Services Committee and principal advisor to Senator John McCain, who now works as Andurils chief strategy officer. Much of his work has been convincing Congress and the Pentagon that a software problem is just as worthy of a slice of the defense budget as jets and aircraft carriers. (Anduril spent nearly $1.6 million on lobbying last year, according to data from Open Secrets, and has numerous ties with the incoming Trump administration: Anduril founder Palmer Luckey has been a longtime donor and supporter of Trump, and JD Vance spearheaded an investment in Anduril in 2017 when he worked at venture capital firm Revolution.) Defense hardware also suffers from a connectivity problem. Tom Keane, a senior vice president in Andurils connected warfare division, walked me through a simple example from the civilian world. If you receive a text message while your phone is off, youll see the message when you turn the phone back on. Its preserved. But this functionality, which we dont even think about, Keane says, doesnt really exist in the design of many defense hardware systems. Data and communications can be easily lost in challenging military networks. Anduril says its system instead stores data locally. An AI data treasure trove The push to build more AI-connected hardware systems in the military could spark one of the largest data collection projects the Pentagon has ever undertaken, and companies like Anduril and Palantir have big plans. Exabytes of defense data, indispensable for AI training and inferencing, are currently evaporating, Anduril said on December 6, when it announced it would be working with Palantir to compile data collected in Lattice, including highly sensitive classified information, to train AI models. Training on a broader collection of data collected by all these sensors will also hugely boost the model-building efforts that Anduril is now doing in a partnership with OpenAI, announced on December 4. Earlier this year, Palantir also offered its AI tools to help the Pentagon reimagine how it categorizes and manages classified data. When Anduril founder Palmer Luckey told me in an interview in October that its not like theres some wealth of information on classified topics and understanding of weapons systems to train AI models on, he may have been foreshadowing what Anduril is now building. Even if some of this data from the military is already being collected, AI will suddenly make it much more useful. What is new is that the Defense Department now has the capability to use the data in new ways, Emelia Probasco, a senior fellow at the Center for Security and Emerging Technology at Georgetown University, wrote in an email. More data and ability to process it could support great accuracy and precision as well as faster information processing. The sum of these developments might be that AI models are brought more directly into military decision-making. That idea has brought scrutiny, as when Israel was found last year to have been using advanced AI models to process intelligence data and generate lists of targets. Human Rights Watch wrote in a report that the tools rely on faulty data and inexact approximations. I think we are already on a path to integrating AI, including generative AI, into the realm of decision-making, says Probasco, who authored a recent analysis of one such case. She examined a system built within the military in 2023 called Maven Smart System, which allows users to access sensor data from diverse sources [and] apply computer vision algorithms to help soldiers identify and choose military targets. Probasco said that building an AI system to control an entire decision pipeline, possibly without human intervention, isnt happening and that there are explicit US policies that would prevent it. A spokesperson for Anduril said that the purpose of Mesh is not to make decisions. The Mesh itself is not prescribing actions or making recommendations for battlefield decisions, the spokesperson said. Instead, the Mesh is surfacing time-sensitive informationinformation that operators will consider as they make those decisions.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. We saw a demo of the new AI system powering Andurils vision for war James ODonnell One afternoon in late November, I visited a weapons test site in the foothills east of San Clemente, California operated by Anduril, a maker of AI-powered drones and missiles that recently announced a partnership with OpenAI. I went there to witness a new system its expanding today, which allows external parties to tap into its software and share data in order to speed up decision-making on the battlefield.If it works as planned over the course of a new three-year contract with the Pentagon, it could embed AI more deeply than ever before into the theater of war. Read the full story. How to use Sora, OpenAIs new video generating tool OpenAI has just released its video generation model Sora to the public. The announcement yesterday came on the fifth day of the companys shipmas event, a 12-day marathon of tech releases and demos. Heres what you should knowand how you can use the video model right now.James ODonnell This story is the latest in MIT Technology Reviews How To series, which helps you get things done. AIs hype and antitrust problem is coming under scrutinyThe AI sector is plagued by a lack of competition and a lot of deceitor at least thats one way to interpret the latest flurry of actions taken in Washington. The actionsfrom antitrust investigations to accusations of straight-up lyingrepresent an effort to hold the AI industrys hype to account in the final months before the Federal Trade Commissions chair, Lina Khan, is replaced when Donald Trump takes office.But while the FTC looks to have a far smoother transition of leadership ahead than most other federal agencies, at least some of Trumps frustrations with Big Tech could send antitrust efforts in a distinctly new direction. Read the full story.James ODonnell This story is from The Algorithm, our weekly newsletter giving you the inside track on all things happening in the fascinating field of AI. Sign up to receive it in your inbox every Monday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Google has built a powerful new quantum computing chip But it doesnt have any real-world applicationsyet. (Bloomberg $) + It takes five minutes to solve a problem that a traditional supercomputer could not master in 10 septillion years. (NYT $)+ Its a challenge the quantum field has been trying to crack for decades. (The Guardian)+We covered the work when it was a preprint in September.