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OpenCyc 1.0 Stutters Out of the Gates
moterizer writes "After some 20 years of work and five years behind schedule, OpenCyc 1.0 was finally released last month. Once touted on these pages as "Prepared to take Over World", the upstart arrived without the fanfare that many watchers had anticipated — its release wasn't even heralded with so much as an announcement on the OpenCyc news page. For those who don't recall: "OpenCyc is the open source version of the Cyc technology, the world's largest and most complete general knowledge base and commonsense reasoning engine." The Cyc ontology "contains hundreds of thousands of terms, along with millions of assertions relating the terms to each other, forming an upper ontology whose domain is all of human consensus reality." So are these the fledgling footsteps of an emerging AI, or just the babbling beginnings of a bloated database?"
Please, for the good of Humanity, vote Obama.
Leave Wikipedia out of this.
I'm sure "SlashdotMedia" will improve on all the wonders that Dice Holdings blessed us all with
...but does it know Linux?
Bragi Ragnarson Lawful Good (I change the law when it's not good)
Is this what I first thought computers were when I was ten? I recall building my Sinclair 1000 from a kit, plugging it into the telly and the mains and seeing that black prompt. I typed in, "What is the capital of the United States?" It said, "SYNTAX ERROR LINE 10" or something to that effect. So, after over 20 years will I finally be able to type that into my own computer and be able to have it actually give me an answer even if it's not on the net?
-"...bad old ideas look confusingly fresh when they are packaged as technology" - Jaron Lanier (Digital Maoism on Edge.o
commonsense reasoning engine.
A reasonable test would be to have it read slashdot, and identify slashback 'articles' as recycled junk.
"We are all geniuses when we dream"
- E.M. Cioran
The alliterative allegations of an angry AI?
- None can love freedom heartily, but good men; the rest love not freedom, but license. -- John Milton
I kind of feel bad for Cyc/OpenCyc... they've put so many years into this project, but using web-based games to collect and verify this common-sense data is much faster than using a few paid experts and can give much more data. For the curious, Luis von Ahn, a grad student (and now assistant professor) at Carnegie Mellon University gave a (rather entertaining) tech talk at Google about his work in this area.
He's recently been working on a project called Verbosity, which uses such games to collect the same sort of common-sense data that Cyc has been trying to collect all these years. Cyc's ontology apparently contains "hundreds of thousands of terms, along with millions of assertions relating the terms to each other." If Verbosity is as popular as von Ahn's ESP Game, the game could probably construct a better database in a matter of weeks.
Here's the abstract from a research paper on the topic:
Verbosity: a game for collecting common-sense facts
We address the problem of collecting a database of ""common-sense facts"" using a computer game. Informally, a common-sense fact is a true statement about the world that is known to most humans: ""milk is white,"" ""touching hot metal hurts,"" etc. Several efforts have been devoted to collecting common-sense knowledge for the purpose of making computer programs more intelligent. Such efforts, however, have not succeeded in amassing enough data because the manual process of entering these facts is tedious. We therefore introduce Verbosity, a novel interactive system in the form of an enjoyable game. People play Verbosity because it is fun, and as a side effect of them playing, we collect accurate common-sense knowledge. Verbosity is an example of a game that not only brings people together for leisure, but also collects useful data for computer science.
So are these the fledgling footsteps of an emerging AI, or just the babbling beginnings of a bloated database?
Cyc is a fledgling AI, depending on how you count "AI". Then again, so is my thermostat. My thermostat "knows" how to keep the room the right temperature. Cyc "knows" about a great deal of conventional human background, just like a database with a query system "knows" how to give you the data in that system.
The real question is not "is this AI", but rather, is it useful, and if so, to who? I think Cyc has the potential to be quite useful in some areas; we'll see how far it goes, and what the limitations are in time.
Right now, I think the real problem with Cyc is understanding it on a practical level, and getting an understanding of what it can do in practice, not in theory. When I last looked at the project nine years ago, they were just starting to open up things a bit, and it sounded like someone who understood the project might make great things happen. They don't seem to have yet; but who knows... perhaps in the future.
