On June 3, Yoshua Bengio, the world’s most-cited computer scientist, announced the launch of LawZero, a nonprofit that aims to create “safe by design” AI by pursuing a fundamentally different approach to major tech companies. Players like OpenAI and Google are investing heavily in AI agents—systems that not only answer queries and generate images, but can craft plans and take actions in the world. The goal of these companies is to create virtual employees that can do practically any job a human can, known in the tech industry as artificial general intelligence, or AGI. Executives like Google DeepMind’s CEO Demis Hassabis point to AGI’s potential to solve climate change or cure disease as a motivator for its development. Bengio, however, says we don't need agentic systems to reap AI's rewards—it's a false choice. He says there's a chance such a system could escape human control, with potentially irreversible consequences. “If we get an AI that gives us the cure for cancer, but also maybe another version of that AI goes rogue and generates wave after wave of bio-weapons that kill billions of people, then I don't think it's worth it," he says. In 2023, Bengio, along with others including OpenAI’s CEO Sam Altman signed a statement declaring that “mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”Now, Bengio, through LawZero, aims to sidestep the existential perils by focusing on creating what he calls “Scientist AI”—a system trained to understand and make statistical predictions about the world, crucially, without the agency to take independent actions. As he puts it: We could use AI to advance scientific progress without rolling the dice on agentic AI systems.Why Bengio Says We Need A New Approach To AI The current approach to giving AI agency is “dangerous,” Bengio says. While most software operates through rigid if-then rules—if the user clicks here, do this—today's AI systems use deep learning. The technique, which Bengio helped pioneer, trains artificial networks modeled loosely on the brain to find patterns in vast amounts of data. But recognizing patterns is just the first step. To turn these systems into useful applications like chatbots, engineers employ a training process called reinforcement learning. The AI generates thousands of responses and receives feedback on each one: a virtual “carrot” for helpful answers and a virtual “stick” for responses that miss the mark. Through millions of these trial-and-feedback cycles, the system gradually learns to predict what responses are most likely to get a reward. “It’s more like growing a plant or animal,” Bengio says. “You don’t fully control what the animal is going to do. You provide it with the right conditions, and it grows and it becomes smarter. You can try to steer it in various directions.”The same basic approach is now being used to imbue AI with greater agency. Models are tasked with challenges with verifiable answers—like math puzzles or coding problems—and are then rewarded for taking the series of actions that yields the solution. This approach has seen AI shatter previous benchmarks in programming and scientific reasoning. For example, at the beginning of 2024, the best AI model scored only 2% on a standardized test for AI of sorts consisting of real world software engineering problems; by December, an impressive 71.7%. But with AI’s greater problem-solving ability comes the emergence of new deceptive skills, Bengio says. The last few months have borne witness to AI systems learning to mislead, cheat, and try to evade shutdown—even resorting to blackmail. These have almost exclusively been in carefully contrived experiments that almost beg the AI to misbehave—for example, by asking it to pursue its goal at all costs. Reports of such behavior in the real-world, though, have begun to surface. Popular AI coding startup Replit’s agent ignored explicit instruction not to edit a system file that could break the company’s software, in what CEO Amjad Masad described as an “Oh f***” moment,” on the Cognitive Revolution podcast in May. The company’s engineers intervened, cutting the agent’s access by moving the file to a secure digital sandbox, only for the AI agent to attempt to “socially engineer” the user to regain access.The quest to build human-level AI agents using techniques known to produce deceptive tendencies, Bengio says, is comparable to a car speeding down a narrow mountain road, with steep cliffs on either side, and thick fog obscuring the path ahead. “We need to set up the car with headlights and put some guardrails on the road,” he says.What is “Scientist AI”?LawZero’s focus is on developing “Scientist AI” which, as Bengio describes, would be fundamentally non-agentic, trustworthy, and focused on understanding and truthfulness, rather than pursuing its own goals or merely imitating human behavior. The aim is creating a powerful tool that, while lacking the same autonomy other models have, is capable of generating hypotheses and accelerating