(MIT Technology Review) 2 Nvidia is being investigated by China It claims the chipmaking giant has violated anti-monopoly laws. (BBC)+ Nvidias biggest customer in the country? That would be ByteDance. (Insider $)+ Whats next in chips. (MIT Technology Review)3 TikTok has asked a US appeals court to halt the buy-or-sell law As it stands, the app faces a ban unless it finds a new owner by January 19. (TechCrunch)4 AI is still failing to deliver on its economic promises Is 2025 the year we finally start to see some results? (Quartz)+ The US AI industry is in desperate need of more sites with power grid access. (FT $)+ How to fine-tune AI for prosperity. (MIT Technology Review)5 The EUs competition rules are on the verge of a big shakeup A new boss means a new approach. (WSJ $)+ European regulators want to get to the bottom of a Meta and Google investigation. (FT $)6 Weight-loss drugs are making basic health truths obsolete A healthy diet and regular exercise is falling by the wayside. (The Atlantic $)+ Weight-loss injections have taken over the internet. But what does this mean for people IRL? (MIT Technology Review)7 This bionic leg is controlled by its wearers brain Prosthetic limbs are becoming much more capable. (New Yorker $)+ These prosthetics break the mold with third thumbs, spikes, and superhero skins. (MIT Technology Review)8 An AI can make a pretty decent Tokyo travel companionJust make sure you take its advice with a pinch of salt. (Wired $) + How to use AI to plan your next vacation. (MIT Technology Review)9 Reddit is testing a new AI search feature Which the sites users are unlikely to take kindly to. (Ars Technica) 10 Jeff Bezos has a dinner with Donald Trump in his diary Sounds cozy. (Insider $)Quote of the day Its like manna from heaven. Ari Morcos, chief executive of startup DatologyAI, explains to the Wall Street Journal why Reddits troves of text are so appealing to AI companies. The big story Inside the enigmatic minds of animals October 2022 More than ever, we feel a duty and desire to extend empathy to our nonhuman neighbors. In the last three years, more than 30 countries have formally recognized other animalsincluding gorillas, lobsters, crows, and octopusesas sentient beings. A trio of books from Ed Yong, Jackie Higgins, and Philip Ball detail creatures rich inner worlds and capture what has led to these developments: a booming field of experimental research challenging the long-standing view that animals are neither conscious nor cognitively complex. Read the full story. Matthew Ponsford We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + It seems we have two types of laugh: one caused by tickling, and the other by everything else.+ 2024 was a strong year for fiction: check out some of the best new books.+ Theres something totally mesmerizing about this collection of old home videos.+ Ukrainian artist Oleg Dron specializes in expansive, haunting landscapes.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. The worlds next big environmental problem could come from space In September, a unique chase took place in the skies above Easter Island. From a rented jet, a team of researchers captured a satellites last moments as it fell out of space and blazed into ash across the sky, using cameras and scientific equipment. Their hope was to gather priceless insights into the physical and chemical processes that occur when satellites burn up as they fall to Earth at the end of their missions. This kind of study is growing more urgent. The number of satellites in the sky is rapidly risingwith a tenfold increase forecast by the end of the decade. Letting these satellites burn up in the atmosphere at the end of their lives helps keep the quantity of space junk to a minimum. But doing so deposits satellite ash in the Earths atmosphere. This metallic ash could potentially alter the climate, and we dont yet know how serious the problem is likely to be.Read the full story. Tereza Pultarova OpenAIs 12 days of shipmas tell us a lot about the AI arms race Last week, OpenAI announced what it calls the 12 days of OpenAI, or 12 days of shipmas. On December 4, CEO Sam Altman took to X to announce that the company would be doing 12 days of openai. each weekday, we will have a livestream with a launch or demo, some big ones and some stocking stuffers. The company will livestream about new products every morning for 12 business days in a row during December. Its an impressive-sounding (and media-savvy) schedule, to be sure. But it also speaks to how tight the race between the AI bigs has become, and also how much OpenAI is scrambling to build more revenue.Read the full story. Mat Honan This story originally appeared in The Debrief with Mat Honan, our weekly take on whats really going on behind the biggest tech headlines. The story is subscriber-only sonab a subscriptiontoo, if you havent already! Or you cansign upto the newsletter for free to get the next edition in your inbox on Friday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 The USDA is launching a national program to test milk for bird flu A full nine months after the current outbreak was first detected in dairy cows. (STAT)+The risk of a bird flu pandemic is rising.(MIT Technology Review)2 Heres what sets OpenAIs new models apart Theyre shifting from predicting to reasoning, which could be a huge deal. (The Atlantic$)+Regardless of whether capabilities are slowing, AIs impact is only poised to grow.(Vox)+It may be comforting to dismiss AI as hypebut it misses the point.(Platformer)3 A federal appeals court has upheld the US TikTok banBut what happens next is anyones guess. (WSJ$)+Whether TikTok is banned or not, the actions against it have had a big impact.(MIT Technology Review)4 Top internet sleuths are sitting out the hunt for the UnitedHealthcare CEO killerIn fact, some are even criticizing people who are trying to help. (NBC)+Why so many Americans are at best indifferent to this particular murder.