LLMs only do superficial pattern recognition, but they can do it incredibly robustly.

They are amazing at superficial absorption of patterns.

But if you bombard them with tons of examples it gets a significantly more robust pattern recognition… but still superficial.

But when it's sufficiently robust it looks like it has deep pattern recognition.

It's like "baking" shadows in old video game engines, where you precompute the lighting and then create object textures with the shadows baked in.

Looks great (if you don't look too closely) but is extremely cheap.

If you give LLMs a gobsmackingly large number of examples, you can get gobsmacking robust recognition of those patterns.