Yann LeCun(@ylecun)

@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.

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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 😉

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@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....

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@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.

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@ziv_ravid No

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

@ziv_ravid No

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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.

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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.

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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).

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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.

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@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.

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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.

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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.

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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.”

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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.

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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.

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@AndrewCurran_ 🤬😡

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

@AndrewCurran_ 🤬😡

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@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?

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@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.

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@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.

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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.

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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.

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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?

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

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

@rednebmas@KenRoththealliance.ai/projects/tapes…

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@KenRoth The biggest risk of AI is the concentration of power in a few dominant providers of proprie...

Yann LeCun (@ylecun) — Thu, 09 Jul 2026 06:20:27 GMT

@KenRoth The biggest risk of AI is the concentration of power in a few dominant providers of proprietary AI assistants. 
The only solution to AI sovereignty is open source foundation models.

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Super-fun in-depth discussion 🙏🙏🙏 World models, JEPA vs generative architectures, anti-collapse m...

Yann LeCun (@ylecun) — Tue, 07 Jul 2026 14:24:33 GMT

Super-fun in-depth discussion 🙏🙏🙏
World models, JEPA vs generative architectures, anti-collapse methods for JEPA SSL including contrastive, distillation, and information maximization methods, an explanation of SIGReg/LeJEPA/LeWM.
Plus some bits on AMI Labs, Project Tapestry, as well as Lisp and homoiconic languages 😅

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@ZhugeEX The median wealth of a French is almost twice the median wealth of an American. So much...

Yann LeCun (@ylecun) — Mon, 06 Jul 2026 16:59:40 GMT

@ZhugeEX The *median* wealth of a French is almost *twice* the median wealth of an American.
So much for the "Europoor" meme.

The *average* American wealth is high because a tiny number of Americans are absurdly rich. But most Americans get screwed.

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Tired of winning

Yann LeCun (@ylecun) — Mon, 06 Jul 2026 14:47:30 GMT

Tired of winning

Steve Rattner@SteveRattner

Labor force participation has fallen to 61.5% — the lowest since 2021, erasing the entire post-pandemic recovery. 

Since Trump's inauguration, over a million people have left the job market — which explains part of the reason the unemployment rate dropped last month.

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It's not merely physical agents, it's anything that deals with something else than sequences of disc...

Yann LeCun (@ylecun) — Sat, 04 Jul 2026 15:30:27 GMT

It's not merely physical agents, it's anything that deals with something else than sequences of discrete symbols. 

Any data modality that is high-dimensional, continuous, and possibly noisy is completely out of reach of current generative models. 

That includes pretty much all real-world signals (aside from human language, computer languages and mathematics).

Furthermore, you can't have reliable agents unless they have the ability to predict the consequences of their actions and plan accordingly. LLMs simply don't.

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@elonmusk @Devon_Eriksen_ If there were any lingering doubts that you and your friends were against ...

Yann LeCun (@ylecun) — Sat, 04 Jul 2026 15:25:25 GMT

@elonmusk@Devon_Eriksen_ If there were any lingering doubts that you and your friends were against the very principles of democracy, you just removed them.

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Yet we still don't have level-5 self-driving cars, and certainly not self-serving cars that can lear...

Yann LeCun (@ylecun) — Sat, 04 Jul 2026 15:15:21 GMT

Yet we still don't have level-5 self-driving cars, and certainly not self-serving cars that can learn to drive in a few hours of practice like any teenager. 
We don't even have domestic robots that can do what 10-year olds can do the first time we ask them. 
We don't even have robots that are nearly as smart as a house cat. 
The G in AGI is nonsense.

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Exactly. I've been disseminating a similar message for years. The concentration of power in AI and...

Yann LeCun (@ylecun) — Fri, 03 Jul 2026 13:35:42 GMT

Exactly. I've been disseminating a similar message for years. 

The concentration of power in AI and the desire for control is by far the biggest danger of AI. It could lead to a few private companies and/or countries being in control of access to information, access to knowledge, and access to the tools of economic expansion. 
It's a kind of medieval obscurantism akin to the Ottoman empire banning the use of the printing press for 200 years, in part to keep control of the dogma, but also to protect the corporation of the calligraphers and scribes.

Relevant historical bits about the Internet:
1. It took a deliberate decision by Al Gore and Bill Clinton to open up access of what was then ARPAnet to commercial entities and to the public, against the desires of the entrenched telecom industry. During a public roundtable about the "information superhighway" in 1993, the CEO of AT&T told Gore and Clinton "leave it to us". Gore said no.
2. In the late 1980s, setting up an Internet presence required buying proprietary hardware with proprietary OS and software stack from Sun Microsystems, HP, IBM, or Dell. By the 2000s, all of this was wiped out by commodity hardware, Linux, Apache, and an entirely free/open software stack. This migration to open platforms was the result of market forces.

