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Cyc: History's Forgotten AI Project

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Re: Cyc: History's Forgotten AI Project

#61

Post by jimmySixDOF »

nextos wrote: post #51
TrevorFSmith wrote: post #50

Has Cyc been forgotten? Maybe it's unknown to tech startup hucksters who haven't studied AI in any real way but it's a well known project among both academic and informed industry folks.

Probably. IMHO there is a lot of low-hanging fruit for startups in the field of symbolic AI applied to biology and medicine. Bonus points if that is combined with modern differentiable methods and SAT/SMT, i.e. neurosymbolic AI.

There is MindAptive who have something about symbolics as a kind of machine language interface that I think went the other way as in trying to do everything under the sun but its the last time I came across anything reminding me of Cyc

https://mindaptiv.com/intro-to-wantware/

Re: Cyc: History's Forgotten AI Project

#62

Post by riku_iki »

nextos wrote: post #51
TrevorFSmith wrote: post #50

Has Cyc been forgotten? Maybe it's unknown to tech startup hucksters who haven't studied AI in any real way but it's a well known project among both academic and informed industry folks.

Probably. IMHO there is a lot of low-hanging fruit for startups in the field of symbolic AI applied to biology and medicine. Bonus points if that is combined with modern differentiable methods and SAT/SMT, i.e. neurosymbolic AI.

> IMHO there is a lot of low-hanging fruit for startups in the field of symbolic AI applied to biology and medicine.

I think the issue in this area is mostly to convince and sell to bureaucratic institutions.

Re: Cyc: History's Forgotten AI Project

#63

Post by riku_iki »

observationist wrote: post #7
mepian wrote: post #3

I wonder what is the closest thing to Cyc we have in the open source realm right now. I know that we have some pretty large knowledge bases, like Wikidata, but what about expert system shells or inference engines?

OWL and SPARQL inference engines that use RDF and DSMs - there are LISPy variants like datadog still kicking around, but there are some great, high performance reasoner FOSS projects, like StarDog or Neo4j https://github.com/orgs/stardog-union/ Looks like Knowledge Graph and semantic reasoner are the search terms du'jour, I haven't tracked these things since OpenCyc stopped being active. Humans may not be able to eff…

> high performance reasoner FOSS projects, like StarDog or Neo4j

StarDog is not FOSS, that github repo is for various utils around their proprietary package in my understanding, actual engine code is not open source.

Re: Cyc: History's Forgotten AI Project

#64

Post by famouswaffles »

Rochus wrote: post #55
famouswaffles wrote: post #52

Earlier quoted context omitted.

>the hype about LLMs has calmed down The hype of LLMs is not the reason the likes of Cyc have been abandoned.

It's not "abandoned"; it's just that most money today goes into curve fitting; but there are features which can be better realized with production systems, e.g. things like explainability or causality.

>it's just that most money today goes into curve fitting

It's pretty interesting to see comments like this like deep nets weren't the underdog for decades. You think they were first choice ? The creator of cyc spent decades on it, and he's dead. We use modern NNs today because they just work that much better.

Gofai was abandoned in NLP long before the likes of GPT because non deep-net alternatives just sucked that much. It has nothing to do with any recent LLM hype.

If the problem space is without clear definitions and unambiguous axioms then non deep-net alternatives fall apart.

Re: Cyc: History's Forgotten AI Project

#65

Post by famouswaffles »

mepian wrote: post #54
famouswaffles wrote: post #53

Earlier quoted context omitted.

Anything other than clear definitions and unambiguous axioms (which happens to be most of the real world) and gofai falls apart. Like it can't even be done. There's a reason it was abandoned in NLP long before the likes of GPT. There aren't any class of problems deep nets can't handle. Will they always be the most efficient or best performing solution ? No, but it will be possible.

They should handle the problem of hallucinations then.

Bigger models hallucinate less.

and we don't call it hallucinations but gofai mispredicts plenty.

Re: Cyc: History's Forgotten AI Project

#66

Post by eru »

goatlover wrote: post #56
thesz wrote: post #46

Earlier quoted context omitted.

