22 ms·

Cyc: History's Forgotten AI Project

287 points by iafisher 2y ago

rhodin 2y ago
Related Stephen Wolfram's note when Doug Lenat passed away [0] [0] https://writings.stephenwolfram.com/2023/09/remembering-doug-lenat-1950-2023-and-his-quest-to-capture-the-world-with-logic/ https://writings.stephenwolfram.com/2023/09/remembering-doug...
- zozbot234 2y ago
  Discussed https://news.ycombinator.com/item?id=37402925 https://news.ycombinator.com/item?id=37402925 see also https://news.ycombinator.com/item?id=37354000 https://news.ycombinator.com/item?id=37354000
mepian 2y ago
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?
- nextos 2y ago
  There are some pretty huge ontology DBs in molecular biology, like GO or Reactome. But they have never truly exploited logic-based inference, except for some small academic efforts.
  - jerven 2y ago
    I think that GO with GO-CAM is definitely going that way. Basic GO is rather simple and can't infer that much (as in GO by itself has low classification or inference logic build in). Uberon, for anatomy, does use a lot of OWL power and shows that the logic-based inference can help a lot. Reactome, is a graph, because that is the domain. But technically it does little with that fact (In my disappointed opinion). Given that GO and Reactome are also relatively small academic efforts in general...
- niviksha 2y ago
  There are a few symbolic logic entailment engines that run atop OWL the Web Ontology Language, some flavors of which which are rough equivalent of Cycs KBs. The challenge though is the underlying approaches are computationally hard so nobody really uses them in practice, plus the retrieval language associated with OWL is SPARQL which also has little traction.
- observationist 2y ago
  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/ 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 effectively trudge through the creation of trillions of little rules and facts needed for an explicit and coherent expert world model, but LLMs definitely can be used for this.
  - zozbot234 2y ago
    You can actually do "inference" or "deduction" over large amounts of data using any old-fashioned RDBMS, and get broadly equal or better performance than the newfangled "graph" based systems. Graph databases may be a clear win for very specialized network analysis, but that is rare in practice.
    - p_l 2y ago
      Graph databases win in flexibility and ease of writing the queries over graphs, honestly. Of course the underlying storage can be (and often is) a bunch of specially prepared relational tables. But the strength in graph databases comes from restating the problem in different way, with query languages targeting the specific problem space. Similarly there are tasks where SQL will be plainly better.
      - zozbot234 2y ago
        > ease of writing the queries over graphs, honestly The SQL standard now includes syntactic sugar for 'Property Graph Query'. Implementations are still in the works AIUI, but can be expected in the reasonably near future.
        p_l 2y ago
        Having seen PGQL, I think I'll stay with SPARQL. And for efficient implementation the database underneath still needs to have extended graph support (in fact, I find it hilarious that Oracle seems to be spearheading it, as they have previously canceled their graph support around 2012 - enough that I wrote about how it was deprecated and removed from support in my thesis in 2014.
- gumby 2y ago
  Err…OpenCyc?
  - Rochus 2y ago
    Unfortunately no longer (officially) available; and only a small subset anyway.
  - mindcrime 2y ago
    Yep. And it may be just a subset, but it's pretty much the answer to "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/therohk/opencyc-kb https://github.com/bovlb/opencyc https://github.com/bovlb/opencyc https://github.com/asanchez75/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 https://en.wikipedia.org/wiki/UMBEL [2]: https://en.wikipedia.org/wiki/Suggested_Upper_Merged_Ontology https://en.wikipedia.org/wiki/Suggested_Upper_Merged_Ontolog... [3]: https://ceur-ws.org/Vol-2050/FOUST_paper_4.pdf https://ceur-ws.org/Vol-2050/FOUST_paper_4.pdf [4]: https://en.wikipedia.org/wiki/Upper_ontology https://en.wikipedia.org/wiki/Upper_ontology
- tunesmith 2y ago
  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/ http://concludia.org/