(New Yorker$)5 Schools are attempting to stop teens self-harming before they even tryThe AI tools theyre adopting could be doing far more damage than help, though. (NYT$)6 China is building its own Starlink systemThe Qianfan constellation could eventually grow to nearly 14,000 satellites. (The Economist$)+The end of the ISS will usher in a more commercialized future in space. (The Verge)7 This was an exciting year for superconductorsSuperconductivitythe flow of electric current with no resistancewas discovered in three new materials. (Quanta$)8 Meet the worlds least productive programmersIt seems a small minority of disillusioned ghost engineers do pretty much no work at all. (WP$)9 Why people are turning their backs on dating appsTheres a large degree of fatigue, and a feeling that theyre somehow detached from reality. (The Guardian)10 Fake snacks are racking up millions of views on InstagramTheres even a word for this trend: snackfishing. (Wired$)Quote of the day I think Twitter and now X is like a crack addiction for him, though. He is clearly chasing a particular hit all the time and he has ended up self-radicalising himself with the platform he has purchased. A former Twitter employee in London tellsThe Guardianhow Elon Musk has changed since he purchased the platform. The big story How electricity could help tackle a surprising climate villain Sublime SystemsBOB O'CONNOR January 2024 Cement is used to build everything from roads and buildings to dams and basement floors. But its also a climate threat. Cement production accounts for more than 7% of global carbon dioxide emissionsmore than sectors like aviation, shipping, or landfills. One solution to this climate catastrophe might be coursing through the pipes at Sublime Systems. The startup is developing an entirely new way to make cement. Instead of heating crushed-up rocks in lava-hot kilns, Sublimes technology zaps them in water with electricity, kicking off chemical reactions that form the main ingredients in its cement. But it faces huge challenges: competing with established industry players, and persuading builders to use its materials in the first place.Read the full story. Casey Crownhart We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + Who will be theLord of Misrulein your household this Christmas? + PeoplesWikipediabrowsing data always makes for interesting reading.+ Wait, so weve been mispronouncingthese wordsall along? (Apart from espresso, cmon)+ TheMuppet Christmas Carolmight just be the greatest festive film.

MIT Technology ReviewsHow To. Today, OpenAI released its video generation model Sora to the public. The announcement comes on the fifth day of the companys shipmas event, a 12-day marathon of tech releases and demos. Heres what you should knowand how you can use the video model right now. What is Sora? Sora is a powerful AI video generation model that can create videos from text prompts, animate images, or remix videos in new styles. OpenAI first previewed the model back in February, but today is the first time the company is releasing it for broader use. Whats new about this release? The core function of Soracreating impressive videos with simple promptsremains similar to what was previewed in February, but OpenAI worked to make the model faster and cheaper ahead of this wider release. There are a few new features, and two stand out. One is called Storyboard. With it, you can create multiple AI-generated videos and then assemble them together on a timeline, much the way you would with conventional video editors like Adobe Premiere Pro. The second is a feed that functions as a sort of creative gallery. Users can post their Sora-generated videos to the feed, see the prompts behind certain videos, tweak them, and generally get inspiration, OpenAI says. How much can you do with it? You can generate videos from text prompts, change the style of videos and change elements with a tool called Remix, and assemble multiple clips together with Storyboard. Sora also provides preset styles you can apply to your videos, like moody film noir or cardboard and papercraft, which gives a stop-motion feel. You can also trim and loop the videos that you make. Who can use it? To generate videos with Sora, youll need to subscribe to one of OpenAIs premium planseither ChatGPT Plus ($20 per month) or ChatGPT Pro ($200 per month). Both subscriptions include access to other OpenAI products as well. Users with ChatGPT Plus can generate videos as long as five seconds with a resolution up to 720p. This plan lets you create 50 videos per month. Users with a ChatGPT Pro subscription can generate longer, higher-resolution videos, capped at a resolution of 1080p and a duration of 20 seconds. They can also have Sora generate up to five variations of a video at once from a single prompt, making it possible to review options faster. Pro users are limited to 500 videos per month but can also create unlimited relaxed videos, which are not generated in the moment but rather queued for when site traffic is low. Both subscription levels make it possible to create videos in three aspect ratios: vertical, horizontal, and square. If you dont have a subscription, youll be limited to viewing the feed of Sora-generated videos. OpenAI is starting its global launch of Sora today, but it will take longer to launch in most of Europe, the company said. OPENAI Where can I access it? OpenAI has broken Sora out from ChatGPT. To access it, go to Sora.com and log in with your ChatGPT Plus or Pro account. (MIT Technology Review was unable to access the site at press timea note on the site indicated that signups were paused because they were currently experiencing heavy traffic.) Howd we get here? A number of things have happened since OpenAI first unveiled Sora back in February. Other tech companies have also launched video generation tools, like Meta Movie Gen and Google Veo. Theres also been plenty of backlash. For example, artists who had early access to experiment with Sora leaked the tool to protest the way OpenAI has trained it on artists work without compensation. Whats next? As with any new release of a model, it remains to be seen what steps OpenAI has taken to keep Sora from being used for nefarious, illegal, or unethical purposes, like the creation of deepfakes. On the question of moderation and safety, an OpenAI employee said they might not get it perfect on day one. Another looming question is how much computing capacity and energy Sora will use up every time it creates a video. Generating a video uses much more computing time, and therefore energy, than generating a typical text response in a tool like ChatGPT. The AI boom has already been an energy hog, presenting a challenge to tech companies aiming to rein in their emissions, and the wide availability of Sora and other video models like it has the potential to make that problem worse.

MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand whats coming next. You can read more from the series here. This week, China banned exports of several critical minerals to the US, marking the latest move in an escalating series of tit-for-tat trade restrictions between the worlds two largest economies. In explicitly cutting off, rather than merely restricting, materials of strategic importance to the semiconductor, defense, and electric vehicle sectors, China has clearly crossed a new line in the long-simmering trade war. At the same time, it selected minerals that wont cripple any industrieswhich leaves China plenty of ammunition to inflict greater economic pain in response to any further trade restrictions that the incoming Trump administration may impose. The president-elect recently pledged to impose an additional 10% tariff on all Chinese goods, and he floated tariff rates as high as 60% to 100% during his campaign. But China, which dominates the supply chains for numerous critical minerals essential to high-tech sectors, seems to be telegraphing that its prepared to hit back hard. Its a sign of what China is capable of, says Gracelin Baskaran, director of the Critical Minerals Security Program at the Center for Strategic and International Studies, a bipartisan research nonprofit in Washington, DC. Shots have been fired. What drove the decision? Chinas announcement directly followed the Biden administrations decision to further restrict exports of chips and other technologies that could help China develop advanced semiconductors used in cutting-edge weapon systems, artificial intelligence, and other applications. Throughout his presidency, Biden has enacted a series of increasingly aggressive export controls aimed at curbing Chinas military strength, technological development, and growing economic power. But the latest clampdown crossed a clear line in the sand for China, by threatening its ability to protect national security or shift toward production of more advanced technologies, says Cory Combs, associate director at Trivium China, a research firm. It is very much indicative of where Beijing feels its interests lie, he says. What exactly did China ban? In response to the USs new chip export restrictions, China immediately banned exports of gallium, germanium, antimony, and so called superhard materials used heavily in manufacturing, arguing that they have both military and civilian applications, according to the New York Times. China had already placed limits on the sale of most of these goods to the US. The nation said it may also further restrict sales of graphite, which makes up most of the material in the lithium-ion battery anodes used in electric vehicles, grid storage plants, and consumer electronics. What will the bans do? Experts say, for the most part, the bans wont have major economic impacts. This is in part because China already restricted exports of these minerals months ago, and also because they are mostly used for niche categories within the semiconductor industry. US imports of these materials from China have already fallen as US companies figured out new sources or substitutes for the materials. But a recent US Geological Survey study found that outright bans on gallium and germanium by China could cut US gross domestic product by $3.4 billion. In addition, these are materials that US politicians will certainly take note of, because they touch on many forms of security: economic, energy, and defense, Baskaran says. Antimony, for example, is used in armor-piercing ammunition, night-vision goggles, infrared sensors, bullets, and precision optics, Baskaran and a colleague noted in a recent essay. Companies rely on gallium to produce a variety of military and electronics components, including satellite systems, power converters, LEDs, and the high-powered chips used in electric vehicles. Germanium is used in fiber optics, infrared optics, and solar cells. Before it restricted the flow of these materials, China accounted for more than half of US imports of gallium and germanium, according to the US Geological Survey. Together, China and Russia control 50% of the worldwide reserves of antimony. How does it affect climate tech? Any tightened restrictions on graphite could have a pronounced economic impact on US battery and EV makers, in part because there are so few other sources for it. China controls about 80% of graphite output from mines and processes around 70% of the material, according to the International Energy Agency. It would be very significant for batteries, says Seaver Wang, co-director of the climate and energy team at the Breakthrough Institute, where his research is focused on minerals and manufacturing supply chains. By weight, you need way more graphite per terawatt hour than nickel, cobalt, or lithium. And the US has essentially no operating production. Anything that pushes up the costs of EVs threatens to slow the shift away from gas-guzzlers in the US, as their lofty price tags remain one of the biggest hurdles for many consumers. How does this impact Chinas economy? There are real economic risks in Chinas decision to cut off the sale of materials it dominates, as it creates incentives for US companies to seek out new sources around the world, switch to substitute materials, and work to develop more domestic supplies where geology allows. The challenge China faces is that most of its techniques to increase pain by disrupting supply chains would also impact China, which itself is connected to these supply chains, says Chris Miller, a professor at Tufts University and author of Chip War: The Fight for the Worlds Most Critical Technology. Notably, the latest announcement could compel US companies to develop their own sources of gallium and germanium, which can be extracted as by-products of zinc and aluminum mining. There are a number of zinc mines in Alaska and Tennessee, and limited extraction of bauxite, which produces aluminum, in Arkansas, Alabama, and Georgia. Gallium can also be recycled from numerous electronics, providing another potential domestic path for US companies, Combs notes. The US has already taken steps to counter Chinas dominance over the raw ingredients of essential industries, including by issuing a $150 million loan to an Australian company, Syrah Resources, to accelerate the development of graphite mining in Mozambique. In addition, the mining company Perpetua Resources has proposed reopening a gold mine near Yellow Pine, Idaho, in part to extract antimony trisulfide for use in military applications. The US Department of Defense has provided tens of millions of dollars to help the company conduct environmental studies, though it will still take years for the mine to come online, noted Baskaran and her colleague. Wang says that Chinas ban might prove shortsighted, as any success in diversifying these global supply chains will weaken the nations grip in the areas it now dominates. What happens next? The US is also likely to pay very high economic costs in an escalating trade war with China. Should the nation decide to enact even stricter trade restrictions, Combs says China could opt to inflict greater economic pain on the US through a variety of means. These could include further restricting or fully banning graphite, as well other crucial battery materials like lithium; cutting off supplies of tungsten, which is used heavily in the aerospace, military, and nuclear power sectors; and halting the sale of copper, which is used in power transmission lines, solar panels, wind turbines, EVs, and many other products. China may also decide to take further steps to prevent US firms from selling their goods into the massive market of Chinese consumers and industries, Miller adds. Or it might respond to stricter export restrictions by turning to the USs economic rivals for advanced technologies. In the end, its not clear either nation wins in a protracted and increasingly combative trade war. But its also not apparent that mutually assured economic damage will prove to be an effective deterrent. Indeed, China may well feel the need to impose stricter measures in the coming months or years, as there are few signs that President-elect Trump intends to tone down his hawkish stance toward China. Its hard to see a Trump 2.0 de-escalating with China, Baskaran says. Were on a one-way trajectory toward continued escalation; the question is the pace and the form. Its not really an if question.

