Is it really so rare? I feel like I know of tons of fields where we have methods that work empirically but don’t understand all the theory. I’d actually argue that we don’t know what’s “actually” happening _ever_, but only have built enough understanding to do useful things.

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ajross a day ago | parent [-]

I mean, most big changes in the tech base don't have that characteristic. Semiconductors require only 1920's physics to describe (and a ton of experimentation to figure out how to manufacture). The motor revolution of the early 1900's was all built on well-settled thermodynamics (chemistry lagged a bit, but you don't need a lot of chemical theory to burn stuff). Maxwell's electrodynamics explained all of industrial electrification but predated it by 50 years, etc...

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skydhash a day ago | parent [-]

Those big changes always happens because someone presented a simpler model that explains stuff enough we can build stuff on it. It's not like semiconductors raw materials wasn't around.

The technologies around LLMs is fairly simple. What is not is the actual size of data being ingested and the number of resulting factors (weight). We have a formula and the parameters to generate grammatically perfect text, but to obtain it, you need TBs of data to get GBs of numbers.

In contrast something like TM or Church's notation is pure genius. Less than a 100 pages of theorems that are one of the main pillars of the tech world.

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ajross 15 hours ago | parent [-]

> Those big changes always happens because someone presented a simpler model that explains stuff enough we can build stuff on it.

Again, no it doesn't. It didn't with industrial steelmaking, which was ad hoc and lucky. It isn't with AI, which no one actually understands.

	▲	skydhash 10 hours ago \| parent [-]
		I’m pretty sure there were always formula for getting high quality steel even before the industrial age. And you only need a few textbooks and papers to understand AI.