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Yann LeCun Raises $1 Billion to Build AI That Understands the Physical World

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Yann LeCun Raises  Billion to Build AI That Understands the Physical World


Advanced Machine Intelligence (AMI), a new Paris-based startup cofounded by Meta’s former chief AI scientist Yann LeCun, announced Monday it has raised more than $1 billion to develop AI world models.

LeCun argues that most human reasoning is grounded in the physical world, not language, and that AI world models are necessary to develop true human-level intelligence. “The idea that you’re going to extend the capabilities of LLMs [large language models] to the point that they’re going to have human-level intelligence is complete nonsense,” he said in an interview with WIRED.

The financing, which values the startup at $3.5 billion, was co-led by investors such as Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions. Other notable backers include Mark Cuban, former Google CEO Eric Schmidt, and French billionaire and telecommunications executive Xavier Niel.

AMI (pronounced like the French word for friend) aims to build “a new breed of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe,” the company says in a press release. The startup says it will be global from day one, with offices in Paris, Montreal, Singapore, and New York, where LeCun will continue working as a New York University professor in addition to leading the startup. AMI will be the first commercial endeavor for LeCun since his departure from Meta in November 2025.

LeCun’s startup represents a bet against many of the world’s biggest AI labs like OpenAI, Anthropic, and even his former workplace, Meta, which believe that scaling up LLMs will eventually deliver AI systems with human-level intelligence or even superintelligence. LLMs have powered viral products such as ChatGPT and Claude Code, but LeCun has been one of the AI industry’s most prominent researchers speaking out about the limitations of these AI models. LeCun is well known for being outspoken, but as a pioneer of modern AI that won a Turing award back in 2018, his skepticism carries weight.

LeCun says AMI aims to work with companies in manufacturing, biomedical, robotics, and other industries that have lots of data. For example, he says AMI could build a realistic world model of an aircraft engine and work with the manufacturer to help them optimize for efficiency, minimize emissions, or ensure reliability.

AMI was cofounded by LeCun and several leaders he worked with at Meta, including the company’s former director of research science, Michael Rabbat; former vice president of Europe, Laurent Solly; and former senior director of AI research, Pascale Fung. Other cofounders include Alexandre LeBrun, former CEO of the AI health care startup Nabla, who will serve as AMI’s CEO, and Saining Xie, a former Google DeepMind researcher who will be the startup’s chief science officer.

The Case for World Models

LeCun does not dismiss the overall utility of LLMs. Rather, in his view, these AI models are simply the tech industry’s latest promising trend, and their success has created a “kind of delusion” among the people who build them. “It’s true that [LLMs] are becoming really good at generating code, and it’s true that they are probably going to become even more useful in a wide area of applications where code generation can help,” says LeCun. “That’s a lot of applications, but it’s not going to lead to human-level intelligence at all.”

LeCun has been working on world models for years inside of Meta, where he founded the company’s Fundamental AI Research lab, FAIR. But he’s now convinced his research is best done outside the social media giant. He says it’s become clear to him that the strongest applications of world models will be selling them to other enterprises, which doesn’t fit neatly into Meta’s core consumer business.

As AI world models like Meta’s Joint-Embedding Predictive Architecture (JEPA) became more sophisticated, “there was a reorientation of Meta’s strategy where it had to basically catch up with the industry on LLMs and kind of do the same thing that other LLM companies are doing, which is not my interest,” says LeCun. “So sometime in November, I went to see Mark Zuckerberg and told him. He’s always been very supportive of [world model research], but I told him I can do this faster, cheaper, and better outside of Meta. I can share the cost of development with other companies … His answer was, OK, we can work together.”



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Robotically assembled building blocks could make construction more efficient and sustainable

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Robotically assembled building blocks could make construction more efficient and sustainable



Robotically assembled building blocks could be a more environmentally friendly method for erecting large-scale structures than some existing construction techniques, according to a new study by MIT researchers.

The team conducted a feasibility study to evaluate the efficiency of constructing a simple building using “voxels,” which are modular 3D subunits that assemble into complex, durable structures.

After studying the performance of multiple voxels, the researchers developed three new designs intended to streamline building construction. They also produced a robotic assembler and a user-friendly interface for generating voxel-based building layouts and feeding instructions to the robots.

Their results indicate this voxel-based robotic assembly system could reduce embodied carbon — all of the carbon emitted during the lifecycle of building materials — by as much as 82 percent, compared with popular techniques like 3D concrete printing, precast modular concrete, and steel framing. The system would also be competitive in terms of cost and construction time. However, the choice of materials used to manufacture the voxels does play a major role in their carbon footprint and cost.

