zlacker

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+(OP)
One of the first things software engineers learn is that people are bad at manually building models/programming.

The language and image models weren't built by people but by observing an obscene amount people going about their daily lives of producing text and images.

>>blackl+(OP)
I started my career in 1985, building expert systems on Symbolics Lisp machines in KEE and ART.

Expert systems were so massively oversold... and it's not at all clear that any of the "super fantastic expert" systems ever did what was claimed of them.

We definitely found out that they were, in practice, extremely difficult to build and make do anything reasonable.

The original paper on Eurisko, for instance, mentioned how the author (and founder of Cyc!) Douglas Lenat, during a run, went ahead and just hand-inserted some knowledge/results of inferences (it's been a long while since I read the paper, sorry), asserting, "Well, it would have figured these things out eventually!"

Later on, he wrote a paper titled, "Why AM and Eurisko appear to work" [0].

0: https://aaai.org/papers/00236-aaai83-059-why-am-and-eurisko-...

>>blackl+(OP)
>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

>>blackl+(OP)
I've read similar things about image models from 12 years ago beating the pants off most radiologists. I think the difference is that most writers, illustrators, musicians, drivers, etc. eke out a marginal living, while radiologists have enough reserves to fight back. The "move fast and break things" crowd in silicon valley isn't going to undertake that fight while there's still so much low-hanging fruit, ripe for the harvest.

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

>>blackl+(OP)
> Cyc was used by the Cleveland Clinic for answering ad hoc questions from medical researchers; it reduced the time from as long as a month of manual back-and-forth between medical and database experts, to less than an hour.

>>blackl+(OP)
Looks like we can now finally experiment with EURISKO ourselves:

>>40070667

>>famous+Tn
How do you know?

>>chris_+Ug
Depends on your definition of "super fantastic expert" systems.

I was one of the developers/knowledge engineers of the SpinPro™ Ultracentrifugation Expert System at Beckman Instruments, Inc. This was released in 1986, developed over about 2 years. This ran on an IBM PC (DOS)! This was a technical success, but not a commercial one. (The sales force was unfamiliar with promoting a software product, and which had little impact on their commissions vs. selling multi-thousand dollar equipment.) https://pubs.acs.org/doi/abs/10.1021/bk-1986-0306.ch023 (behind ACS paywall)

Our second Expert System was PepPro™, which designed procedures for the chemical synthesis of peptides (essentially very small proteins). This was completed and to be released in 1989, but Beckman discontinued their peptide synthesis instrument product line just two months before. This system was able to integrate end-user knowledge with the built-in domain knowledge. PepPro was recognized in the first AAAI Conference on Innovative Applications of Artificial Intelligence in 1989. https://www.aaai.org/Papers/IAAI/1989/IAAI89-010.pdf

Both of these were developed in Interlisp-D on Xerox 1108/1186 workstations, using an in-house expert system development environment, and deployed in Gold Hills Common Lisp for the PC.