The day after his inauguration in January, President Donald Trump announced Stargate, a $500 billion initiative to build out AI infrastructure, backed by some of the biggest companies in tech. Stargate aims to accelerate the construction of massive data centers and electricity networks across the US to ensure it keeps its edge over China. This story is a part of MIT Technology Review’s series “Power Hungry: AI and our energy future,” on the energy demands and carbon costs of the artificial-intelligence revolution. The whatever-it-takes approach to the race for worldwide AI dominance was the talk of Davos, says Raquel Urtasun, founder and CEO of the Canadian robotruck startup Waabi, referring to the World Economic Forum’s annual January meeting in Switzerland, which was held the same week as Trump’s announcement. “I’m pretty worried about where the industry is going,” Urtasun says.  She’s not alone. “Dollars are being invested, GPUs are being burned, water is being evaporated—it’s just absolutely the wrong direction,” says Ali Farhadi, CEO of the Seattle-based nonprofit Allen Institute for AI. But sift through the talk of rocketing costs—and climate impact—and you’ll find reasons to be hopeful. There are innovations underway that could improve the efficiency of the software behind AI models, the computer chips those models run on, and the data centers where those chips hum around the clock. Here’s what you need to know about how energy use, and therefore carbon emissions, could be cut across all three of those domains, plus an added argument for cautious optimism: There are reasons to believe that the underlying business realities will ultimately bend toward more energy-efficient AI. 1/ More efficient models The most obvious place to start is with the models themselves—the way they’re created and the way they’re run. AI models are built by training neural networks on lots and lots of data. Large language models are trained on vast amounts of text, self-driving models are trained on vast amounts of driving data, and so on. But the way such data is collected is often indiscriminate. Large language models are trained on data sets that include text scraped from most of the internet and huge libraries of scanned books. The practice has been to grab everything that’s not nailed down, throw it into the mix, and see what comes out. This approach has certainly worked, but training a model on a massive data set over and over so it can extract relevant patterns by itself is a waste of time and energy. There might be a more efficient way. Children aren’t expected to learn just by reading everything that’s ever been written; they are given a focused curriculum. Urtasun thinks we should do something similar with AI, training models with more curated data tailored to specific tasks. (Waabi trains its robotrucks inside a superrealistic simulation that allows fine-grained control of the virtual data its models are presented with.) It’s not just Waabi. Writer, an AI startup that builds large language models for enterprise customers, claims that its models are cheaper to train and run in part because it trains them using synthetic data. Feeding its models bespoke data sets rather than larger but less curated ones makes the training process quicker (and therefore less expensive). For example, instead of simply downloading Wikipedia, the team at Writer takes individual Wikipedia pages and rewrites their contents in different formats—as a Q&A instead of a block of text, and so on—so that its models can learn more from less. Training is just the start of a model’s life cycle. As models have become bigger, they have become more expensive to run. So-called reasoning models that work through a query step by step before producing a response are especially power-hungry because they compute a series of intermediate subresponses for each response. The price tag of these new capabilities is eye-watering: OpenAI’s o3 reasoning model has been estimated to cost up to $30,000 per task to run.   But this technology is only a few months old and still experimental. Farhadi expects that these costs will soon come down. For example, engineers will figure out how to stop reasoning models from going too far down a dead-end path before they determine it’s not viable. “The first time you do something it’s way more expensive, and then you figure out how to make it smaller and more efficient,” says Farhadi. “It’s a fairly consistent trend in technology.” One way to get performance gains without big jumps in energy consumption is to run inference steps (the computations a model makes to come up with its response) in parallel, he says. Parallel computing underpins much of today’s software, especially large language models (GPUs are parallel by design). Even so, the basic technique could be applied to a wider range of problems. By splitting up a task and running different parts of it at the same time, parallel computing can generate results more quickly. It can also save energy by making more efficient use of available hardware. But it requires clever new algorithms to coordinate the multiple subtasks and pull them together into a single result at the end.  The largest, most powerful models won’t be used all the time, either. There is a lot of talk about small models, versions of large language models that have been distilled into pocket-size packages. In many cases, these more efficient models perform as well as larger ones, especially for specific use cases. As businesses figure out how large language models fit their needs (or not), this trend toward more efficient bespoke models is taking off. You don’t need an all-purpose LLM to manage inventory or to respond to niche customer queries. “There’s going to be a really, really large number of specialized models, not one God-given model that solves everything,” says Farhadi. Christina Shim, chief sustainability officer at IBM, is seeing this trend play out in the way her clients adopt the technology. She works with businesses to make sure they choose the smallest and least power-hungry models possible. “It’s not just the biggest model that will give you a big bang for your buck,” she says. A smaller model that does exactly what you need is a better investment than a larger one that does the same thing: “Let’s not use a sledgehammer to hit a nail.” 2/ More efficient computer chips As the software becomes more streamlined, the hardware it runs on will become more efficient too. There’s a tension at play here: In the short term, chipmakers like Nvidia are racing to develop increasingly powerful chips to meet demand from companies wanting to run increasingly powerful models. But in the long term, this race isn’t sustainable. “The models have gotten so big, even running the inference step now starts to become a big challenge,” says Naveen Verma, cofounder and CEO of the upstart microchip maker EnCharge AI. Companies like Microsoft and OpenAI are losing money running their models inside data centers to meet the demand from millions of people. Smaller models will help. Another option is to move the computing out of the data centers and into people’s own machines. That’s something that Microsoft tried with its Copilot+ PC initiative, in which it marketed a supercharged PC that would let you run an AI model (and cover the energy bills) yourself. It hasn’t taken off, but Verma thinks the push will continue because companies will want to offload as much of the costs of running a model as they can. But getting AI models (even small ones) to run reliably on people’s personal devices will require a step change in the chips that typically power those devices. These chips need to be made even more energy efficient because they need to be able to work with just a battery, says Verma. That’s where EnCharge comes in. Its solution is a new kind of chip that ditches digital computation in favor of something called analog in-memory computing. Instead of representing information with binary 0s and 1s, like the electronics inside conventional, digital computer chips, the electronics inside analog chips can represent information along a range of values in between 0 and 1. In theory, this lets you do more with the same amount of power.  SHIWEN SVEN WANG EnCharge was spun out from Verma’s research lab at Princeton in 2022. “We’ve known for decades that analog compute can be much more efficient—orders of magnitude more efficient—than digital,” says Verma. But analog computers never worked well in practice because they made lots of errors. Verma and his colleagues have discovered a way to do analog computing that’s precise. EnCharge is focusing just on the core computation required by AI today. With support from semiconductor giants like TSMC, the startup is developing hardware that performs high-dimensional matrix multiplication (the basic math behind all deep-learning models) in an analog chip and then passes the result back out to the surrounding digital computer. EnCharge’s hardware is just one of a number of experimental new chip designs on the horizon. IBM and others have been exploring something called neuromorphic computing for years. The idea is to design computers that mimic the brain’s super-efficient processing powers. Another path involves optical chips, which swap out the electrons in a traditional chip for light, again cutting the energy required for computation. None of these designs yet come close to competing with the electronic digital chips made by the likes of Nvidia. But as the demand for efficiency grows, such alternatives will be waiting in the wings.  It is also not just chips that can be made more efficient. A lot of the energy inside computers is spent passing data back and forth. IBM says that it has developed a new kind of optical switch, a device that controls digital traffic, that is 80% more efficient than previous switches.    3/ More efficient cooling in data centers Another huge source of energy demand is the need to manage the waste heat produced by the high-end hardware on which AI models run. Tom Earp, engineering director at the design firm Page, has been building data centers since 2006, including a six-year stint doing so for Meta. Earp looks for efficiencies in everything from the structure of the building to the electrical supply, the cooling systems, and the way data is transferred in and out. For a decade or more, as Moore’s Law tailed off, data-center designs were pretty stable, says Earp. And then everything changed. With the shift to processors like GPUs, and with even newer chip designs on the horizon, it is hard to predict what kind of hardware a new data center will need to house—and thus what energy demands it will have to support—in a few years’ time. But in the short term the safe bet is that chips will continue getting faster and hotter: “What I see is that the people who have to make these choices are planning for a lot of upside in how much power we’re going to need,” says Earp. One thing is clear: The chips that run AI models, such as GPUs, require more power per unit of space than previous types of computer chips. And that has big knock-on implications for the cooling infrastructure inside a data center. “When power goes up, heat goes up,” says Earp. With so many high-powered chips squashed together, air cooling (big fans, in other words) is no longer sufficient. Water has become the go-to coolant because it is better than air at whisking heat away. That’s not great news for local water sources around data centers. But there are ways to make water cooling more efficient. One option is to use water to send the waste heat from a data center to places where it can be used. In Denmark water from data centers has been used to heat homes. In Paris, during the Olympics, it was used to heat swimming pools.   