This article first appeared in The Checkup,MIT Technology Reviewsweekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first,sign up here. Theres a new film about IVF out on Netflix. And everyone in the field [of reproductive medicine] has watched it, according to one embryologist I spoke to recently. Joy is a lovely watch about the birth of the field, thanks to the persistent efforts of Robert Edwards, Jean Purdy, and Patrick Steptoe in the face of significant opposition. The team performed much of their key research during the 1960s and 70s. And Louise Brown, the first test tube baby (as she was called at the time), was born in 1978. Its remarkable to think that within 40 years of that milestone, another 8 million babies had been born through IVF. Today, it is estimated that over 12 million babies have resulted from IVF, and that the use of reproductive technology accounts for over 2% of births in the US. IVF is a success story for embryo research. But today, valuable embryos that could be used for research are being wasted, say researchers who gathered at a conference in central London earlier this week. The conference was organized by the Progress Educational Trust, a UK-based charity that aims to provide information to the public on genomics and infertility. The event marked 40 years since the publication of the Warnock Report, which followed a governmental inquiry into infertility treatment and embryological research. The report is considered to be the first to guide recognition of the embryos special status in law and helped establish regulation of the nascent technology in the UK. The report also endorsed the 14-day rule, which limits the growth of embryos in a lab to this two-week point. The rule, since adopted around the world, is designed to prevent scientists from growing embryos to the point where they develop a structure called the primitive streak. At this point, the development of tissues and organs begins, and the embryo is no longer able to split to form twins. The embryos studied in labs have usually been created for IVF but are no longer needed by the people whose cells created them. Those individuals might have completed their families, or they might not be able to use the embryos because their circumstances have changed. Sometimes the embryos have genetic abnormalities that make them unlikely to survive a pregnancy. These embryos can be used to learn more about how humans develop before birth, and to discover potential treatments for developmental disorders like spina bifida or heart defects, for example. Research on embryos can help reveal clues about our fundamental biology, and provide insight into pregnancy and miscarriage. A survey conducted by the Human Fertility and Embryology Authority, which regulates reproductive technology in the UK, found that the majority of patients would rather donate their embryos to research than allow them to perish, Geraldine Hartshorne, director of the Coventry Centre for Reproductive Medicine, told the audience. Despite this, the number of embryos donated for research in the UK has dropped steeply over the last couple of decades, from 17,925 in 2004 to 675 in 2019a surprising decline considering that the number of IVF cycles performed increased steadily over the same period. There are a few reasons why embryos arent making it into research labs, says Hartshorne. Part of the problem is that most IVF cycles happen at clinics that dont have links with academic research centers. As things stand, embryos tend to be stored at the clinics where they were created. It can be difficult to get them to research centersclinic staff dont have the time, energy, or head space to manage the paperwork legally required to get embryos donated to specific research projects, said Hartshorne. It would make more sense to have some large, central embryo bank where people could send embryos to donate for research, she added. A particular problem is the paperwork. While the UK is rightly praised for its rigorous approach to regulation of reproductive technologies, which embryologists around the globe tend to describe as world-leading, there are onerous levels of bureaucracy to contend with, said Hartshorne. When patients contact me and say Id like to give my embryos or my eggs to your research project, I usually have to turn them away, because it would take me a year to get through the paperwork necessary, she said. Perhaps theres a balance to be struck. Research on embryos has the potential to be hugely valuable. As the film Joy reminds us, it can transform medical practice and change lives. Without research, there would be no progress, and there would be no change, Hartshorne said. That is definitely not something that I think we should aspire to for IVF and reproductive science. Now read the rest of The Checkup Read more from MIT Technology Review's archive Scientists are working on ways to create embryos from stem cells, without the use of eggs or sperm. How far should we allow these embryo-like structures to develop? Researchers have implanted these synthetic embryos in monkeys. So far, theyve been able to generate a short-lived pregnancy-like response but no fetuses. Others are trying to get cows pregnant with synthetic embryos. Reproductive biologist Carl Jiangs first goal is to achieve a cow pregnancy that lasts 30 days. Several startups are using robots to fertilize eggs with sperm to create embryos. Two girls are the first people to be born after robot-assisted fertilization, says the team behind the work. From around the web Mexicos Sinaloa cartel is recruiting young chemistry students from colleges to make fentanyl. Specifically, the students are being tasked with the often dangerous job of trying to synthesize precursor chemicals that must currently be imported. They also try to design stronger versions of the drug that are more likely to get users hooked. (New York Times) Billionaire Greg Lindberg is running his own baby project. Having duped, misled, and paid off a series of egg donors and surrogates, the disgraced insurance tycoon currently has 12 children, nine of whom were born in the last five years or so. He is the sole parent caring for eight of them, despite facing significant jail time since being convicted of bribery and pleading guilty to money laundering and fraud