While scalability, durability, long-term robustness, and important considerations like fire resistance remain to be explored before such a system could be widely deployed, the researchers say these initial results highlight the potential of this approach for automated, on-site construction.

“I’m particularly excited about how the robotic assembly of discrete lattices can enable a practical way to apply digital fabrication to the built environment in a way that can let us build much more efficiently and sustainably,” says Miana Smith, a graduate student in the Center for Bits and Atoms (CBA) at MIT and lead author the study.

She is joined on the paper by Paul Richard, a graduate student at École Polytechnique Fédérale de Lausanne in Switzerland and former visiting researcher at MIT; Alfonso Parra Rubio, a CBA graduate student; and senior author Neil Gershenfeld, an MIT professor and the director of the CBA. The research appears in Automation in Construction.

Designing better building blocks

Over the past several years, researchers in the Center for Bits and Atoms have been developing voxels, which are lattice-structured building blocks that can be assembled into objects with high strength and stiffness, like airplane wings, wind turbine blades, and space structures.

“Here, we are taking aerospace principles and applying them to buildings. Why don’t we make buildings as efficiently as we make airplanes?” Gershenfeld says, based on prior work his lab has done on voxel assembly with NASA, Airbus, and Boeing.

To explore the feasibility of voxel-based assembly strategies for buildings, the researchers first evaluated the mechanical performance and sustainability of eight existing voxel designs, including a cuboctahedron made from glass-reinforced nylon and a Kelvin lattice made from steel.

Based on those evaluations, they developed a set of three voxels using a new geometry that could be more easily assembled robotically into a larger structure. The new design, based on a high-strength and high-stiffness octet lattice, mechanically self-aligns into rigid structures.

“The interlocking nature of these voxels means we can get nice mechanical properties without needing to have a lot of connectors in the system, so the construction process can run a lot faster,” Smith says.

To accelerate construction, they designed a robotic assembly system based on inchworm-like robots that crawl across a voxel structure by anchoring and extending their bodies. These Modular Inchworm Lattice Assembler robots, or MILAbots, use grippers on each end to place voxel building blocks and engage the snap-fit connections.

“The robots can assemble the voxels by dropping them into place and then stepping on them to have the pieces interlock. We can do precise maneuvers based on the mechanical relationship between the robots and the voxels,” Smith explains.

The team studied the embodied carbon needed to fabricate their new voxel designs using three materials: plastic, plywood, and steel. Then they evaluated the throughput and cost of using the robotic assembly system to build a simple, one-story building. The researchers compared these estimates with the performance of other construction methods.

Potential environmental benefits

They found that most existing voxels, and especially those made from plastics, performed poorly compared to existing methods in terms of sustainability, but the steel and wood voxels they designed offered significant environmental benefits.

For instance, utilizing their steel voxels would generate only 36 percent of the embodied carbon required for 3D concrete printing and 52 percent of the embodied carbon of precast concrete. The plywood voxels had the lowest carbon footprint, requiring about 17 percent and 24 percent of the embodied carbon needed, respectively.

“There is still a potential viable option for a plastics-based voxel approach, we just have to be a bit more strategic about which types of plastics, infills, and geometries we use,” Smith says.

In addition, projected on-site assembly time for the steel and wood voxel approaches averaged 99 hours, whereas existing construction methods averaged 155 hours.

These speed benefits rely on the distributed nature of voxel-based assembly. While one MILAbot working alone is far slower than existing techniques, with a team of 20 robots working in parallel, the system catches up to or surpasses existing automation methods at a lower cost.

“One benefit of this method is how incremental it is. You can start building, and if it turns out you need a new room, you can just add onto the structure. It is also reversible, so if your use changes, you can dissemble the voxels and change the structure,” Gershenfeld says.

The researchers also developed an interface that enables users to input or hand-design a voxelized structure. The automatic system determines the paths the MILAbots should follow for construction and sends commands to the assemblers.

The next step in this project will be a larger testbed in Bhutan, using the “super fab lab” that CBA helped set up there to replicate the robots to test construction for a planned sustainable city, Gershenfeld says.

Additional areas of future work include studying the stability of voxel structures under lateral loads, improving the design tool to account for the physics of the system, enhancing the MILAbots, and evaluating voxels that have integrated sheeting, insulation, or electrical and plumbing routing.

“Our work helps support why doing this type of distributed robot assembly might be a practical way to bring digital fabrication into building construction,” Smith says.

This work was funded, in part, by the MIT Center for Bits and Atoms Consortia.