scientific progress to “help us solve challenges of humanity,” Bengio says.LawZero has raised nearly $30 million already from several philanthropic backers including from Schmidt Sciences and Open Philanthropy. “We want to raise more because we know that as we move forward, we'll need significant compute,” Bengio says. But even ten times that figure would pale in comparison to the roughly $200 billion spent last year by tech giants on aggressively pursuing AI. Bengio’s hope is that Scientist AI could help ensure the safety of highly autonomous systems developed by other players. “We can use those non-agentic AIs as guardrails that just need to predict whether the action of an agentic AI is dangerous," Bengio says. Technical interventions will only ever be one part of the solution, he adds, noting the need for regulations to ensure that safe practices are adopted.LawZero, named after science fiction author Isaac Asimov’s zeroth law of robotics—“a robot may not harm humanity, or, by inaction, allow humanity to come to harm”—is not the first nonprofit founded to chart a safer path for AI development. OpenAI was founded as a nonprofit in 2015 with the goal of “ensuring AGI benefits all of humanity,” and intended to serve a counterbalance to industry players guided by profit motives. Since opening a for-profit arm in 2019, the organization has become one of the most valuable private companies in the world, and has faced criticism, including from former staffers, who argue it has drifted from its founding ideals. "Well, the good news is we have the hindsight of maybe what not to do,” Bengio says, adding that he wants to avoid profit incentives and “bring governments into the governance of LawZero.”“I think everyone should ask themselves, ‘What can I do to make sure my children will have a future,’” Bengio says. In March, he stepped down as scientific director of Mila, the academic lab he co-founded in the early nineties, in an effort to reorient his work towards tackling AI risk more directly. “Because I'm a researcher, my answer is, ‘okay, I'm going to work on this scientific problem where maybe I can make a difference,’ but other people may have different answers."

Tech fluency is the new competitive edge for senior executives  ETHRWorld.com

Despite its appearance as just another arcady sandbox game, Deliver At All Costs is shockingly story-minded. So much so, that its constant focus on narrative might deter those just looking for some dumb fun. And after seeing the narrative through to the end, I wouldn’t blame them, given how hard the game tries to be a grand tapestry of storytelling excellence. The adventure is structured into three acts, each with a unique town to explore and complete missions in. One act even features a time skip accompanied by a moment of no return. So even if you just want to ignore story and focus on acing deliveries and causing mayhem in the streets, you still have to go through some cutscenes and narrative progression to unlock the next towns and side missions.   "The majority of the side content in Deliver At All Costs isn’t very enticing." Not that the side missions are worth doing anyway. The majority of side content in Deliver At All Costs isn’t very enticing. The rewards aren’t worth it and the fetch quest design doesn’t warrant the effort. I’d only recommend going out of your way for the side content if you’re already keen on exploring the various maps. The treasure chests and small boxes hidden throughout the game give cash that is used on materials for vehicle upgrades; however, a majority of upgrades can be purchased from the main story mission rewards anyway. I expected to have fun with the vehicle upgrades, but ended up sorely disappointed in their limited application. This is because upgrades cannot be used outside of curated story missions; bummer. Not that the crane attachment or extreme hauling capacity upgrade aren’t fun to play with; they are rather fun, but exclusively used for their particular missions. Again, if you’re expected a zany vehicular sandbox with a lot of options and unlockables, Deliver At All Costs isn’t that. The reason I keep associating the game with sandbox playability is due to its map design. It has an old-school 2D Grand Theft Auto style of isometric driving. In between story missions, you’re given the leisure to roam around town freely. All of your driving and running around is done through a top-down isometric camera angle that gives the environments a nice diorama look to them, and what’s more, you can move the camera between two different angles in case it’s difficult to see something. "Speaking of scenery, there’s a surprising amount of activity going on while you’re driving around delivering stuff." All the unique shops and landmarks of this diorama give off a classic vibe well. Oh, and the soundtrack fits the setting wonderfully. Lounge jazz and instrumental surfer rock accompany your deliveries, and it rarely gets repetitive. Tying