The most interesting thing is the "dreaming" idea for on-device adaptation. I guess regularly adjusting weights becomes possible when the model is so small and the math is simplified.

I'm assuming that doesn't actually exist yet, though, as I don't see anything about an implementation in the code that's been released.

But, it's a really interesting idea for a personal model. There's a risk of more AI psychosis if these things actually start "learning", but the value of it is also probably pretty big. I'm not sure I buy it will actually be able to self-improve, though. The best models are helping improve themselves, but the best models are considerably smarter and more capable than this one. I've asked models like Gemma 4 31B to help figure out training and synthesizing data, and it mostly fails on anything more than categorization and summarization. This little model is much dumber than that.

So, I'm skeptical, but maybe there's deterministic tooling that can assist and maybe it will be scoped tightly enough to just learn and update facts and not so much try to retrain the whole thing.