Yes those quotes do refer to the need for a model to develop heterogeneous skills based on private information, and to adapt to changing situations in real life with very little data. I don’t see your problem.
In case it’s helpful, I prompted Claude Sonnet 4.5 with extended thinking to explain three of the key concepts we’re discussing and I thought it gave a pretty good answer, which you can read here. (I archived that answer here, in case that link breaks.)
I gave GPT-5 Thinking almost the same prompt (I had to add some instructions because the first response it gave was way too technical) and it gave an okay answer, which you can read here. (Archive link here.)
I tried to Google for human-written explanations of the similarities and differences first, since that’s obviously preferable. But I couldn’t quickly find one, probably because there’s no particular reason to compare these concepts directly to each other.
No, those definitions quite clearly don’t say anything about data efficiency or generalization, or the other problems I raised.
I think you have misunderstood the concept of continual learning. It doesn’t mean what you seem to think it means. You seem to be confusing the concept of continual learning with some much more expansive concept, such as generality.
If I’m wrong, you should be able to quite easily provide citations that clearly show otherwise.
Yes those quotes do refer to the need for a model to develop heterogeneous skills based on private information, and to adapt to changing situations in real life with very little data. I don’t see your problem.
In case it’s helpful, I prompted Claude Sonnet 4.5 with extended thinking to explain three of the key concepts we’re discussing and I thought it gave a pretty good answer, which you can read here. (I archived that answer here, in case that link breaks.)
I gave GPT-5 Thinking almost the same prompt (I had to add some instructions because the first response it gave was way too technical) and it gave an okay answer, which you can read here. (Archive link here.)
I tried to Google for human-written explanations of the similarities and differences first, since that’s obviously preferable. But I couldn’t quickly find one, probably because there’s no particular reason to compare these concepts directly to each other.
No, those definitions quite clearly don’t say anything about data efficiency or generalization, or the other problems I raised.
I think you have misunderstood the concept of continual learning. It doesn’t mean what you seem to think it means. You seem to be confusing the concept of continual learning with some much more expansive concept, such as generality.
If I’m wrong, you should be able to quite easily provide citations that clearly show otherwise.