Infrastructure wants to be open.
Foundation models are becoming an infrastructure and will inevitably become commoditized.
Long term, the money is in the application layer, which is what I, Arthur Mensch, Alex Karp, and others have been saying.

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@elonmusk More copious copium. Whether you like it or not, everyone thinks you're evil (except for a...

Yann LeCun (@ylecun) — Mon, 29 Jun 2026 21:25:07 GMT

@elonmusk More copious copium.
Whether you like it or not, everyone thinks you're evil (except for a few fanbois on this platform).

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Moving bits to and from memory. Because of parasitic capacitance+resistance of the wires. The bigger...

Yann LeCun (@ylecun) — Sat, 27 Jun 2026 18:34:08 GMT

Moving bits to and from memory.
Because of parasitic capacitance+resistance of the wires.
The bigger the memory, the longer the wires.
The main trick is to organize the memory hierarchically: registers, small on-chip SRAM, caches of various types, and external RAM.
It's all because we have to use hardware multiplexing: reusing the same multiply-accumulate unit for multiple parts of the network.

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@FukuyamaFrancis No, we don't. That's like saying in 1920 "we need an international treaty to ban ...

Yann LeCun (@ylecun) — Thu, 25 Jun 2026 21:59:35 GMT

@FukuyamaFrancis No, we don't. 

That's like saying in 1920 "we need an international treaty to ban jet engines"

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https://t.co/ZrOeFyHgeo

Yann LeCun (@ylecun) — Wed, 24 Jun 2026 12:53:20 GMT

webtv.un.org/en/asset/k14/k…

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@HarryStebbings The answer is Project Tapestry https://t.co/5MOgouVplV

Yann LeCun (@ylecun) — Sat, 20 Jun 2026 09:57:50 GMT

@HarryStebbings The answer is Project Tapestry 
thealliance.ai/projects/tapes…

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1. Je n'ai jamais dit que les LLMs étaient inutiles ou n'avaient pas de valeur commerciale. 2. Mais...

Yann LeCun (@ylecun) — Thu, 18 Jun 2026 10:51:34 GMT

Je n'ai jamais dit que les LLMs étaient inutiles ou n'avaient pas de valeur commerciale. 
Mais beaucoup de technologies sont utiles et à haute valeur sans être particulièrement "intelligentes" 
Les LLMs sont essentiellement inutiles et sans grande valeur pour ce qui est du pilotage de processus industriels ou de compréhension de données continues, de haute dimension, et/ou bruitées. 
Il y a énormément d'applications de haute valeur dans le pilotage de processus industriels ou de compréhension de données continues, de haute dimension, et/ou bruitées. 
A long terme, l'intelligence, la compréhension du monde, et la capacité à planifier est ce qui compte vraiment.

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@ClementDelangue @Dan_Jeffries1 Everyone, please join Project Tapestry https://t.co/5MOgouVplV

Yann LeCun (@ylecun) — Wed, 10 Jun 2026 12:54:31 GMT

@ClementDelangue@Dan_Jeffries1 Everyone, please join Project Tapestry 
thealliance.ai/projects/tapes…

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@JitendraMalikCV Exactly. Also, you can't act without the ability to predict the consequences of you...

Yann LeCun (@ylecun) — Sat, 06 Jun 2026 18:49:37 GMT

@JitendraMalikCV Exactly.
Also, you can't act without the ability to predict the consequences of your actions.
Also, VLAs are dead.

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@Dan_Jeffries1 Did some exponential-pilled bros finally realize that real-world processes have irred...

Yann LeCun (@ylecun) — Sat, 06 Jun 2026 12:50:35 GMT

@Dan_Jeffries1 Did some exponential-pilled bros finally realize that real-world processes have irreducible time constants and that you can't run the real world faster than real time?

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To be clear: there should not be a president of AI (let alone me 😅). Which is pretty much one point...

Yann LeCun (@ylecun) — Fri, 05 Jun 2026 19:34:31 GMT

To be clear: there should not be a president of AI (let alone me 😅).
Which is pretty much one point I make in the video.
This reminder is about the content of the video, which is 3 years old, but every more relevant.

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Reminder.

Yann LeCun (@ylecun) — Fri, 05 Jun 2026 16:00:49 GMT

Reminder.

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Some billionaires (or their foundations) do fund certain areas of basic research. Examples: Simons ...

Yann LeCun (@ylecun) — Fri, 05 Jun 2026 15:47:36 GMT

Some billionaires (or their foundations) do fund certain areas of basic research. 
Examples: Simons Foundation, Moore Foundation, Sloan Foundation, Keck Foundation, Schmidt Sciences, and several others.
But most of them are in biomedicine: Howard Hughes Medical Institute, Chan-Zuckerberg Initiative, Wellcome Trust, and many others.
However, this is all small compared with federal funding:  around 25% of academic funding is from philanthropy, and over 50% from federal grants. This proportion is much lower in STEM than in biomedicine, and much lower in less prestigious universities.
So historical evidence that fundamental research can be helped, but not entirely funded, by philanthropic billionaires.