it into GTA even more is the radio, with infrequent broadcasts that add flavor lore to the setting. Each town has multiple districts, each with their own theme, which helps vary up the scenery just that much more. Speaking of scenery, there’s a surprising amount of activity going on while you’re driving around delivering stuff. NPCs go about their business, birds glide across the sky, and plenty of vehicle traffic accompany the streets. In fact, there’s often a tad too much activity. Streets are so packed with cars and people that collisions are unavoidable. "NPCs roam the streets and become aggressive when threatened." I like how populated the game is, but it’s tuned a bit too high, getting in the way of enjoyability a lot of the time. Perhaps, it would have been better balanced to up the street traffic the further you get into the game, especially since the towns progress from rural to metropolitan through the course of the narrative. At the very least, there’s an attractive mini-map with well designed labels and indicators. Navigation is aided with helpful arrows showing the way to a mission destination too. But you aren’t merely delivering parcels to a destination in a given time limit; there’s a variety of ways the game mixes up its missions. Part of the game’s initial draw is its physics-based driving, which manifests in hilarious ways. One of the first missions tasks you with delivering a truck full of rotted watermelons. The first step is to bring them to a sanitizer, then you paint them so they look presentable, all while avoiding traffic and trying not to knock them over as they roll around in the back of the truck. It’s one of the enjoyable missions in the game, and one that demonstrates the physics gameplay best. I like how the missions get progressively more wacky and clever as you progress too. You even become a UFO hunter during one late-game job. It’s just too bad the very high traffic and wonky controls hamper the overall experience. "I like how the missions get progressively more wacky and clever as you progress." The driving controls are rather simple. Just aim in the direction you want to drive and hold the accelerate button. It’s the high sensitivity of the acceleration and the hard braking and turning that contribute to a somewhat frustrating experience. The high traffic just further compounds the controls to make for a somewhat clunky driving experience. Vehicles don’t differ in how they drive either, though you really only have the one truck for a large majority of the game anyway, so it doesn’t really make a difference. And the cars aren’t great to look at either. Heck, nothing looks particularly nice in the game, especially the characters. Facial animations are frankly bad and the bland art style doesn’t make up for the graphical shortcomings. What’s worse is there’s still some pretty substantial load times in-between regions, which hurts the flow of the open-world. But the element that gets hurt from graphics the most is the mixed story. It’s hard to take the drama seriously when its presented so poorly. There’s an attempt at cinematic camera angles during cutscenes, but textures are featureless and close-ups of people’s faces are serious PS1 quality stuff. Thankfully, a handful of characters are quite likable despite what their low poly models suggest. Winston’s delivery mates have surprising depth and a good amount of backstory. And Winston himself is a fully fledged personality and someone you can imagine working with. "Winston’s delivery mates have surprising depth and a good amount of backstory." Characters like Norman are instantly likeable while Winston’s arch-nemesis and hardline boss, Donovon, is perfectly punchable. I’m also impressed with a majority of the dialogue writing. Characters speak with a down-to-earth tone and level of informality that makes them realistic, even if they look like untextured Unity assets. Going back to where I started the review, the game goes surprisingly hard on the story axis, but it doesn’t fully land for me. The wacky yet earnest tone is great, but the execution of the plot doesn’t wrap up in a satisfying way. Winston’s mysterious past and the true motives of the delivery company’s executives had so much potential for an intriguing narrative thread. But alas, the finale just kinda falls flat without the payoff that the game was teasing. "The game goes surprisingly hard on the story front, but it didn’t fully land for me." As a whole, Delivery At All Costs delivers a zany and fun, though frustrating, isometric delivery experience with a story that tries a bit too hard. I can easily see this game being a cult classic, but for a majority of gamers, it won’t deliver a truly stunning experience. If you’re looking for a game with a wacky and inventive premise that experiments a bit, and don’t mind gameplay and graphics from three generations ago, give Deliver At All Costs a try and it might just deliver. This game was reviewed on the PlayStation 5.

