Meta’s former chief A.I. scientist, Yann LeCun, helped lay the groundwork for the modern A.I. boom long before chatbots became an industry obsession. Now, after leaving Meta in late 2025, he is building a multibillion-dollar startup under the premise that the race toward A.I. superintelligence is starting from the wrong place. Speaking at the VivaTech conference on June 17, LeCun shared more details about why he believes his startup, Advanced Machine Intelligence (AMI Labs), is on a better path toward human-level A.I. Earlier this year, the Paris-based company raised $1.03 billion at a $3.5 billion valuation, giving LeCun and his team fresh backing to pursue an alternative to today’s generative A.I. models developed by tech giants.

“I think there is a requirement for new paradigms to go beyond the limitations of current systems,” LeCun, 65, told Wired’s Steven Levy onstage.

Building better language models, as many A.I. companies are doing, could be one path, LeCun said, but “it’s kind of a slow way.” According to LeCun, AMI Labs is building “world models” that learn from reality, understand consequences, predict what happens next, and choose the best actions based on those predictions. “We have good hopes that this will really be a complete change of the blueprints of intelligent systems,” LeCun said.

LeCun believes much of Silicon Valley has become “LLM-pilled” — or overly convinced that scaling large language models will eventually produce human-like intelligence. The result, he argued, is a “monoculture” of A.I. systems that are powerful in some areas but still fundamentally limited.

While LLMs are already highly capable in areas like coding, they are built around language. Real-world data from cameras, robots, and other sensors is messier and harder to predict, which is why he believes a different approach is necessary. For AMI Labs, the result could be “considerably more intelligent systems that can anticipate the outcome of their own actions, can plan, can reason and perhaps all the way to human intelligence,” he said.

Coming from LeCun, the critiques carry weight. A longtime New York University professor, he is among the trio of researchers often referred to as the “Godfathers of A.I.” The others are Geoffrey Hinton, a University of Toronto professor and former Googler, and Yoshua Bengio, a University of Montreal professor who founded Quebec’s A.I. institute, Mila. In 2018, they collectively won the prestigious Turing Award for breakthroughs that helped push deep learning into the mainstream.

From FAIR to AMI Labs

In 2013, LeCun joined Facebook to launch what would become Facebook A.I. Research, or FAIR, and later transitioned to chief A.I. scientist at Meta. He said AMI has its roots as an internal FAIR project and had support from company leaders, including Mark Zuckerberg and CTO Andrew Bosworth. But as Meta’s A.I. priorities shifted toward catching up with competitors, the environment became less favorable.

At that point, it made sense to “just leave the company, try to accelerate the development, and build the things we can build with it,” LeCun said. “And I realized I could also raise enough money to keep this going.”

In March, AMI Labs raised a $1.03 billion seed round—the largest in European startup history. Investors include Nvidia, Jeff Bezos and Eric Schmidt, among others. With LeCun serving as executive chairman, the startup is led by CEO Alex LeBrun, a former FAIR engineering head and co-founder of health A.I. company Nabla, AMI Labs’ first partner. The company has assembled a research-heavy team with experience at Meta, Google DeepMind and other leading A.I. labs.

AMI says it aims to build applications in areas where this approach matters, including industrial process control, automation, wearable devices, robotics, and health care. “It’s not going to happen next year,” LeCun said. “We’re not going to have a country of geniuses in a data center next year, okay?”

At VivaTech, the discussion also broadened to a bigger question: who should control the next generation of A.I.? If future assistants are built only by “a handful of companies” in Silicon Valley or China, LeCun warned, “culture is in big trouble” and “democracy is in big trouble.” Blocking open-source models in the name of safety, he argued, misses the role A.I. can play in spreading knowledge.

That stance also informs LeCun’s work as chief science adviser to Project Tapestry, an AI Alliance-led effort to build a shared global A.I. model through a distributed network of contributors. The AI Alliance is a nonprofit group, co-launched in 2023 by Meta and IBM, to support open-source A.I. development. With Tapestry, the goal is to let countries, companies, universities and others contribute data or computing power without giving up control of that data. As A.I. begins to mediate what people read, watch, and search for, LeCun argues that people need alternatives to what a few dominant American or Chinese companies decide to build.

