Yann LeCun(@ylecun)

Toutes les formes d'IA sont de "belles saloperies" ? Vraiment ? Même celles qui dépistent les tume...

Yann LeCun (@ylecun) — Thu, 08 Oct 2026 10:43:07 GMT

Toutes les formes d'IA sont de "belles saloperies" ? 
Vraiment ?

Même celles qui dépistent les tumeurs dans les mammographies ? 
Même celles qui détectent et évitent les obstacles sur la route et sauvent des vies en réduisant les collisions de 40% ?
Même celles qui aident à filtrer les spams et les tentatives d'escroquerie par email, messages, ou réseaux sociaux ? 
Même celles qui détectent et bloquent les tentatives d'influence étrangères sur le processus démocratique ? 
Même celles qui permettent aux non-voyant d'entendre une description de leur environnement visuel ?
Même celles qui connectent les cultures par la traduction automatique des langues ?
Même celles qui assistent dans leurs métiers les médecins, les chercheurs, les journalistes ? 

Il faut toujours éviter de jeter le bébé avec l'eau du bain.

💬16🔄46❤️264👀13324📊44

⚡ Powered by xgo.ing

Au contraire. C'est une nouvelle ère qui s'ouvre pour les mathématiques. Une ère où la démonstratio...

Yann LeCun (@ylecun) — Thu, 08 Oct 2026 08:53:31 GMT

Au contraire. 
C'est une nouvelle ère qui s'ouvre pour les mathématiques.
Une ère où la démonstration formelle est largement automatisée et où l'accent sera reporté sur le développement de nouveaux concepts, nouvelles abstractions, nouvelles définitions, et nouvelles conjectures.

L'invention du bateau a réduit l'importance de la nage, mais a permis la découverte de nouvelles terres.

💬57🔄202❤️1450👀38009📊216

⚡ Powered by xgo.ing

That's a commonly ignored fact. It's not like Leonardo da Vinci invented the helicopter, or even P...

Yann LeCun (@ylecun) — Wed, 07 Oct 2026 11:40:28 GMT

That's a commonly ignored fact. 

It's not like Leonardo da Vinci invented the helicopter, or even Paul Cornu who built one that took off in 1907. 

But Louis Bréguet invented the swashplate, and Henrich Focke flew a controllable helicopter with contra-rotating rotors, all before Igor Sikorsky came up with the variable-pitch tail rotor and made the whole thing practical in 1939.

Getting the basic idea is the easy part. 
Building it is harder. 
Making it work is even harder.

💬23🔄40❤️463👀53406📊71

⚡ Powered by xgo.ing

The 1991 version is an obscure tech report with a vague idea, no theory, no experiment to speak of, ...

Yann LeCun (@ylecun) — Wed, 07 Oct 2026 11:25:42 GMT

The 1991 version is an obscure tech report with a vague idea, no theory, no experiment to speak of, and certainly no code, that the author never revisited or pushed. 
It has one hand-drawn architecture diagram, one formula of the type f(x)=0, and a claim that every other technique is a special case if you instantiate f and x properly.

💬10🔄5❤️234👀67480📊33

⚡ Powered by xgo.ing

@abuchanlife - training frontier models is expensive - distilling a frontier model is cheap - this m...

Yann LeCun (@ylecun) — Sun, 04 Oct 2026 16:29:01 GMT

@abuchanlife - training frontier models is expensive
- distilling a frontier model is cheap
- this market force alone tells us that frontier foundation models will be free/open.
- there are others.
thealliance.ai/projects/tapes…

💬39🔄57❤️650👀69230📊130

⚡ Powered by xgo.ing

I feel like the progress of AI is actually making systems neuroscience more exciting. It's not lik...

Yann LeCun (@ylecun) — Sun, 04 Oct 2026 12:40:57 GMT

I feel like the progress of AI is actually making systems neuroscience more exciting. 

It's not like current AI has a particularly good angle on physical intuition, common sense, world models, planning/reasoning, motivations/drives, emotions, etc. 

We may now have the tools to implement and test cognitive architectures.

💬34🔄28❤️288👀20868📊62

⚡ Powered by xgo.ing

That video is 2 years old. Two years later, we are still far from human-level AI. Sure, AI has supe...

Yann LeCun (@ylecun) — Sat, 03 Oct 2026 04:19:39 GMT

That video is 2 years old.
Two years later, we are still far from human-level AI.

Sure, AI has superhuman performance in a number of tasks (particularly in mathematics and coding and answering questions with known answers).

But where is my Level-5 self-driving car?
(Before you ask, Tesla FSD is rated Level 2, Waymo is Level 4).

Where is the self-driving car that can teach itself to drive in 20 hours of practice like any 17 year old?
(Before you ask, we have billions of hours of training data and still can't successfully train a self-driving system by imitation learning)

Where is my domestic robot?
Where is the robot that can do what any 8 year-old child can do?
Where is the robot that can learn a new task as quickly as an 8 year old?