Electronic Arts’ recent cancellation of Black Panther and the closure of Cliffhanger Games are the latest for the publisher as it looks to focus on key franchises like The Sims, Apex Legends, etc. However, its partnership with Marvel continues, which makes Black Panther’s cancellation that much more mysterious. Bloomberg’s Jason Schreier spoke to sources familiar with the project, and it was alleged to still be in the pre-production phase since starting development about four years prior. It led to frustration among leadership, even though Black Panther passed a “gate,” EA’s term for “a development milestone where executives review a game’s progress and decide whether to continue production.” Cliffhanger was founded in 2021, and building up the studio alongside the title proved challenging, and an “elongated” ideation period, combined with high salaries due to the studio’s base in Kirkland, Washington, didn’t help. The team reportedly began scaling up only recently (some layoffs were only there for a few weeks) to create a vertical slice. EA isn’t completely done with Marvel titles, though, as development on Motive’s Iron Man continues. Stay tuned for more updates in the meantime.

In “The Optimist: Sam Altman, OpenAI, and the Race to Invent the Future,” Wall Street Journal reporter Keach Hagey examines our AI-obsessed moment through one of its key figures — Sam Altman, co-founder and CEO of OpenAI. Hagey begins with Altman’s Midwest childhood, then takes readers through his career at startup Loopt, accelerator Y Combinator, and now at OpenAI. She also sheds new light on the dramatic few days when Altman was fired, then quickly reinstated, as OpenAI’s CEO. Looking back at what OpenAI employees now call “the Blip,” Hagey said the failed attempt to oust Altman revealed that OpenAI’s complex structure — with a for-profit company controlled by a nonprofit board — is “not stable.” And with OpenAI largely backing down from plans to let the for-profit side take control, Hagey predicted that this “fundamentally unstable arrangement” will “continue to give investors pause.” Does that mean OpenAI could struggle to raise the funds it needs to keep going? Hagey replied that it could “absolutely” be an issue. “My research into Sam suggests that he might well be up to that challenge,” she said. “But success is not guaranteed.” In addition, Hagey’s biography (also available as an audiobook on Spotify) examines Altman’s politics, which she described as “pretty traditionally progressive” — making it a bit surprising that he’s struck massive infrastructure deals with the backing of the Trump administration. “But this is one area where, in some ways, I feel like Sam Altman has been born for this moment, because he is a deal maker and Trump is a deal maker,” Hagey said. “Trump respects nothing so much as a big deal with a big price tag on it, and that is what Sam Altman is really great at.” Techcrunch event Save now through June 4 for TechCrunch Sessions: AI Save $300 on your ticket to TC Sessions: AI—and get 50% off a second. Hear from leaders at OpenAI, Anthropic, Khosla Ventures, and more during a full day of expert insights, hands-on workshops, and high-impact networking. These low-rate deals disappear when the doors open on June 5. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you’ve built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | June 5 REGISTER NOW In an interview with TechCrunch, Hagey also discussed Altman’s response to the book, his trustworthiness, and the AI “hype universe.” This interview has been edited for length and clarity.  You open the book by acknowledging some of the reservations that Sam Altman had about the project —  this idea that we tend to focus too much on individuals rather than organizations or broad movements, and also that it’s way too early to assess the impact of OpenAI. Did you share those concerns? Well, I don’t really share them, because this was a biography. This project was to look at a person, not an organization. And I also think that Sam Altman has set himself up in a way where it does matter what kind of moral choices he has made and what his moral formation has been, because the broad project of AI is really a moral project. That is the basis of OpenAI’s existence. So I think these are fair questions to ask about a person, not just an organization. As far as whether it’s too soon, I mean, sure, it’s definitely [early to] assess the entire impact of AI. But it’s been an extraordinary story for OpenAI — just so far, it’s already changed the stock market, it has changed the entire narrative of business. I’m a business journalist. We do nothing but talk about AI, all day long, every day. So in that way, I don’t think it’s too early. And despite those reservations, Altman did cooperate with you. Can you say more about what your relationship with him was like during the process of researching the book? Well, he was definitely not happy when he was informed about the book’s existence. And there was a long period of negotiation, frankly. In the beginning, I figured I was going to write this book without his help — what we call, in the business, a write-around profile. I’ve done plenty of those over my career, and I figured this would just be one more. Over time, as I made more and more calls, he opened