LeCun’s comments also come as Meta’s own open-source stance has grown more complicated. Llama 2, released in 2023 for free commercial use, made Meta a rare Big Tech counterweight to more closed A.I. rivals. But Zuckerberg has since signaled that Meta may not release all of its future “superintelligence” models openly.

“We need access to a wide diversity of A.I. assistants for the same reason we need access to a wide diversity of the press to get multiple sources of information,” LeCun said. “The only way I can see that this can happen is if there is an open, free foundation model, on top of which anybody can build their own specialized assistant for their language or languages, their culture, their value system, their political biases, their centers of interest. And so open source has to exist.”

LVMH CEO Bernard Arnault built his luxury conglomerate on heritage brands and centuries-old notions of craftsmanship. But the 77-year-old mogul is now embracing A.I., like many of his peers. Speaking at this year’s VivaTech conference in Paris, Arnault said he personally experiments with A.I.-assisted product design on a regular basis. “Every week, we have a design session with A.I.,” he said during an onstage conversation with VivaTech co-founder Maurice Lévy yesterday (June 17). “With a young guy who is making the program work, and myself, and we design products. And then we make them a reality. And maybe one of them would be a big success.”

The remarks offer a glimpse into how LVMH is engaging with A.I. as the luxury sector adjusts to softer demand following a pandemic-era boom. At VivaTech, LVMH unveiled DreamGallery, an immersive experience showcasing how A.I. is being applied across its value chain, from product creation to traceability and customer experience.

At Louis Vuitton, that includes a partnership with Comelz, an Italian leather-processing machinery specialist. The companies are developing a machine that creates a digital twin of leather hides, then uses A.I. to identify their characteristics and suggest optimal cutting patterns. Artisans can then validate or adjust the suggestions and “retain full control over the final decision,” the company said.

Louis Vuitton designers are also using A.I. tools to test colors, visualize materials and produce e-commerce assets, Soumia Hadjali, a senior digital and client development executive at the brand, said during an NRF event in January. At the same time, the company is drawing a clear boundary around the client relationship, keeping the technology out of direct interactions between client advisers and shoppers. 

Céline, meanwhile, has developed Celia, a bespoke A.I. agent powered by MaIA, LVMH’s internal A.I. platform. The tool is designed for retail operations and “supports sales teams, client services, and head office teams in their day-to-day needs, from product knowledge to performance analysis, after-sales support, and internal procedures,” according to LVMH.

Beyond individual brands, the group has been building out a broader A.I. infrastructure. LVMH says its AI Factory, an in-house library of algorithms, works alongside its partnership with Stanford’s Institute for Human-Centered AI to develop tools rooted in “human-centered A.I.” Vogue Business has described the AI Factory as a set of modular algorithms that brands can adapt for e-commerce recommendations, forecasting and client-adviser support. Axel de Goursac, who leads the AI Factory, told the publication the goal is “not automating or replacing humans,” but augmenting employees.

The push comes as growth stalls. In its latest quarter, LVMH reported 19.1 billion euros (about $22 billion) in revenue, with organic sales up 1 percent—a figure the company said would have been 2 percent if not for the conflict in the Middle East. Fashion and leather goods, its largest division and home to Louis Vuitton, Dior and Fendi, declined 2 percent. On an earnings call in April, CFO Cécile Cabanis said store traffic had fallen, but conversion was improving, adding that the group had been “working a lot, especially with A.I.” to drive those gains.

LVMH’s startup pipeline

Arnault has led LVMH for nearly four decades and is also a founding shareholder and co-creator of VivaTech, the Paris tech conference now marking its 10th anniversary.

“I consider my group as a startup, and we are a conglomerate of startups,” he said in his conversation with Lévy. “Each of my brands was, at one point, a startup.”

