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Cyc: History's Forgotten AI Project

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101–110 of 145 posts

Re: Cyc: History's Forgotten AI Project

#101
Cyc was an interesting project - you might consider it as the ultimate scaling experiment in expert systems. There seemed to be two ideas being explored - could you give an expert system "common sense" by laboriously hand-entering in the rules for things we, and babies, learn by everyday experience, and could you make it generally intelligent by scaling it up and making the ruleset comprehensive enough.

Ultimately it failed, although people's opinions may differ. The company is still around, but from what people who've worked there have said, it seems as if the original goal is all but abandoned (although Lenat might have disagreed, and seemed eternally optimistic, at least in public). It seems they survive on private contracts for custom systems premised on the power of Cyc being brought to bear, when in reality these projects could be accomplished in simpler ways.

I can't help but see somewhat of a parallel between Cyc - an expert system scaling experiment, and today's LLMs - a language model scaling experiment. It seems that at heart LLMs are also rule-based expert systems of sorts, but with the massive convenience factor of learning the rules from data rather than needing to have the rules hand-entered. They both have/had the same promise of "scale it up and it'll achieve AGI", and "add more rules/data and it'll have common sense" and stop being brittle (having dumb failure modes, based on missing knowledge/experience).

While the underlying world model and reasoning power of LLMs might be compared to an expert system like Cyc, they do of course also have the critical ability to input and output language as a way to interface to this underlying capability (as well as perhaps fool us a bit with the ability to regurgitate human-derived surface forms of language). I wonder what Cyc would feel like in terms of intelligence and reasoning power if one somehow added an equally powerful natural language interface to it?

As LLMs continue to evolve, they are not just being scaled up, but also new functionality such as short term memory being added, so perhaps going beyond expert system in that regard, although there is/was also more to Cyc that just the massive knowledge base - a multitude of inference engines as well. Still, I can't help but wonder if the progress of LLMs won't also peter out, unless there are some fairly fundamental changes/additions to their pre-trained transformer basis. Are we just replicating the scaling experiment of Cyc, just with a fancy natural language interface?

Re: Cyc: History's Forgotten AI Project

#102
post #38

Earlier quoted context omitted.

I think before 2022 it was still an open question whether it was a good approach. Now it's clear that knowledge graphs are far inferior to deep neural nets, but even still few people can explain the _root_ reason why. I don't think Lenat's bet was a waste. I think it was sensible based on the information at the time. The decision to research it largely in secret, closed source, I think was a mistake.

I assume the problem with symbolic inference is that from a single inconsistent premise logic can produce any statement possible. If that is so then symbolic AI does not easily scale because you cannot feed inconsistent information into it. Compare this to how humans and LLMs learn, they both have no problem with inconsistent information. Yet statistically speaking humans can easily produce "useful" information.

Based on the article, it seems like the Cyc had ways to deal with inconsistency. I don't know the details of how they did it, but Paraconsistant Logics [0] provide a general way to prevent any statement from being provable from an inconsistency.

[0] https://en.wikipedia.org/wiki/Paraconsistent_logic

Re: Cyc: History's Forgotten AI Project

#103

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 o…

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.

Re: Cyc: History's Forgotten AI Project

#104

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 o…

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-...

Re: Cyc: History's Forgotten AI Project

#105
One thing the article doesn't really speak to: the future of Cyc now that Doug Lenat has passed away. Obviously a company can continue on even after the passing of a founder, but it always felt like Cyc was "Doug's baby" to a large extent. I wonder if the others that remain at Cycorp will remain as committed without him around leading the charge?

Does anybody have any insights into where things stand at Cycorp and any expected fallout from the world losing Doug?

Re: Cyc: History's Forgotten AI Project

#106
post #73

Are there any efforts to combining a knowledge base like Cyc together with LLMs and the like? Something like RAG could benefit I suppose. Have some vector for a concept match a KB entry etc, IDK :).

Are there any efforts to combining a knowledge base like Cyc together with LLMs and the like?

Yes. It's something I've been working on, so there's at least 1 such effort. And I'm reasonably sure there are others. The idea is too obvious for there to not be other people pursuing it.

Re: Cyc: History's Forgotten AI Project

#107
post #5

I would love to see a Cyc 2.0 modeled in the age of LLMs. I think it could be very powerful, especially to help deal with hallucinations. I would love to see a causality engine built with LLMs and Cyc. I wrote some notes on it before ChatGPT came out: https://blog.jtoy.net/understanding-cyc-the-ai-database/

I used to volunteer inputting data into Cyc back in the day. And I get massive déjà vu with current LLM's. I remember that the system ended up with an obsession with HVAC systems lol.

When I got to go to Cycorp in the late 80's for training, I had some really interesting talks with the people there. They got funding from a lot of sources, and of course each source needed their own knowledge encoded. One person mentioned that they had a fairly large bit of the knowledge base filled with content about military vehicles.

Re: Cyc: History's Forgotten AI Project

#108

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 o…

>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

Re: Cyc: History's Forgotten AI Project

#109
post #73

Are there any efforts to combining a knowledge base like Cyc together with LLMs and the like? Something like RAG could benefit I suppose. Have some vector for a concept match a KB entry etc, IDK :).

Are there any efforts to combining a knowledge base like Cyc together with LLMs and the like? Yes. It's something I've been working on, so there's at least 1 such effort. And I'm reasonably sure there are others. The idea is too obvious for there to not be other people pursuing it.

Too obvious indeed. Can I read anywhere about what you're working on? What other approaches exist?

Re: Cyc: History's Forgotten AI Project

#110

Earlier quoted context omitted.

Are there any efforts to combining a knowledge base like Cyc together with LLMs and the like? Yes. It's something I've been working on, so there's at least 1 such effort. And I'm reasonably sure there are others. The idea is too obvious for there to not be other people pursuing it.

Too obvious indeed. Can I read anywhere about what you're working on? What other approaches exist?

> Can I read anywhere about what you're working on?

Not yet. It's still early days.

> What other approaches exist?

Loosely speaking, I'd say this entire discussion falls into the general rubric of what people are calling "neuro-symbolic AI". Now within that there are a lot of different ways to try and combine different modalities. There are things like DeepProbLog, LogicTensorNetworks, etc.

For anybody who wants to learn more, consider starting with:

https://en.wikipedia.org/wiki/Neuro-symbolic_AI

and the videos from the previous two "Neurosymbolic Summer School" events:

https://neurosymbolic.github.io/nsss2023/

https://www.neurosymbolic.org/summerschool.html (2022)

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