  - sundarurfriend 2y ago
    Nice! I've wanted to build something like this for a long time. It requires good faith argument construction from both parties, but it's useful to make the possibility available when you do find the small segment of people who can do that.
  - jnwatson 2y ago
    Very cool! I've had this idea for 20 years. I'm glad I didn't get around to making it.
- breck 2y ago
  I tried to make something along these lines (https://truebase.treenotation.org/ https://truebase.treenotation.org/). My approach, Cyc's, and others are fundamentally flawed for the same reason. There's a low level reason why deep nets work and symbolic engines are very bad.
  - eschaton 2y ago
    And what is that reason?
    - breck 2y ago
      The language before language.
      - eschaton 2y ago
        Care to expand on this, provide evidence, or even pointers to what you mean by it?
        breck 2y ago
        Pardon the cliffhanger style. I have begun crafting an explanation, but not sure when it will be ready. But when you recognize that thinking predates symbolic language, and start thinking about what thinking needs, you get closer to the answer.
toisanji 2y ago
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/ https://blog.jtoy.net/understanding-cyc-the-ai-database/
- ImHereToVote 2y ago
  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.
  - chris_st 2y ago
    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.
Rochus 2y ago
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 https://muse.jhu.edu/pub/87/article/853382/pdf Unfortunately paywalled; does anyone have a downloadable copy?
- dmd 2y ago
  https://jumpshare.com/s/X5arOz0ld3AzBGQ47hWf https://jumpshare.com/s/X5arOz0ld3AzBGQ47hWf
  - Rochus 2y ago
    Great, thank you very much!
- famouswaffles 2y ago
  >the hype about LLMs has calmed down The hype of LLMs is not the reason the likes of Cyc have been abandoned.
  - Rochus 2y ago
    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.
    - famouswaffles 2y ago
      >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.
gumby 2y ago
This is a pretty good article. I was one of the first hires on the Cyc project when it started at MCC and was at first responsible for the decision to abandon the Interlisp-D implementation and replace it with one I wrote on Symbolics machines. Yes, back then one person could write the code base, which has long since grown and been ported off those machines. The KB is what matters anyway. I built it so different people could work on the kb simultaneously, which was unusual in those days, even though cloud computing was ubiquitous at PARC (where Doug had been working, and I had too). Neurosymbolic approaches are pretty important and there’s good work going on in that area. I was back in that field myself until I got dragged away to work on the climate. But I’m not sure that manually curated KBs will make much of a difference beyond bootstrapping.
- pfdietz 2y ago
  Is Cyc still implemented in Lisp?
  - mepian 2y ago
    Yes: https://cyc.com/archives/glossary/subl/ https://cyc.com/archives/glossary/subl/ Also see: https://www.youtube.com/watch?v=cMMiaCtOzV0 https://www.youtube.com/watch?v=cMMiaCtOzV0
    - pfdietz 2y ago
      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.
      - dreamcompiler 2y ago
        Franz has a nice RDF triple store. No idea if Cyc uses it but if so that could be a factor.
      - jonathankoren 2y ago
        Allegro has an amazing UI and debugger. Like seriously, every alternative is janky experience that should be embarrassed to exist.
avodonosov 2y ago
Related: https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/ https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/
- radomir_cernoch 2y ago
  OMG, what an archeological discovery!
- mietek 2y ago
  Wow! Thank you for mentioning this!
mtraven 2y ago
I worked on Cyc as a visiting student for a couple of summers; built some visualization tools to help people navigate around the complex graph. But I never was quite sold on the project, some tangential learnings here: https://hyperphor.com/ammdi/alpha-ontologist https://hyperphor.com/ammdi/alpha-ontologist
- optimalsolver 2y ago
  >if they could not come to a consensus, would have to take it before the Master, Doug Lenat, who would think for a bit, maybe draw some diagrams on a whiteboard, and come up with the Right Representation So looks like Cyc did have to fall back on a neural net after all (Lenat's).
