--- Stephen Reed <[EMAIL PROTECTED]> wrote: > I worked at Cycorp when the FACTory game was developed. The examples below > do not reveal Cyc's knowledge of the assertions connecting these disparate > concepts, rather most show that the argument constraints of the terms > compared are rather overly generalized. The exception is the example "Most > BTU dozer blades are wider than most T-64 medium tanks." in which both > concepts are specializations of Platform-Military. Download and examine > concepts in OpenCyc and Cyc's world model (or lack thereof by your > standards) will be readily apparent. You need ResearchCyc which has no > license fee for research purposes, in order to evaluate its language model. > -Steve
Thanks. I did take another look at Cyc, at least this talk by Lenat at Google. http://video.google.com/videoplay?docid=-7704388615049492068 In spite of Cyc's lack of success at AGI (so far), it is still the biggest repository of common sense knowledge. He explains how Cyc had tried machine learning approaches to acquiring such knowledge and why they failed. They knew early on that it would require a 1000 person-year effort to develop the knowledge base and proceeded anyway. Cyc has 3.2 million assertions, 300,000 concepts and 16,000 relations (is-a, contains, etc). They tried very hard to "simplfy" the knowledge base, to keep these numbers small. Cyc is planning a Web interface to its knowledge base. If they make something useful, a 1000 person-year effort is nothing. Lenat briefly mentions "Sergey's (one of Google's founders) goal of solving AI by 2020". I think if Google and Cyc work together on this, they will succeed. > > ----- Original Message ---- > From: Matt Mahoney <[EMAIL PROTECTED]> > To: [email protected] > Sent: Sunday, January 14, 2007 3:14:07 PM > Subject: Re: [agi] Project proposal: MindPixel 2 > > --- Gabriel R <[EMAIL PROTECTED]> wrote: > > Also, if you can think of any way to turn the knowledge-entry process into > a > > fun game or competition, go for it. I've been told by a few people > working > > on similar projects that making the knowledge-providing process engaging > and > > fun for visitors ended up being a lot more important (and difficult) than > > they'd expected. > > Cyc has a game like this called FACTory at http://www.cyc.com/ > It's purpose is to help refine its knowledge base. It presents statements > and > asks you to rate them as true, false, don't know or doesn't make sense. For > example. > > - Most shirts are heavier than most appendixes. > - Pages are typically located in HVAC Chem Bio facilities. > - Terminals are typically located in studies. > - People perform or are involved in paying a mortgage more frequenty than > they > perform or are involved in overbearing. > - Most BTU dozer blades are wider than most T-64 medium tanks. > > The game exposes Cyc's shortcomings pretty quickly. Cyc seems to lack a > world > model and a language model. Sentences seem to be constructed by relating > common properties of unrelated objects. The set of common properties is > fairly small: size, weight, cost, frequency (for events), containment, etc. > There does not seem to be any sense that Cyc understands the purpose or > function of objects. The result is that context is no help in > disambiguating > terms that have more than one meaning, such as "appendix", "page", or > "terminal". > > A language model would allow a more natural grammar, such as "People pay > mortgages more often than they are overbearing". This example also exposes > the fallacy of logical inference. Inference allows you to draw conclusions > such as this, but why would you? Inference is not a good model of human > thought. A good model would compare related objects. It might ask instead > whether people make mortgage payments more frequently than they receive > paychecks. The game gives no hint that Cyc understands such relations. > > Cyc has millions of hand coded assertions. It has taken over 20 years to > get > this far, and it seems we are not even close. This seems to be a problem > with > every knowledge representation based on labeled graphs (frame-slot, first > order logic, connectionist, expert system, etc). Using English words to > label > the elements of your data structure does not substitute for a language > model. > Also, this labeling tempts you to examine and update the knowledge manually. > > We should know by now that there is just too much data to do this. > > > -- Matt Mahoney, [EMAIL PROTECTED] > > ----- > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?list_id=303 > > > > > > > ____________________________________________________________________________________ > Never miss an email again! > Yahoo! Toolbar alerts you the instant new Mail arrives. > http://tools.search.yahoo.com/toolbar/features/mail/ > > ----- > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?list_id=303 > -- Matt Mahoney, [EMAIL PROTECTED] ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?list_id=303