Now that OpenCyc is finally released, the most important steps to get people using it is to drop the learning curve down to a reasonable level, so that developers can start playing with it and find out what it can do without committing their lives to the project...
We'll have to see what happens: Cyc is a big (bloated?) database that's also a fledgling AI -- the real question is, what cool things can we make it DO? Time will tell...
Google's 6 DVDs full of n-grams are much more interesting than that: they "processed 1,011,582,453,213 words of running text and are publishing the counts for all 1,146,580,664 five-word sequences that appear at least 40 times. There are 13,653,070 unique words, after discarding words that appear less than 200 times."
r -n-gram-are-belong-to-you.html
r eleases-massive-amounts-of-user-search-data/
http://googleresearch.blogspot.com/2006/08/all-ou
AOL has released interesting data as well...
http://www.techcrunch.com/2006/08/06/aol-proudly-
Having done a great deal of data processing, I have watched these projects off and on with minor amusement. The reason why is that, in my humble opinion, it will never work. That is not to say that it can't, just that these projects just love to forget Gödel's Theorem, which states, roughly: any sufficiently complex system will have things that are obviously true or false, but are not provable within the system.
Put another way, any complex set of rules will inherently be unable to stay consistent because eventually the syntax complexity become able to state, "The following sentence is false. The previous sentence is true." This occurs regularly in data processing when a given field's syntax (datum value) bridges or is not defined by your context (schema).
The real crutch is that syntax is inductive, where we try to fit each word into a category; however, our context (use of language) is deductive, we all learn it through experience with a physical world. I have seen this problem over and over as people constantly modify the schema to overcome syntactic limitation. While Cyc is designed to be constantly expanded with new rules, they are still syntactical statements.
By Gödel's Theorem, syntactic systems are doomed to fail. Instead, Cyc should be allowed to learn through observation and deduce its own understanding of the world so that it is not bound by any particular syntax. While this could work, it fails the ultimate intent. We want a computer that can both learn and yet not be wrong.
The problem is you can't have that. You can either be syntactically correct, but simplify the model until it works (Physics). Or, you can allow deductions and have to work in the realm of probability (Humans).
Although, I would gladly accept a computer that erred like a human and yet didn't bitch about how it was someone else's fault.
Bel, the mostly sane.. "Of course I can't see anything! I'm standing on the shoulders of idiots." -- Me
The funny thing about common sense is that it is not common!
The key is not to "feed in" Wikipedia, but to get Wikipedia to move to a variant of SemanticWiki so that users can add in semantic statements. If semantic statements become the standard, Wikipedia can be queried, which means that Cyc could be fed the data automatically.
My hand to God. Baby geese. Goslings. They were juggled.
If you could build a Cyc-like database simply by feeding it a large amount of more-or-less unstructured text, then the Cyc project wouldn't have been necessary in the first place.
Cyc is only words and descriptors. If you attach them to 3d shapes and actions in the 3d world, the program can imagine what you're saying. It can even obey and do tasks if hooked up into a robotic body and scan the room. It requires the technology of being able to scan its environment then run something like the program they run to find text inside of images. Instead of finding text inside of images, its finding objects inside an environment. Pretty simple once you understand the basics, but it will take a lot of work. A longer descriptor of this can be found at: AI page Cyc isn't a waste, but you need to do something harder to make it into AI, you need to attach 3d objects to every noun, and apply 3d actions to every verb, etc. I'd say that'd be on the realm of next to impossible, so yeah what they've done really doesn't advance AI at all.
God spoke to me.
Cyc has an ontology of general conceptual terms, and represents the precise logical way in which
those concepts interrelate. In other words, it emulates an aspect of the pure rational part of
human reasoning about the world.
But it's known that humans are not dispassionate rational agents. And indeed that there probably
is no such thing as a dispassionate rational agent. Commander Data and Spock are very ill-conceived
ideas of robot-like reasoners. Passion (emotion, affect) is the prioritizer of reasoning that allows
it to respond effectively (sometimes in real time) to the relevant aspects
of situations. Without the guidance of emotion, no common-sense reasoning engine would be powerful
enough, no matter how parallel it was, to process all of the ramifications of situations and
come up with relevant and useful and communicable and actionable conclusions.