Water can also serve as a type of battery. Energy generated from renewable sources, such as wind turbines or solar panels, can be used to chill water that is stored until it is needed to cool computers later, which reduces the power usage at peak times. But as data centers get hotter, water cooling alone doesn’t cut it, says Tony Atti, CEO of Phononic, a startup that supplies specialist cooling chips. Chipmakers are creating chips that move data around faster and faster. He points to Nvidia, which is about to release a chip that processes 1.6 terabytes a second: “At that data rate, all hell breaks loose and the demand for cooling goes up exponentially,” he says. According to Atti, the chips inside servers suck up around 45% of the power in a data center. But cooling those chips now takes almost as much power, around 40%. “For the first time, thermal management is becoming the gate to the expansion of this AI infrastructure,” he says. Phononic’s cooling chips are small thermoelectric devices that can be placed on or near the hardware that needs cooling. Power an LED chip and it emits photons; power a thermoelectric chip and it emits phonons (which are to vibrational energy—a.k.a. temperature—as photons are to light). In short, phononic chips push heat from one surface to another. Squeezed into tight spaces inside and around servers, such chips can detect minute increases in heat and switch on and off to maintain a stable temperature. When they’re on, they push excess heat into a water pipe to be whisked away. Atti says they can also be used to increase the efficiency of existing cooling systems. The faster you can cool water in a data center, the less of it you need. 4/ Cutting costs goes hand in hand with cutting energy use Despite the explosion in AI’s energy use, there’s reason to be optimistic. Sustainability is often an afterthought or a nice-to-have. But with AI, the best way to reduce overall costs is to cut your energy bill. That’s good news, as it should incentivize companies to increase efficiency. “I think we’ve got an alignment between climate sustainability and cost sustainability,” says Verma. ”I think ultimately that will become the big driver that will push the industry to be more energy efficient.” Shim agrees: “It’s just good business, you know?” Companies will be forced to think hard about how and when they use AI, choosing smaller, bespoke options whenever they can, she says: “Just look at the world right now. Spending on technology, like everything else, is going to be even more critical going forward.” Shim thinks the concerns around AI’s energy use are valid. But she points to the rise of the internet and the personal computer boom 25 years ago. As the technology behind those revolutions improved, the energy costs stayed more or less stable even though the number of users skyrocketed, she says. It’s a general rule Shim thinks will apply this time around as well: When tech matures, it gets more efficient. “I think that’s where we are right now with AI,” she says. AI is fast becoming a commodity, which means that market competition will drive prices down. To stay in the game, companies will be looking to cut energy use for the sake of their bottom line if nothing else.  In the end, capitalism may save us after all. 

Google is rapidly expanding its AI search capabilities, as reflected in the announcements it made Tuesday at its Google I/O developer conference. The search giant announced the general availability of AI Mode, its chatbot-format AI search product; some changes to its AI Overviews search results; and its plans to add new visual and agentic search features this summer.  Google’s biggest announcement in the realm of search was the general availability of its AI Mode, a chatbot-style search interface that allows users to enter a back-and-forth with the underlying large language model to zero in on a complete and satisfying answer. “AI Mode is really our most powerful version of AI search,” Robby Stein, Google’s VP of Product for Search, tells Fast Company. The tool had been available as an experimental product from Google Labs. Now it’s a real product, available to all users and accessible within various Google apps, and as a tab within the Google mobile app.  AI Mode is powered by Gemini 2.5, Google’s most formidable model, which was developed by DeepMind. The model can remember a lot of data during a user interaction, and can reason its way to a responsive answer. Because of this, AI Mode can be used for more complex, multipart queries. “We’re seeing this being used for the more sophisticated set of questions people have,” Stein says. “You have math questions, you have how-to questions, you want to compare two products—like many things that haven’t been done before, that are probably unique to you.”  The user gets back a conversational AI answer synthesized from a variety of sources. “The main magic of the system is this new advanced modeling capability for AI Mode, something called a query fan-out where the model has learned to use Google,” Stein says. “It generates potentially dozens of queries off of your single question.” The LLM might make data calls to the web, indexes of web data, maps and location data, product information, as well as API connections to more dynamic data such as sports scores, weather, or stock prices.  New shopping tools  Google also introduced some new shopping features in AI Mode that leverage the multimodal and reasoning capabilities of the Gemini 2.5 models. Google indexes millions of products, along with prices and other information. The agentic capability of the Gemini model lets AI Mode keep an eye out for a product the user wants, with the right set of desired features and below a price threshold that the user sets. The AI can then alert the user with the information, as well as a button that says “buy for me.” If the user clicks it the agent will complete the purchase.  Google is also releasing a virtual clothing try-on function in AI Mode. The feature addresses perhaps the biggest problem with buying and selling apparel online. “It’s a problem that we’ve been trying to solve over the last few years,” says Lilian Rincon, VP of Consumer Shopping Products. “Which is this dilemma of [where] users see a product but they don’t know what that product will look like on them.” Virtual Try-on lets a user upload a photo of themself, then the AI shows the user what they’d look like in any of the billions of clothing products Google indexes. The feature is powered by a new custom image generation model for fashion that understands the nuances of the human body and how various fabrics fold and bend over the body type of the user, Rincon says. Google has released Virtual Try-on as an experimental feature in Google Labs.  New features coming to AI Mode this summer Google says it intends to roll out further enhancements to AI Mode over the summer.  For starters, it’s adding the functionality of its previously announced Project Mariner (an AI agent prototype that works with the Chrome browser) to AI Mode. So the LLM will be able to control the user’s web browser to access information from websites, fill out and submit forms, and use websites to plan and book tasks. Google is going to start by enabling the AI to do things like book event tickets, make restaurant reservations, and set appointments for local services.  The user can give the AI agent special instructions or conditions, such as “buy tickets only if less than $100, and only if the weather (if its an outdoor event) forecast looks good.” The AI will not only find the best ticket prices to a show, but will also submit the data needed to buy the ticket for the user. (The user gets final sign-off, of course.)  Google will be adding a new “deep search” function in which the model might access, and reason about, hundreds of online, indexed, or AI data sources. The model might spend several minutes thinking through the completeness of its answer, and perhaps make additional data queries. The end result is a comprehensive research report on a given topic.   At last year’s I/O, Google revealed its Project Astra, a prototype of a universal AI assistant that can see, hear, and reason, and converse with the user, out loud, in real time. The assistant taps into search in several ways. A user could show the assistant an object in front of the phone camera and ask for more information about it, which the agent would get from the web. Or the assistant might be shown a recipe, and help the user shop for the ingredients.  Google also plans to launch enhanced personalization features to AI search as a way of delivering more relevant search results. “The best version of search is one that knows you well,” Stein says. For example, AI Mode and AI Overviews soon might consult a user’s search history to use past preferences to inform the content of current queries. That’s not all. Google also intends to consult user data from other Google services, including Gmail, to inform searches, subject to user opt-in.  Finally, the company will add data visualizations to search results, which it believes will help users draw meaning from data returned in search results. It will start by modeling sports and financial data this summer, Stein says.  AI Overviews now reaches almost all Google users AI Overviews is Google’s original AI search experience. For some types of search queries, users see an AI-generated narrative summary of information synthesized from various web documents and Google’s information graphs. Stein says Google is now making AI Overviews available to 95 more countries and territories, bringing the total to around 200, and in 40 languages. Google claims that AI Overviews, its generative AI search experience, now has 1.5 billion users.  Where search is concerned, Google is a victim of the “inventor’s dilemma.” It built a massive business placing ads around its search results, so it has a good reason to keep optimizing and improving that experience, rather than pivoting toward new AI-based search, which nobody has reliably monetized with ads yet. Indeed Google’s core experience still consists of relatively short queries and results consisting of ranked websites and an assortment of Google-owned content. But development of AI search products and functions seems to be accelerating. Google is protecting its cash cow (traditional search with ads) while keeping pace with the chatbot search experiences offered by newcomers like OpenAI’s ChatGPT.  But it’s more than that. Google’s VP and Head of Search Liz Reid suggests that we may be looking at the future of Google Search—full stop. “I think one of the things that’s very exciting with AI Mode is not just that it is our cutting-edge AI search, but it becomes a glimpse of what we think can be more broadly available,” Reid tells Fast Company. “And so our current belief is that we’re going to take the things that work really well in AI Mode and bring them right to the core of search and AI Overviews.” 