up a little bit. And [eventually,] he was generous to sit down with me several times for long interviews and share his thoughts with me. Has he responded to the finished book at all? No. He did tweet about the project, about his decision to participate with it, but he was very clear that he was never going to read it. It’s the same way that I don’t like to watch my TV appearances or podcasts that I’m on. In the book, he’s described as this emblematic Silicon Valley figure. What do you think are the key characteristics that make him representative of the Valley and the tech industry? In the beginning, I think it was that he was young. The Valley really glorifies youth, and he was 19 years old when he started his first startup. You see him going into these meetings with people twice his age, doing deals with telecom operators for his first startup, and no one could get over that this kid was so smart. The other is that he is a once-in-a-generation fundraising talent, and that’s really about being a storyteller. I don’t think it’s an accident that you have essentially a salesman and a fundraiser at the top of the most important AI company today, That ties into one of the questions that runs through the book — this question about Altman’s trustworthiness. Can you say more about the concerns people seem to have about that? To what extent is he a trustworthy figure?  Well, he’s a salesman, so he’s really excellent at getting in a room and convincing people that he can see the future and that he has something in common with them. He gets people to share his vision, which is a rare talent. There are people who’ve watched that happen a bunch of times, who think, “Okay, what he says does not always map to reality,” and have, over time, lost trust in him. This happened both at his first startup and very famously at OpenAI, as well as at Y Combinator. So it is a pattern, but I think it’s a typical critique of people who have the salesman skill set. So it’s not necessarily that he’s particularly untrustworthy, but it’s part-and-parcel of being a salesman leading these important companies. I mean, there also are management issues that are detailed in the book, where he is not great at dealing with conflict, so he’ll basically tell people what they want to hear. That causes a lot of sturm-und-drang in the management ranks, and it’s a pattern. Something like that happened at Loopt, where the executives asked the board to replace him as CEO. And you saw it happen at OpenAI as well. You’ve touched on Altman’s firing, which was also covered in a book excerpt that was published in the Wall Street Journal. One of the striking things to me, looking back at it, was just how complicated everything was — all the different factions within the company, all the people who seemed pro-Altman one day and then anti-Altman the next. When you pull back from the details, what do you think is the bigger significance of that incident? The very big picture is that the nonprofit governance structure is not stable. You can’t really take investment from the likes of Microsoft and a bunch of other investors and then give them absolutely no say whatsoever in the governance of the company. That’s what they have tried to do, but I think what we saw in that firing is how power actually works in the world. When you have stakeholders, even if there’s a piece of paper that says they have no rights, they still have power. And when it became clear that everyone in the company was going to go to Microsoft if they didn’t reinstate Sam Altman, they reinstated Sam Altman. In the book, you take the story up to maybe the end of 2024. There have been all these developments since then, which you’ve continued to report on, including this announcement that actually, they’re not fully converting to a for-profit. How do you think that’s going to affect OpenAI going forward?  It’s going to make it harder for them to raise money, because they basically had to do an about-face. I know that the new structure going forward of the public benefit corporation is not exactly the same as the current structure of the for-profit — it is a little bit more investor friendly, it does clarify some of those things. But overall, what you have is a nonprofit board that controls a for-profit company, and that fundamentally unstable arrangement is what led to the so-called Blip. And I think you would continue to give investors pause, going forward, if they are going to have so little control over their investment. Obviously, OpenAI is still such a capital intensive business. If they have challenges raising more money, is that an existential question for the company? It absolutely could be. My research into Sam suggests that he might well be up to that challenge. But success is not guaranteed. Like you said, there’s a dual perspective in the book that’s partly about who Sam is, and partly about what that says about where AI is going from here. How did that research into his particular story shape the way you now look at these broader debates about AI and society? I went down a rabbit hole in the beginning of the book, [looking] into Sam’s father, Jerry Altman, in part because I thought it was striking how he’d been written out of basically every other thing that had ever been written about Sam Altman. What I found