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In industry research, someone in a chief position like LeCun should know how to balance long-term research with short-term projects. However, for whatever reaso
by xuancanh 11mo ago
In industry research, someone in a chief position like LeCun should know how to balance long-term research with short-term projects. However, for whatever reason, he consistently shows hostility toward LLMs and engineering projects, even though Llama and PyTorch are two of the most influential projects from Meta AI. His attitude doesn’t really match what is expected from a Chief position at a product company like Facebook. When Llama 4 got criticized, he distanced himself from the project, stating that he only leads FAIR and that the project falls under a different organization. That kind of attitude doesn’t seem suitable for the face of AI at the company. It's not a surprise that Zuck tried to demote him.
- throwaw12 11mo agoI would pose a question differently, under his leadership did Meta achieve good outcome? If the answer is yes, then better to keep him, because he has already proved himself and you can win in the long-term. With Meta's pockets, you can always create a new department specifically for short-term projects. If the answer is no, then nothing to discuss here.
- rw2 11mo agoI believe that the fact that Chinese models are beating the crap of of Llama means it's a huge no.
- amelius 11mo agoWhy? The Chinese are very capable. Most DL papers have at least one Chinese name on it. That doesn't mean they are Chinese but it's telling.
- UrineSqueegee 11mo agois an american model chinese because chinese people were in the team?
- rob_c 11mo agomost papers are also written in the same language, what's your point?
- xuancanh 11mo agoMeta did exactly that, kept him but reduced his scope. Did the broader research community benefit from his research? Absolutely. But did Meta achieve a good outcome? Probably not. If you follow LeCun on social media, you can see that the way FAIR’s results are assessed is very narrow-minded and still follows the academic mindset. He mentioned that his research is evaluated by: "Research evaluation is a difficult task because the product impact may occur years (sometimes decades) after the work. For that reason, evaluation must often rely on the collective opinion of the research community through proxies such as publications, citations, invited talks, awards, etc." But as an industry researcher, he should know how his research fits with the company vision and be able to assess that easily. If the company's vision is to be the leader in AI, then as of now, he seems to have failed that objective, even though he has been at Meta for more than 10 years.
- nsonha 11mo agoAlso he always sounds like "I know this will not work". Dude are you a researcher? You're supposed to experiment and follow the results. That's what separates you from oracles and freaking philosophers or whatever.
- yawnxyz 11mo agohe probably predicted the asymptote everyone is approaching right now
- brazukadev 11mo agoSo did I after trying llama/Meta AI
- uoaei 11mo agoHe's speaking to the entire feedforward Transformer-based paradigm. He sees little point in continuing to try to squeeze more blood out of that stone and instead move on to more appropriate ways to model ontologies per se rather than the crude-for-what-we-use-them-for embedding-based methods that are popular today. I really resonate with his view due to my background in physics and information theory. I for one welcome his new experimentation in other realms while so many still hack away at their LLMs in pursuit of SOTA benchmarks.
- deleted 11mo ago[deleted]
- HarHarVeryFunny 11mo agoLeCun was always part of FAIR, doing research, not part of the LLM/product group, who reported to someone else.
- rockinghigh 11mo agoWasn't the original LLaMA developed by FAIR Paris?
- HarHarVeryFunny 11mo agoI hadn't heard that, but he was heavily involved in a cancelled project called Galactica that was an LLM for scientific knowledge.
- fooker 11mo agoYeah that stuff generated embarrassingly wrong scientific 'facts' and citations. That kind of hallucination is somewhat acceptable for something marketed as a chatbot, less so for an assistant helping you with scientific knowledge and research.
- baobabKoodaa 11mo agoI thought it was weird at the time how much hate Galactica got for its hallucinations compared to hallucinations of competing models. I get your point and it partially explains things. But it's not a fully satisfying explanation.
- fooker 11mo agoI guess another aspect is - being too early is not too different from being wrong.