nintendoByEthan GachPublished44 minutes agoWe may earn a commission from links on this page.Image: Nintendo / KotakuSwitch 2 pre-orders have basically been sold out since they went live last month, but a lucky few might still be able to nab the new Nintendo console in person when it launches on June 5. GameStop, Best Buy, and others have promised limited quantities on site at certain stores when fans go to pick-up their midnight pre-orders.Suggested ReadingNintendo Switch 2 Could Launch With Almost No Reviews Share SubtitlesOffEnglishSuggested ReadingNintendo Switch 2 Could Launch With Almost No Reviews Share SubtitlesOffEnglishNintendo Switch 2 Could Launch With Almost No ReviewsBest Buy was the first to signal that at least some of its Switch 2 inventory at certain stores was being set aside for day-one sales. The electronics retailer promised “limited inventory of systems, games, accessories [and] the chance for a free Nintendo collectible” for those showing up at 12:01 a.m. ET on June 5. Target appears to be doing something similar. According to multiple reports, certain locations will have anywhere from 30 to 100 Switch 2 consoles available to the first customers to arrive without existing pre-orders. The company hasn’t announced anything official yet, and it’s not clear if its stores will be doing midnight pre-order pickups or customers there will have to wait until regular opening hours. GameStop, on the other hand, is all-in on the Switch 2 midnight launch party. “Additional Switch 2 units will be available in-store and online while supplies last,” the retailer confirmed last week. The “launch event” begins at 3:00 p.m. local time, with pre-order pickups beginning at midnight. The suggestion is that if you want a shot at one of those on-site consoles, you’ll need to be some of the first in line for that 3:00 p.m. start time. You’ll also get a free Red Bull. Walmart hasn’t yet confirmed its plans for launch day inventory yet, and Amazon has been completely silent about pre-orders and when it will begin selling the Switch 2, if at all. Nintendo is still slowly going through its own My Nintendo Store pre-order process with invitations going out on a rolling basis. But those units aren’t guaranteed to arrive on launch day and some might not arrive until days or weeks later. Basically, what I’m saying is that if you failed to lock down a pre-order in the initial frenzy last month, there’s still hope. Now, does that mean showing up on the day of or camping out for a week? Knowing Nintendo fans, and with the Switch 2 being the biggest console launch in the company’s history, I wouldn’t put anything past them. .

Boxes Full of Nazi Propaganda Discovered in the Basement of Argentina’s Supreme Court Workers found crates packed with swastika-covered notebooks, postcards and photographs while preparing to move the court’s archives to a new museum Notebooks decorated with swastikas were among the documents found in the wooden crates. Supreme Court of Argentina Boxes full of Nazi propaganda that were confiscated during World War II have been rediscovered in the basement of Argentina’s Supreme Court. Workers recently stumbled across the cache while preparing to move the court’s archives to a new museum, according to BBC News’ Vanessa Buschschlüter. They found wooden champagne crates that were packed with documents that had been “intended to consolidate and propagate Adolf Hitler’s ideology in Argentina,” according to a statement from the court. On May 9, officials formally opened the boxes during a ceremony led by Horacio Rosatti, president of Argentina’s Supreme Court. Also in attendance were Eliahu Hamra, the chief rabbi of the Argentine Israelite Mutual Association, and Jonathan Karszenbaum, the executive director of the Holocaust Museum of Buenos Aires. “I was shocked because of the volume of this,” Karszenbaum tells the New York Times’ Claire Moses. Now, Rosatti has ordered a thorough investigation and detailed inventorying of the contents. Historians hope the documents will shed new light on the Nazis’ international financing network. Workers found the crates while preparing to move the court's archives to a new museum. Supreme Court of Argentina Officials think the boxes arrived in Argentina on June 20, 1941, aboard the Japanese steamship Nan-a-Maru. That year, the German embassy in Tokyo sent 83 packages to Argentina that supposedly contained the personal effects of members of the German diplomatic mission. But Argentine customs officials were suspicious. They wanted to inspect the boxes’ contents to ensure they did not undermine Argentina’s neutrality during World War II. When they randomly opened five containers, they found Nazi propaganda material—including postcards, photographs and notebooks decorated with swastikas. German diplomatic representatives wanted to send the boxes back to the German embassy in Tokyo. Instead, a federal judge ordered that the boxes be seized and brought the affair to Argentina’s Supreme Court. What happened to them after that isn’t clear. Karszenbaum hopes to get to the bottom of why the boxes were hidden away for so many years, per the Times. The boxes arrived on a Japanese steamship in 1941. Supreme Court of Argentina Argentina maintained neutrality until 1944, when it cut off its relationships with the Axis powers. In 1945, the nation declared war on Germany and Japan. Some 44,000 European Jews fled to Argentina between 1933 and 1943, according to the United States Holocaust Memorial Museum. After the war, thousands of Nazi officers and sympathizers escaped to Argentina in a bid to evade justice. They included prominent figures such as Adolf Eichmann, who orchestrated Hitler’s “final solution” to exterminate European Jews, and Josef Mengele, who was nicknamed the “angel of death” for conducting inhumane medical experiments on Auschwitz prisoners. In 2000, President Fernando de la Rúa formally apologized for the refuge Argentina provided for Nazi war criminals. Today, Argentina is home to around 200,000 Jews, the largest Jewish population in Latin America. Get the latest stories in your inbox every weekday.

Ethan Zuckerman wrote in The Atlantic in 2014: I have come to believe that advertising is the original sin of the web. The fallen state of our Internet is a direct, if unintentional, consequence of choosing advertising as the default model to support online content and services. Through successive rounds of innovation and investor storytime, we’ve trained Internet users to expect that everything they say and do online will be aggregated into profiles (which they cannot review, challenge, or change) that shape both what ads and what content they see. Outrage over experimental manipulation of these profiles by social networks and dating companies has led to heated debates amongst the technologically savvy, but hasn’t shrunk the user bases of these services, as users now accept that this sort of manipulation is an integral part of the online experience. Marc Andreessen, who was there when the web was born, explained in a 2019 podcast why this sin was committed (this quote is lightly edited for clarity): One would think the most obvious thing to do would be building in the browser the ability to actually spend money, right? You’ll notice that didn’t happen, and in a lot of ways, we don’t even think it’s unusual that that didn’t happen, because maybe that shouldn’t have happened. I think the original sin was we couldn’t actually build economics, which is to say money, into the core of the internet and so therefore advertising became the primary business model… We tried very hard to build payments into the browser. It was not possible…We made a huge mistake. We tried to work with the banks and we tried to work with the credit card companies…it was sort of the classic kind of single point of failure bottleneck, or at least in this case, two points of failure. Visa and MasterCard essentially had a duopoly at the time, and so they were just literally, if they did not want you to be in the switch, they did want you to be able to do transactions, you just simply weren’t going to do it. I think Andreessen is too hard on himself, and I think Zuckerman is too harsh on the model Andreessen created the conditions for. The original web was the human web, and advertising was and is one of the best possible ways to monetize the only scarce resource in digital: human attention. The incentives all align: Users get to access a vastly larger amount of content and services because they are free. Content makers get to reach the largest possible audience because access is free. Advertisers have the opportunity to find customers they would have been never able to reach otherwise. Yes, there are the downsides to advertising Zuckerman fretted about, but everything is a trade-off, and the particular set of trade-offs that led to the advertising-centric web were, on balance, a win-win-win that generated an astronomical amount of economic value. Moreover, I disagree with Andreessen that we could have ended up with a better system if the banks and credit card companies had been willing to play ball. In fact, over the last thirty years, the credit card companies in particular have — in part thanks to companies like Stripe — gotten their digital acts together, and are integral to a huge amount of web-based commerce, which itself is driven through digital advertising (the largest category of advertising for both Google and Meta). That too is human, in that the biggest outcome of digital advertising is physical products and real-world experiences like travel (digital products like apps and games, meanwhile, are themselves pursuing human attention). What was not viable in the 1990s, nor at any time since then, was something like micro-transactions for content. One obvious problem is that the fee structure of credit cards don’t allow for very small transactions; another problem is that the costs to product content are front-loaded, and the potential payoff is both back-loaded and unpredictable, making it impossible to make a living. The biggest problem of all, however, is that micro-transactions are anti-human: forcing a potential content consumer to continually decide on whether or not to pay for a piece of content is alienating, particularly when plenty of alternatives for their scarce attention exist. Subscriptions do work at smaller scales, because they are ultimately not about paying for content, but giving money to another human (or human institution); from The Local News Business Model: It is very important to clearly define what a subscriptions means. First, it’s not a donation: it is asking a customer to pay money for a product. What, then, is the product? It is not, in fact, any one article (a point that is missed by the misguided focus on micro-transactions). Rather, a