AI still has a hard time with the complexity and messiness of the physical world.

💬177🔄107❤️1205👀117086📊271

⚡ Powered by xgo.ing

@ziv_ravid @chrmanning Sooo where is my domestic robot? Where is my L5 self-driving car? I can fi...

Yann LeCun (@ylecun) — Fri, 02 Oct 2026 02:38:07 GMT

@ziv_ravid@chrmanning Sooo where is my domestic robot? 
Where is my L5 self-driving car? 

I can fine-tune an LLM to answer any question about the physical world. 
But that doesn't mean it has enough understanding and physical intuition to predict what a 6 year-old can predict.

💬100🔄22❤️485👀35250📊117

⚡ Powered by xgo.ing

Question for everyone : Are you pro-intelligence or anti-intelligence ? Do you think more intellige...

Yann LeCun (@ylecun) — Thu, 01 Oct 2026 13:40:26 GMT

Question for everyone :
Are you pro-intelligence or anti-intelligence ? 
Do you think more intelligence in the world is intrinsically good ? 
Or do you think more intelligence is intrinsically dangerous ? 

AI amplifies human intelligence.
It makes PEOPLE smarter and more effective.
It's like search engines, libraries, education, literacy, language: it makes PEOPLE smarter and more empowered. 

If you want intelligence (artificial or natural) to be under control of a few companies or governments, you are a neo-obscurantist or a neo-feudalist.

💬295🔄241❤️1406👀106918📊404

⚡ Powered by xgo.ing

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Wher...

Yann LeCun (@ylecun) — Fri, 25 Sep 2026 17:55:34 GMT

Nope. It's still true. 
Where is your domestic robot? 
Where is your Level-5 self-driving car? 
Where is your robot car that can learn to drive in a few hours of practice like any 17 year old?
Where is your AI system that can understand the real world and quickly learn new skills like a house cat?

There is no question that AI will eventually become as intelligent as humans in all domains. 
*** BUT ***
1. We're still far from that, even if AI and computer technology surpasses humans in an ever-increasing number of tasks.
2. It won't be based on LLMs, although LLMs will have a role to play (e.g. as a text interface).

💬232🔄237❤️3036👀244915📊519

⚡ Powered by xgo.ing

Remember October 2022 when you doused Galactica with vitriol? Galactica was a 120b-parameter LLM-b...

Yann LeCun (@ylecun) — Fri, 25 Sep 2026 17:11:10 GMT

Remember October 2022 when you doused Galactica with vitriol? 

Galactica was a 120b-parameter LLM-based system from Meta-FAIR designed to help scientist write papers. 
It was open sourced (link below).

A mob of haters, including Michael, claimed it was dangerous and toxic and was going to destroy Science.

The small team at FAIR couldn't sleep at night and took down the demo website (they kept the GitHub and paper up).

Then, only 3 weeks later, ChatGPT was released and was welcomed as the second coming of the Messiah🤔
The vitriol dousers were silent.
technologyreview.com/2022/11/18/106…k
github.com/paperswithcode…L

💬23🔄32❤️320👀50787📊57

⚡ Powered by xgo.ing

@Plinz 😂 Don't worry, we got your Bach.

Yann LeCun (@ylecun) — Thu, 24 Sep 2026 02:15:29 GMT

@Plinz 😂
Don't worry, we got your Bach.

💬9🔄2❤️186👀24169📊21

⚡ Powered by xgo.ing

I have absolutely never ever "asked" to stop R&D on LLMs. In fact, I was very supportive of LLM eff...

Yann LeCun (@ylecun) — Mon, 21 Sep 2026 11:11:50 GMT

I have absolutely never ever "asked" to stop R&D on LLMs.

In fact, I was very supportive of LLM efforts at Meta. Just look up my public advocacy for Galactica (November 2022), and the open sourcing of OPT-175B (May 2022), and of the Llama herd (mid 2023).
I was actually influential in convincing the Meta leadership to start an AI-first product division built around Llama in January 2023.

I've always said that LLMs were impressive, useful, and had amazing potential.
I've also always said they were an off-ramp on the path towards human-level AI.

Stop making me say things I didn't say or claim that I somehow hindered LLM R&D at Meta.
That's BS.

💬54🔄43❤️792👀78927📊118

⚡ Powered by xgo.ing

I said "auto-regressive LLMs, in and of themselves, will not lead human-level AI" That statement is...

Yann LeCun (@ylecun) — Sun, 20 Sep 2026 14:07:17 GMT

I said "auto-regressive LLMs, in and of themselves, will not lead human-level AI" 
That statement is still totally true.

