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That was obviously him getting sidelined. And it's easy to see why. LLMs get results. None of the Yann LeCun's pet projects do. He had ample time to prove that

That was obviously him getting sidelined. And it's easy to see why. LLMs get results. None of the Yann LeCun's pet projects do. He had ample time to prove that his approach is promising, and he didn't.

dude250711 1y ago
There is someone else at Facebook who's pet projects do not get results...
- jb1991 1y ago
  Who are you referring to?
  - nolok 1y ago
    I think he means Zuckerberg himself, the metaverse isn't exactly a major success, but this is a false equivalency the way he organized it only his vote matters he does what he wants
- ergocoder 1y ago
  If you hire a house cleaner to clean your house, and the cleaner didn't do well, would you eject yourself out of the house? You would not. You would change to a new cleaner.
  - psychoslave 1y ago
    But if we hire someone to deal on R&D to automate fully the house cleaning process, we might not necessarily expect the office to be maintained in clean state by the researchers themselves any time we enter the room.
    - ergocoder 1y ago
      As far as an analogy, whatever happens, whoever messes up, Zuck, as the owner, of course, takes the final blame. That's why he is changing the team. Still, people bring up this weird point that would be equivalent to you giving up your house equity for free because you fucked up on hiring and managing your house.
- ACCount37 1y ago
  Sure, but that "someone else" is the man writing the checks. If the roles were reversed, he'd be the one being fired now.
camillomiller 1y ago
LLMs get results is quite the bold statement. If they get results, they should be getting adopted, and they should be making money. This is all built on hazy promises. If you had marketable results, you wouldn't have to hide 20+ billion dollars of debt financing into an obscure SPV. LLMs are the most baffling piece of tech. They are incredible, and yet marred by their non-deterministic hallucinatory nature, and bound to fail in adoption unless you convince everyone that they don't need precision and accuracy, but they can do their business at 75% quality, just with less human overhead. It's quite the thing to convince people of, and that's why it needs the spend it's needing. A lot of we-need-to-stay-in-the-loop CEOs and bigwigs got infatuated with the idea, and most probably they just had their companies get addicted to the tech equivalent of crack cocaine. A reckoning is coming.
- deleted 1y ago
  [deleted]
- ACCount37 1y ago
  LLMs get results, yes. They are getting adopted, and they are making money. Frontier models are all profitable. Inference is sold with a damn good margin, and the amounts of inference AI companies sell keeps rising. This necessitates putting more and more money into infrastructure. AI R&D is extremely expensive too, and this necessitates even more spending. A mistake I see people make over and over again is keeping track of the spending but overlooking the revenue altogether. Which sure is weird: you don't get from $0B in revenue to $12B in revenue in a few years by not having a product anyone wants to buy. And I find all the talk of "non-deterministic hallucinatory nature" to be overrated. Because humans suffer from all of that too, just less severely. On top of a number of other issues current AIs don't suffer from. Nonetheless, we use human labor for things. All AI has to do is provide a "good enough" alternative, and it often does.
  - camillomiller 1y ago
    In this comment you proceeded to basically reinvent the meaning of "profitable company", but sure. I won't even get into the point of comparing LLM to humans, because I choose not to engage with whoever doesn't have the human decency, humanistic compass, or basic phylosophical understanding of how putting LLMs and human labor on the same level to justify hallucinations and non-determinism is deranged and morally bankrupt.
chaoz_ 1y ago
I agree. I never understood LeCun's statement that we need to pivot toward the visual aspects of things because the bitrate of text is low while visual input through the eye is high. Text and languages contain structured information and encode a lot of real-world complexity (or it's "modelling" that). Not saying we won't pivot to visual data or world simulations, but he was clearly not the type of person to compete with other LLM research labs, nor did he propose any alternative that could be used to create something interesting for end-users.
- ACCount37 1y ago
  If LeCun's research has made Meta a powerhouse of video generation or general purpose robotics - the two promising directions that benefit from working with visual I/O and world modeling as LeCun sees it - it could have been a justified detour. But that sure didn't happen.
- tarsinge 1y ago
  Text and language contain only approximate information filtered through humans eyes and brains. Also animals don't have language and can show quite advanced capabilities compared to what we can currently do in robotics. And if you do enough mindfulness you can dissociate cognition/consciousness from language. I think we are lured because how important language is for us humans, but intuitively it's obvious to me language (and LLMs) are only a subcomponent, or even irrelevant for say self driving or robotics.
  - deleted 1y ago
    [deleted]
  - ACCount37 1y ago
    Seems like that "approximation" is perfectly sufficient for just about any task. That whole take about the language being basically useless without a human mind to back it lost its legs in 2022. In the meanwhile, what do those "world model" AIs do? Video generation? Meta didn't release anything like that. Robotics, self-driving? Also basically nothing from Meta there. In the meanwhile, other companies are perfectly content with bolting multimodal transformers together for robotics tasks. Gemini Robotics being a research example - while modern Tesla FSD stack being a production grade one. Gemini even uses a language transformer as a key part of its stack.

