AI doesn't "create", it "modifies" existing data.

It regurgitates whatever was in it's training set.

If you’re lucky.

Don't we all :)

Knowledge is significantly different from a training set. In particular we can hold incomplete knowledge that is eventually resolved through further practice and observation. Also knowledge access is analog and inaccurate to a degree that often introduces emergent behavior into outputs.

Isn't a collage a creative work?

Do you mean FPGAs?

Because fixed silicon inevitably has fixed "baked in" choices.

This is, like, the entirety of computing. Did x86 spring fully-formed from Zeus's forehead or did people bake in their knowledge of what programmers wanted their programs to do?

When you write programs do you not use heuristics? And tests?

It’s a little known fact that x86 is literally Athena! Which I guess means Intel should be casting some lightning bolts towards AMD and others.

Yep, the crowning achievement of machine complexity in recent human history is easily generalized in computational efficacy by effectively markov chain chatbots that were trained on project Gutenberg, reddit comments, and github python and javascript repos.

theres lots of ai other than llms

Ok fair point.

One such method was an improvement in matrix matrix multiplication in 2022. So I’m sure there is a potential discovery of many efficient numerical algorithms that will be uncovered with machine learning.

https://www.nature.com/articles/s41586-022-05172-4

My parent comment was a knee jerk response to the over confidence and wishful thinking of computer work people to a magic AI box solving all the hard physical problems like its some simple conversation prompt away.

Unfortunately I think the fetishization of prompting is a self-fulfilling prophecy. Over time these models will be able to understand enough of the physical problems to have a dumb prompt yield a reasonable if not optimal solution. But of course that house of cards collapses when fundamental advances appear.

If you're not smart enough to make use of a optimal or even acceptable solution, the quality of the LLM answer doesn't matter.

Human brains have lots of "hard wired" heuristic knowledge literally baked into them. See for example https://www.sciencedirect.com/topics/computer-science/ventra...

Is it surprising that silicon does too?

> Is it surprising that silicon does too?

Given that human brains and silicon has nothing in common, then yes, it is surprising. What makes you think otherwise?

If evolution has worked out that having specifically optimized pathways for specific actions it doesn't seem terrible that human designed machines are similar.

I feel that's assuming a whole lot of unrelated things, such as machines and humans having anything at all in common.

I get that your take qualifies as stoner philosophy, so I won't push too far, but really. Do give some concrete examples to support your ideas rather than GPT fluff.