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Political appointees vetting science funding? Trump is doing to science what the Right accused previ...

Yann LeCun (@ylecun) — Fri, 05 Jun 2026 15:18:56 GMT

Political appointees vetting science funding?
Trump is doing to science what the Right accused previous administrations of doing.
But in previous administrations, there was no political control of research grant approvals.
Grant proposals were evaluated through peer review: the research community decided which proposals had merit.

Bye-bye Vannevar Bush, hello Trofim Lysenko.
Bye-bye meritocracy, hello political favoritism.

From The Guardian: "A set of sweeping policy changes unveiled by the White House would leave officials appointed by Donald Trump vetting every public grant issued to universities and nongovernmental  organizations on the basis of their fidelity to “American values”, as  defined by the president, triggering widespread concern."

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The incentives and time horizons are different for private and public research funding. Very, very f...

Yann LeCun (@ylecun) — Wed, 03 Jun 2026 16:20:36 GMT

The incentives and time horizons are different for private and public research funding.
Very, very few private outfits will fund fundamental research. Even fewer will fund PhD fellowships. 
Without PhD fellowships, no PhD graduates. 
Without PhD graduates, no new scientists. 
Without new scientists, no new discoveries, 
Without new discoveries, no innovation. 
No innovation, no economic growth.

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@DavidSacks If Trump really were "the most pro-innovation president we’ve ever had" he would not att...

Yann LeCun (@ylecun) — Tue, 02 Jun 2026 22:25:29 GMT

@DavidSacks If Trump really were "the most pro-innovation president we’ve ever had" he would not attempt to cut research budgets by half.

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I'm MAGA's twisted sense of reality and morality, a scientist who developed treatments and vaccines ...

Yann LeCun (@ylecun) — Sat, 30 May 2026 13:41:55 GMT

I'm MAGA's twisted sense of reality and morality, a scientist who developed treatments and vaccines that have saved hundreds of thousands of lives (without getting rich from it) should be sent to Gitmo. 

"In addition to continuing work on vaccines already in clinical trials for hookworm as of 2010 and schistosomiasis, Hotez led a team of researchers developing vaccines against other diseases including leishmaniasis, Chagas disease, SARS, and MERS, As of 2020, he was also working in development of a Coronavirus vaccine. With Maria Elena Bottazzi, he led the team that designed COVID-19 vaccine named Corbevax." 

en.wikipedia.org/wiki/Peter_Hot…

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@Pontifex Indeed, AI today does not do or possess any of those things. But at some point in the fut...

Yann LeCun (@ylecun) — Sat, 30 May 2026 13:21:09 GMT

@Pontifex Indeed, AI today does not do or possess any of those things. 
But at some point in the future they will. 

Except perhaps for the spiritual part.
Many humans aren't spiritual either, yet have empathy and are highly moral.

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@CSProfKGD Thanks, Kosta. Slide deck here: https://t.co/GetNmw87hS

Yann LeCun (@ylecun) — Thu, 28 May 2026 12:12:13 GMT

@CSProfKGD Thanks, Kosta.
Slide deck here:
drive.google.com/file/d/1gHy1Te…

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@Nature NSF secretly blocking grants to Duke, Harvard, Yale, Princeton ... And they will call that ...

Yann LeCun (@ylecun) — Thu, 28 May 2026 08:43:49 GMT

@Nature NSF secretly blocking grants to Duke, Harvard, Yale, Princeton ... 
And they will call that meritocracy 🙄🤬

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Yann LeCun(@ylecun)

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Tired of winning

@AndrewCurran_ 🤬😡

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Super-fun in-depth discussion 🙏🙏🙏 World models, JEPA vs generative architectures, anti-collapse m...

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Tired of winning

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https://t.co/ZrOeFyHgeo

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Reminder.

Some billionaires (or their foundations) do fund certain areas of basic research. Examples: Simons ...

Political appointees vetting science funding? Trump is doing to science what the Right accused previ...

The incentives and time horizons are different for private and public research funding. Very, very f...

@DavidSacks If Trump really were "the most pro-innovation president we’ve ever had" he would not att...

I'm MAGA's twisted sense of reality and morality, a scientist who developed treatments and vaccines ...

@Pontifex Indeed, AI today does not do or possess any of those things. But at some point in the fut...

@CSProfKGD Thanks, Kosta. Slide deck here: https://t.co/GetNmw87hS

@Nature NSF secretly blocking grants to Duke, Harvard, Yale, Princeton ... And they will call that ...

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...

@ZhugeEX The median wealth of a French is almost twice the median wealth of an American. So much...