blueyes 2y ago
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.
- zopf 2y ago
  I wonder to what degree an LLM could now produce frames/slots/values in the knowledge graph. With so much structure already existing in the Cyc knowledge graph, could those frames act as the crystal seed upon which an LLM could crystallize its latent knowledge about the world from the trillions of tokens it was trained upon?
  - tkgally 2y ago
    I had the same thought. Does anybody know if there have been attempts either to incorporate Cyc-like graphs into LLM training data or to extend such graphs with LLMs?
    - radomir_cernoch 2y ago
      From time to time, I read articles on the boundary between neural nets and knowledge graphs like a recent [1]. Sadly, no mention of Cyc. I'd bet, judging mostly from my failed attempts at playing with OpenCyc around 2009, is that the Cyc has always been too closed and to complex to tinker with. That doesn't play nicely with academic work. When people finish their PhDs and start working for OpenAI, they simply don't have Cyc in their toolbox. [1] https://www.sciencedirect.com/science/article/pii/S0893608023003398?casa_token=9BR_Z2dV39IAAAAA:u6DfBRbwmjnyNSXojCTrKrMvZYDB7LMgFzF6ZtargJuEqrk7dx3l2_zaEG4tPUPVBqOpc5Q33A https://www.sciencedirect.com/science/article/pii/S089360802...
      - viksit 2y ago
        oh i just commented elsewhere in the thread about our work in integrating frames and slots into LSTMs a few years ago! second this.
chx 2y ago
deleted.
- anyfoo 2y ago
  > If Susan goes shopping does her go with her? Is there a typo in that question? Because this does not parse as a sentence in any way for me, and if that's part of the point, I don't understand how. How would a toddler answer this question (except for looking confused like an adult, or maybe making up some nonsense to go with it)? Happy to be told how I missed the obvious! (EDIT: By the way, I don't know why you got downvoted, I certainly didn't.)
  - chx 2y ago
    deleted
    - anyfoo 2y ago
      Oh, I think just fixing the original comment would quite likely have netted you upvotes, if there wasn't anything else wrong with your comment. I think downvoting because of an obvious typo is pretty dumb in the first place.
shrubble 2y ago
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!
- markc 2y ago
  Probably could have driven round trip for under $500!
  - shrubble 2y ago
    I had a 2 door VW Golf... would have needed more space!
    - galaxyLogic 2y ago
      You also would have needed more money for the power-bill
nikolay 2y ago
No, Cyc has not been forgotten; Eurisko has been!
fidesomnes 2y ago
[dead]
viksit 2y ago
from 2015-2019 i was working on a bot company (myra labs) where we were directly inspired by cyc to create knowledge graphs and integrate into LSTMs. the frames, slots and values integrated were learned via a RNN for specific applications. we even created a library for it called keyframe (modeling it after having the programmer specify the bot action states and have the model figure out the dialog in a structured way) - similar to how keyframes in animation work. it would be interesting to resurrect that in the age of LLMs!
ultra_nick 2y ago
I interviewed with them in 2018. They're still kicking as far as I know. They asked me recursive and functional programming questions. I wonder if they've adopted ML yet.
TrevorFSmith 2y ago
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.
- nextos 2y ago
  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.
  - jimmySixDOF 2y ago
    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/ https://mindaptiv.com/intro-to-wantware/
  - riku_iki 2y ago
    > 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.
    - nextos 2y ago
      I was thinking more in terms of a pharma startup.
- deleted 2y ago
  [deleted]
acutesoftware 2y ago
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.
ragebol 2y ago
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 :).
- mindcrime 2y ago
  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.
  - ragebol 2y ago
    Too obvious indeed. Can I read anywhere about what you're working on? What other approaches exist?
    - mindcrime 2y ago