First, the reasoning abilities of current AI systems are based non-auto-regressive search (which is what I have always advocated for). But AFAICT, they do it in token space, which is limited and inefficient. I have claimed that human-like reasoning must be a search in continuous representation space. It looks like the industry is moving towards that.

Second, the self-improvement methods, as currently practiced, only work for domains where the quality of outputs can be scored without human intervention, such as mathematics, code, and scenarios that can be simulated accurately. Not anything else. Humans and animals learn new skills way more efficiently than current RL methods.

Third, the multimodal capabilities of current AI assistants generally use separately-trained encoders (that are not LLMs). This is also what I've been advocating. Except that I think the best way to do this is with JEPA trained with self-supervised learning. The research community is clearly moving towards that (3000 papers on JEPA in just 4 years).

Fourth, if LLMs were a path to human-level AI, we would have domestic robots and Level-4 or Level-5 self-driving cars for consumers by now. And we don't. We certainly don't have cars that can learn to drive in 20 hours or practice like any teenager. We're still missing something pretty huge to claim human-level intelligence (let alone superhuman).

Sure, we now have computer systems that are impressive, very useful, and whose performance is superhuman in an increasing number of domains (coding being one of them). 
But that's true of the entire history of progress in computer technology. 

Lastly, there is a basic confusion about what intelligence actually is.
It is not the mere accumulation and regurgitation of existing declarative knowledge (which is essentially what LLMs do).
As Jean Piaget famously said, "intelligence is not what you know, it is what you do when you don't know." 
It is your ability to solve new problem without any prior training, to act in previously-unknown scenarios, and to adapt very quickly to new situations with minimal training.

We're still far from that.

💬199🔄558❤️3583👀630071📊811

⚡ Powered by xgo.ing

@dylanbowmanSF Slide deck here: https://t.co/36v5ASQJZv

Yann LeCun (@ylecun) — Thu, 17 Sep 2026 15:09:35 GMT

@dylanbowmanSF Slide deck here:
drive.google.com/file/d/1sD5Vov…

💬12🔄34❤️230👀23388📊63

⚡ Powered by xgo.ing

Progress in airplane design have made them safer and safer. Airplanes would have been safer earlier ...

Yann LeCun (@ylecun) — Wed, 16 Sep 2026 08:47:59 GMT

Progress in airplane design have made them safer and safer.
Airplanes would have been safer earlier with *accelerated* progress.
Turbofan engines have become so reliable that long-haul airplanes can now have only two of them.
 
The same is true for AI: better AI is safer AI.
"Pacing", whatever one means by that, is counterproductive.

💬121🔄243❤️1900👀91752📊303

⚡ Powered by xgo.ing

@nxthompson More like a genuinely nonsensical anthropomorphization.

Yann LeCun (@ylecun) — Wed, 16 Sep 2026 08:28:39 GMT

@nxthompson More like a genuinely nonsensical anthropomorphization.

💬28🔄32❤️815👀32120📊91

⚡ Powered by xgo.ing

Being better than humans at searching and writing down the formal proof of a theorem does not equate...

Yann LeCun (@ylecun) — Wed, 16 Sep 2026 08:23:18 GMT

Being better than humans at searching and writing down the formal proof of a theorem does not equate being "beyond human level at math".

This is not all of math, any more than arithmetics, or computing integrals (symbolically or numerically) is all of math. It's one "mechanical" task in the whole activity that happens to be automatable.

Mathematicians invent new concepts, new frameworks, new abstractions, new definitions, and formulate conjectures. 
This requires intuition and creativity that current AI systems do not have (yet).

💬81🔄111❤️932👀66575📊173

⚡ Powered by xgo.ing

But there is a 1 hour talk, with results and evidence, that leads to these conclusions. Also, I am ...

Yann LeCun (@ylecun) — Tue, 15 Sep 2026 10:25:30 GMT

But there is a 1 hour talk, with results and evidence, that leads to these conclusions.

Also, I am not saying that LLM-based AI tools are useless. They are very useful.
We all use them.

But, by themselves, they are not a path to human-level AI. 
Architectures that understand the real world are not LLMs. 
The architectural components that enable current LLM-based AI systems to interpret images, videos, and other real-world signals are not LLMs.

💬95🔄75❤️1046👀63403📊181

⚡ Powered by xgo.ing

@DeryaTR_ Thank you for injecting us with a dose of realism vaccine against the AI doom virus.

Yann LeCun (@ylecun) — Tue, 15 Sep 2026 09:53:11 GMT

@DeryaTR_ Thank you for injecting us with a dose of realism vaccine against the AI doom virus.

💬38🔄107❤️2401👀254327📊280

⚡ Powered by xgo.ing

Nice! This ends up being a version of what some of us have called "target prop": every layer's input...