subscriber is paying for the regular delivery of well-defined value. Each of those words is meaningful: Paying: A subscription is an ongoing commitment to the production of content, not a one-off payment for one piece of content that catches the eye. Regular Delivery: A subscriber does not need to depend on the random discovery of content; said content can be delivered to the subscriber directly, whether that be email, a bookmark, or an app. Well-defined Value: A subscriber needs to know what they are paying for, and it needs to be worth it. This last point is at the crux of why many ad-based newspapers will find it all but impossible to switch to a real subscription business model. When asking people to pay, quality matters far more than quantity, and the ratio matters: a publication with 1 valuable article a day about a well-defined topic will more easily earn subscriptions than one with 3 valuable articles and 20 worthless ones covering a variety of subjects. Yet all too many local newspapers, built for an ad-based business model that calls for daily content to wrap around ads, spend their limited resources churning out daily filler even though those ads no longer exist. I expect that this model will endure in the age of AI; obviously I’m biased on this point, but in a world of infinite content-on-demand, common content becomes community: if I’m successful this essay will generate a lot of discussion amongst a lot of people precisely because it is both original and widely accessible, funded by an audience that wants me to keep on writing Articles exactly like this. The Death of the Ad-Supported Web The ad-supported web — particularly text-based sites — is going to fare considerably worse. In fact, the most substantive pushback to my defense of advertising was in my own excerpt: most ad-supported content is already terrible, thanks to the bad incentives both Zuckerman and Andreessen bemoaned, and the impossible economics enabled by zero marginal cost content generation and consumption. The center of this world for the last twenty years has been Google. Google in its most idealized form Aggregated content consumers by mastering discovery in this world of abundance, directing users to exactly the site they were looking for, which was monetized through ads that were sold and served by Google. Indeed, this is the great irony in the ads antitrust case in which Google is currently embroiled; Eric Seufert asked on MobileDevMemo: I’ve heard arguments that, because Google suppressed competition in open web advertising markets, those markets should flourish when Google’s monopoly is broken. But my sense is that this ignores two realities. First, that consumer engagement has shifted into apps and walled gardens irreversibly. And second, that Google was keeping the open web on life support, and the open web’s demise will be hastened when Google no longer has an incentive to support it. What happens to the open web when its biggest, albeit imperfect, benefactor loses the motivation to sustain it? Note Seufert’s two points: walled gardens like social networks are both more attractive to most users and also better for advertisers, and Google might soon lose what little motivation they had left to support the open web. However, that’s not Google’s — and the web’s — only problem. Why go through the hassle of typing a search term and choosing the best link — particularly as search results are polluted by an increasingly overwhelming amount of SEO spam, now augmented by generative AI — when ChatGPT (or Google itself) will simply give you the answer you are looking for? In short, every leg of the stool that supported the open web is at best wobbly: users are less likely to go to ad-supported content-based websites, even as the long tail of advertisers might soon lose their conduit to place ads on those websites, leaving said websites even less viable than they are today — and they’re barely hanging on as it is! Microsoft and the Open Agentic Web This reality is the fly in the ointment of an intriguing set of proposals that Microsoft put forward yesterday at the Build 2025 Developer Conference about “The Open Agentic Web”; here’s CTO Kevin Scott: The thing that is super important if you think about what an open-agentic web could be, is you need agents to be able to take actions on your behalf, and one of the really important things about agents being able to take actions on your behalf is they have to be plumbed up to the greater world. So you need protocols, things like MCP and A2A and things that likely are going to be emerging over the coming year that will help connect in an open, reliable, interoperable way the agents that you are writing and agents that are being used so actively now by hundreds of millions of people to be able to go access content, to access services, to take action on behalf of users in fulfilling the tasks that have been delegated to them. One aspect of this vision of the agentic web was Microsoft’s commitment to the Model Context Protocol created by Anthropic; Scott told Nilay Patel in an excellent interview in The Verge that while MCP wasn’t exactly what he would have designed from scratch, ubiquity is more important than semantic differences, particularly when you’re trying to create HTTP for AI agents. The second part of Scott’s vision was something Microsoft created called NLWeb, a natural language interface for websites that makes them more directly accessible for agents: If you think back to the web, we have HTTP, and then we had things that sit on top of HTTP, like HTML mainly, that are opinionated about the payload, and so we’re announcing today NLWeb. The idea behind NLWeb is it is a way for anyone who has a website or an API already to very easily make their website or their API an agentic application. It lets you implement and leverage the full power of large language models to enrich the services and products that you’re already offering, and because every NLWeb endpoint is by default an MCP server, It means that those things that people are offering up via NLWeb will be accessible to any agent that speaks MCP. So you really can think about it a little bit like HTML for the agentic web. We have done a bunch of work already with partners who have been really excited and been able to really very quickly get to quick implementations and prototypes using NLWeb. We’ve worked with TripAdvisor, O’Reilly Media, a ton of really great companies that offer important products and services on the internet to add in a web functionality to their sites so that they can have these agentic experiences directly on their sites. Scott concluded by re-emphasizing how important it was that the layers of the agentic web be open, and used the evolution of the Internet as his example of why: So the last thing that I want to say before handing things back over to Satya is to just sort of press on these two points about why like open is so important here. So you know it is unbelievable what can happen in the world when simple components and simple protocols that are composable with one another are out there, exposed to the full scrutiny and creativity of every developer in the world who wants to participate or who has an idea. This thought game that I play with myself all the time is trying to imagine what the web would have looked like if one of the actors in the early development of the web, say the browser manufacturers, had decided that they wanted to vertically integrate and own the entire web. A hundred percent of the web would have been…dictated by the limits of their imagination, and it’s just obvious with 30 years of history that that wouldn’t have been a very interesting web. The web is interesting because millions, tens of millions, hundreds of millions of people are participating to make it into this rich dynamic thing. That’s what we think we need with the agentic web, and that’s what we’re hoping you all can get inspired to go work on a little bit, to riff on, and to use the full extent of your imagination to help make this thing interesting. I think that widespread adoption of MCP as a protocol layer and NLWeb as a markup layer sounds excellent; the big hole in Scott’s proposal, however, was pointed out by Patel in that interview: That is the piece that on the web right now seems most under threat, the underlying business dynamics of I start a website, I put in a bunch of schema that allows search engines to read my website and surface my content across different distributions. I might add an RSS feed, which is a standardized distribution that everyone uses and agrees on. There’s lots of ways to do this. But if I make a website, I open myself up to distribution on different surfaces. What I will get in return for that is not necessarily money — almost in every case, not money. What I’ll get is visitors to my website, and then I’ll monetize them however I choose to: selling a subscription, display ads, whatever it is. That’s broken, right? As more and more of the answers appear directly, particularly in AI-based search products, traffic to websites has generally dropped. We see this over and over again. What’s going to replace that in the agentic era, where we’ve created new schema for agents to come and talk to my website and receive some answers? What’s going to make that worth it? Scott in his answer noted that websites would be able to communicate to agents what they wanted to make available and on what terms, along with some vague hand-waving about new advertising models and transactions. The last point is valid: Trip Advisor sells hotel rooms, and O’Reilly sells training courses, and you can see a world where websites based on transactions can not only benefit from exposing themselves to agents, but in fact transact more (and potentially pay an affiliate fee). Patel, however, rightly pressed Scott on the prospects for ad-supported content sites: As Google keeps more of the traffic for itself or it thinks differently about training data, all this stuff is changing. The trade here is make your website more agentic, and then MCP as a protocol will allow you to build some new business models on it. The problem, as I see it, is that the traffic to the web is in precipitous decline as Google referrals go into decline. How do you fix that problem so that everyone is incentivized to keep building on the web? I don’t know, honestly. “The Original Sin” of the Internet lacking native payments was not, in my opinion, a sin at all: advertising supported the human web not because Andreessen failed to make a deal with the credit card companies, but because it was the only business model that made sense. No, the real neglect and missed opportunity in terms of payments is happening right now: Microsoft is on to the right idea with its adoption of MCP and introduction