      > 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 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://neurosymbolic.github.io/nsss2023/ https://www.neurosymbolic.org/summerschool.html https://www.neurosymbolic.org/summerschool.html (2022)
- brendonwong 2y ago
  This is a significant part of my vision for Web 10! https://www.web10.ai/p/web-10-in-under-10-minutes https://www.web10.ai/p/web-10-in-under-10-minutes One of the immediate things I'm working on is a text to knowledge graph system. Yohei (creator of BabyAGI) is also working on text to knowledge graphs: https://twitter.com/yoheinakajima/status/1769019899245158648 https://twitter.com/yoheinakajima/status/1769019899245158648. LlamaIndex has a basic implementation. This isn't quite connecting the system to an automated reasoner though. There is some research in this area, like: https://news.ycombinator.com/item?id=35735375 https://news.ycombinator.com/item?id=35735375 Cyc + LLMs is vaguely related to more advanced "cognitive architectures" for AI, for instance see the world model in Davidad's architecture, which LLMs can be used to help build: https://www.lesswrong.com/posts/jRf4WENQnhssCb6mJ/davidad-s-bold-plan-for-alignment-an-in-depth-explanation https://www.lesswrong.com/posts/jRf4WENQnhssCb6mJ/davidad-s-...
astrange 2y ago
I have a vague memory in the 90s of a website that was trying to collect crowdsourced somewhat-structured facts about everything that would be used to build GOFAI. Was trying to find it the other day and AI searches suggested Cyc; I feel like that's not it, but maybe it was? (It definitely wasn't Everything2.)
- dredmorbius 2y ago
  Portland Pattern Repository? <https://c2.com/ppr/ https://c2.com/ppr/> <https://en.wikipedia.org/wiki/Portland_Pattern_Repository https://en.wikipedia.org/wiki/Portland_Pattern_Repository>
- DonaldFisk 2y ago
  It might have been one of these two projects https://en.wikipedia.org/wiki/Open_Mind_Common_Sense https://en.wikipedia.org/wiki/Open_Mind_Common_Sense https://en.wikipedia.org/wiki/Mindpixel https://en.wikipedia.org/wiki/Mindpixel The leaders of both these projects committed suicide.
  - astrange 2y ago
    GAC! Yeah, it was Mindpixel. I guess that's what happens when you learn too many facts.
carlsborg 2y ago
The Cyc project proposed the idea of software "assistants" : formally represented knowledge based on a shared ontology, reasoning systems that can draw on that knowledge, handle tasks and anticipate the need to perform them.[1] The lead author on [1] is Kathy Panton who has no publications after that and zero internet presence as far as i can tell. [1] Common Sense Reasoning – From Cyc to Intelligent Assistant https://iral.cs.umbc.edu/Pubs/FromCycToIntelligentAssistant-IJHCS-LNAI3864.pdf https://iral.cs.umbc.edu/Pubs/FromCycToIntelligentAssistant-...
SilverSlash 2y ago
I first heard about Cyc's creator Douglas Lenat a few months back when I watched an old talk by Richard Feynman. https://youtu.be/ipRvjS7q1DI?si=fEU1zd6u79Oe4SgH&t=675 https://youtu.be/ipRvjS7q1DI?si=fEU1zd6u79Oe4SgH&t=675
- dredmorbius 2y ago
  <https://yewtu.be/watch?v=ipRvjS7q1DI&t=675 https://yewtu.be/watch?v=ipRvjS7q1DI&t=675>
blacklion 2y ago
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?..
- brain_elision 2y ago
  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.
- chris_st 2y ago
  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-appear-to-work/ https://aaai.org/papers/00236-aaai83-059-why-am-and-eurisko-...
HarHarVeryFunny 2y ago
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?
mindcrime 2y ago
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?
PeterStuer 2y ago
Cyc was the last remaining GOFAI champion back in the day when everyone in AI was going the 'Nouvelle AI' route. Eventually the approach would be rediscovered (but not recuperated) by the database field desparate for 'new' research topics. We might see a revival now that transformets can front and backend the hard edges of the knowledge based tech, but it will remain to be seen wether scaled monolyth systems like Cyc are the right way to pair.
bilsbie 2y ago
Could cyc data be used as an anti hallucination tool for LLM’s? Or for quality checks during training?
bshanks 2y ago
The first thing to do is to put LLMs to work to generate large knowledge bases of commonsense knowledge in symbolic machine-readable formats that Cyc-like projects can consume.