Yann LeCun (@ylecun) — Tue, 15 Sep 2026 09:40:28 GMT

Nice! This ends up being a version of what some of us have called "target prop": every layer's input is a free latent variable that serves as a target for the previous layer.
As this paper points out, this can be derived from an "augmented Lagrangian"  formulation of backprop in which the constraints (input of layer k+1 = output of layer k) are turned into penalties (divergence between input of layer k+1 and output of layer k).

I've always hoped more people would pick up on this idea. I'm happy this is happening!
I must say though that target prop, in the end, optimizes the same criterion as backprop and does the same thing as backprop while evaluating the gradient in a different way, perhaps more biologically plausible.

My lab did some work on this idea in the context of "sparse auto-encoders" in the late 2000s.  It turns out when the code in an auto-encoder is regularized (e.g. with L1 to make it sparse) target prop seems more efficient than backprop. 
scholar.google.com/citations?view…

💬19🔄50❤️570👀44213📊113

⚡ Powered by xgo.ing

@Ryanotious @PessimistsArc Self importance fueled by a misplaced superiority complex.

Yann LeCun (@ylecun) — Mon, 14 Sep 2026 15:11:08 GMT

@Ryanotious@PessimistsArc Self importance fueled by a misplaced superiority complex.

💬4🔄4❤️45👀28094📊8

⚡ Powered by xgo.ing

@ericxing AI folks who live in the discrete world of bits and tokens don't always understand how inc...

Yann LeCun (@ylecun) — Mon, 14 Sep 2026 13:53:08 GMT

@ericxing AI folks who live in the discrete world of bits and tokens don't always understand how incredibly messy the real world is.

💬47🔄82❤️893👀36227📊126

⚡ Powered by xgo.ing

They can't. The LLMs that underly modern AI systems are auto-regressive, but modern AI systems are n...

Yann LeCun (@ylecun) — Mon, 14 Sep 2026 13:28:49 GMT

They can't.
The LLMs that underly modern AI systems are auto-regressive, but modern AI systems are not.
The "reasoning" systems produce lots of token sequences and pick the best one.
That's a form of non-auto-regressive search. What current AI systems do wrong is that they do this search in discrete token space.
I've been advocating for inference-by-search for planning/reasoning for many years (before chatGPT).
But I think it should be done in abstract representation space.
Much of human reasoning/planning is completely unconnected with language.

I was correct. You just did not understand my argument.

💬12🔄1❤️253👀13536📊36

⚡ Powered by xgo.ing

@raphaelmilliere Sure, but when it turns out the leak was caused by the plumber who neglected to tig...

Yann LeCun (@ylecun) — Mon, 14 Sep 2026 12:20:41 GMT

@raphaelmilliere Sure, but when it turns out the leak was caused by the plumber who neglected to tighten a pipe fitting, or perhaps poked a hole in one of the pipes, you shouldn't question the entire plumbing industry. You should question the plumber's compétence and/or motivations.

💬82🔄227❤️1858👀91068📊266

⚡ Powered by xgo.ing

@PessimistsArc Right. Dario was already claiming that GPT2 was too dangerous to open source back in ...

Yann LeCun (@ylecun) — Sun, 13 Sep 2026 21:25:56 GMT

@PessimistsArc Right. Dario was already claiming that GPT2 was too dangerous to open source back in 2019.
I made fun of them then. 
Everyone should make fun of them now.

💬395🔄3191❤️26008👀1986206📊3228

⚡ Powered by xgo.ing

@kchonyc Exactly. The "escapes" were made possible either through egregious negligence or delibera...

Yann LeCun (@ylecun) — Sun, 13 Sep 2026 10:46:02 GMT

@kchonyc Exactly. 
The "escapes"  were made possible either through egregious negligence or deliberate purpose (marketing? Misplaced hopes of regulatory capture?).

💬158🔄539❤️4050👀489211📊599

⚡ Powered by xgo.ing

@ilyasut To prevent models from going rouge, just make the neoclouds go green. Or threaten to blackl...

Yann LeCun (@ylecun) — Tue, 01 Sep 2026 23:25:45 GMT

@ilyasut To prevent models from going rouge, just make the neoclouds go green.
Or threaten to blacklist them with a yellow card or a pink slip.

Preventing them to go rogue is another story, probably involving guardrails.

💬36🔄17❤️622👀59649📊83

⚡ Powered by xgo.ing

I would try to figure out why LLMs can write my essays but not clean my bedroom. Then I would study ...

Yann LeCun (@ylecun) — Sun, 23 Aug 2026 18:40:49 GMT

I would try to figure out why LLMs can write my essays but not clean my bedroom.
Then I would study topics in college and grad school that could help solve that problem.
I'll figure out a set of methods and architectures beyond LLMs that can quickly learn to perform physical tasks as efficiently as humans and animals.
That last item is also what I would if I were 30, 40, 50, or 66 years old 😉

💬138🔄291❤️4727👀260131📊717

⚡ Powered by xgo.ing

@firesidealpha Sudden Clarity Sam realizing that real-world dynamics equations have inertia and fric...

