61–70 of 529 posts
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> they are setting up in Singapore as their base Europe in general has been tightening up their rules / taxes / laws around startups / companies especially tech and remote. It's been less friendly. these days.
Yann Le Cun litteraly said this morning on the radio in France that it is headquarted in Paris and will pay taxes in France. Go figure…
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I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. World models don't solve any of these problems; they are fundamentally the same kind of deep learning architectures we are used to work with. Heck, if you think learning from the world i…
> I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. Even with continuous backpropagation and "learning", enriching the training data, so called online-learning, the limitations will not disappear. The LLMs will not be able to conclude t…
That's what I said. Backpropagation cannot be enough; that's not how neurons work in the slightest. When you put biological neurons in a Pong environment they learn to play not through some kind of loss or reward function; they self-organize to avoid unpredictable stimulation. As far as I know, no architecture learns in such an unsupervised way.
https://www.sciencedirect.com/science/article/pii/S089662732...
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I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. World models don't solve any of these problems; they are fundamentally the same kind of deep learning architectures we are used to work with. Heck, if you think learning from the world i…
> I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. Even with continuous backpropagation and "learning", enriching the training data, so called online-learning, the limitations will not disappear. The LLMs will not be able to conclude t…
So my question is: when is there enough training data that you can handle 99.99% of the world ?
> But this is not an applied AI company. There is absolutely no doubt about Yann's impact on AI/ML, but he had access to many more resources in Meta, and we didn't see anything. It could be a management issue, though, and I sincerely wish we will see more competition, but from what I quoted above, it does not seem like it. Understanding world through videos (mentioned in the article), is just what video models have a…
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why LLMs (transformers trained on multimodal token sequences, potentially containing spatiotemporal information) can't be a world model?
https://medium.com/state-of-the-art-technology/world-models-... > One major critique LeCun raises is that LLMs operate only in the realm of language, which is a simple, discrete space compared to the continuous, complex physical world we live in. LLMs can solve math problems or answer trivia because such tasks reduce to pattern completion on text, but they lack any meaningful grounding in physical reality. LeCun poin…
Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists a…
There seem to be other news articles mentioning that they are setting up in Singapore as their base. https://www.straitstimes.com/business/ai-godfather-raises-1-...
Justifiable. There are a lot more degrees of freedom in world models. LLMs are fundamentally capped because they only learn from static text -- human communications about the world -- rather than from the world itself, which is why they can remix existing ideas but find it all but impossible to produce genuinely novel discoveries or inventions. A well-funded and well-run startup building physical world models (ground…
I have a pet peeve with the concept of "a genuinely novel discovery or invention", what do you imagine this to be? Can you point me towards a discovery or invention that was "genuinely novel", ever? I don't think it makes sense conceptually unless you're literally referring to discovering new physical things like elements or something. Humans are remixers of ideas. That's all we do all the time. Our thoughts and acti…
You can't get Suno to do anything that's not in its training data. It is physically incapable of inventing a new musical genre. No matter how detailed the instructions you give it, and even if you cheat and provide it with actual MP3 examples of what you want it to create, it is impossible.
The same goes for LLMs and invention generally, which is why they've made no important scientific discoveries.
You can learn a lot by playing with Suno.
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> they are setting up in Singapore as their base Europe in general has been tightening up their rules / taxes / laws around startups / companies especially tech and remote. It's been less friendly. these days.
Yann Le Cun litteraly said this morning on the radio in France that it is headquarted in Paris and will pay taxes in France. Go figure…
That article is from June 2025 so may be out of date, and the definition of "seed round" is a bit fuzzy.