of NLWeb, but its proposal, by virtue of not including native payments, isn’t nearly as compelling as it should be. The key difference from the 1990s is that on the agentic web native digital payments are both viable and the best possible way to not only keep the web alive, but also in the process create better and more useful AI. Stablecoins and Agentic Micro-transactions Start with the viability; from Bloomberg: Stablecoin legislation overcame a procedural blockade in the US Senate, marking a major victory for the crypto industry after a group of Democrats dropped their opposition Monday. The industry-backed regulatory bill is now set for debate on the Senate floor with a bipartisan group hoping to pass it as soon as this week, although senators said a final vote could slip until after the Memorial Day recess. I know I have driven long-time Stratechery readers a bit batty with my long-running and still-enduring-in-the-face-of-massive-grift-and-seemingly-unending-scandals interest in crypto, but stablecoins are genuinely a big deal. I wrote a brief explainer last fall when Stripe acquired Bridge: Stablecoins distill crypto to these most interesting bits. Unlike Bitcoin, stablecoins do not have intrinsic value downstream from a network effect, and unlike Ethereum, they are not set up to execute smart contracts or other applications; rather, their value is right there in the name: they are stable representations of value — usually the U.S. dollar…What remains is a synthetic currency that is digital but scarce, with all of the affordances that allows for, including the ability to move money frictionlessly (thus Collison’s analogy). The analogy I think of is to the Internet itself: Physical goods are scarce, but while you can scale up from hand-delivery, you still have to pay a lot for a delivery service, and if you cross borders you have to deal with customs. Information used to be delivered in person, then via physical media like letters or newspapers, but now it is purely digital and freely distributed and duplicated all over the world; it is abundant. Dollars right now are more akin to physical goods than they are to information: you can deliver it by hand, or even via delivery services like ACH or SWIFT, but the need for verification and confirmation flows introduce a ton of friction. Moreover, you can’t actually do anything with dollars at rest, other than watch them deflate. Stablecoins solve these problems: you can transfer them like information, while preserving scarcity, while blockchains provide verification and confirmation that scales from the smallest transactions to the biggest; meanwhile, they also earn a return while at rest thanks to the assets backing them. Stablecoins solve several of the micro-transaction problems I listed above, including dramatically lower — or no — fees, and the fact that they are infinitely divisible, and thus can scale to very small amounts. Stablecoins, by virtue of being programmable, are also well-suited to agents; agents, meanwhile, are much more suited to micro-transactions, because they are, in the end, simply software making a decision, unencumbered by the very human feeling of decision paralysis. In fact, we already have an excellent example of (deterministic) agents making micro-transactions at scale: the entire digital ads ecosystem! Every time a human loads a webpage, an awe-inspiring amount of computation and communication happens in milliseconds, as an auction is run to fill the inventory on that page with an ad that is likely to appeal to the human. These micro-transactions are only worth fractions of a penny, but the aggregate volume of them drives trillions of dollars worth of value. The problem, as both I and Patel noted, is that this ecosystem depends on humans seeing those webpages, not impersonal agents impervious to advertising, which destroys the economics of ad-supported content sites, which, in the long run, dries up the supply of new content for AI. OpenAI and Google in particular are clumsily addressing the supply issue by cutting deals with news providers and user-generated content sites like Reddit; this, however, is bad for the sort of competition Microsoft wants to engender, and ultimately won’t scale to the amount of new content that needs to be generated. What is possible — not probable, but at least possible — is to in the long run build an entirely new marketplace for content that results in a new win-win-win equilibrium. First, the protocol layer should have a mechanism for payments via digital currency, i.e. stablecoins. Second, AI providers like ChatGPT should build an auction mechanism that pays out content sources based on the frequency with which they are cited in AI answers. The result would be a new universe of creators who will be incentivized to produce high quality content that is more likely to be useful to AI, competing in a marketplace a la the open web; indeed, this would be the new open web, but one that operates at even greater scale than the current web given the fact that human attention is a scarce resource, while the number of potential agents is infinite. There is, to be sure, a tremendous amount of complexity in what I am proposing, and the path to a marketplace for data generation is quite unclear at the moment. Who, however, could have predicted exactly how the ad-supported web would have evolved, or centrally designed the incredible complexity that undergirds it? This is where Scott’s exhortation of openness is spot on: a world of one dominant AI making business development deals with a few blessed content creators, and scraping the carcass of what remains on the web for everything else, is a far less interesting one than one driven by marketplaces, auctions, and aligned incentives. To get there, however, means realizing that the Internet’s so-called “Original Sin” was in fact the key to realizing the human web’s potential, while the actual mistake would be in not building in payments now for the coming agentic web.

Brand safety is always a high priority, but has been a particularly hot topic the past few weeks. Times like this present an opportunity to consider additional channels to add to your media plan that make brand safety a priority.To find out which channels are the safest for brands, we leveraged MobileVoice®, ironSource's market research platform, to go straight to the source: the consumers. 3,130 consumers shared their opinions on the safety of advertising platforms and how it affects their purchasing decisions. According to the survey, mobile apps, games, and news sites are among the safest channels, with the lowest amount of inappropriate content. Let's explore why.67% of consumers believe the brand has a responsibility to not advertise on platforms with inappropriate content and 74% of consumers believe the platform has a responsibility to make sure they don’t house inappropriate content. For platforms, this means building safe environments for consumers and advertisers, according to these results. For brands, this means being intentional about the platforms you choose.To combat unauthorized reselling and app spoofing, apps and games add the app-ads.txt file to their websites, which lists all the ad sources authorized to sell their inventory. Meanwhile, ad platforms that apps and games use like the ironSource Exchange have the sellers.json file, which lists out all our authorized sellers and resellers, to increase transparency and combat fraud. These ad platforms also often have the IAB Open Measurement SDK integrated to ensure that all the ads passing through are brand safe. Specifically, it gives advertisers transparency into inventory quality, ad viewability, and fraud detection. The ironSource Exchange for example has had the Open Measurement SDK integrated for 3+ years, for example. The consequences for deferring responsibility can be harmful, as 66% of consumers would feel negative about a brand that advertised on sites that contain inappropriate content and only 21% of consumers would continue using those brands according to the survey. Gen Xers, who have the largest spending power with 31% of all income dollars than any other generation according to reports from American Express, are the most likely (70%) to feel negative or very negative about a brand that advertised on sites that contain inappropriate content and the least likely (19%) to continue using the brand.2. Apps and games are closed channels that don’t allow for user generated contentHate speech is the most common (61%) and the most offensive (60%) form of inappropriate digital content, according to consumers according to the survey. The next is fake news (49%), followed by explicit material, profanity, and violence.Generally, these are found on channels centered around user generated content, where people can do and say as they want, whenever they want. On the other hand, mobile apps and games, news sites, and search engines don’t have space for user generated content and open dialogue, meaning ads can’t be seen next to inappropriate material people are writing and sharing. This is likely the reason why many consumers believe these sources have the smallest problem with inappropriate content compared to other channels, according to the research.3. Ad content on apps and games is heavily monitoredMore than any other generation, 72% of parents say that inappropriate digital content is a significant or very significant problem according to the survey. Because parents make the final call on where their family spends time online and have the responsibility to prevent their family from using platforms that don’t adhere to their standards, it’s especially important that the channels you use have extremely advanced and thorough review processes for inappropriate content. Otherwise, you risk missing out on a large audience not using the platforms you're running on, according to the survey results.The ad platforms that apps and games use have built-in features and dedicated teams to monitor and flag inappropriate content before it reaches the app. For the ironSource Exchange, that includes automatic testing as well as manual review for each and every ad that passes through. In fact, each ad is tagged according to the type of content it displays and ranked according to its maturity level. This way, the Exchange only serves the ad on apps suited for it, and inappropriate content can never make it to the app environment.To take the ad review process a step further, there are tools that app developers can use to get visibility into all the ad content their users see, ensuring their app stays clean.There’s a lot of commotion in the brand advertising space right now. To ensure your brand ads are deployed on safe and clean environments, start running on apps and games through the ironSource Exchange.