dude250711 1y ago

There is someone else at Facebook who's pet projects do not get results...

jb1991 1y ago
Who are you referring to?
- nolok 1y ago
  I think he means Zuckerberg himself, the metaverse isn't exactly a major success, but this is a false equivalency the way he organized it only his vote matters he does what he wants
ergocoder 1y ago
If you hire a house cleaner to clean your house, and the cleaner didn't do well, would you eject yourself out of the house? You would not. You would change to a new cleaner.
- psychoslave 1y ago
  But if we hire someone to deal on R&D to automate fully the house cleaning process, we might not necessarily expect the office to be maintained in clean state by the researchers themselves any time we enter the room.
  - ergocoder 1y ago
    As far as an analogy, whatever happens, whoever messes up, Zuck, as the owner, of course, takes the final blame. That's why he is changing the team. Still, people bring up this weird point that would be equivalent to you giving up your house equity for free because you fucked up on hiring and managing your house.
ACCount37 1y ago
Sure, but that "someone else" is the man writing the checks. If the roles were reversed, he'd be the one being fired now.

camillomiller 1y ago

LLMs get results is quite the bold statement. If they get results, they should be getting adopted, and they should be making money. This is all built on hazy promises. If you had marketable results, you wouldn't have to hide 20+ billion dollars of debt financing into an obscure SPV. LLMs are the most baffling piece of tech. They are incredible, and yet marred by their non-deterministic hallucinatory nature, and bound to fail in adoption unless you convince everyone that they don't need precision and accuracy, but they can do their business at 75% quality, just with less human overhead. It's quite the thing to convince people of, and that's why it needs the spend it's needing. A lot of we-need-to-stay-in-the-loop CEOs and bigwigs got infatuated with the idea, and most probably they just had their companies get addicted to the tech equivalent of crack cocaine. A reckoning is coming.

deleted 1y ago
[deleted]
ACCount37 1y ago
LLMs get results, yes. They are getting adopted, and they are making money. Frontier models are all profitable. Inference is sold with a damn good margin, and the amounts of inference AI companies sell keeps rising. This necessitates putting more and more money into infrastructure. AI R&D is extremely expensive too, and this necessitates even more spending. A mistake I see people make over and over again is keeping track of the spending but overlooking the revenue altogether. Which sure is weird: you don't get from $0B in revenue to $12B in revenue in a few years by not having a product anyone wants to buy. And I find all the talk of "non-deterministic hallucinatory nature" to be overrated. Because humans suffer from all of that too, just less severely. On top of a number of other issues current AIs don't suffer from. Nonetheless, we use human labor for things. All AI has to do is provide a "good enough" alternative, and it often does.
- camillomiller 1y ago
  In this comment you proceeded to basically reinvent the meaning of "profitable company", but sure. I won't even get into the point of comparing LLM to humans, because I choose not to engage with whoever doesn't have the human decency, humanistic compass, or basic phylosophical understanding of how putting LLMs and human labor on the same level to justify hallucinations and non-determinism is deranged and morally bankrupt.

chaoz_ 1y ago

I agree. I never understood LeCun's statement that we need to pivot toward the visual aspects of things because the bitrate of text is low while visual input through the eye is high. Text and languages contain structured information and encode a lot of real-world complexity (or it's "modelling" that). Not saying we won't pivot to visual data or world simulations, but he was clearly not the type of person to compete with other LLM research labs, nor did he propose any alternative that could be used to create something interesting for end-users.

ACCount37 1y ago
If LeCun's research has made Meta a powerhouse of video generation or general purpose robotics - the two promising directions that benefit from working with visual I/O and world modeling as LeCun sees it - it could have been a justified detour. But that sure didn't happen.
tarsinge 1y ago
Text and language contain only approximate information filtered through humans eyes and brains. Also animals don't have language and can show quite advanced capabilities compared to what we can currently do in robotics. And if you do enough mindfulness you can dissociate cognition/consciousness from language. I think we are lured because how important language is for us humans, but intuitively it's obvious to me language (and LLMs) are only a subcomponent, or even irrelevant for say self driving or robotics.
- deleted 1y ago
  [deleted]
- ACCount37 1y ago
  Seems like that "approximation" is perfectly sufficient for just about any task. That whole take about the language being basically useless without a human mind to back it lost its legs in 2022. In the meanwhile, what do those "world model" AIs do? Video generation? Meta didn't release anything like that. Robotics, self-driving? Also basically nothing from Meta there. In the meanwhile, other companies are perfectly content with bolting multimodal transformers together for robotics tasks. Gemini Robotics being a research example - while modern Tesla FSD stack being a production grade one. Gemini even uses a language transformer as a key part of its stack.