[anon291]

> Do "AI" fanbois really think LLMs work like a biological brain?

If you read the article you'd know two things: (1) the article explicitly calls out Hopfield networks as being more bio-similar (Hopfield networks are intricately connected to attention layers) and (2) the overall architecture (the inference pass) of the networks studied here remain unmodified. Only the training mechanism changes.

As for a direct addressing of the claim... if the article is on point, then 'learning' has a much more encompassing physical manifestation than was previously thought. Really any system that self optimizes would be seen as bio-similar. In both mechanisms, there's a process to drive the system to 'convergence'. The issue is how fast that convergence is, not the end result.