Yann LeCun raises $1B to build AI that understands the physical world • Hacker News Board

Re: Yann LeCun raises $1B to build AI that understands the physical world

#271

Post by AngryData » Tue, Mar 10, 2026, 8:10 PM UTC

crystal_revenge wrote: post #203

ZeroCool2u wrote: post #32

Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…

> fully ceding the research front is not a good way to keep the EU competitive Tech is ultimately a red herring as far as what's needed to keep the EU competitive. The EU has a trillion dollar hole[0] to fill if they want to replace US military presence, and current net import over 50% of their energy. Unfortunately the current situation in Iran is not helping either of these as they constrains energy further and ris…

Hard disagree, military might isn't going to secure anybody into the future, modern society and our economies will only get more vulnerable as time goes on and large wars or engagements will just push economies closer to collapse. And without a solid modern economy to back up the military, modern military will fall apart.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#272

Post by masteranza » Tue, Mar 10, 2026, 8:11 PM UTC

A_D_E_P_T wrote: post #11

Justifiable. There are a lot more degrees of freedom in world models. LLMs are fundamentally capped because they only learn from static text -- human communications about the world -- rather than from the world itself, which is why they can remix existing ideas but find it all but impossible to produce genuinely novel discoveries or inventions. A well-funded and well-run startup building physical world models (ground…

A few years ago I've made this simple thought experiment to convince myself that LLM's won't achieve superhuman level (in the sense of being better than all human experts):

Imagine that we made an LLM out of all dolphin songs ever recorded, would such LLM ever reach human level intelligence? Obviously and intuitively the answer is NO.

Your comment actually extended this observation for me sparking hope that systems consuming natural world as input might actually avoid this trap, but then I realized that tool use & learning can in fact be all that's needed for singularity while consuming raw data streams most of the time might actually be counterproductive.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#273

Post by libraryofbabel » Tue, Mar 10, 2026, 8:11 PM UTC

sothatsit wrote: post #241

HarHarVeryFunny wrote: post #227

Earlier quoted context omitted.

I think "world models" is the wrong thing to focus on when contrasting the "animal intelligence" approach (which is what LeCun is striving for) with LLMs, especially since "world model" means different things to different people. Some people would call the internal abstractions/representations that an LLM learns during training a "world model" (of sorts). The fundamental problem with today's LLMs that will prevent th…

RL on LLMs has changed things. LLMs are not stuck in continuation predicting territory any more. Models build up this big knowledge base by predicting continuations. But then their RL stage gives rewards for completing problems successfully. This requires learning and generalisation to do well, and indeed RL marked a turning point in LLM performance. A year after RL was made to work, LLMs can now operate in agent har…

Thanks for saying this. It never ceases to amaze me how many people still talk about LLMs like it’s 2023, completely ignoring the RLVR revolution that gave us models like Opus that can one-shot huge chunks of works-first-time code for novel use cases. Modern LLMs aren’t just trained to guess the next token, they are trained to solve tasks.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#274

Post by scarmig » Tue, Mar 10, 2026, 8:12 PM UTC

Insanity wrote: post #190

jsnell wrote: post #117

Earlier quoted context omitted.

I don't think it's "regardless", your opinion on LeCun being right should be highly correlated to your opinion on whether this is good for Europe. If you think that LLMs are sufficient and RSI is imminent (<1 year), this is horrible for Europe. It is a distracting boondoggle exactly at the wrong time.

Whenever I see claims about AGI being reachable through large language models, it reminds me of the miasma theory of disease. Many respectable medical professionals were convinced this was true, and they viewed the entire world through this lens. They interpreted data in ways that aligned with a miasmatic view. Of course now we know this was delusional and it seems almost funny in retrospect. I feel the same way when…

The miasma theory of disease, though wrong, made lots of predictions that proved useful and productive. Swamps smell bad, so drain them; malaria decreases. Excrement in the street smells bad, so build sewage systems; cholera decreases. Florence Nightingale implemented sanitary improvements in hospitals inspired by miasma theory that improved outcomes.

It was empirical and, though ultimately wrong, useful. Apply as you will to theories of learning.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#275

Post by lordmathis » Tue, Mar 10, 2026, 8:12 PM UTC

HarHarVeryFunny wrote: post #179

lordmathis wrote: post #166

Earlier quoted context omitted.

It's 6 months away the same way coding is apparently "solved" now.