So how do we give CYC passion? Or at least a simulation of it?
Well the key would seem to lie in measuring the level of human concern with each concept, and with
each type of situational relationship between pairs (and n-tuples) of concepts.
How could we do that? How about doing a latent semantic analysis from google search results. Something
similar to Google Trends, but which measures specifically the correlation strengths of pairs of
concepts (in human discourse, which Google indexes). The relative number of occurrences (and co-occurrences)
of concept terms in the web corpus should provide a concept weighting and a concept-relationship weighting.
If we then map that weighting on top of the CYC semantic network, we should have a nicely "concern"-weighted
common-sense knowledge base, which should be similar in some sense to a human's memory that supports
human-like comprehension of situations.
Combining a derivative of google search results with CYC is my suggestion for beginning to make an AI that can talk to
us in our terms, and understand our global stream of drivel.
I wish I had time to work on this.
Where are we going and why are we in a handbasket?
"OpenCyc is the open source version of the Cyc technology, the world's largest and most complete general knowledge base and commonsense reasoning engine."
Is one to assume that the way to common sense logic in a machine is via linguistic/symbolic knowledge representation? How can this handwritten knowledge base be used to build a robot with the common sense required to carry a cup of coffee without spilling the coffee? And why is it that my pet dog has plenty of common sense even though it has very limited linguistic skills? I think it's about time that the GOFAI/symbol processing crowd realize that intelligence and common sense are founded exclusivley on the temporal/causal relationships between sensed events. It's time that they stop wasting everybody's time with their obsolete and bankrupt ideas of the last century. The AI world has moved on to better and greener pastures. Sorry.
Don't be alarmed, Arthur Dent. Be very, very frightened.
Human thought is a rather complex thing, that don't always appear to follow logical patterns or rules. Or not the simple "if I want X, I must do Y" clear-cut rules that nerds everywhere expect. Human thought is a complex attempt at balancing the priority of not only "I want X", but also stuff like "but it would be socially bad to be seen doing Y", and "I could do Y1 instead, but that's way more effort than I can be arsed to do today", and "it would be nice to have time left to do Z too today, or the missus will blow a gasket", and quite often "actually I don't really want X, I want Z, but it would be uncool to admit that." It's not just following rules and logic, it's trying to fit it all in a complex scheme of priorities, social rituals, and whatnot, and most often boiling down to finding the least crappy compromise in that space.
In other words, whenever you find yourself thinking, "meh, people/men/women/engineers/PHBs/whatever are so stupid/illogical/whatever. If they want X, they should just do Y", chances are it's not them who are illogical. It's you who don't understand their personal version of that maze of priorities and rituals. Or what is the real Z they're after, when they say they want X.
Most of those things aren't even at a conscious level. Even if you poll people along the lines of "if you wanted X, would you do Y?", you'll get an answer that's most often useless. For starters it will be heavily skewed towards what they'd like to think of themselves, not what they'd actually do. Second, without providing a _lot_ of context, it will bypass most of those priorities and rituals that might override that in practice.
What's the point of this whole rant? That the first AIs trained by humans will inherently be a dud.
If you make an AI that functions by precise, inflexible rules, congratulations, you've just programmed OCPD. Literally.
Add a lack of perceptions of human reactions, feelings, body language, etc, and you've given it Autism too. Again, pretty literally.
I.e., I'd expect the first few AIs, or even generations of AIs to be... well, don't think the lovable R2D2 or the essentially human C3-PO, but an electronic equivalent of the most obnoxious socially-dysfunctional kind of geek.
If you want that as an overlord... I don't know, I hope I'm not around at least.
A polar bear is a cartesian bear after a coordinate transform.
According to this FAQ entry, it's not fully open-source...
"So are these the fledgling footsteps of an emerging AI, or just the babbling beginnings of a bloated database?"
How about putting that question to Opencyc?
Done with slashdot, done with nerds, getting a life.