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Some Musk v. Altman Jurors Don’t Like Elon Musk

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Some Musk v. Altman Jurors Don’t Like Elon Musk


A jury was selected on Monday during the first day of trial for Musk v. Altman in a federal court in Oakland, California. Some of the jurors that were ultimately selected voiced concerns over Musk himself, as well as the AI technology at the core of the case, but assured the court they would put these concerns aside for the trial. The kick off also catalyzed an array of shenanigans outside the courtroom.

OpenAI CEO Sam Altman and president Greg Brockman were spotted in the security line inside the courthouse this morning, but Elon Musk was nowhere to be found. A few dozen journalists crammed into an overflow room to listen to an audio stream of the proceedings.

The goal today was to select nine jurors who could be fair and impartial in this case—an especially difficult challenge considering the main characters are some of the most high-profile tech executives in the world. Several potential jurors said they had negative opinions about Musk when questioned by Judge Yvonne Gonzalez Rogers and attorneys. But that didn’t necessarily disqualify them; only one juror was ultimately excused on the basis of their strong negative opinions regarding Musk.

“The reality is that many people don’t like him,” Gonzalez Rogers told the courtroom. She added that she believed Americans with negative feelings about Musk could still have integrity for the judicial process and decide the case fairly. The jury will help establish the core facts regarding whether Sam Altman and other defendants improperly steered OpenAI’s nonprofit venture away from its original mission, potentially violating the law in the process. But their verdict will be advisory—Gonzalez Rogers will have the final call.

The nine jurors that were ultimately selected represent quite a diverse group, including a painter, a former Lockheed Martin employee, and a psychiatrist. Some of them said they had negative opinions about artificial intelligence technology more broadly. In the end, however, all of the people selected assured the court that their outside opinions about Musk and AI shouldn’t interfere with their ability to determine the facts of the case.

OpenAI’s attorney William Savitt said at a press briefing afterward that he was satisfied with the jury the court settled on.

“Mr. Altman, Mr. Brockman, and OpenAI are looking forward to presenting their case to that jury. They’re confident in their position and are looking forward to the facts being known,” Savitt told reporters. “The hurdle we think we need to get over is just to present the truth here. We’ve got a story about what happened that is consistent with the facts, it’s consistent with the documents, and we just want the jury to see that.”

Musk is already trying to win his case in the court of public opinion. On Monday morning, the billionaire used his social media platform X to boost a recent New Yorker investigation into Altman’s alleged deceptive business conduct. The story is weeks old, and the fact that Musk promoted it on the first day of the trial is no coincidence. Earlier this morning, OpenAI’s official newsroom account published a post on X calling Musk’s lawsuit an “attempt to undermine our work to ensure that artificial general intelligence benefits all of humanity.” Meanwhile, demonstrators were outside the court protesting the AI race altogether and calling for a pause on further development.

On Tuesday, lawyers for OpenAI and Elon Musk will deliver opening statements, and the first witness in the case will be called to the stand.


This is an edition of Maxwell Zeff’s Model Behavior newsletter. Read previous newsletters here.



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This M5 MacBook Air Discount Has Renewed My Faith in Cheap Laptops for 2026

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This M5 MacBook Air Discount Has Renewed My Faith in Cheap Laptops for 2026


In a time when almost everything is getting more expensive, this deal on the M5 MacBook Air has me hopeful about how laptop pricing will play out the rest of the year. The M5 MacBook Air has dropped back down to $949, which is $150 off its retail price. It’s only been at this price one other time since the product launched in early March and has more consistently sold for $1,049. As someone who’s reviewed every available MacBook and their strongest competitors, I can unequivocally say that this MacBook Air is one of the very best laptop deals right now.

Apple

MacBook Air (M5, 2026)

Take the Surface Laptop 7th Edition, for example, which has been one of my favorite alternatives to the MacBook Air through all of 2025. It had been at competitive prices with the M4 MacBook Air all along, with both laptops sometimes dropping to as low as $799 during sales events like Prime Day throughout the year. But now, the Surface Laptop has gotten an official price hike due to the RAM shortage and is currently sitting at $1,200. It’s still a laptop I like quite a lot, but at $350 more than a similarly configured M5 MacBook Air, it’s very difficult to recommend.

Or consider the MacBook Neo, Apple’s new budget laptop that also launched in March. While it’s much cheaper overall, it’s only ever been sold for $10 off its full price. At this reduced price for the M5 MacBook Air of $949, that leaves only a dangerously small $260 gap between the Neo and the Air. It’s almost embarrassing how much better the Air is by comparison—in every way imaginable. If you’re curious how these two laptops stack up, I’ve done a comprehensive comparison between them that’s worth checking out. But to put it simply, despite all the excitement (and controversy) around the much cheaper MacBook Neo, the MacBook Air still has the most price flexibility in terms of deals.



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