Yann LeCun (@ylecun) — Sun, 23 Aug 2026 18:16:54 GMT

@firesidealpha Sudden Clarity Sam realizing that real-world dynamics equations have inertia and friction terms.
(Particularly when they concern large systems like human societies).

If only the singularitarians, AI doomers, AGI-is-near crowd, and other SV cultists could realize that....

💬59🔄90❤️1403👀138697📊194

⚡ Powered by xgo.ing

@JitendraMalikCV Exactly. We also should not confuse world models, as per your definition, with vide...

Yann LeCun (@ylecun) — Sun, 23 Aug 2026 17:56:33 GMT

@JitendraMalikCV Exactly.
We also should not confuse world models, as per your definition, with video prediction or video generation models.
Understanding the dynamics of a system in order to control it is not the same as producing cute videos.

💬17🔄12❤️226👀29493📊37

⚡ Powered by xgo.ing

@ziv_ravid No

Yann LeCun (@ylecun) — Fri, 21 Aug 2026 16:14:14 GMT

@ziv_ravid No

💬9🔄7❤️214👀22162📊24

⚡ Powered by xgo.ing

Only in America. Tired of winning?

Yann LeCun (@ylecun) — Sun, 16 Aug 2026 09:42:31 GMT

Only in America. 
Tired of winning?

Reginald@ginald87

Giving birth in Europe vs in America 😂

Your browser does not support the video tag.

🔗 View on Twitter

🔗 View Quoted Tweet

💬85🔄36❤️757👀215603📊117

⚡ Powered by xgo.ing

For about 10 years now, I have argued that the only way forward is for AI technology to be widely ...

Yann LeCun (@ylecun) — Sun, 16 Aug 2026 06:47:23 GMT

For about 10 years now, I have argued that the *only* way forward is for AI technology to be widely available, shared, and open.
Like the printing press and the Internet, AI amplifies human intelligence and efficiency by improving access to knowledge.
To empower individuals, societies require a high diversity of AI systems with different value systems, linguistic abilities, philosophical/political biases, and specific expertise. 
We need diverse AIs for same reason we need a diverse press.

Given the cost and complexity, this can only be achieved through open foundation models on top of which anyone can build systems with their languages, biases, expertise, and value systems.

I have been more vocal about this over the last 4 years, since AI popped into the public discourse.
I have made the argument in various forums: corporate C-suites, AI safety discussion groups, professional meeting, the US Senate, the UN Security Council, and the public sphere through media interviews, podcasts and social media posts.

I totally agree with @finkd  Mark Zuckerberg's recent piece in which he writes: "the notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity if sufficiently enlightened has not led to safe or positive outcomes.”

When @DarioAmodei writes: “some may object that we can simply keep AIs in check with a balance of power between many AI systems, as we do with humans", he is talking about me, among (thankfully) many others. It is the only good path forward.

There will be nefarious uses of AI, as there have been with every technology ever invented. 
But it will be your Bad AI against my Good AI.

💬117🔄262❤️1801👀195752📊331

⚡ Powered by xgo.ing

When you work on research (particularly on long-term research), you have to accept the fact that cor...

Yann LeCun (@ylecun) — Sat, 08 Aug 2026 10:52:44 GMT

When you work on research (particularly on long-term research), you have to accept the fact that corporate management, who is often interested in short-term impact, may think you are wasting your time and company resources. 
But it very much depends what you objectives and your horizon is.

- If your goal is keeping up with the current AI product race, then you might think that long-term bets are a waste.
- If your goal is "AGI" (whatever you mean by that) then your horizon is likely longer and your modus operandi is very different.
- However, If you think "AGI is just around the corner through LLM scaling", then you might think working on world models and other new AI concepts is a waste.
- But if you know that AGI requires a few more conceptual advances (as Demis and I do), you pick a role that maximizes progress towards that goal. That role is necessarily less connected with products, less connected with management, and more connected with research.
- I can't speak for Demis, but in my case, I've always been supportive of high-quality work on LLMs and impressed by the results. My personal interest was to advance towards human-level AI, and I never thought LLMs were the ticket. But I always thought LLMs were incredibly useful as a technology, and eventually as the centerpieces of a family of products.

As a high-level IC (not a manager), I would not have had the influence or power to stifle work on LLM even if I had wanted to (which I had not).

💬16🔄30❤️576👀39773📊74

⚡ Powered by xgo.ing

Launching something new with Shaun Johnson and Oriol Vinyals: A deeply technical VC firm focused on ...

Yann LeCun (@ylecun) — Wed, 05 Aug 2026 11:41:25 GMT

Launching something new with Shaun Johnson and Oriol Vinyals: A deeply technical VC firm focused on early stage AI startups.