287 points by iafisher 2y ago

Related Stephen Wolfram's note when Doug Lenat passed away [0] [0] https://writings.stephenwolfram.com/2023/09/remembering-doug-lenat-1950-2023-and-his-quest-to-capture-the-world-with-logic/ https://writings.stephenwolfram.com/2023/09/remembering-doug...

zozbot234 2y ago
Discussed https://news.ycombinator.com/item?id=37402925 https://news.ycombinator.com/item?id=37402925 see also https://news.ycombinator.com/item?id=37354000 https://news.ycombinator.com/item?id=37354000

mepian 2y ago

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?

nextos 2y ago
There are some pretty huge ontology DBs in molecular biology, like GO or Reactome. But they have never truly exploited logic-based inference, except for some small academic efforts.
- jerven 2y ago
  I think that GO with GO-CAM is definitely going that way. Basic GO is rather simple and can't infer that much (as in GO by itself has low classification or inference logic build in). Uberon, for anatomy, does use a lot of OWL power and shows that the logic-based inference can help a lot. Reactome, is a graph, because that is the domain. But technically it does little with that fact (In my disappointed opinion). Given that GO and Reactome are also relatively small academic efforts in general...
niviksha 2y ago
There are a few symbolic logic entailment engines that run atop OWL the Web Ontology Language, some flavors of which which are rough equivalent of Cycs KBs. The challenge though is the underlying approaches are computationally hard so nobody really uses them in practice, plus the retrieval language associated with OWL is SPARQL which also has little traction.
observationist 2y ago
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/ 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 effectively trudge through the creation of trillions of little rules and facts needed for an explicit and coherent expert world model, but LLMs definitely can be used for this.
- zozbot234 2y ago
  You can actually do "inference" or "deduction" over large amounts of data using any old-fashioned RDBMS, and get broadly equal or better performance than the newfangled "graph" based systems. Graph databases may be a clear win for very specialized network analysis, but that is rare in practice.
  - p_l 2y ago
    Graph databases win in flexibility and ease of writing the queries over graphs, honestly. Of course the underlying storage can be (and often is) a bunch of specially prepared relational tables. But the strength in graph databases comes from restating the problem in different way, with query languages targeting the specific problem space. Similarly there are tasks where SQL will be plainly better.
    - zozbot234 2y ago
      > ease of writing the queries over graphs, honestly The SQL standard now includes syntactic sugar for 'Property Graph Query'. Implementations are still in the works AIUI, but can be expected in the reasonably near future.
      - p_l 2y ago
        Having seen PGQL, I think I'll stay with SPARQL. And for efficient implementation the database underneath still needs to have extended graph support (in fact, I find it hilarious that Oracle seems to be spearheading it, as they have previously canceled their graph support around 2012 - enough that I wrote about how it was deprecated and removed from support in my thesis in 2014.
gumby 2y ago
Err…OpenCyc?
- Rochus 2y ago
  Unfortunately no longer (officially) available; and only a small subset anyway.
- mindcrime 2y ago
  Yep. And it may be just a subset, but it's pretty much the answer to "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/therohk/opencyc-kb https://github.com/bovlb/opencyc https://github.com/bovlb/opencyc https://github.com/asanchez75/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 https://en.wikipedia.org/wiki/UMBEL [2]: https://en.wikipedia.org/wiki/Suggested_Upper_Merged_Ontology https://en.wikipedia.org/wiki/Suggested_Upper_Merged_Ontolog... [3]: https://ceur-ws.org/Vol-2050/FOUST_paper_4.pdf https://ceur-ws.org/Vol-2050/FOUST_paper_4.pdf [4]: https://en.wikipedia.org/wiki/Upper_ontology https://en.wikipedia.org/wiki/Upper_ontology
tunesmith 2y ago
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/ http://concludia.org/
- sundarurfriend 2y ago
  Nice! I've wanted to build something like this for a long time. It requires good faith argument construction from both parties, but it's useful to make the possibility available when you do find the small segment of people who can do that.
- jnwatson 2y ago
  Very cool! I've had this idea for 20 years. I'm glad I didn't get around to making it.
breck 2y ago
I tried to make something along these lines (https://truebase.treenotation.org/ https://truebase.treenotation.org/). My approach, Cyc's, and others are fundamentally flawed for the same reason. There's a low level reason why deep nets work and symbolic engines are very bad.
- eschaton 2y ago
  And what is that reason?
  - breck 2y ago
    The language before language.
    - eschaton 2y ago
      Care to expand on this, provide evidence, or even pointers to what you mean by it?
      - breck 2y ago
        Pardon the cliffhanger style. I have begun crafting an explanation, but not sure when it will be ready. But when you recognize that thinking predates symbolic language, and start thinking about what thinking needs, you get closer to the answer.