- anotherd1p 11mo agothen we should ask: will Meta come close enough to the fulfillment of the promises made, or will it keep achieving good enough outcomes?
- rapsey 11mo agoYann was never a good fit for Meta.
- runeblaze 11mo agoAgreed, I am surprised he is happy to stay this long. He would have been on paper a far better match at a place like pre-Gemini-era Google
- rob_c 11mo agotbf, transformers from more of a developmental perspective are hugely wasteful. they're long-range stable sure, but the whole training process requires so much power/data compared to even slightly simpler model designs I can see why people are drawn to alternative complex model designs down-playing the reliance on pure attention.
- blutoot 11mo agoThese are the types that want academic freedom in a cut-throat industry setup and conversely never fit into academia because their profiles and growth ambitions far exceed what an academic research lab can afford (barring some marquee names). It's an unfortunate paradox.
- sigbottle 11mo agoMaybe it's time for Bell Labs 2? I guess everyone is racing towards AGI in a few years or whatever so it's kind of impossible to cultivate that environment.
- belter 11mo ago> I guess everyone is racing towards AGI in a few years A pipe dream sustaining the biggest stock market bubble in history. Smart investors are jumping to the next bubble already...Quantum...
- re-thc 11mo ago> A pipe dream sustaining the biggest stock market bubble in history This is why we're losing innovation. Look at electric cars, batteries, solar panels, rare earths and many more. Bubble or struggle for survival? Right, because if US has no AI the world will have no AI? That's the real bubble - being stuck in an ancient world view. Meta's stock has already tanked for "over" investing in AI. Bubble, where?
- belter 11mo ago2 Trillion dollars in Capex to get code generators with hallucinations, that run at a loss, and you ask where is the Bubble?
- re-thc 11mo ago> 2 Trillion dollars in Capex to get code generators with hallucinations You assume that's the only use of it. And are people not using these code generators? Is this an issue with a lost generation that forgot what Capex is? We've moved from Capex to Opex and now the notion is lost, is it? You can hire an army of software developers but can't build hardware. Is it better when everyone buys DeepSeek or a non-US version? Well then you don't need to spend Capex but you won't have revenue either.
- sharmajai 11mo agoProduct companies with deprioritized R&D wings are the first ones to die.
- deleted 11mo ago[deleted]
- StilesCrisis 11mo agoNone of Meta's revenue has anything to do with AI at all. (Other than GenAI slop in old people's feeds.) Meta is in the strange position of investing very heavily in multiple fields where they have no successful product: VR, hardware devices, and now AI. Ad revenue funds it all.
- skeeter2020 11mo agoHasn't happened to Google yet
- anshumankmr 11mo agoHas Google depriortized R&D?
- astrange 11mo agoApple doesn't have an "R&D wing". It's a bad idea to split your company into the cool part and the boring part.
- fooker 11mo ago
- Grimblewald 11mo agoLLM hostility was warrented. The overhype/downright charlartan nature of ai hype and marketing threatens another AI winter. It happened to cybernetics, it'll happen to us too. The finance folks will be fine, they'll move to the next big thing to overhype, it is the researchers who suffer the fall-out. I am considered anti LLM (transformers anyway) for this reason, i like the the architecture, it is cool amd rather capable at its problem set, which is a unique set, but, it isnt going to deliver any of what has been promised, any more than a plain DNN or a CNN will.
- HDThoreaun 11mo agoMeta is in last place among the big tech companies making an AI push because of lecun’s llm hostility. Refusing to properly invest in the biggest product breakthrough this century was not even a little bit warranted. He had more than enough resources available to do the research he wanted and create a fantastic open source llm.