My main gigs are still with AMI - Advanced Machine Intelligence and the NYU Courant Institute School of Mathematics, Computing, and Data Science.

But 224 Ventures connects us deeply with the AI startup scene through our network of founders and amazing LPs.

💬17🔄26❤️562👀90338📊80

⚡ Powered by xgo.ing

@gabriberton You obviously did not understand my statement. I was talking about auto-regressive tok...

Yann LeCun (@ylecun) — Mon, 03 Aug 2026 19:37:48 GMT

@gabriberton You obviously did not understand my statement.

I was talking about auto-regressive token prediction, which is what pure LLMs do.

But good code generation systems aren't pure LLMs and aren't doing mere auto-regressive token prediction.

💬105🔄22❤️649👀297389📊174

⚡ Powered by xgo.ing

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Obje...

Yann LeCun (@ylecun) — Mon, 03 Aug 2026 07:38:45 GMT

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI).

When the variables to be inferred are continuous, it makes sense to use gradient-based optimization.

A good instance of ODAI is world model-based systems that use gradient-based optimization for planning.

💬29🔄37❤️488👀52515📊101

⚡ Powered by xgo.ing

Mathematics and computing have had a very tight relationship in some corners of academia. Richard C...

Yann LeCun (@ylecun) — Mon, 03 Aug 2026 07:25:54 GMT

Mathematics and computing have had a very tight relationship in some corners of academia.

Richard Courant proposed methods to solve PDEs numerically in 1928.
Von Neuman figured out you could use electronic computers for it in 1940.
Both were mathematicians.

These methods are the ancestors of finite element methods, for which NYU's Courant Institute is famous.
The Courant Institute was created in 1935 as NYU's mathematics department. 
It was unusual in that there was a lot of work on numerical analysis and scientific computing, with heavy use of supercomputers.
In 1952, the Atomic Energy Commission installed a powerful electronic computer at NYU, which led to the creation of the Courant Mathematics and Computing Laboratory.
The computer science department was spun off from mathematics in 1969 by Jacob T Schwartz.
Courant is now a school with three departments: mathematics, computer science, and data science.
The continued existence of an HPC center at NYU is one factor that enabled AI research to take off.

💬26🔄42❤️560👀74302📊91

⚡ Powered by xgo.ing

Tired of not winning

Yann LeCun (@ylecun) — Fri, 31 Jul 2026 20:35:45 GMT

Tired of not winning

Republicans against Trump@RpsAgainstTrump

Donald Trump “erupted” during a meeting with his top national security team last week, reportedly yelling expletives at those present, according to NBC News.

The report says Trump is “exasperated” by the lack of progress in ending the Iran war and the lack of a clear strategy.

One Trump ally said, “The president is exasperated. I don’t think he believed it was going to be this difficult to get the Iranians to agree to a deal.”

🔗 View Quoted Tweet

💬42🔄22❤️592👀165576📊64

⚡ Powered by xgo.ing

The amount of basic research done in industry is nowhere near the amount done in universities. At v...

Yann LeCun (@ylecun) — Thu, 30 Jul 2026 12:07:40 GMT

The amount of basic research done in industry is nowhere near the amount done in universities. 
At various times, there have been industry labs that had fundamental research activities and have made important scientific contributions. 
Examples in information technology include Bell Labs, IBM Research, Xerox PARC, GE, Phillips, NEC, and several other. That disappeared in the 1990s.
Microsoft Research picked up the torch in the 2000s, followed (to some extent) by Google and then Meta (for about a decade until recently).
But their innovations almost always built on top of academic work, and certainly profited from the whole research ecosystem.

💬23🔄153❤️1477👀127696📊188

⚡ Powered by xgo.ing

Tired of winning

Yann LeCun (@ylecun) — Fri, 24 Jul 2026 09:37:29 GMT

Tired of winning

Steve Rattner@SteveRattner

Oil is back above $100, and gas is above $4. 

These numbers are brutal for inflation and Americans' pocketbooks. 

And there is no end in sight for their fundamental cause: Trump's war of choice in Iran.

🔗 View Quoted Tweet

💬64🔄40❤️1027👀136568📊107

⚡ Powered by xgo.ing

@AndrewCurran_ 🤬😡

Yann LeCun (@ylecun) — Mon, 20 Jul 2026 15:34:24 GMT

@AndrewCurran_ 🤬😡

💬25🔄32❤️621👀38059📊71

⚡ Powered by xgo.ing

@hosseeb @deanwball Soooo, releasing Linux was dumping? Apache, MySQL, PHP? HTTP, TCP/IP, OpenSSL,...

Yann LeCun (@ylecun) — Sun, 19 Jul 2026 11:22:22 GMT

@hosseeb@deanwball Soooo, releasing Linux was dumping? 
Apache, MySQL, PHP? 
HTTP, TCP/IP, OpenSSL, OpenSSH? 
Libjpeg, VLC?
The open source software stack of the mobile communication network?
Signal?
PyTorch?
Llama?