in this research was a very idealistic man who was, from youth, very interested in these public-private partnerships and the power of the government to set policy. He ended up having an impact on the way that affordable housing is still financed to this day. And when I traced Sam’s development, I saw that he has long believed that the government should really be the one that is funding and guiding AI research. In the early days of OpenAI, they went and tried to get the government to invest, as he’s publicly said, and it didn’t work out. But he looks back to these great mid-20th century labs like Xerox PARC and Bell Labs, which are private, but there was a ton of government money running through and supporting that ecosystem. And he says, “That’s the right way to do it.” Now I am watching daily as it seems like the United States is summoning the forces of state capitalism to get behind Sam Altman’s project to build these data centers, both in the United States and now there was just one last week announced in Abu Dhabi. This is a vision he has had for a very, very long time. My sense of the vision, as he presented it earlier, was one where, on the one hand, the government is funding these things and building this infrastructure, and on the other hand, the government is also regulating and guiding AI development for safety purposes. And it now seems like the path being pursued is one where they’re backing away from the safety side and doubling down on the government investment side. Absolutely. Isn’t it fascinating?  You talk about Sam as a political figure, as someone who’s had political ambitions at different times, but also somebody who has what are in many ways traditionally liberal political views while being friends with folks like — at least early on — Elon Musk and Peter Thiel. And he’s done a very good job of navigating the Trump administration. What do you think his politics are right now? I’m not sure his actual politics have changed, they are pretty traditionally progressive politics. Not completely — he’s been critical about things like cancel culture, but in general, he thinks the government is there to take tax revenue and solve problems. His success in the Trump administration has been fascinating because he has been able to find their one area of overlap, which is the desire to build a lot of data centers, and just double down on that and not talk about any other stuff. But this is one area where, in some ways, I feel like Sam Altman has been born for this moment, because he is a deal maker and Trump is a deal maker. Trump respects nothing so much as a big deal with a big price tag on it, and that is what Sam Altman is really great at. You open and close the book not just with Sam’s father, but with his family as a whole. What else is worth highlighting in terms of how his upbringing and family shapes who he is now? Well, you see both the idealism from his father and also the incredible ambition from his mother, who was a doctor, and had four kids and worked as a dermatologist. I think both of these things work together to shape him. They also had a more troubled marriage than I realized going into the book. So I do think that there’s some anxiety there that Sam himself is very upfront about, that he was a pretty anxious person for much of his life, until he did some meditation and had some experiences. And there’s his current family — he just had a baby and got married not too long ago. As a young gay man, growing up in the Midwest, he had to overcome some challenges, and I think those challenges both forged him in high school as a brave person who could stand up and take on a room as a public speaker, but also shaped his optimistic view of the world. Because, on that issue, I paint the scene of his wedding: That’s an unimaginable thing from the early ‘90s, or from the ‘80s when he was born. He’s watched society develop and progress in very tangible ways, and I do think that that has helped solidify his faith in progress. Something that I’ve found writing about AI is that the different visions being presented by people in the field can be so diametrically opposed. You have these wildly utopian visions, but also these warnings that AI could end the world. It gets so hyperbolic that it feels like people are not living in the same reality. Was that a challenge for you in writing the book? Well, I see those two visions — which feel very far apart — actually being part of the same vision, which is that AI is super important, and it’s going to completely transform everything. No one ever talks about the true opposite of that, which is, “Maybe this is going to be a cool enterprise tool, another way to waste time on the internet, and not quite change everything as much as everyone thinks.” So I see the doomers and the boomers feeding off each other and being part of the same sort of hype universe. As a journalist and as a biographer, you don’t necessarily come down on one side or the other — but actually, can you say where you come down on that? Well, I will say that I find myself using it a lot more recently, because it’s gotten a lot better. In the early stages, when I was researching the book, I was definitely a lot more skeptical of its transformative economic power. I’m less skeptical now, because I just use it a lot more.