toisanji 2y ago

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/ https://blog.jtoy.net/understanding-cyc-the-ai-database/

ImHereToVote 2y ago
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.
- chris_st 2y ago
  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.

Rochus 2y ago

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 https://muse.jhu.edu/pub/87/article/853382/pdf Unfortunately paywalled; does anyone have a downloadable copy?

dmd 2y ago
https://jumpshare.com/s/X5arOz0ld3AzBGQ47hWf https://jumpshare.com/s/X5arOz0ld3AzBGQ47hWf
- Rochus 2y ago
  Great, thank you very much!
famouswaffles 2y ago
>the hype about LLMs has calmed down The hype of LLMs is not the reason the likes of Cyc have been abandoned.
- Rochus 2y ago
  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.
  - famouswaffles 2y ago
    >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.

gumby 2y ago

This is a pretty good article. I was one of the first hires on the Cyc project when it started at MCC and was at first responsible for the decision to abandon the Interlisp-D implementation and replace it with one I wrote on Symbolics machines. Yes, back then one person could write the code base, which has long since grown and been ported off those machines. The KB is what matters anyway. I built it so different people could work on the kb simultaneously, which was unusual in those days, even though cloud computing was ubiquitous at PARC (where Doug had been working, and I had too). Neurosymbolic approaches are pretty important and there’s good work going on in that area. I was back in that field myself until I got dragged away to work on the climate. But I’m not sure that manually curated KBs will make much of a difference beyond bootstrapping.

pfdietz 2y ago
Is Cyc still implemented in Lisp?
- mepian 2y ago
  Yes: https://cyc.com/archives/glossary/subl/ https://cyc.com/archives/glossary/subl/ Also see: https://www.youtube.com/watch?v=cMMiaCtOzV0 https://www.youtube.com/watch?v=cMMiaCtOzV0
  - pfdietz 2y ago
    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.
    - dreamcompiler 2y ago
      Franz has a nice RDF triple store. No idea if Cyc uses it but if so that could be a factor.
    - jonathankoren 2y ago
      Allegro has an amazing UI and debugger. Like seriously, every alternative is janky experience that should be embarrassed to exist.

avodonosov 2y ago

Related: https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/ https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/

radomir_cernoch 2y ago
OMG, what an archeological discovery!
mietek 2y ago
Wow! Thank you for mentioning this!

mtraven 2y ago

I worked on Cyc as a visiting student for a couple of summers; built some visualization tools to help people navigate around the complex graph. But I never was quite sold on the project, some tangential learnings here: https://hyperphor.com/ammdi/alpha-ontologist https://hyperphor.com/ammdi/alpha-ontologist

optimalsolver 2y ago
>if they could not come to a consensus, would have to take it before the Master, Doug Lenat, who would think for a bit, maybe draw some diagrams on a whiteboard, and come up with the Right Representation So looks like Cyc did have to fall back on a neural net after all (Lenat's).

blueyes 2y ago

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.