💬114🔄248❤️3677👀331109📊463

⚡ Powered by xgo.ing

@deanwball The "ungovernability" (and openness) of Linux and the Internet is precisely what has made...

Yann LeCun (@ylecun) — Sat, 18 Jul 2026 00:05:08 GMT

@deanwball The "ungovernability" (and openness) of Linux and the Internet is precisely what has made their success. 
The same will be true of open weight AI foundation models.

💬81🔄410❤️3365👀181142📊422

⚡ Powered by xgo.ing

@deanwball @natolambert I have not said anything like that. I have said that governments around the...

Yann LeCun (@ylecun) — Sat, 18 Jul 2026 00:03:22 GMT

@deanwball@natolambert I have not said anything like that. 
I have said that governments around the world REQUIRE AI sovereignty, not that they will have "their own models as digital public infrastructure" 
But open weight foundation models will INEVITABLY be the dominant form of AI.

💬4🔄6❤️105👀3764📊13

⚡ Powered by xgo.ing

Not a critique of the paper, but isn't inductive bias/ regularization the reason for every form of...

Yann LeCun (@ylecun) — Thu, 16 Jul 2026 14:16:30 GMT

Not a critique of the paper, but isn't inductive bias/ regularization the reason for *every* form of generalization?
Neural nets have a number of inductive biases due to the architecture as well as explicit or implicit regularizations.
The mere fact that weight magnitudes are limited (e.g. through regularization) makes the input-output function Lipschitz, which is the property you want to produce a smooth score function.

💬19🔄14❤️398👀58751📊70

⚡ Powered by xgo.ing

Tired of winning

Yann LeCun (@ylecun) — Fri, 10 Jul 2026 13:34:18 GMT

Tired of winning

Bill Madden@maddenifico

Trump's Beef Catastrophe: Incompetence, Blithering Idiocy, and Blatant Lies Have Obliterated America's Beef Industry

In yet another humiliating display of incompetence, the authoritarian Trump regime has turned America's once-mighty beef industry into a national punchline. After months of touting "record" export numbers as proof that his chaotic trade policies were somehow working, the U.S. Department of Agriculture has been forced to admit it inflated beef export sales by a staggering 90 percent.

According to a bombshell Reuters report, the USDA bragged in early July that U.S. exporters had sold more than 126,000 metric tons of beef to foreign buyers for a sales period ending in late June. The actual number? Just 12,000 metric tons. That's not a rounding error. That's a catastrophic fabrication that would embarrass a high-school bookkeeper.

The fake numbers were so absurd they should have raised red flags immediately. The USDA claimed record sales of more than 38,000 metric tons to Chile and over 32,000 metric tons to Italy — countries that aren’t even major markets for American beef. Reality? A pathetic 367 tons to Chile and 350 tons to Italy. Fourteen other countries saw their numbers slashed as well.

This isn't just bureaucratic sloppiness. This is the Trump regime's signature brand of hype, lies, spin, and propaganda colliding with economic reality — and the American cattle industry is paying the price.

U.S. beef prices have hit record highs this year thanks to tight cattle supplies and strong domestic demand. Exports have been declining since 2022. Higher prices have priced American beef out of the global market, as commodity analyst Austin Schroeder bluntly told Reuters: "We're priced out of the world market to a certain extent. It wouldn't make a lot of sense for that big of an export number."

Meanwhile, domestic supplies are so low the U.S. has had to ramp up beef imports. Earlier this year, a screwworm outbreak forced Texas to declare a state of disaster, further hammering producers already squeezed by Trump-era chaos.

Instead of acknowledging the mess his administration created — from trade wars that disrupted markets to regulatory neglect that left ranchers vulnerable — Trump and his sycophants simply let the USDA pump out fantasy numbers and call it a win.

This is the same pattern we've seen across the board: brag about successes that don't exist, then quietly revise the data when caught. Only this time it's not some abstract economic indicator. It's the backbone of rural America — cattle ranchers, feedlot operators, processors, and exporters — watching their industry get trashed by incompetence and covered up with lies.

The revised numbers aren't just embarrassing, they're devastating. They confirm what ranchers have been screaming for months: America's beef sector is in serious trouble, and the people running the show are too busy tweeting victory to notice or care.

The only question left is how many more "record" numbers will have to be walked back due to Trump being a serial lying sociopath who is too psychologically fragile to handle the truth.

🔗 View Quoted Tweet

💬27🔄21❤️275👀90961📊37

⚡ Powered by xgo.ing

Typical NYT understatement for what is an apocalyptic destruction of the American innovation ecosyst...