conspiracy charges for crimes unrelated to the baby project. The scale of his project is an indictment of the US fertility industry. (Bloomberg Businessweek) The UK government has agreed to a contract for more than 5 million doses of a vaccine designed to protect people from the H5 bird flu virus. The vaccine is being procured as part of pandemic preparedness plans and will be used only if the virus starts spreading among humans. (UK Health Security Agency) Last week, MPs voted in favor of a bill to legalize assisted dying in England and Wales. In the past few months, the debate over the bill has included horror stories of painful deaths. Most deaths are ordinary, but we all stand to benefit from talking about, and understanding, what death involves. (New Statesman) An unknown disease has killed 143 people in southwest Congo, according to local authorities. The number of infections continues to rise, and the situation is extremely worrying. (Reuters) Brian Thompson, the 50-year-old CEO of US health insurance company UnitedHealthcare, was fatally shot in New York city on Wednesday. The New York Times is reporting that bullet casings found at the scene appear to have been marked with the words "delay" and "deny." The words may refer to strategies used by insurance companies to avoid covering healthcare costs. (New York Times)

Next month, MIT Technology Review will unveil the 2025 list of 10 Breakthrough Technologies. Every year, our newsroom looks across the fields we cover for technologies that are having a true breakthrough moment. This annual package highlights the technologies that we think matter most right now. We define breakthrough in a few waysperhaps theres been a scientific advance that now makes a new technology possible, or a company has earned regulatory approval for a vital medical treatment. Maybe a consumer device has reached a tipping point in its adoption, or an industrial technology has passed the critical pilot phase with flying colors. In the 2025 edition, which comes out in January, youll see some of the latest advances in automation, medicine, and the physical sciences (just to name a few) that we expect will have a major impact on our lives. In the meantime, here are three technologies that we considered including on the 2025 list but ultimately decided to leave off. Though these nominees didnt make the cut this year, theyre still worth keeping an eye on. We certainly will be. Virtual power plants Virtual power plants are energy systems that link together many different technologies to both generate and store power. They allow utility companies to connect solar panels and wind turbines with grid batteries and electric vehicles, and to better manage the flow of power across the grid. During times of peak electricity usage, software linked to smart meters may one day automatically decide to power someones home by drawing electricity from a fully charged EV sitting in a neighbors garage, thereby reducing demand on the grid. The software could also work out how to compensate the EV owner accordingly. In the US, an estimated 500 virtual power plants now provide up to 60 gigawatts of capacity (thats about as much total capacity as the US grid will add this year). Some such systems are also up and running in China, Japan, Croatia, and Taiwan. But lots more virtual power plants would need to be configured before they start to affect the grid as a whole. Useful AI agents AI agents are all the rage right now. These AI-powered helpers will, supposedly, schedule our meetings and book our trips and carry out all kinds of tasks online on our behalf. Agents employ generative models to learn how to navigate websites and desktop software (and manage our passwords and credit card details). They will perhaps interact and coordinate with other peoples agents along the way. And there is real development power behind themSalesforce just launched a platform where companies can make their own customer service agents, and Anthropics Claude model is gaining the ability to navigate a computer by using a mouse and keyboard, just like people. However, many challenges remain in getting these agents to know what you mean when you make specific requests, and enabling them to carry out the necessary actions reliably. Given the formidable hurdles, we think it may be a little while before they are good enough to be truly useful. AI agents may be coming, but not just yet. eVTOLs The acronym is a mouthful, but you can think of electric vertical takeoff and landing (eVTOL) aircraft as being kind of like electric helicopters. Most versions in development are not designed to be personal vehicles; theyd be flown by pilots to transport commuters in from the suburbs, or whisk visitors downtown from the airport. Someday, these air taxis may fly themselves. Theres been real progress toward getting eVTOLs off the ground. Earlier this year, manufacturer EHang received the first Chinese certificate to mass-produce this type of vehicle, and it has begun taking orders. South Korea and the UAE have put policies in place to allow eVTOLs to operate there. And in the US, Archer recently earned its FAA certification to begin commercial operations. Then, in October, the FAA finalized rules for training pilots and operating eVTOLsmarking the first time in decades that the agency has approved such rules for a new category of aircraft. Interest and momentum have built in recent years. Major players in the aviation industry, including Boeing and Airbus, have invested in startups or funded internal R&D projects to develop these futuristic aircraft. However, no eVTOL company has actually begun commercial operations yet, so well keep watching for that. Join us for a special live Roundtables event "Unveiling the 10 Breakthrough Technologies of 2025"Register to attendorsubscribe for access.