3 ms·
As a cognitive scientist, I think there's nothing special about the ability to "understand", or about "intelligence". When I hear someone say "AI can't understa
by luplex 3y ago
As a cognitive scientist, I think there's nothing special about the ability to "understand", or about "intelligence". When I hear someone say "AI can't understand", I think they mean "AI does not have a soul", and I think they actually want to say "I can't emphasize with AI".
On the other hand, I think understanding is gradual, not a binary. If I teach a neural network what the letter "A" looks like, it will understand the general shape of the letter "A" and even generalize to unseen examples!
That's a remarkable amount of understanding for some chunk of metal.
I wouldn't say LLMs understand the world anything like we do, but they do understand something: what kind of text a human would write. That is, LLMs can work with the concept of "gravity", but do not have access to gravity.
So in my view, LLMs have conceptual, abstract understanding of text but they lack grounding in physical reality. But also it doesn't really matter whether we say they "understand". What would it change?
- kromem 3y agoSo far most of the research around establishing world models has shown its occurring in linear representations. I suspect as we see networks become increasingly nonlinear (perhaps as we see hardware changes in the next few years to things like photonics), we will see additional jumps that bring it more in line with what we expect from human cognition. For example, right now it's very hard for a model to conceptualize "I don't know." Which seems more like a nonlinear process.