zopf 2y ago
I wonder to what degree an LLM could now produce frames/slots/values in the knowledge graph. With so much structure already existing in the Cyc knowledge graph, could those frames act as the crystal seed upon which an LLM could crystallize its latent knowledge about the world from the trillions of tokens it was trained upon?
- tkgally 2y ago
  I had the same thought. Does anybody know if there have been attempts either to incorporate Cyc-like graphs into LLM training data or to extend such graphs with LLMs?
  - radomir_cernoch 2y ago
    From time to time, I read articles on the boundary between neural nets and knowledge graphs like a recent [1]. Sadly, no mention of Cyc. I'd bet, judging mostly from my failed attempts at playing with OpenCyc around 2009, is that the Cyc has always been too closed and to complex to tinker with. That doesn't play nicely with academic work. When people finish their PhDs and start working for OpenAI, they simply don't have Cyc in their toolbox. [1] https://www.sciencedirect.com/science/article/pii/S0893608023003398?casa_token=9BR_Z2dV39IAAAAA:u6DfBRbwmjnyNSXojCTrKrMvZYDB7LMgFzF6ZtargJuEqrk7dx3l2_zaEG4tPUPVBqOpc5Q33A https://www.sciencedirect.com/science/article/pii/S089360802...
    - viksit 2y ago
      oh i just commented elsewhere in the thread about our work in integrating frames and slots into LSTMs a few years ago! second this.

chx 2y ago

deleted.

anyfoo 2y ago
> If Susan goes shopping does her go with her? Is there a typo in that question? Because this does not parse as a sentence in any way for me, and if that's part of the point, I don't understand how. How would a toddler answer this question (except for looking confused like an adult, or maybe making up some nonsense to go with it)? Happy to be told how I missed the obvious! (EDIT: By the way, I don't know why you got downvoted, I certainly didn't.)
- chx 2y ago
  deleted
  - anyfoo 2y ago
    Oh, I think just fixing the original comment would quite likely have netted you upvotes, if there wasn't anything else wrong with your comment. I think downvoting because of an obvious typo is pretty dumb in the first place.

shrubble 2y ago

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!

markc 2y ago
Probably could have driven round trip for under $500!
- shrubble 2y ago
  I had a 2 door VW Golf... would have needed more space!
  - galaxyLogic 2y ago
    You also would have needed more money for the power-bill

nikolay 2y ago

No, Cyc has not been forgotten; Eurisko has been!

fidesomnes 2y ago

[dead]

viksit 2y ago

from 2015-2019 i was working on a bot company (myra labs) where we were directly inspired by cyc to create knowledge graphs and integrate into LSTMs. the frames, slots and values integrated were learned via a RNN for specific applications. we even created a library for it called keyframe (modeling it after having the programmer specify the bot action states and have the model figure out the dialog in a structured way) - similar to how keyframes in animation work. it would be interesting to resurrect that in the age of LLMs!

ultra_nick 2y ago

I interviewed with them in 2018. They're still kicking as far as I know. They asked me recursive and functional programming questions. I wonder if they've adopted ML yet.

TrevorFSmith 2y ago

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.

nextos 2y ago
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.
- jimmySixDOF 2y ago
  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/ https://mindaptiv.com/intro-to-wantware/
- riku_iki 2y ago
  > 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.
  - nextos 2y ago
    I was thinking more in terms of a pharma startup.
deleted 2y ago
[deleted]

acutesoftware 2y ago

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.

ragebol 2y ago

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 :).