Lenat was able to produce superhuman performing AI in the early 1980s [1]. [1] https://voidfarer.livejournal.com/623.html You can label it "bad idea" but you can't bring LLMs back in time.

Why didn't it ever have the impact that LLMs are having now? Or that DeepMind has had? Cyc didn't pass the Turing Test or become superhuman chess and go players. Yet it's had much more time to become successful.

I'm very skeptical of Cyc and other symbolic approaches.

However I think they have a good excuse for 'Why didn't it ever have the impact that LLMs are having now?': lack of data and lack of compute.

And it's the same excuse that neural networks themselves have: back in those days, we just didn't have enough data, and we didn't have enough compute, even if we had the data.

(Of course, we learned in the meantime that neural networks benefit a lot from extra data and extra compute. Whether that can be brought to bear on Cyc-style symbolic approaches is another question.)

Re: Cyc: History's Forgotten AI Project

#67

Post by eru »

mepian wrote: post #54
famouswaffles wrote: post #53

Earlier quoted context omitted.

Anything other than clear definitions and unambiguous axioms (which happens to be most of the real world) and gofai falls apart. Like it can't even be done. There's a reason it was abandoned in NLP long before the likes of GPT. There aren't any class of problems deep nets can't handle. Will they always be the most efficient or best performing solution ? No, but it will be possible.

They should handle the problem of hallucinations then.

They are working on it. And current large language models via eg transformers aren't the only way to do AI with neural networks nor are they the only way to do AI with statistical approaches in general.

Cyc also has the equivalent of hallucinations, when their definitions don't cleanly apply to the real world.

Re: Cyc: History's Forgotten AI Project

#68

Post by eru »

famouswaffles wrote: post #64
Rochus wrote: post #55

Earlier quoted context omitted.

It's not "abandoned"; it's just that most money today goes into curve fitting; but there are features which can be better realized with production systems, e.g. things like explainability or causality.

>it's just that most money today goes into curve fitting It's pretty interesting to see comments like this like deep nets weren't the underdog for decades. You think they were first choice ? The creator of cyc spent decades on it, and he's dead. We use modern NNs today because they just work that much better. Gofai was abandoned in NLP long before the likes of GPT because non deep-net alternatives just sucked that mu…

> If the problem space is without clear definitions and unambiguous axioms then non deep-net alternatives fall apart.

I'm not sure deep-nets are the key here. I see the key as being lots of data and using statistical modeling. Instead of trying to fit what's happening into nice and clean black-and-white categories.

Btw, I don't even think Gofai is all that good at domains with clear definitions and unambiguous axioms: it took neural nets to beat the best people at the very clearly defined game of Go. And neural net approaches have also soundly beaten the best traditional chess engines. (Traditional chess engines have caught up a lot since then. Competition is good for development, of course.)

I suspect part of the problem for Gofai is that all the techniques that work are re-labelled to be just 'normal algorithms', like A* or dynamic programming etc, and no longer bear the (Gof) AI label.

(Tangent: that's very similar to philosophy. Where every time we turn anything into a proper science, we relabel it from 'natural philosophy' to something like 'physics'. John von Neumann was one of these recent geniuses who liberated large swaths of knowledge from the dark kludges of the philosophy ghetto.)

Re: Cyc: History's Forgotten AI Project

#69

Post by acutesoftware »

Cyc seemed to be the best application for proper AI in my opinion - all the ML and LLM tricks are statistically really good, but you need to parse it through Cyc to check for common sense.

I am really pleased they continue to work on this - it is a lot of work, but it needs to be done and checked manually, once done the base stuff shouldn't change much and it will be a great common sense check for generated content.

Re: Cyc: History's Forgotten AI Project

#70

Post by shrubble »

markc wrote: post #48
shrubble wrote: post #27

Back in the mid 1990s Cyc was giving away their Symbolics machines and I waffled on spending the $1500 in shipping to get them to me in Denver. In retrospect I should have, of course!

Probably could have driven round trip for under $500!

I had a 2 door VW Golf... would have needed more space!
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