The notions that are crucial for distinguishing between intelligence and what large NNs are doing, are generalization and abstraction. I'm impressed with DALL-E's ability to connect words to images and exploit the compositionality of language to model the compositionality of the physical world. Gato seems to be using the same trick for more domains.
But that's riding on human-created abstractions, rather than creating abstractions. In terms of practical consequences, that means these systems won't learn new things unless humans learn then first and provide ample training data.
But someday we will develop systems that can learn their own abstractions, and teach themselves anything. Aligning those systems is imperative.
Yup, I think this is the pretty much describes the limitation of today's AIs. They are gigantic statistics machines at best. It's still amazing how far we can get with this technique, but we know where they stop getting better.
But that's riding on human-created abstractions, rather than creating abstractions. In terms of practical consequences, that means these systems won't learn new things unless humans learn then first and provide ample training data.
But someday we will develop systems that can learn their own abstractions, and teach themselves anything. Aligning those systems is imperative.