[HN Gopher] Cyc: History's Forgotten AI Project
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Cyc: History's Forgotten AI Project
Author : iafisher
Score : 71 points
Date : 2024-04-17 19:46 UTC (3 hours ago)
(HTM) web link (outsiderart.substack.com)
(TXT) w3m dump (outsiderart.substack.com)
| rhodin wrote:
| Related Stephen Wolfram's note when Doug Lenat passed away [0]
|
| [0] https://writings.stephenwolfram.com/2023/09/remembering-
| doug...
| zozbot234 wrote:
| Discussed https://news.ycombinator.com/item?id=37402925 see
| also https://news.ycombinator.com/item?id=37354000
| mepian wrote:
| 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 wrote:
| 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.
| niviksha wrote:
| 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 wrote:
| 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 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 wrote:
| 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 wrote:
| 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 wrote:
| > 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 wrote:
| 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.
| totetsu wrote:
| Every time I try to write a query for GitHub's graphql
| API I lose a few hours and go back to rest. May be it's
| easy if all the edges and inputs are actually implemented
| in ways you would expect.
| p_l wrote:
| GraphQL isn't exactly a proper graph database query
| language. The name IIRC comes from Facebook Graph API,
| and the language isn't actually designed as graph
| database interface.
| gumby wrote:
| Err...OpenCyc?
| Rochus wrote:
| Unfortunately no longer (officially) available; and only a
| small subset anyway.
| toisanji wrote:
| 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/
| Rochus wrote:
| 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?
| gumby wrote:
| 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 wrote:
| Is Cyc still implemented in Lisp?
| mepian wrote:
| Yes: https://cyc.com/archives/glossary/subl/
|
| Also see: https://www.youtube.com/watch?v=cMMiaCtOzV0
| pfdietz wrote:
| 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.
| avodonosov wrote:
| Related: https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/
| mtraven wrote:
| 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
| blueyes wrote:
| 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.
| chx wrote:
| There's a lot more to the birth of CyC than what's described
| here.
|
| As far as I know Lenat basically made a 180 degree turn when
| faced with such questions such as If Susan goes shopping does her
| go with her? which a human toddler can answer with ease but the
| kind of AI systems which existed back then could not possibly
| deal with it -- unless this kind of knowledge was specified to
| them. I am surprised this is called "forgotten" or "a cautionary
| tale of tremendous effort wasted on a misguided approach". In a
| world where plausible bullshit generators are hyped to the sky an
| actual fact and inference database is anything but misguided.
|
| Make no mistake: that's the only thing LLMs are good for. As
| https://hachyderm.io/@inthehands/112006855076082650 explains
|
| > You might be surprised to learn that I actually think LLMs have
| the potential to be not only fun but genuinely useful. "Show me
| some bullshit that would be typical in this context" can be a
| genuinely helpful question to have answered, in code and in
| natural language -- for brainstorming, for seeing common
| conventions in an unfamiliar context, for having something crappy
| to react to.
|
| > Alas, that does not remotely resemble how people are pitching
| this technology.
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