One of the most momentous developments of the new Trump era is how major billionaires in the tech industry — frequently known as the broligarchs — have thrown their weight behind the president. During the 2024 election, they offered high-profile support and made big donations; after the inauguration, they announced new company policies that aligned them with President Donald Trump’s regressive cultural ideologies. Elon Musk had already turned Twitter into a right-wing echo chamber since purchasing it in 2022, and spent several chaotic months earlier this year as Trump’s government efficiency henchman. Jeff Bezos has revamped the Washington Post’s editorial section to build support for “personal liberties and free markets.” Mark Zuckerberg decided to get rid of fact-checkers at Meta. It was a massive show of power that revealed how possible it is for these wealthy men to remake our culture in their own image, transforming how we speak to each other and what we know to be true. Using that power on Trump’s behalf seems to have paid mixed dividends for Silicon Valley, but it nonetheless makes clear how important it is to understand their worldview and their vision for the future. Which is why it is striking to note that Musk, Bezos, and Zuckerberg share a favorite author: Iain M. Banks, the Scottish science fiction writer best known for his Culture series. Banks is an odd choice for a bunch of tech billionaires. The author, who died in 2013, was a socialist and avowed hater of the super-rich.“The Culture series is certainly, in terms of more modern science fiction, one of my absolute favorites,” Bezos told GeekWire in 2018, adding, “there’s a utopian element to it that I find very attractive.” Bezos has attempted twice to adapt the series for TV at Amazon, once in 2018 and again in February. Meanwhile, Zuckerberg picked the Culture novel Player of Games for his book club in 2015. Banks is an odd choice for a bunch of tech billionaires. The author, who died in 2013, was a socialist and avowed hater of the super-rich.The most avowed Culture fan among the broligarchs, however, is Musk. Musk has named Space X drone ships after the starships in the Culture books. His original name for the neuralink — a computer chip that can be implanted in human brains, pioneered by his neurotechnology company — was the neural lace, a piece of telepathic technology that Banks came up with in the Culture books. In 2018, Musk declared himself “a utopian anarchist of the kind best described by Iain Banks.” (It’s worth noting that in 2018, Musk was under fire for union busting but had not yet waded so far into national politics or declared public war against the “woke mind virus.”)Plenty of us like and even identify with pieces of pop culture whose politics we don’t entirely agree with, like the libertarian Little House on the Prairie books or the Christian Chronicles of Narnia. Still, the Banks Culture series, which consists of 10 books released between 1987 and 2012, is not politically coded so much as it is downright didactic. “The Culture is hippy commies with hyper-weapons and a deep distrust of both Marketolatry and Greedism,” Banks said in an interview with Strange Horizons in 2010, in a line that’s only barely more explicit than the books themselves.The Culture series takes place in a post-scarcity galactic society known only as the Culture, which strictly values empathy, pluralism, and social cooperation. Most of the volumes of the series see the Culture navigating an altercation with another civilization, usually one with a much less progressive ethos, and figuring out how to handle the resulting tension. Does the Culture intervene in the affairs of another planet to, for instance, stop the spread of a theocratic empire? What does it do about civilizations where slavery is legal?The politics of these books are not subtle, and they are also not compatible with the existence of billionaires. So it’s worth thinking about why the broligarchs have so consistently cited a socialist author as an inspiration. What do they find tantalizing about Banks’ work? Are they missing the point altogether? Nearly every aspect of the Culture seems to be diametrically opposed to the worldview of the tech right.Banks takes as his starting principle for the Culture the idea that a space-faring civilization will have to be socialist to be effective. In the hostile environment of the vacuum of space, he argues, you will need to be able to count on the collective. Banks further reasons that each spaceship or planet in the Culture will have to be reasonably self-sufficient to survive. At the same time, the Culture is stringently non-hierarchical and non-individualistic. There is no money and no want; therefore, there can’t be any billionaires or any economic inequality. There are no laws and almost no crime. This is not a world in which supremely wealthy people who use their power to influence the social fabric make sense. “Succinctly; socialism within, anarchy without,” Banks concluded in a 1994 Usenet post in which he lays out his full theory of the Culture. In the Culture, should someone commit an action that most people agreed was unacceptable, everyone responds with social shaming rather than the rule of law: They stop inviting the person in question to parties. In other words, like a group of proper leftists, they deal with misbehavior by social cancellation, that great threat against which the broligarchs have declared war.Even work-life balance in the Culture exists in opposition to the ethos of Silicon Valley. The Culture’s citizens have invented vastly powerful AIs that take care of governance for them. This delegation frees up the Culture citizens themselves to indulge in what Banks describes as “the things that really mattered in life, such as sports, games, romance, studying dead languages, barbarian societies and impossible problems, and climbing high mountains without the aid of a safety harness.” Those who are burdened with too much ambition to be content in such a soft life take on (unpaid) jobs managing the Culture’s relationships with other civilizations, mostly for the prestige and the adrenaline rush of it all. This vision appears to have influenced Musk’s idea of a future in which AI has rendered work “optional,” so that “if you want to do a job that’s kinda like a hobby, you can do a job.” Musk allows that there would need to be “universal high income” for this plan to work, but outlines no ideas as to how such an ambitious policy could take effect. In the meantime, in our own world, Amazon, Meta, and Tesla are all infamous for requiring employees to work abusively long hours. Elon Musk is one of the most ardent fans of Iain M. Banks’s Culture series. Nathan Laine/Bloomberg via Getty ImagesFinally, and perhaps most discordantly given the broligarchs’ current gender politics, the Culture is genderfluid. Anyone can change gender just by thinking about it, and most people do at least once in their lives, a state of affairs Banks argues is responsible for its strict regime of gender equality. Meanwhile, Musk is notoriously anti-trans, Zuckerberg has been leaning into the retrograde gender ideologies of the manosphere as he tweaks Meta’s policies to allow more hate speech, particularly toward LGBTQ+ people, and Amazon has removed LGBTQ+ rights support from its website.But it’s not just that the Culture holds the inverse of the ideology these men stand for. The most detestable villain in Banks’s series is Joiler Veppers, a wealthy man in a civilization less evolved than the Culture, who uses his riches to purchase and influence media outlets, undercut labor unions, and rape his indentured servants. Veppers’s money comes from a family fortune built in the computer game industry, and he compounds that fortune by investing in the servers to a series of virtual reality hellscapes, where unfortunates are horribly tortured for all eternity.If you want to know how Banks views capitalist tech billionaires, you don’t have to hunt very hard. In the Culture series, a capitalist tech billionaire is the literal devil, only he couldn’t be bothered to build hell himself. So why are the broligarchs so into the Culture books?So what’s the appeal of the Culture series if you actually are a capitalist tech billionaire? Probably the tech itself.If politics offer the Culture books their intellectual framing, the tech is what gives them their zing, their spectacle. Throughout the series, Banks lovingly describes spaceships and AIs (and lots of spaceships that are also AIs), and artificial planets and gizmos and gadgets. Generally, at the end of the book, the Culture uses one of those gizmos in an inventive way to win a big, explosive space war. Read through this light, the Culture’s technological prowess offers the brute force that backs up its warm and fuzzy ideology. The Culture can afford to be idealistic and worry about its moral culpability because it has better technology than all the other civilizations it faces off with, which means it will nearly always win in a fight.If you think of yourself as a titan of industry who is making that technology for your own culture — who is providing the brute force that allows for wishy-washy moralizing — there is a certain easy comfort that comes with this alignment. You know you are on the correct side of history because you’re on the side that is building the strongest and most advanced technology. Yet within the larger metaphor Banks is building, the relationship between politics and strength is supposed to be the other way around. The Culture is not good because they are strong. Their strength is a metaphor for their goodness. They have the best technology because that shows that they are rational, that they value intelligence, that they are motivated to give their citizens the best possible quality of life. The Culture is not good because they are strong. Their strength is a metaphor for their goodness.To avoid this idea when reading Banks, you would have to be exquisitely attuned to the pleasurable spectacle of technology and the power that tech offers its users, and then ignore everything else. In that case, what the broligarchs’ love of the Culture series reveals is that they see the world through the lens of power and spectacle first and foremost, and have no particular problem evading the work’s deeper meaning. That’s why this group has a propensity for big, pointless stunts, like trips to almost-space and carting a kitchen sink through Twitter headquarters and threatening to punch one another in a public fight. It’s as though they feel entitled to their power because their favorite book taught them that the side with the best tech always wins, and the most important thing you can do with that tech is put on a show. They seem not to have read deeply enough to understand what the book was really trying to say: that the most important thing powerful people can do is use their power to make the world freer, fairer, and more pleasurable for everyone else.See More:

The BBC’s research and development (R&D) arm serves a public purpose, which, according to the department’s director Jatin Aythora, is to make some of the technologies and inventions it creates available either for free or at really low cost. This is something Aythora says BBC R&D has done for many years. Aythora sees his job as helping the team to achieve the technical breakthroughs that the news and media industry can benefit from. The team is tasked with developing technologies and capabilities that benefit the wider society within the UK in a way that minimises the cost to the BBC.  “We all focus on the public purpose of the BBC, which is very much about researching and developing for societal good,” he says. Aythora believes he is a technologist at heart, having started his career as an engineer, and has worked across different industries as he climbed the career ladder. “Every time I’ve changed jobs, I’ve changed industries,” he adds. The benefit of working in many different industries has given Aythora the opportunity to continue learning, which he regards as an important skill for technology leadership. “Curiosity and the ability to learn plays an important role,” he says, adding that these help with confidence and broadens the depth and breadth of knowledge. When asked about applying technology know-how in different sectors, in Aythora’s experience, irrespective of the business sector, technology challenges and opportunities are quite similar: “It’s how you apply technology and what you do with it in the organisational context that matters the most. Technology is linked to the return on investment, which, in any organisation, has to deliver value.” A recent project the BBC Research and Development team has been working on is around demonstrating the authenticity of content. “The verifiability of content has become quite an important aspect of our daily lives. We often come across news that we question, and then we ask [for] or we go to search for other sources to validate and verify,” Aythora says. The team has been working with Microsoft and its chief scientific officer, Eric Horvitz, for several years, developing an approach to verifying content called Content Credentials. “This is a really good example of transferable knowledge from one industry to another,” adds Aythora.  Aythora previously worked at De Beers and in diamond mining. One of the important challenges De Beers faced was to prove where a particular stone came from and whether it was a “clean” diamond, which resulted in the development of Forevermark to verify the authenticity of diamonds. “We invented a piece of technology [Forevermark] that would mark a diamond with a specific watermark that can be traced from where it originates to how many hands it would have exchanged over a period of time,” he says, adding that the same concept can be applied in the content world. “If a piece of BBC content is appearing on social media platforms, you want to be sure of where it has actually come from.” “It’s how you apply technology and what you do with it in the organisational context that matters the most” Jatin Aythora, BBC Research and Development For Aythora, verifying content is an important challenge not only for the news, the media industry and the BBC, but also the wider technology industry. “The content credentials capability and the standards that we’ve invented are now being adopted by most of the large technology organisations, including OpenAI, Google and Microsoft,” he says. The Content Credentials feature on the BBC news site provides a button which enables people reading stories to check the authenticity of the information. The tool uses metadata, such as the time or date an image was taken, compares locations, matches the weather conditions in the image to actual reported weather, notes whether shadows are casting in the correct way, and runs searches for other instances of the material online in case the image has been taken out of context. Content Credentials is now a technical standard from the Coalition for Content Provenance and Authenticity (C2PA), which was co-founded in 2019 by BBC Research and Development – alongside other members including Adobe and Microsoft. BBC News Verify published its first article using the C2PA standard in March 2024. Another project coming out of BBC R&D looks at evolving radio using virtual worlds in a way that can draw in a younger audience, as Aythora explains: “We’ve been exploring how can we make that performance much more interactive and immersive for younger generations who are not going to listen to the radio.” Last year, the BBC partnered with Bristol-based tech company Condense to design immersive live music experiences for younger audiences, which enables fans to join these live events as avatars on their mobile or laptop. The New Music Portal, which began with Radio 1’s New Music Show, hosted by Jack Saunders, enables the audience to navigate the venue like a video game while chatting with other fans via an instant messaging platform.  “We made this experience easy for people to access – you [just] need a device that’s connected to the internet,” says Aythora. He hopes that as virtual reality headsets become more popular and affordable, the experience can evolve to provide a true immersive experience using these devices. Speech-to-text tech and AI BBC R&D tends to have a decade-long outlook on technology, which implies it has been working on certain technologies such as artificial intelligence (AI) for a long time. Recalling the first implementation, Aythora says: “We take it for granted today, because we have access to technology that can do speech to text, but 10 years ago that wasn’t the case. BBC R&D had the best speech-to-text algorithm that was delivering 85% accuracy.” This was significantly higher than the accuracy available from some providers, which, according to Aythora, was only 30% accuracy. Speech-to-text tech powers also subtitles on BBC Sounds. “When we started with the journey of speech to text, we were the market leaders, but we’re not market leaders anymore. AI has matured quite significantly, so what we do is take the best of our capability and the best of what the industry has to provide,” he says, adding that BBC R&D combines the AI technologies developed in-house and products available from speech-to-text providers to deliver “amazing experiences for our audiences”. The BBC is also looking at using AI with video. “We believe defect detection using computer vision and AI models is going to be important for organisations like the BBC,” Aythora says. “There needs to be a method through which we are able to highlight if a particular piece of video or an image has been manipulated.” The BBC’s biggest challenge – and one that the research and development team needs to be cognizant of as it embarks on technology innovation – is how to deliver services at scale at an affordable cost point. “We are a public service organisation. We don’t have an endless amount of money available to us,” Aythora says, adding that this is a different challenge compared with a commercial organisation that uses technology either to gain a competitive edge or drive profit.  IT and technology leaders often encounter situations when they cannot achieve results as quickly as they would like due to organisational constraints. Aythora believes patience is key: “Patience plays an important role in your ability as a leader not only to manage certainty and opportunities, but the challenges as well.” Aythora also recommends IT leaders validate their ideas, adding: “Don’t assume that your idea is the right idea and the best idea. Validate it with various people to build confidence. The more you validate, the more confident you will become, either to pursue it or not to pursue it. Sometimes your ideas might just not be the right idea, and that’s OK, you just have to accept that. But at the same time, continue to validate it.” This is important as good ideas tend to be taken up eventually. “It’s only a matter of time and context before the idea becomes more relevant,” he says. Technologists and IT leaders can often face what may seem like insurmountable barriers and objections to the technology proposals they put forward, but perseverance is key. Among the themes to come out of the conversation with Aythora is one of self-belief – to use Aythora’s words: “Self-belief is not instant; it becomes a belief over a period of time. It’s a journey that we go through.” Read more executive interviews Executive interview – Adding common sense to generative AI creativity: We speak to the chief scientist at Neo4j about why graph databases should work alongside large language models to keep them in check. Executive interview – Will video kill the streaming star?: While we are used to live streaming, video messages seem cheesy – but Vimeo’s chief product officer believes they will revolutionise communications.

