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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.
Bonus points if that is combined with modern differentiable methods and SAT/SMT, i.e. neurosymbolic AI.
Interesting article, thanks. > Perhaps their time will come again. That's pretty sure, as soon as the hype about LLMs has calmed down. I hope that Cyc's data will then still be available, ideally open-source. > https://muse.jhu.edu/pub/87/article/853382/pdf Unfortunately paywalled; does anyone have a downloadable copy?
The hype of LLMs is not the reason the likes of Cyc have been abandoned.
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.
> Now it's clear that knowledge graphs are far inferior to deep neural nets No. It depends. In general, two technologies can’t be assessed independently of the application.
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.
Earlier quoted context omitted.
> Now it's clear that knowledge graphs are far inferior to deep neural nets No. It depends. In general, two technologies can’t be assessed independently of the application.
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.
Interesting article, thanks. > Perhaps their time will come again. That's pretty sure, as soon as the hype about LLMs has calmed down. I hope that Cyc's data will then still be available, ideally open-source. > https://muse.jhu.edu/pub/87/article/853382/pdf Unfortunately paywalled; does anyone have a downloadable copy?
>the hype about LLMs has calmed down The hype of LLMs is not the reason the likes of Cyc have been abandoned.
Cyc is one of those bad ideas that won't die, and which keeps getting rediscovered on HN. Lenat wasted decades of his life on it. Knowledge graphs like Cyc are labor intensive to build and difficult to maintain. They are brittle in the face of change, and useless if they cannot represent the underlying changes of reality.
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.
Earlier quoted context omitted.
Yes: https://cyc.com/archives/glossary/subl/ Also see: https://www.youtube.com/watch?v=cMMiaCtOzV0
Interesting that they're still using Allegro Common Lisp. I would be interested in knowing what technical issues (if any) prevented them from migrating to other implementations.
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.
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?
At a much lower level, I've been having fun hacking away at my Concludia side project over time. It's purely proposition level and will eventually support people being able to create their own arguments and contest others. http://concludia.org/
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?
Err…OpenCyc?
"I wonder what is the closest thing to Cyc we have in the open source realm right now?".
See:
https://github.com/therohk/opencyc-kb
https://github.com/bovlb/opencyc
https://github.com/asanchez75/opencyc
Outside of that, you have the entire world of Semantic Web projects, especially things like UMBEL[1], SUMO[2], YAMATO[3], and other "upper ontologies"[4] etc.
[1]: https://en.wikipedia.org/wiki/UMBEL
[2]: https://en.wikipedia.org/wiki/Suggested_Upper_Merged_Ontolog...