zlacker

>>iafish+(OP)
I was born in late USSR and my father is software engineer. We had several books that were not available for "general public" (they were intended for libraries of science institutions). One of the book was, as I understand now, abridged translation of papers from some "Western" AI conference.

And there were description if EURISCO (with claims that it not only "win some game" but also that it "invented new structure of NAND-gate in silicon, used by industry now") and other expert systems.

One of the mentioned expert systems (without technical details) said was 2 times better in diagnose cancer than best human diagnostician of some university hospital.

And after that... Silence.

I always wonder, why did this expert system were not deployed in all USA hospitals, for example? If it is so good?

Now we have LLMs, but they are LANGUAGE models, not WORLD models. They predict distribution of possible next words. Same with images — pixels, not world concepts.

Looks like such systems are good for generating marketing texts, but can not be used as diagnosticians by definition.

Why did all these (slice of) world model approaches dead? Except Cyc, I think. Why we have good text generators and image generators but not diagnosticians 40 years later? What happens?..

>>blackl+tD1
>Looks like such systems are good for generating marketing texts, but can not be used as diagnosticians by definition.

That's not true

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10425828/

>Why did all these (slice of) world model approaches dead?

Because they don't work

>>famous+m12
Your article is a review of one language model (GPT-4) in diagnostics, while the original comment was an inquiry about world models.