We are starting to mine Wikipedia at the Cyc Foundation (cycfoundation.org, sorry not much of a website yet), which is an independent non-profit org that's working closely with Cycorp. We're managing the growth of the public knowledge base. Linking Wikipedia article titles to Cyc concepts is one of the first things we're doing. That will grow the set of concepts, and it will also create a way to browse and search Wikipedia conceptually, such as letting you look for a list of all articles about parks west of the Rockies that contain bears.
We're also working on creating Semantic Web compatible URIs for the all of the Cyc terms.
Anyone who wants to join the Cyc Foundation can contact me: johndcyc at cycfoundation.org.
Check the schedule of Skypecasts at Skype.org. We can add you to the chat, but you probably won't be allowed to talk UNLESS you have a USB microphone or headset.
You can also listen in on our Skypecast tonight. It's every Thursday at 9:30pm EST, 8:30 CST.
You can't compare Wikipedia to Cyc. If you do, then you are just misunderstanding what Cyc is and what it is not. Cyc is a database of logical relations representing common sense knowledge. It contains something like 20 different meanings of the word "lie" and such things as this. It is not concerned with knowledge of popular culture, but rather the underlying semantic rules that we use to talk about things such as pop culture.
Completely different.
I think one place where Cyc or similar types of knowledge engines could really shine is in business. A business model is vastly simpler then the model of reality that people carry around in their heads; and one benefit that Cyc has is that it understands *everything* -- it is integrated by default.
So once it gets basic understanding of accounting, inventory, retailing, management, logistics, etc., you could easily build a natural language interface to it: "Three boxes arrived today from supplier X and we paid $90 for them". If there is ambiguity in the sentence, Cyc would ask natural language clarifying questions: "Was each box a line item on the invoice, or were there many line items?"
I think this would be much improved over the current data-interfaces we have today, which are basically graphical recapitulations of paper-based forms in the format of "field: [value]".
Another problem with modern apps is that they all contain their own internal, add-hoc ontologies. These ontologies are hard-coded, and usually aren't designed to intergrate with ontologies in apps from different domains -- e.g. logistics and accounting (unless they are from the same vendor). Cyc has a standardized, presumably well-thought-out and near comprehensive ontology. It can also grow its ontologies based on user input. So you have this automatic integration feature that's sorely lacking in the end-user computer world.
Computers are useless. They can only give you answers.
-- Pablo Picasso
I agree with everything you said, and we at the Cyc Foundation are working to fix the accessibility problem.
The Cyc Foundation is a new independent non-profit org. I worked at Cycorp for 7 years before forming the Foundation with a co-founder that has a totally outside perspective. We're very optimistic about the progress being made. We've got about 2 dozen people helping so far, and that's before we've made anything available (such as the Web game we're working on) that will allow for much broader involvement.
Listen in on our Skypecast tonight (every Thursday night) at 9:30pm EST. Look for it on the list of scheduled Skypecasts at skype.org. You can participate if you have a USB microphone or headset.
We plan to exploit the N-grams in our knowledge collection work at the Cyc Foundation.
:-), you can join our Skypecast tonight.
If you hadn't seen me mention it already
I remember cyc from an old (early 90's) PBS doumentary series about computers called The Machine that Changed the World. IIRC, cyc isn't just a database of facts, it's also an engine for making inferences based on those facts. The researcher on the show said that every morning they would come in and read the list on new inferences cyc had generated overnight and fix the incorrect ones and then start inputting new information. One amusing example they gave was that since most of the individuals they had told cyc about were historical figures, it inferred that most people were famous.
Yes, we are. It will probably be published next week. OWL, specifically.
Meanwhile google happily eats whatever crap its spiders manage to find and thru some hacking and dark magic algorithms is still able to give not so meaningless answers to not to much badly worded queries.
That's a key point explaining why OpenCyc came too late. Wordnet, Thoughtreasure, Cyc et alii all share a set of common drawbacks. Their input data need to be specially formated. That's why all those overly ambitious project have progress so slowly in the past years, and are still only limited to answers precise non-ambous simple question like "Is a cat a mamal ?".
This is linked to their fundamental design around a solid, non-flexible, pure logical architectures (reading their repective Wikipedia entries help understand how they work). In a way, the scientist behind those projects tryed to apply the same kind of language logic that is used in maths and programming languages to human language, and while this may be usefull for some academic purpose or very specific application were some reasonning may be useful (which has been used and applied well - I've seen it at least for WN and TT), they don't scale that well to REAL-WORD(tm) situations.