I think we - in last few months - are very close to, if not already at, the point where "coding" is solved. That doesn't mean that software design or software engineering is solved, but it does mean that a SOTA model like GPT 5.4 or Opus 4.6 has a good chance of being able to code up a working version of whatever you specify, with reason. What's still missing is the general reasoning ability to plan what to build or…

Sure, Claude and other SOTA LLMs do generate about 90% of my code but I feel like we are not closer to solving the last 10% than we were a year ago in the days of Claude 3.7. It can pretty reliably get 90% there and then I can either keep prompting it to get the rest done or just do it manually which is quite often faster.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#276

Post by brandonb » Tue, Mar 10, 2026, 8:13 PM UTC

mandeepj wrote: post #256

brandonb wrote: post #114

Earlier quoted context omitted.

LeCun's technical approach with AMI will likely be based on JEPA, which is also a very different approach than most US-based or Chinese AI labs are taking. If you're looking to learn about JEPA, LeCun's vision document "A Path Towards Autonomous Machine Intelligence" is long but sketches out a very comprehensive vision of AI research: https://openreview.net/pdf?id=BZ5a1r-kVsf Training JEPA models within reach, even f…

Appreciate your work! Healthcare is a regulated industry. Everything (Research, proposals, FDA submissions, Compliance docs, Accreditation Standards, etc.) is documented and follows a process, which means there's a lot of thesis. You can't sneak in anything unverified or unreliable. Why does healthcare need a JEPA\World model?

Regulation is quickly catching up to modern AI techniques; for the most part, the approach is to verify outputs rather than process. For example, Utah's pilot to let AI prescribe medications has doctors check the first N prescriptions of each medication. Medicare is starting to pay for AI-enabled care, but tying payment to objective biomarkers like cholesterol or blood pressure actually got better.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#277

Post by doruk101 » Tue, Mar 10, 2026, 8:18 PM UTC

az226 wrote: post #104

Yann LeCun seeks $5B+ valuation for world model startup AMI (Amilabs). He has hired LeBrun to the helm as CEO. AMI has also hired LeFunde as CFO and LeTune as head of post-training. They’re also considering hiring LeMune as Head of Growth and LePrune to lead inference efficiency. https://techcrunch.com/2025/12/19/yann-lecun-confirms-his-ne...

nominative determinists are running the world

Re: Yann LeCun raises $1B to build AI that understands the physical world

#278

Post by airstrike » Tue, Mar 10, 2026, 8:29 PM UTC

Oras wrote: post #217

LarsDu88 wrote: post #201

Earlier quoted context omitted.

That's such a terrible take. For a hot minute Meta had a top 3 LLM and open sourced the whole thing, even with LeCunn's reservations around the technology. At the same time Meta spat out huge breakthroughs in: - 3d model generation - Self-supervised label-free training (DINO). Remember Alexandr Wang built a multibillion dollar company just around having people in third world countries label data, so this is a huge br…

> - Self-supervised label-free training (DINO). Remember Alexandr Wang built a multibillion dollar company just around having people in third world countries label data, so this is a huge breakthrough. If it was a breakthrough, why did Meta acquire Wang and his company? I'm genuinely curious.

People make stupid acquisitions all of the time.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#279

Post by vidarh » Tue, Mar 10, 2026, 8:31 PM UTC

leptons wrote: post #263

vidarh wrote: post #198

Earlier quoted context omitted.

Cold fusion reactors haven't produced usable intermediate results. LLMs have.

LLMs produce slop far to often to say they are in any way better than cold fusion in terms of usable results. "AI" kind of is the cold fusion of tech. We've always been 5 or 10 years away from "AGI" and likely always will be.

That's just nonsense. That they produce slop does not negate that I and many others get plenty of value out of them in their current form, while we get zero value out of fusion so far - cold or otherwise.

Re: Yann LeCun raises $1B to build AI that understands the physical world

#280

Post by MITSardine » Tue, Mar 10, 2026, 8:36 PM UTC

jandrewrogers wrote: post #208

jnd-cz wrote: post #139

Earlier quoted context omitted.

The sum of human knowledge is more than enough to come up with innovative ideas and not every field is working directly with the physical world. Still I would say there's enough information in the written history to create virtual simulation of 3d world with all ohysical laws applying (to a certain degree because computation is limited). What current LLMs lack is inner motivation to create something on their own with…

> virtual simulation of 3d world Virtual simulations are not substitutable for the physical world. They are fundamentally different theory problems that have almost no overlap in applicability. You could in principle create a simulation with the same mathematical properties as the physical world but no one has ever done that. I'm not sure if we even know how. Physical world dynamics are metastable and non-linear at e…

> You could in principle create a simulation with the same mathematical properties as the physical world but no one has ever done that. I'm not sure if we even know how.

What do you mean by that? Simulating physics is a rich field, which incidentally was one of the main drivers of parallel/super computing before AI came along.