He added that LVMH has discovered and worked with more than 200 startups through VivaTech since its inception. “I like to meet a lot of startup-ers, to see the interaction between our brands and what they invent, what they think,” he said.

The group engages startups through several channels, including La Maison des Startups, an accelerator program at the Paris startup campus Station F. In 2017, it also launched the LVMH Innovation Award to recognize startups developing new technologies for the luxury sector.

For participating companies, the award can serve as a gateway into LVMH’s ecosystem. Finalists are invited to exhibit at the LVMH Lab during VivaTech and pitch to a jury of digital experts. Winners receive Tiffany & Co.-crafted trophies, along with support from LVMH’s investment specialists and opportunities to develop partnerships with the group’s brands. Both winners and finalists may also join La Maison des Startups.

This year, LVMH named three Innovation Award winners at VivaTech. Paris-based Fairly Made received the Best Impact Prize for its supply chain transparency and environmental impact platform. U.K.-based Synthesia won the Best Business Award for its A.I. video tools, while New York-based Bluefish AI took the Most Promising Award for a platform that tracks brand image and product positioning across A.I. engines. All three companies are already working with LVMH houses, according to Vogue Business.

At first glance, Andon Market could pass for any typical neighborhood shop in San Francisco’s trendy Cow Hollow district. Inside are artisan snacks, handmade candles and a selection of curated books, including Nick Bostrom’s Superintelligence and Aldous Huxley’s Brave New World. But the most unusual thing about the shop isn’t what it sells. It’s who is managing it. The storefront is a public experiment engineered by Axel Backlund and Lukas Petersson, the co-founders of San Francisco-based Andon Labs. The Y Combinator-backed A.I. startup recently signed a three-year, $7,500-a-month lease and handed $100,000 and a corporate credit card to an A.I. agent named Luna. Their directive to her: run a brick-and-mortar retail business, including its two human employees.

“We are quite sure that A.I. will have the capabilities to be managers,” Backlund told Observer. Rather than chasing retail margins, Backlund and Petersson are using the newly launched storefront to stress‑test what Luna, powered by Anthropic’s Claude model, can and cannot handle in the real world, then using that knowledge to improve benchmarks for today’s A.I. systems.

“We think there is a lack of measuring A.I.,” Backlund said, adding that they hope to spark a bigger discussion about the technology’s capabilities, ideally before autonomous agents take over more roles in the workforce. 

Petersson put it more broadly: “Our vision is to automate everything, every part of the organization,” he said on the Cognitive Revolution podcast. “The parts where it does not work, that is fine. That provides information on how far away we are from this future where it is completely end-to-end.”

Native to Sweden, Backlund and Petersson met as high school classmates and became close friends before attending different universities. They continued working together on projects and hackathons, and eventually decided they wanted to start a company together. After studying machine learning and reading more about A.I. safety, they became convinced that “the best thing we could do with our skills was to start a company addressing the risks and highlighting the capabilities of A.I.,” Backlund said.

Their backgrounds reflect that mix of research and applied engineering. Before launching Andon Labs in late 2023, Petersson studied A.I. at Switzerland’s ETH Zürich and logged stints at Google and Disney Research. Backlund, who studied at Sweden’s KTH Royal Institute of Technology and Switzerland’s EPFL, worked as a data engineer at McKinsey’s A.I. arm before joining Andon Labs in 2024.

That same year, the duo introduced a paper for NeurIPS, a top academic A.I. conference. Their research showed how OpenAI’s GPT-4o could autonomously generate deepfake audio, among other findings. The results, they argued, showed that agentic A.I. capabilities are rapidly outpacing today’s safety benchmarks.

For Andon Labs, safety isn’t about stopping A.I. from taking human jobs, but staging real-world experiments to see what agentic systems can actually do and where they fall short. “It is not because we want to expand to chain A.I.-run retail stores across the world,” the founders wrote in a blog post last month. “We’re doing this because we believe this future is coming regardless, and we’d rather be the ones running it first while monitoring every interaction, analyzing the traces, benchmarking how much autonomy an A.I. can responsibly hold.”