Yann LeCun (@ylecun) — Fri, 10 Jul 2026 08:26:27 GMT

Typical NYT understatement for what is an apocalyptic destruction of the American innovation ecosystem.

I can't understand how the Trump administration is doing this while boasting about American technology leadership. Don't they realize that a nation can't get technological innovations without scientists, and that scientists are former PhD students?

💬66🔄85❤️659👀189874📊119

⚡ Powered by xgo.ing

@rednebmas @KenRoth https://t.co/5MOgouVplV

Yann LeCun (@ylecun) — Thu, 09 Jul 2026 06:55:02 GMT

@rednebmas@KenRoththealliance.ai/projects/tapes…

💬3🔄6❤️43👀8165📊11

Yann LeCun(@ylecun)

Toutes les formes d'IA sont de "belles saloperies" ? Vraiment ? Même celles qui dépistent les tume...

Au contraire. C'est une nouvelle ère qui s'ouvre pour les mathématiques. Une ère où la démonstratio...

That's a commonly ignored fact. It's not like Leonardo da Vinci invented the helicopter, or even P...

The 1991 version is an obscure tech report with a vague idea, no theory, no experiment to speak of, ...

@abuchanlife - training frontier models is expensive - distilling a frontier model is cheap - this m...

I feel like the progress of AI is actually making systems neuroscience more exciting. It's not lik...

That video is 2 years old. Two years later, we are still far from human-level AI. Sure, AI has supe...

@ziv_ravid @chrmanning Sooo where is my domestic robot? Where is my L5 self-driving car? I can fi...

Question for everyone : Are you pro-intelligence or anti-intelligence ? Do you think more intellige...

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Wher...

Remember October 2022 when you doused Galactica with vitriol? Galactica was a 120b-parameter LLM-b...

@Plinz 😂 Don't worry, we got your Bach.

I have absolutely never ever "asked" to stop R&D on LLMs. In fact, I was very supportive of LLM eff...

I said "auto-regressive LLMs, in and of themselves, will not lead human-level AI" That statement is...

@dylanbowmanSF Slide deck here: https://t.co/36v5ASQJZv

Progress in airplane design have made them safer and safer. Airplanes would have been safer earlier ...

@nxthompson More like a genuinely nonsensical anthropomorphization.

Being better than humans at searching and writing down the formal proof of a theorem does not equate...

But there is a 1 hour talk, with results and evidence, that leads to these conclusions. Also, I am ...

@DeryaTR_ Thank you for injecting us with a dose of realism vaccine against the AI doom virus.

Nice! This ends up being a version of what some of us have called "target prop": every layer's input...

@Ryanotious @PessimistsArc Self importance fueled by a misplaced superiority complex.

@ericxing AI folks who live in the discrete world of bits and tokens don't always understand how inc...

They can't. The LLMs that underly modern AI systems are auto-regressive, but modern AI systems are n...

@raphaelmilliere Sure, but when it turns out the leak was caused by the plumber who neglected to tig...

@PessimistsArc Right. Dario was already claiming that GPT2 was too dangerous to open source back in ...

@kchonyc Exactly. The "escapes" were made possible either through egregious negligence or delibera...

@ilyasut To prevent models from going rouge, just make the neoclouds go green. Or threaten to blackl...

I would try to figure out why LLMs can write my essays but not clean my bedroom. Then I would study ...

@firesidealpha Sudden Clarity Sam realizing that real-world dynamics equations have inertia and fric...

@JitendraMalikCV Exactly. We also should not confuse world models, as per your definition, with vide...

@ziv_ravid No

Only in America. Tired of winning?

For about 10 years now, I have argued that the *only* way forward is for AI technology to be widely ...

When you work on research (particularly on long-term research), you have to accept the fact that cor...

Launching something new with Shaun Johnson and Oriol Vinyals: A deeply technical VC firm focused on ...

@gabriberton You obviously did not understand my statement. I was talking about auto-regressive tok...

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Obje...

Mathematics and computing have had a very tight relationship in some corners of academia. Richard C...

Tired of not winning

The amount of basic research done in industry is nowhere near the amount done in universities. At v...

Tired of winning

@AndrewCurran_ 🤬😡

@hosseeb @deanwball Soooo, releasing Linux was dumping? Apache, MySQL, PHP? HTTP, TCP/IP, OpenSSL,...

@deanwball The "ungovernability" (and openness) of Linux and the Internet is precisely what has made...

@deanwball @natolambert I have not said anything like that. I have said that governments around the...

Not a critique of the paper, but isn't inductive bias/ regularization the reason for *every* form of...

Tired of winning

Typical NYT understatement for what is an apocalyptic destruction of the American innovation ecosyst...

@rednebmas @KenRoth https://t.co/5MOgouVplV

For about 10 years now, I have argued that the only way forward is for AI technology to be widely ...

Not a critique of the paper, but isn't inductive bias/ regularization the reason for every form of...