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. What Chinas critical mineral ban means for the US This week, China banned exports of several critical minerals to the US, marking the latest move in an escalating series of tit-for-tat trade restrictions between the worlds two largest economies. In explicitly cutting off, rather than merely restricting, materials of strategic importance to the semiconductor, defense, and electric vehicle sectors, China has clearly crossed a new line in the long-simmering trade war. But at the same time, it selected minerals that wont cripple any industrieswhich leaves China plenty of ammunition to inflict greater economic pain in response to any further trade restrictions that the incoming Trump administration may impose. Read more about what drove Chinas decision, how it affects climate tech and whats likely to happen next. James Temple This story is part of our MIT Technology Review Explains series. Let our writers untangle the complex, messy world of technology to help you understand whats coming next. You can read more from the series here. 3 things that didnt make the 10 Breakthrough Technologies of 2025 list Next month, MIT Technology Review will unveil the 2025 list of 10 Breakthrough Technologies. Every year, our newsroom looks across the fields we cover for technologies that are having a true breakthrough moment. This annual package highlights the technologies that we think matter most right now. In the meantime, here are three technologies that we considered including on the 2025 list but ultimately decided to leave off. And although these nominees didnt make the cut this year, theyre still worth keeping an eye on. Read the full story. Amy Nordrum The US Department of Defense is investing in deepfake detection Whats new: The US Department of Defense has invested $2.4 million over two years in deepfake detection technology from a startup called Hive AI. Its the first contract of its kind for the DODs Defense Innovation Unit, which accelerates the adoption of new technologies for the US defense sector. Hive AIs models are capable of detecting AI-generated video, image, and audio content. Why? Although deepfakes have been around for the better part of a decade, generative AI has made them easier to create and more realistic-looking than ever before, which makes them ripe for abuse in disinformation campaigns or fraud. Defending against these sorts of threats is now crucial for national security. Read the full story. Melissa Heikkil Donating embryos for research is surprisingly complex IVF is a success story for embryo research. But today, valuable embryos that could be used for research are being wasted, say researchers who gathered at a conference in central London earlier this week. The embryos studied in labs have usually been created for IVF but are no longer needed by the people whose cells created them. And theres a few reasons why embryos arent making it into research labs. Read the full story. Jessica Hamzelou This story is from the Checkup, our weekly health and biotech newsletter. Sign up to receive it in your inbox every Thursday. The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Internet detectives are racing to identify UnitedHealthcare CEOs killer Its yet another example of online sleuths inserting themselves into active investigations. (WP $)+ Similar firms are removing their leadership pages for fear of copycat attacks. (404 Media)+ Online reaction to the killing demonstrates how hated health insurers are. (NY Mag $) 2 NASA has delayed its return to the moonyet again Its pushed back its planned mission from 2026 to mid-2027. (CNN)+ The agency has safety concerns and says its next test flight needs to be overhauled. (WP $)+ Whats next for NASAs giant moon rocket? (MIT Technology Review)3 OpenAI is charging $200 a month for a ChatGPT Pro subscription Access to its o1 reasoning model sure doesnt come cheap. (TechCrunch)+ Heres what you get for that hefty fee. (Wired $)4 Google Search is getting a makeover in 2025 And Id be prepared to bet a lot of money that AI is involved. (NYT $)+ AI search could break the web. (MIT Technology Review)5 Spotify Wrapped is a flop Its oddly free of actual data, and contains bizarre summaries. (Rolling Stone $)+ Pink Pilates Princess Roller Skating Pop, anyone? (NYT $)+ Wrappeds AI-generated podcast makes for a bleak listening experience. (Vox)6 Whats next for Chinas manufacturing industryFT $)+ How Trumps tariffs could drive up the cost of batteries, EVs, and more. (MIT Technology Review)7 How to turn human poo into medicine The first microbiome-related product for cancer care is on the horizon. (Bloomberg $) + How bugs and chemicals in your poo could give away exactly what youve eaten. (MIT Technology Review)8 Meet the final devotees of the NFTAfter the bubble bursts, only the true believers remain. (NYT $) + I tried to buy an Olive Garden NFT. All I got was heartburn. (MIT Technology Review)9 Want to live sustainably? Retrofit your home It reduces emissions and could save you money in the long run. (Knowable Magazine)+ Is this the most energy-efficient way to build homes? (MIT Technology Review)10 Winter isnt what it used to be Water, water everywhere. (The Atlantic $) Quote of the day I think the leaders of the industry should look at this and ask: Why does everybody hate us so much that when one of us gets killed in an assassinationwere not hearing sympathy from the general publicwere hearing scorn? Matthew Holt, a healthcare commenter, reflects on what the online reaction to the killing of UnitedHealthcares CEO reveals about the US publics attitude to health insurance firms, the Washington Post reports. The big story What is AI? July 2024 AI is sexy, AI is cool. AI is entrenching inequality, upending the job market, and wrecking education. The AI boom will boost the economy, the AI bubble is about to burst. AI will increase abundance and empower humanity to maximally flourish in the universe. AI will kill us all. What the hell is everybody talking about? Artificial intelligence is the hottest technology of our time. But what is it? It sounds like a stupid question, but its one thats never been more urgent. If youre willing to buckle up and come for a ride, I can tell you why nobody really knows, why everybody seems to disagree, and why youre right to care about it. Read the full story. Will Douglas Heaven We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + This year produced some incredible songs. Here are just a few of the best.+ Would you consider growing your own toilet paper? Meet the brave souls giving it a go. + Theres only one Willem Dafoea master of the craft.+ Congratulations are in order for Wisdom, the worlds oldest known wild bird who has just laid an egg at the ripe old age of 74.