mindcrime 2y ago
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.
- ragebol 2y ago
  Too obvious indeed. Can I read anywhere about what you're working on? What other approaches exist?
  - mindcrime 2y ago
    > 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 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://neurosymbolic.github.io/nsss2023/ https://www.neurosymbolic.org/summerschool.html https://www.neurosymbolic.org/summerschool.html (2022)
brendonwong 2y ago
This is a significant part of my vision for Web 10! https://www.web10.ai/p/web-10-in-under-10-minutes https://www.web10.ai/p/web-10-in-under-10-minutes One of the immediate things I'm working on is a text to knowledge graph system. Yohei (creator of BabyAGI) is also working on text to knowledge graphs: https://twitter.com/yoheinakajima/status/1769019899245158648 https://twitter.com/yoheinakajima/status/1769019899245158648. LlamaIndex has a basic implementation. This isn't quite connecting the system to an automated reasoner though. There is some research in this area, like: https://news.ycombinator.com/item?id=35735375 https://news.ycombinator.com/item?id=35735375 Cyc + LLMs is vaguely related to more advanced "cognitive architectures" for AI, for instance see the world model in Davidad's architecture, which LLMs can be used to help build: https://www.lesswrong.com/posts/jRf4WENQnhssCb6mJ/davidad-s-bold-plan-for-alignment-an-in-depth-explanation https://www.lesswrong.com/posts/jRf4WENQnhssCb6mJ/davidad-s-...

astrange 2y ago

I have a vague memory in the 90s of a website that was trying to collect crowdsourced somewhat-structured facts about everything that would be used to build GOFAI. Was trying to find it the other day and AI searches suggested Cyc; I feel like that's not it, but maybe it was? (It definitely wasn't Everything2.)

dredmorbius 2y ago
Portland Pattern Repository? <https://c2.com/ppr/ https://c2.com/ppr/> <https://en.wikipedia.org/wiki/Portland_Pattern_Repository https://en.wikipedia.org/wiki/Portland_Pattern_Repository>
DonaldFisk 2y ago
It might have been one of these two projects https://en.wikipedia.org/wiki/Open_Mind_Common_Sense https://en.wikipedia.org/wiki/Open_Mind_Common_Sense https://en.wikipedia.org/wiki/Mindpixel https://en.wikipedia.org/wiki/Mindpixel The leaders of both these projects committed suicide.
- astrange 2y ago
  GAC! Yeah, it was Mindpixel. I guess that's what happens when you learn too many facts.

carlsborg 2y ago

The Cyc project proposed the idea of software "assistants" : formally represented knowledge based on a shared ontology, reasoning systems that can draw on that knowledge, handle tasks and anticipate the need to perform them.[1] The lead author on [1] is Kathy Panton who has no publications after that and zero internet presence as far as i can tell. [1] Common Sense Reasoning – From Cyc to Intelligent Assistant https://iral.cs.umbc.edu/Pubs/FromCycToIntelligentAssistant-IJHCS-LNAI3864.pdf https://iral.cs.umbc.edu/Pubs/FromCycToIntelligentAssistant-...

SilverSlash 2y ago

I first heard about Cyc's creator Douglas Lenat a few months back when I watched an old talk by Richard Feynman. https://youtu.be/ipRvjS7q1DI?si=fEU1zd6u79Oe4SgH&t=675 https://youtu.be/ipRvjS7q1DI?si=fEU1zd6u79Oe4SgH&t=675

dredmorbius 2y ago
<https://yewtu.be/watch?v=ipRvjS7q1DI&t=675 https://yewtu.be/watch?v=ipRvjS7q1DI&t=675>

blacklion 2y ago

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?..

brain_elision 2y ago
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.
chris_st 2y ago
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-appear-to-work/ https://aaai.org/papers/00236-aaai83-059-why-am-and-eurisko-...

HarHarVeryFunny 2y ago

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?

mindcrime 2y ago

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?

PeterStuer 2y ago

Cyc was the last remaining GOFAI champion back in the day when everyone in AI was going the 'Nouvelle AI' route. Eventually the approach would be rediscovered (but not recuperated) by the database field desparate for 'new' research topics. We might see a revival now that transformets can front and backend the hard edges of the knowledge based tech, but it will remain to be seen wether scaled monolyth systems like Cyc are the right way to pair.

bilsbie 2y ago

Could cyc data be used as an anti hallucination tool for LLM’s? Or for quality checks during training?

bshanks 2y ago

The first thing to do is to put LLMs to work to generate large knowledge bases of commonsense knowledge in symbolic machine-readable formats that Cyc-like projects can consume.