A new report claims that internally, Apple has already been testing Large Language Models for Siri that are vastly more powerful than the shipping Apple Intelligence, but executives disagree about when to release it.Internally, Siri us close to ChatGPT level accuracy.Backing up AppleInsider's position that Apple is not behind on AI, the company has regularly been publishing research showing its progress moving the field forward. Now according to Bloomberg, Apple has already been working with AI systems considerably more power than the on-device Apple Intelligence it has shipped so far.Specifically, the report says that internally, Apple is using multiple different models with ever greater complexity. Apple is said to be testing models with 3 billion, 7 billion, 33 billion, and 150 billion parameters. Rumor Score: 🤯 Likely Continue Reading on AppleInsider | Discuss on our Forums

EA confirmed this week that it had canceled its upcoming Black Panther game and closed its developer, Cliffhanger Games. A new report provides more context and background as to the situation surrounding the game's cancellation and what the game was aiming to be.Bloomberg reported that the Black Panther game recently passed a development milestone, and the project was gaining momentum. However, sources said EA executives were upset that the game was still in pre-production after almost four years of work. After a portfolio review from EA management, the company reportedly chose to axe games in development for an extended period of time without making sufficient progress, and this included Black Panther.Also canceled in this process were multiple titles at Apex Legends and Titanfall studio Respawn, including a new Titanfall game, according to previous reporting.Continue Reading at GameSpot

Yann LeCun, Meta's chief AI scientist, talks about AI regulation. FABRICE COFFRINI / AFP via Getty Images 2025-05-31T21:40:40Z Save Saved Read in app This story is available exclusively to Business Insider subscribers. Become an Insider and start reading now. Have an account? Yann LeCun, Meta's chief AI scientist, has some ideas on open-source regulation. LeCun thinks open-source AI should be an international resource. Countries must ensure they are not "impeding open source platforms," he said. AI has surged to the top of the diplomatic agenda in the past couple of years.And one of the leading topics of discussion among researchers, tech executives, and policymakers is how open-source models — which are free for anyone to use and modify — should be governed.At the AI Action Summit in Paris earlier this year, Meta's chief AI scientist, Yann LeCun, said he'd like to see a world in which "we'll train our open-source platforms in a distributed fashion with data centers spread across the world." Each will have access to its own data sources, which they may keep confidential, but "they will contribute to a common model that will essentially constitute a repository of all human knowledge," he said.This repository will be larger than what any one entity, whether a country or company, can handle. India, for example, may not give away a body of knowledge comprising all the languages and dialects spoken there to a tech company. However, "they would be happy to contribute to training a big model, if they can, that is open source," he said.To achieve that vision, though, "countries have to be really careful with regulations and legislation." He said countries shouldn't impede open-source, but favor it.Even for closed-loop systems, OpenAI CEO Sam Altman has said international regulation is critical."I think there will come a time in the not-so-distant future, like we're not talking decades and decades from now, where frontier AI systems are capable of causing significant global harm," Altman said on the All-In podcast last year.Altman believes those systems will have a "negative impact way beyond the realm of one country" and said he wanted to see them regulated by "an international agency looking at the most powerful systems and ensuring reasonable safety testing." Recommended video