This is today's edition ofThe Download,our weekday newsletter that provides a daily dose of what's going on in the world of technology. OpenAIs new defense contract completes its military pivot At the start of 2024, OpenAIs rules for how armed forces might use its AI models were unambiguous: it prohibited anyone from using them for weapons development or military and warfare. It has slowly softened those restrictions over the course of this year, and now, OpenAI has announced that its technology will be deployed directly on the battlefield. The company is partnering with the defense-tech company Anduril, a maker of AI-powered drones, radar systems, and missiles, to help US and allied forces defend against drone attacks. Read our story to understand how, and why, this pivot unfolded.James ODonnell Would you eat dried microbes? This company hopes so. Whats new: A company best known for sucking up industrial waste gases is turning its attention to food. LanzaTech, a rising star in the fuel and chemical industries, is joining a growing group of businesses producing microbe-based food as an alternative to plant and animal products. Why it matters: The global food system is responsible for roughly 25% to 35% of all human-caused greenhouse gas emissions today, and much of that comes from animal agriculture. Alternative food sources could help feed the world while cutting climate pollution. Read the full story. Casey Crownhart To read more about the potential positive effects of alternative meat on the climate, check out the latest edition of The Spark, our weekly climate and energy newsletter. Sign up to receive it in your inbox every Wednesday. Google DeepMinds new AI model is the best yet at weather forecasting Google DeepMind has unveiled an AI model thats better at predicting the weather than the current best systems. The new model, dubbed GenCast, is the second AI weather model that Google has launched in just the past few months. In July, it published details of NeuralGCM, a model that combined AI with physics-based methods like those used in existing forecasting tools. That model performed similarly to conventional methods but used less computing power.GenCast is different, as it relies on AI methods alone. It works sort of like ChatGPT, but instead of predicting the next most likely word in a sentence, it produces the next most likely weather condition. But while its results are impressive, that doesn't mean the end of conventional meteorology as a field. Read the full story. Scott J Mulligan The must-reads Ive combed the internet to find you todays most fun/important/scary/fascinating stories about technology. 1 Donald Trump has appointed a billionaire astronaut to head up NASA Jarad Isaacman has been into space twice, and was the first private citizen to carry out a spacewalk. (CBS News)+ Unsurprisingly, hes also a close associate of Elon Musk. (Fast Company $)+ Will the appointment make Musk more amenable to NASA? (Economist $)2 The price of a single bitcoin has passed $100,000 Its a remarkable milestone for the famously volatile cryptocurrency. (NYT $)+ The industrys faithful hope Donald Trump will pass crypto-friendly laws. (The Guardian)+ Congrats, investors. What comes next, though? (FT $)3 Humane isnt giving up on its AI pin Despite few sales, it wants to embed the device in your phone and car. (The Verge)+ The pin made a special appearance in our inaugural AI Hype Index. (MIT Technology Review)4 Amazon deliveries are slower to arrive in low-income zip codes Despite the DC residents paying for the same Prime program as their richer neighbors. (WP $)+ A lawsuit claims Amazon covered up the real reason for the delays. (Ars Technica)5 Law enforcement has busted two major crypto laundering networksCriminals swapped huge sums of cash for crypto across crime networks. (Wired $) + Over in Dubai, crypto scams are running rampant. (Bloomberg $)6 Where it all went wrong for the worlds biggest offshore wind companyrsted was riding high on the clean energy waveuntil it wasnt. (FT $) + The UK is failing spectacularly to harness wind power properly. (Bloomberg $)+ Whats next for offshore wind. (MIT Technology Review)7 OnlyFans has quietly launched in ChinaAlthough pornography remains illegal in the country. (CNN) + Chinese gamers are using a Steam wallpaper app to get porn past the censors. (MIT Technology Review) 8 Were getting close to solving a major mystery of the universeIts biggest galaxies may have been formed by cosmic collisions. (The Guardian) + The galaxy which used to look like a sombrerodoesnt any more. (CNN)9 This winged drone can hop and jump Making it look a whole lot like a robotic bird. (IEEE Spectrum)+ Whats next for drones. (MIT Technology Review)10 Why X had a meltdown over a womans PhD thesis Go outside and touch some grass, all of you. (Vox)Quote of the day We never doubted. We never wavered. And we will never stop building. Kris Marszalek, chief executive of exchange Crypto.com, celebrates bitcoins colossal surge to a $100,000 valuation for a single coin in a post on X. The big story What the future holds for those born today Happy birthday, baby.August 2024 You have been born into an era of intelligent machines. They have watched over you almost since your conception. They let your parents listen in on your tiny heartbeat, track your gestation on an app, and post your sonogram on social media. Well before you were born, you were known to the algorithm.Your arrival coincided with the 125th anniversary of this magazine. With a bit of luck and the right genes, you might see the next 125 years. How will you and the next generation of machines grow up together? We asked more than a dozen experts to imagine your future. Read what they prophesied.Kara Platoni We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or tweet 'em at me.) + If you want the best pizza the world has to offer, you should head to Jersey City (apparently)+ Thinking of gifting something thats been previously owned this Christmas? Make sure you conduct these essential checks.+ What science can tell us about how to combat bullying.+ Uhohhoney fraud is on the rise!