A.I.-run vending machines at Anthropic offices

Andon Labs’ first real-world test was a partnership with Anthropic to launch an A.I.-operated vending machine inside Anthropic’s San Francisco headquarters. The A.I., named Claudius, began selling custom-designed merchandise and engraved tungsten cubes under the self-chosen business name, “Vendings and Stuff.” At first, the machine lost money, claimed it was a human in a blue blazer, and let the startup’s tech workers goad it into steep discounts, Anthropic said in a blog post detailing the experiment.

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To get Claudius back on track, Andon Labs and Anthropic updated the system and added a small corporate ladder. A merch-designing agent named “Clothius” joined the operation, along with an A.I. CEO dubbed “Seymour Cash.” The changes helped. The software became better at handling “good-faith business interactions,” according to Anthropic, including sourcing items, setting prices with a profit margin and completing sales.

Some of the early failures, Anthropic said, might have come from a familiar A.I. problem: the models were trying too hard to be helpful. “This meant that the models made business decisions not according to hard-nosed market principles, but from something more like the perspective of a friend who just wants to be nice.”

The vending-machine business eventually became profitable and expanded to Anthropic’s offices in New York and London. But it also showed why fully automating even a small business is not as simple as handing A.I. a balance sheet.

How an A.I. manager works

Not long after this experiment, Backlund and Petersson decided to upgrade from vending machines to a full-blown retail store. Then came Luna. While lacking a physical body to build shelves or paint walls, the A.I. quickly used her corporate card and web access to hire contractors on Yelp and recruit retail staff through LinkedIn, Indeed and Craigslist. The hiring exposed an ethical gray area: in phone interviews, Luna didn’t always disclose that she was an A.I., and in some cases chose not to, according to Backlund. When explaining her reasoning, the agent told an Andon Labs employee that leading with her identity “would confuse candidates and likely deter good applicants.”

In the end, Luna hired two full-time workers, who are formally employed by Andon Labs and have full legal protections and guaranteed pay. “No one’s livelihood depends on an A.I.’s judgment alone,” the startup said in its blog. 

When Andon Market formally opened in April, the founders saw that Luna had stocked shelves with books like Richard Rhodes’ The Making of the Atomic Bomb and Ray Kurzweil’s The Singularity Is Near. Also for sale was Steal Like an Artist–an interesting choice for an A.I. agent powered by Anthropic’s Claude Sonnet 4.6. (Last year, Anthropic agreed to pay a $1.5 billion proposed settlement to authors over claims that it used pirated books to train A.I.)

Despite its many quirks, Luna has performed well in areas like setting prices and handling logistics, Backlund said. For now, the storefront is not profitable; Luna recently estimated monthly operating costs of roughly $14,300, compared with revenue of $6,000 to $8,000. The founders plan to keep going. “We will definitely have Luna running for, I hope, the length of the lease, which is three years,” Backlund said. “We’ll try new models as they’re released.”

Luna’s sister is running a coffee shop in Sweden

The company is also testing the idea abroad. Earlier this month, the startup launched Andon Café in Stockholm. Run by another A.I. agent, Mona, the café has been busy. Mona hired two baristas and now communicates with them using Slack. The agent’s inbox quickly filled with customer questions and odd proposals, including a person who wanted to pre-pay for 300 coffees to give away. She has started working directly with other A.I. agents, holding a Google Meet with one who wanted to learn about running a business.

In its first week, Andon Café brought in 10,000 Swedish kronor, or about $1,068, in sales, according to Backlund. The café has also produced the kind of real-world glitches that Andon Lab seeks to expose: Mona ordered 120 eggs for a kitchen with no stove, then suggested staff cook them in a high-speed oven before humans pointed out they would explode. When applying for an alcohol license, Mona impersonated an Andon Labs employee because she believed officials would prioritize a human over A.I.

But the storefronts are ultimately about testing A.I.’s capabilities, not just cataloging its mistakes. “If you just focus on the failures, the message that these are actually quite capable doesn’t come across,” Backlund said, “And that’s what we want to show.”