[HN Gopher] Cyc: History's Forgotten AI Project
___________________________________________________________________
Cyc: History's Forgotten AI Project
Author : iafisher
Score : 263 points
Date : 2024-04-17 19:46 UTC (1 days 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.
| jerven wrote:
| 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 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.
| totetsu wrote:
| Thanks for the correction
| riku_iki wrote:
| > 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.
| justinhj wrote:
| Did you mean Datalog here?
| gumby wrote:
| Err...OpenCyc?
| Rochus wrote:
| Unfortunately no longer (officially) available; and only a
| small subset anyway.
| mindcrime wrote:
| 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/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_Ont
| olog...
|
| [3]: https://ceur-ws.org/Vol-2050/FOUST_paper_4.pdf
|
| [4]: https://en.wikipedia.org/wiki/Upper_ontology
| tunesmith wrote:
| 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/
| sundarurfriend wrote:
| 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 wrote:
| Very cool! I've had this idea for 20 years. I'm glad I didn't
| get around to making it.
| breck wrote:
| I tried to make something along these lines
| (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.
| 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/
| ImHereToVote wrote:
| I used to volunteer inputting data into Cyc back in the day.
| And I get massive deja vu with current LLM's. I remember that
| the system ended up with an obsession with HVAC systems lol.
| chris_st wrote:
| 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 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?
| dmd wrote:
| https://jumpshare.com/s/X5arOz0ld3AzBGQ47hWf
| Rochus wrote:
| Great, thank you very much!
| og_kalu wrote:
| >the hype about LLMs has calmed down
|
| The hype of LLMs is not the reason the likes of Cyc have been
| abandoned.
| Rochus wrote:
| 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.
| og_kalu wrote:
| >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.
| eru wrote:
| > 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.)
| radomir_cernoch wrote:
| I very much agree about the A* idea, but this idea
|
| > Tangent: that's very similar to philosophy.
|
| doesn't click with me. Maybe, could your elaborate a bit,
| or provide an example, please?
| Rochus wrote:
| Curve-fitting has demonstrated impressive results, but
| it's definitely not the end of science.
| 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.
| dreamcompiler wrote:
| Franz has a nice RDF triple store. No idea if Cyc uses it
| but if so that could be a factor.
| jonathankoren wrote:
| Allegro has an amazing UI and debugger. Like seriously,
| every alternative is janky experience that should be
| embarrassed to exist.
| guenthert wrote:
| Out of curiosity, which implementation(s) did you have in
| mind and why would it be desirable to migrate a large
| project there?
| pfdietz wrote:
| Steel Bank Common Lisp is the most performant (by speed
| of compiled code) and stable open source implementation,
| and arguably the most standard compliant and bug free of
| any Common Lisp implementation, free or otherwise. It
| also is available free of charge.
|
| I mostly wanted to know of any technical obstacles so
| SBCL could be improved. If I had to wildly guess, maybe
| GC performance? SBCL was behind ACL on that many years
| ago (on both speed and physical memory requirements) the
| last time I made a comparison.
| lispm wrote:
| Maybe it's not "technical issues", but features and
| support? Allegro CL has a proven GUI toolkit, for
| example, and now they moved it into the web browser.
|
| FYI: here are the release notes of the recently release
| Allegro CL 11.0:
| https://franz.com/support/documentation/current/release-
| note...
|
| IIRC, Cyc gets delivered on other platforms&languages (C,
| JVM, ... ?). Would be interesting to know what they use
| for deployment/delivery.
| guenthert wrote:
| > which was unusual in those days, even though cloud computing
| was ubiquitous at PARC
|
| I don't want to rob you of your literary freedom, but that
| threw me off. Mainframes were meant, yes?
| gumby wrote:
| > Mainframes were meant, yes?
|
| No not at all. We're talking early-mid 1980s so people in the
| research community (at least at the leading institutions)
| were by then pretty used to what's called cloud computing
| these days. In fact the term "cloud" for independent
| resources you could call upon without knowing the underlying
| architecture came from the original Internet papers (talking
| originally about routing, and then the DNS) in the late 70s
|
| So for example the mail or file or other services at PARC
| just lived in the network; you did the equivalent of an
| anycast to check your mail or look for a file. These had
| standardized APIs so it didn't matter if you were running
| Smalltalk, Interlisp-D, or Cedar/Mesa you just had a local
| window into a general computing space, just as you do today.