We're glad to see everyone enjoying Apocalypse Rising! It's been three weeks since release and this marks our first major balance pass! We are also releasing the modding SDK so users can look into our tools for custom projects! Posted by FRAYDO on May 16th, 2025 We are glad to see everyone playing and enjoying Apocalypse Rising so far! It has been three week since release and this update marks our first major balance pass. The initial feedback has reported that the "Allies are overpowered", and we aim to address that notion with this major patch. This post will include patches 0.9.0.1 through 0.9.0.5 in descending order to describe everything that has been adjusted since our release. At the bottom of this post, after all of the patch notes, we are also including information on the release of our Modding SDK! Patches 0.9.0.3 - 0.9.0.5 There are three patches here because we ran internal testing before settling on the final build (0.9.0.5) Based on game experience and player feedback, it was identified that the Allies were winning the majority of the games. This patch brings the Soviets up to compensate whilst also nerfing some key Allied units. Soviet will now have more of a chance in the face of the Allied teamwork machine. Bug Fixes Fixed several crashes reported by players via crash dumps (thank you!) Fixed Nvidia App "game filters" crashing the game Keyboard keys no longer get stuck when the window loses focus (e.g. Alt+Tab would leave Alt stuck) Less hitching when units spawn Fixed an issue relating to Chrono Miner Objective Markers Performance has been improved by optimizing some game objects General Changes Team remixing/rebalancing logic was re-implemented to improve team variety for players from match to match Players can no longer refill when in combat. Players can now set max FPS to any value instead of an arbitrary selection Bots can path their way out of buildings now (mostly) Mesh optimizations have been applied to the War Factories and Refineries. The legacy "Battlefield Key Success Tips" document has been removed from the game. Several PT icons have been updated Reinforcement Bays are no longer targetable by enemies. Kill messages: Grand Cannon kill strings no longer fill the feed on FreezingStraits. Added crushed kill string. Revolver kill string has been added to the nagant. Shotgun kill string has been added to the shotguns. Map Changes Fort Bradley: Fixed a bunch of buildings, improving performance and removing ngons Adjusted some of the building roofs to prevent degenerate gameplay FreezingStraits: Added visible boundary stripes. The hills behind the bases are now considered out of bounds. Removed a chunk of terrain sticking into the Radar Tower basement. LittleBigLake: Fixed a floating rock on the cliff behind the Allied base. SnowBound: The cliff to the northwest of the Allied base is now considered out-of-bounds. Fixed a couple texture seams at the main road north of the Allied base. Updated the screenshot on loading screen. Updated the overhead map. Dune Patrol: Adjusted out of bounds area to prevent degenerate gameplay General Balance Changes The targeting ranges of several weapons were increased by 3m in order to for units to be able to target enemies a little way before they are actually in range. Lock-on untrack time increased: 1.25s -> 1.75s Prevented some map objects from being locked onto (i.e. Bridge repair Huts) Deployed Infantry Damage Resistance Reduced: 50%->40% Damage from Explosions now affects Mines, C4 and Dynamite Infantry that are crushed by vehicles now register on the kill feed Proximity Mines are now placed at the player's feet. This is in order to prevent mines from being placed on walls and in other weird places. All thrown cooldown-based weapons now autoswap back to the unit's Primary after being used. i.e. After using Molotovs, the Conscript will switch back to it's PPSH automatically Dogs can now reload their bite and bark weapons whilst sprinting. Allies Guardian GI Secondary Fire now shoots a missile that does not lock-on Rocketeer Jetpack Cooldown increased 1s->2s Projectile Damage Reduced: 25->20 Projectile Explosion Damage Outer Radius Increased: 3m->3.25m Projectile Explosion Damage Inner Radius Increased: 1.5m->2m Sniper Projectile Range Decreased: 350m -> 220m Corrected Damage Falloff Range (Within the last 50m of range, the damage falls off by around half) Navy SEAL Projectile Warhead changed: Bullet -> Bullet Anti Infantry This change nerfs the MP5N vs armoured targets Primary Projectile Damage: 15->14 Primary Projectile Spray angle Increased: 0.24°->0.75° Secondary Projectile Damage: 15->14 Secondary Projectile Burst Delay time: 0.12s->0.15s Secondary Projectile Spray angle Increased: 0.1°->0.5° C4 Inventory Count Reduced: 2->1 C4 Explosion Damage Increased: 60->90 Tanya Projectile Damage Increased: 20->22 Projectile Rate of Fire Increased: 6->12 Weapon now fires in 2 round bursts Weapon Clip Sized Increased 18->36 Tanya is supposed to be holding two pistols, so this new clip size aims to reflect that C4 Range: 5m->10m IFV Guardian GI Range Decreased: 120->115 Seal Damage Increased 12->14 Rate of Fire Increased 14->16 Range Increased 95m->115m Sniper Changed Warhead form Bullet_AV to Bullet_AI Projectile Damage: 102 -> 100 Projectile Range: 300 -> 275 Corrected Damage Falloff Range (Within the last 50m of range, the damage falls off by around half) Mirage Tank Range Decreased: 115->110 Prism Tank Projectile Range Increased 145m->150m Tank Destroyer Projectile Range Decreased: 135m->120m Cost Increased: 900->1000 Howitzer Adjusted the model so that it looks less like the Tank Destroyer Harrier Projectile Range Decreased: 130m->120m Black Eagle Projectile Velocity Decreased: 120->100 Projectile Range Decreased: 130m->120m Soviets Crazy Ivan Grenade Launcher Explosion Damage Increased: 50->75 Large Dynamite Inventory Count Reduced: 2->1 Large Dynamite Explosion Damage Increased: 60->90 Terrorist Self Explosion Damage Inner Radius Increased: 4m->6m Weapons are now hidden when not being held. Boris Airtsrike Timer Reduced: 15s->12s Terror Drone The physics have been altered for better handling and cliff climbing performance Jump Height Increased: 12->15 Flak Track Has a new model! Weapon Reload Time: 1.5s ->1.25s Primary Projectile Damage Decreased 33->30 Secondary Projectile Velocity Increased: 400->500 V3 Rocket Launcher Projectile Velocity Decreased: 112->90 Projectile Gravity Increased: 7.0->3.75 Projectile Extension Adjusted Explosion Damage Inner Radius Increased: 10m->12m ***TOTAL RANGE IS AROUND 230m*** Tesla Tank: Weapon handling adjusted to reduce the arc of fire overall Demo Truck Cost Reduced: 1500->1400 Explosion Damage Increased: 400->500 Radiation Radius Increased: 24m->30m Apocalypse Tank Cannon Velocity Increased 250m/s->275m/s Missile Range Increased 135m->140m Missile Lock-on Time Decreased: 1.25->2 Missile Turn Rate increased: 350°/s->420°/s Siege Chopper Model updated with Rotor Blur Cameras re-worked Physics altered to make the controls more responsive Projectile Explosion Damage Outer Radius Increased: 1.5m->2.5m Projectile Explosion Damage Inner Radius Increased: 1m->1.85m Kirov Airship The Kirov now takes half as much damage from all non-AA weapons Points Given on Death: 200 -> 175 MG Damage Increased: 10->11 MG Spray Decreased: 1°->0.9° Bomb Impact Damage Increased: 110->125 Explosion Damage Increased: 100->110 Patch 0.9.0.2 This patch introduced more fixes and altered the balance of some of the most egregious units ingame. Bug Fixes Fixed a crash when spotting a disguised Mirage Tank as an Attack Dog, Tentatively fixed an exploit where GIs and GGIs could become invincible after using a parachute General Changes Added Siege Chopper Weapon Strings, Removed a Projectile Blocker from the doors of the Allied Power Plant Elm and Aca trees now have less upper branch projectile collision Fixed Allied Supply Truck and Siege Chopper entry/exit zones Fixed Shotgun Scaling Terror Drones and Robot Tanks now tell the pilot that the vehicle will be killed if they leave it Added a missing texture fron the loading screen AI turrets on the Battle Fortress and War Miner will now search for targets Terror Drone now has an attack sound Desolator Weapons no longer leave black marks everywhere New Soviet Technician PT Icon Re-ordered the infantry purchase list When using Artillery Auto-Aim feature when out of range, the auto aim will now adopt the max weapon elevation Updated the Credits Map Changes Little Big Lake: Fixed a hole in the ground by the Allied base. Adjusted pathfinding for Harvesters. Dune Patrol: Removed out-of-bounds lines in the small infantry tunnel next to the Soviet base. Snowbound: Added more ground clutter New terrain textures Added some rocks Fort Bradley: Fixed a bunch of NGons on the Urban Buildings Balance Changes The Attack Dog's Bark can now pierce through multiple targets Engineer + IFV Repair Reduced: 0.65 -> 0.6 Technician + IFV Repair Reduced: 0.32 -> 0.3 Technician IFv Self Healing Halved Deployed Infantry now take 50% less incoming damage from all sources (was inconsistent beforehand) AA Flak Damage vs Helicopters Increased Sniper IFV Laser now uses the correct range Patch 0.9.0.1 Released shortly after the game launched, this patch contained key fixes to the game. Bug Fixes Fixed a Server Crash that was sometimes occurring when a player added a vehicle to the queue and then left the server Siege Chopper can no longer deploy in mid-air Siege Chopper animation has been fixed Fixed an issue with Fort Bradley where Allies were getting 500 free points at the start of the match Fixed some graphical issues with Fort Bradley General Changes Added Siege Cameras to the V3 Launcher and Howitzer Added Encyclopaedia entries for the weapons and infantry Ricardo Engineer credit to Scorched Earth! Check out his RA2 and Apocalypse Rising videos on his YouTube channel! Youtube.com Over the course of these past few weeks, we have heard several requests from our players to release the tools for the game so they can make mods, dive into unit statistics, and translate the game into various languages. We are proud to announce we've made the modding SDK available here: Gitlab.com Whenever we release we will aim to update the tools to match the latest public version, much like we do with the server (also found here: Gitlab.com). If you're looking for tutorials and documentation, we have a wealth of info in our Tutorials forum but also on Tacitus, which is our documentation resource. Links below the image. Tacitus: Documentation Tutorials: W3D Tutorials Over time we will aim to add more to these tools, like pieces of example content and maps for you guy to dissect. In the meantime though, we can't wait to see what you'll all end up making and if you need any help creating things, please feel free to reach out to us over Discord! Found here: Discord.gg Keep 'Em Coming! That's all for now. Please feel free to leave your feedback and report bugs in our Discord and on our forums. We've got eyes on both platforms, so we'll make sure that every point gets a fair shake. Thanks again for supporting the game and our community! - The W3D Hub Team