- Grimblewald 11mo agoMeta has made some fantastic llm's publically avliable many of which continue to outperform all but the qwen series in real world applications. LLMs cannot do any of the major claims made for them, so competing at the current frontier is a massive resource waste. Right now a locally running 8b model with large context window (10k tokens+) beat google/openAI models easily on any task you like. why would anyone then pay for something that is possible to run on consumer hardware with higher token/second throughput and better performance? What exactly have the billions invested given google/oai in return? Nothing more than an existensial crisis I'd say. Companies aren't trying to force AI costs into their subscription models in dishonest ways because they've got a winning product.
- HDThoreaun 11mo agoI dont really agree with your perception of current LLMs, but the point is it doesnt even matter. This is a pr war. Lecun lost it for meta. Meta needs to be thought of as an AI leader to gain traction in their metaverse stuff. They can live with everyone thinking theyre evil but if everyone thinks theyre lame has beens they are fucked.
- HarHarVeryFunny 11mo agoMeta had a two prong AI approach - product-focused group working on LLMs, and blue-sky research (FAIR) working on alternate approaches, such as LeCun's JEPA. It seems they've given up on the research and are now doubling down on LLMs.
- _the_inflator 11mo agoI totally agree. He appeared to act against his employer and actively undermined Meta's effort to attract talent by his behavior visible on X. And I stopped reading him, since he - in my opinion - trashed on autopilot everything 99% did - and these 99% were already beyond the two standard deviation of greatness. It is even more highly problematic if you have absolutely no results eg products to back your claims.
- hbarka 11mo agoLeCun truly believes the future is in world models. He’s not alone. Good for him to now be in the position he’s always wanted and hopefully prove out what he constantly talks about.
- astrange 11mo agoHe seems stuck in the GOFAI development philosophy where they just decide humans have something called a "world model" because they said so, and then decide that if they just develop some random thing and call it a "world model" it'll create intelligence because it has the same name as the thing they made up. And of course it doesn't work. Humans don't have world models. There's no such thing as a world model!
- HarHarVeryFunny 11mo agoI don't think the focus is really on world models, rather than on animal intelligence based around predicting the real world, but to predict it you need to model it in some sense.
- astrange 11mo agoIMO the issue is that animals can't have a specific "world model" system, because if you create a model ahead of time you will mostly waste energy because most of the model is not used. And animals' main concern is energy conservation, so they must be doing something else.
- HarHarVeryFunny 11mo agoThere are many factors playing into "survival of the fittest", and energy conservation is only one. Animals build mental models to predict the world because this superpower of seeing into the future is critical to survival - predict where the water is in a drought, where the food is, and how to catch it, etc, etc. The animal learns as it encounters learning signals - prediction failure - which is the only way to do it. Of course you need to learn/remember something before you can use that in the future, so in that sense it's "ahead of time", but the reason it's done that way because evolution has found that learning patterns will ultimately prove beneficial.
- nailer 11mo agoLecun has also consistently tried to redefine open source away from the open source definition.
- mi_lk 11mo agoThis is the right take. He is obviously a pioneer and much more knowledgeable than Wang in the field, but if you don't have the product mind to serve company's business interest in short term and long term capacity anymore, you may as well stay in academia and be your own research director, let alone a chief executive in one of the largest public companies
- Nimitz14 11mo agoYann was in charge of FAIR which has nothing to do with llama4 or the product focussed AI orgs. In general your comment is filled with misrepresentations. Sad.
- HDThoreaun 11mo agoFAIR having shit for products is the whole reason he is being demoted/fired. Yes, he had nothing to do with applied research, that was the problem.
- whiplash451 11mo agoIt's very hard (and almost irreconcilable) to lead both Applied Research -- that optimizes for product/business outcomes -- and Fundamental Research -- that optimizes for novel ideas -- especially at the scale of Meta. LeCun had chosen to focus on the latter. He can't be blamed for not having taken the second hat.
- HDThoreaun 11mo agoYes he can. If he wanted to focus on fundamental research he shouldn’t have accepted a leadership position at a product company. He knew going in that releasing products was part of his job and largely blew it.