|
| Most was on the LAN, of course, as the ARPANET was pretty
| slow. But when we switched to TCP/IP the LAN/WAN boundaries
| became transparent and instead of manually bouncing through
| different machines I could casually check my mail at MIT from
| my desk at PARC.
|
| Lispms were slightly less flexible in this regard back then,
| but then again Ethernet started at PARC. But even in the late
| 70s it wasn't weird to have part of your computation run on a
| remote machine you weren't logged into interactively.
|
| The Unix guys at Berkeley eventually caught up with this
| (just look at the original sockets interface, very un-unixy)
| but they didn't quite get it: I always laughed when I saw a
| sun machine running sendmail rather than trusting the network
| to do the right thing on its behalf. By the time Sun was
| founded that felt paleolithic to me.
|
| Because I didn't start computing until the late 70s I pretty
| much missed the whole removable media thing and was pretty
| much always network connected.
| p_l wrote:
| Sockets were essentially a crash development program to
| deal with TOPS-20 being discontinued by DEC
| stcredzero wrote:
| _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_
|
| A coworker of mine who used to work at Symbolics told me that
| this was endemic with Lisp development back in the day. Some
| customers would think there was a team of 300 doing the OS
| software at Symbolics. It was just 10 programmers.
| avodonosov wrote:
| Related: https://blog.funcall.org//lisp/2024/03/22/eurisko-lives/
| radomir_cernoch wrote:
| OMG, what an archeological discovery!
| mietek wrote:
| Wow! Thank you for mentioning this!
| 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
| optimalsolver wrote:
| >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 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.
| zopf wrote:
| 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 wrote:
| 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 wrote:
| 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/S0893
| 60802...
| viksit wrote:
| oh i just commented elsewhere in the thread about our
| work in integrating frames and slots into LSTMs a few
| years ago! second this.
| thesz wrote:
| There are lattice-based RNNs applied as language models.
|
| In fact, if you have a graph and a path-weighting model
| (RNN, TDCNN or Transformer), you can use beam search to
| evaluate paths through graphs.
| mike_hearn wrote:
| The problem is not one of KB size. The Cyc KB is huge. The
| problem is that the underlying inferencing algorithms don't
| scale whereas the transformer algorithm does.
| breck wrote:
| 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.
| xpe wrote:
| > 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.
| og_kalu wrote:
| 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.
| mepian wrote:
| They should handle the problem of hallucinations then.
| og_kalu wrote:
| Bigger models hallucinate less.
|
| and we don't call it hallucinations but gofai mispredicts
| plenty.
| eru wrote:
| 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.
| xpe wrote:
| > but even still few people can explain the _root_ reason
| why.
|
| _The_ (one) root reason? Ok, I'll bite.
|
| But you need to define your claim. What application?
| galaxyLogic wrote:
| 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.
| genrilz wrote:
| 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
| galaxyLogic wrote:
| Interesting, from the article:
|
| "Mathematical framework and rules of paraconsistent logic
| have been proposed as the activation function of an
| artificial neuron in order to build a neural network"
| xpe wrote:
| The comment above misses the point in at least four ways. (1)
| Being aware of history is not the same as endorsing it. (2)
| Knowledge graphs are useful for many applications. (3) How
| narrow of a mindset and how much hindsight bias must one have
| to claim that Lenat wasted decades of his life? (4) Don't
| forget to think about this in context about what was happening
| in the field of AI.
| thesz wrote:
| 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.
| goatlover wrote:
| 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.
| eru wrote:
| 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.)
| thesz wrote:
| Usually, LLM's output gets passed through beam search [1]
| which is as symbolic as one can get.
|
| [1] https://www.width.ai/post/what-is-beam-search
|
| It is possible to even have 3-gram model to output better
| text predictions if you combine it with the beam search.
| eru wrote:
| See https://news.ycombinator.com/item?id=40073039 for a
| discussion.
| thesz wrote:
| I guess it is funding. Compare funding of Google+Meta to
| what was/is available to Cyc.
|
| Cyc was able to produce an impact, I keep pointing to
| MathCraft [1] which, at 2017, did not have a rival in the
| neural AI.