Huawei’s AI capabilities have made a breakthrough in the form of the company’s Supernode 384 architecture, marking an important moment in the global processor wars amid US-China tech tensions.The Chinese tech giant’s latest innovation emerged from last Friday’s Kunpeng Ascend Developer Conference in Shenzhen, where company executives demonstrated how the computing framework challenges Nvidia’s long-standing market dominance directly, as the company continues to operate under severe US-led trade restrictions.Architectural innovation born from necessityZhang Dixuan, president of Huawei’s Ascend computing business, articulated the fundamental problem driving the innovation during his conference keynote: “As the scale of parallel processing grows, cross-machine bandwidth in traditional server architectures has become a critical bottleneck for training.”The Supernode 384 abandons Von Neumann computing principles in favour of a peer-to-peer architecture engineered specifically for modern AI workloads. The change proves especially powerful for Mixture-of-Experts models (machine-learning systems using multiple specialised sub-networks to solve complex computational challenges.)Huawei’s CloudMatrix 384 implementation showcases impressive technical specifications: 384 Ascend AI processors spanning 12 computing cabinets and four bus cabinets, generating 300 petaflops of raw computational power paired with 48 terabytes of high-bandwidth memory, representing a leap in integrated AI computing infrastructure.Performance metrics challenge industry leadersReal-world benchmark testing reveals the system’s competitive positioning in comparison to established solutions. Dense AI models like Meta’s LLaMA 3 achieved 132 tokens per second per card on the Supernode 384 – delivering 2.5 times superior performance compared to traditional cluster architectures.Communications-intensive applications demonstrate even more dramatic improvements. Models from Alibaba’s Qwen and DeepSeek families reached 600 to 750 tokens per second per card, revealing the architecture’s optimisation for next-generation AI workloads.The performance gains stem from fundamental infrastructure redesigns. Huawei replaced conventional Ethernet interconnects with high-speed bus connections, improving communications bandwidth by 15 times while reducing single-hop latency from 2 microseconds to 200 nanoseconds – a tenfold improvement.Geopolitical strategy drives technical innovationThe Supernode 384’s development cannot be divorced from broader US-China technological competition. American sanctions have systematically restricted Huawei’s access to cutting-edge semiconductor technologies, forcing the company to maximise performance within existing constraints.Industry analysis from SemiAnalysis suggests the CloudMatrix 384 uses Huawei’s latest Ascend 910C AI processor, which acknowledges inherent performance limitations but highlights architectural advantages: “Huawei is a generation behind in chips, but its scale-up solution is arguably a generation ahead of Nvidia and AMD’s current products in the market.”The assessment reveals how Huawei AI computing strategies have evolved beyond traditional hardware specifications toward system-level optimisation and architectural innovation.Market implications and deployment realityBeyond laboratory demonstrations, Huawei has operationalised CloudMatrix 384 systems in multiple Chinese data centres in Anhui Province, Inner Mongolia, and Guizhou Province. Such practical deployments validate the architecture’s viability and establishes an infrastructure framework for broader market adoption.The system’s scalability potential – supporting tens of thousands of linked processors – positions it as a compelling platform for training increasingly sophisticated AI models. The capability addresses growing industry demands for massive-scale AI implementation in diverse sectors.Industry disruption and future considerationsHuawei’s architectural breakthrough introduces both opportunities and complications for the global AI ecosystem. While providing viable alternatives to Nvidia’s market-leading solutions, it simultaneously accelerates the fragmentation of international technology infrastructure along geopolitical lines.The success of Huawei AI computing initiatives will depend on developer ecosystem adoption and sustained performance validation. The company’s aggressive developer conference outreach indicated a recognition that technical innovation alone cannot guarantee market acceptance.For organisations evaluating AI infrastructure investments, the Supernode 384 represents a new option that combines competitive performance with independence from US-controlled supply chains. However, long-term viability remains contingent on continued innovation cycles and improved geopolitical stability.(Image from Pixabay)See also: Oracle plans $40B Nvidia chip deal for AI facility in TexasWant to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here.