|
| [1] https://en.wikipedia.org/wiki/Cyc#MathCraft
| Barrin92 wrote:
| Because the goal of Cyc was always to build a genuinely
| generally intelligent common sense reasoning system and
| that is a non-sexy long term research project. Being great
| at chess isn't a measure that's relevant for a project like
| this, Stockfish is superhuman at chess.
| riku_iki wrote:
| > Why didn't it ever have the impact that LLMs are having
| now?
|
| Google has its own Knowledge Graph, with billions of daily
| views, which is wider but more shallow version of Cyc. It
| is unclear if LLM user facing impact surpassed that
| project.
| richardatlarge wrote:
| We are living in the future /
|
| I'll tell you how I know /
|
| I read it in the paper /
|
| Fifteen years ago -
|
| (John Prine)
| mindcrime wrote:
| _They are brittle in the face of change, and useless if they
| cannot represent the underlying changes of reality._
|
| FWIW, KG's don't _have_ to be brittle. Or, at least they don 't
| have to be _as_ brittle as they 've historically been. There
| are approaches (like PROWL[1]) to making graphs probabilistic
| so that they're asserting subjective beliefs about statements,
| instead of absolute statements. And then the strength of those
| beliefs can increase or decrease in response to new evidence
| (per Bayes Theorem). Probably the biggest problem with this
| stuff is that it tends to be crazy computationally expensive.
|
| Still, there's always the chance of an algorithmic breakthrough
| or just hardware improvements bringing some of this stuff into
| the real of practical.
|
| [1]: https://www.pr-owl.org/
| chx wrote:
| deleted.
| anyfoo wrote:
| > 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 wrote:
| deleted
| anyfoo wrote:
| 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 wrote:
| 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 wrote:
| Probably could have driven round trip for under $500!
| shrubble wrote:
| I had a 2 door VW Golf... would have needed more space!
| galaxyLogic wrote:
| You also would have needed more money for the power-bill
| nikolay wrote:
| No, Cyc has not been forgotten; Eurisko has been!
| viksit wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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/
| riku_iki wrote:
| > 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.
| acutesoftware wrote:
| 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 wrote:
| 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 wrote:
| _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 wrote:
| Too obvious indeed. Can I read anywhere about what you're
| working on? What other approaches exist?
| mindcrime wrote:
| > 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)
| astrange wrote:
| 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 wrote:
| Portland Pattern Repository?
|
| <https://c2.com/ppr/>
|
| <https://en.wikipedia.org/wiki/Portland_Pattern_Repository>
| DonaldFisk wrote:
| It might have been one of these two projects
|
| https://en.wikipedia.org/wiki/Open_Mind_Common_Sense
|
| https://en.wikipedia.org/wiki/Mindpixel
|
| The leaders of both these projects committed suicide.
| astrange wrote:
| GAC! Yeah, it was Mindpixel.
|
| I guess that's what happens when you learn too many facts.
| carlsborg wrote:
| 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-...
| SilverSlash wrote:
| 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
| dredmorbius wrote:
| <https://yewtu.be/watch?v=ipRvjS7q1DI&t=675>
| blacklion wrote:
| 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 wrote:
| 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 wrote:
| 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-...
| og_kalu wrote:
| >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
| hello_computer wrote:
| Your article is a review of one language model (GPT-4) in
| diagnostics, while the original comment was an inquiry about
| _world_ models.
| hello_computer wrote:
| I've read similar things about image models from 12 years ago
| beating the pants off most radiologists. I think the difference
| is that most writers, illustrators, musicians, drivers, etc.
| eke out a marginal living, while radiologists have enough
| reserves to fight back. The " _move fast and break things_ "
| crowd in silicon valley isn't going to undertake that fight
| while there's still so much low-hanging fruit, ripe for the
| harvest.
| BlueTemplar wrote:
| > Cyc was used by the Cleveland Clinic for answering _ad hoc_
| questions from medical researchers; it reduced the time from as
| long as a month of manual back-and-forth between medical and
| database experts, to less than an hour.
| mietek wrote:
| Looks like we can now finally experiment with EURISKO
| ourselves:
|
| https://news.ycombinator.com/item?id=40070667
| HarHarVeryFunny wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| Could cyc data be used as an anti hallucination tool for LLM's?
|
| Or for quality checks during training?
| bshanks wrote:
| 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.
___________________________________________________________________
(page generated 2024-04-18 23:01 UTC)