Their fundamental structure clashes with reality of human reasonning : WordNet is limited to single non-ambigous meaning for terms (no things like "nut" as in the seed, and "nut" as in the thing that can be screwed on a bolt). Other "stuctured" designs clash with real life's fuzzy nature with the other softwares.
Meanwhile search engines have grown in a completly different way. Initially they were designed only to scan pages content and then index their keywords for later queries. Only after that, slowly, one hack after another, they where tuned. In order to make results more revelant. In order to avoid link farms. Finding some complexe strategies in the ranking calculation to return more correct and more meaningful. To find results not with matching keyword, but with related keywords (Google's "Keyword is encountered only in page linking to thig target"). To cope easily with bad spelling (something that is very common in the real life. Something that is difficult to even detect for a common-sense engine. something that is very intuitive in search enginges, and that is even more optimisable given the statistics that such engine can do). And lot of other small ponctual improvement.
And slowly, by on one hand having a system that gets each day a little bit more optimised, and, on the other hand, an incredibly huge corpus to process that grows at a very fast rate, the search enginges, like google, become fantastic multipurpose information retrieving tools.
By now, you can type crap in google and still get something (as long it's not a "google-sepuku" like of crap, but more of "I'm very clumsy with my wording and my keyboard-skills"). You can have also other wonderful information, including stats on spelling errors or even statistic based translation (that are otherwise very difficult to get by classical mean), static about currently hot topic (which can be fed back to improve results for ambigous queries).
All this because search engines are built around a fuzzy logic : at the core is a braindead simple indexing rule, slightly modified by a bunch of hacks.
Such fuzzy logic approach "without really needing to teach the machine everything" has been recently successfully used on
"Sufficiently advanced satire is indistinguishable from reality." - [Tips: 1DrYakQDKCQ6y52z6QbnkxHXAocMZJE61o ]
Cool. I'll look out for it. Maybe it's time to blow the dust off my old NL -> CycL program for Cypher and release an alpha.
Just reading TFA right now, but I got pretty interested in this tech a year ago...
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Cyc (I don't know for openCyc) there is a natural language module, I never had the occasion to work on Cyc and they promised it for OpenCyc 1.0. The goal of it is to be able to feed from large text corpus exactly like the wikipedia, full of general knowledge.
The goal of Cyc is to be able to resolve conflicts between two apparent contradicting proposition. Example
* George W. Bush is the president of the USA.
* In 1790, George Washington is the president of the USA.
Cyc is built with a sense of context. Where a simple NL (natural language) parser would not understand it, Cyc has the following common sense knowledge or has inferred it
- a president is a living human being
- presidency is a mandate limited in time
- only one human being can be president of a given region at one time
- a human being can not live two hundred years
- "In 1790" denotes the past
It can know make a serie of hypotheses
GW Bush is a human being.
GW Bush is a living human being.
GW Bush is the current president of USA
GW Bush is was president of USA at an unspecified time
Georges Washington is still president of the USA (and "in 1790" must be interpreted in another way)
Georges Wasington and GW Bush are both president of the USA (and therefore we must be in an unknown context where the rule of the uniqueness of a president of the USA is false)
etc...
Given its knowledge, it can order its hypotheses from more probable to less probable given the cost of the assumptions it must make to maintain each of its hypotheses. So yes, I would say it can feed from the wikipedia to some extent.
A lesser known fact about CycCorp is that they work with the NSA on the Terrorrist Information Awareness program, already datamining GiBs of natural language datas.
The Wise adapts himself to the world. The Fool adapts the world to himself. Therefore, all progress depends on the Fool.
Would you like it if they were not these the fledgling footsteps of an emerging ai or just the babbling beginnings of a bloated database?
If you're going to use that AI as a tool, yes, ok. But the post I was answering to was the usual "I, for one, welcome our overlords."
And trust me, you _don't_ want an overlord that's inhumanly logical about it. It's that kind of thing that led to such logical solutions as "let's extermine the population of Poland until 1970 to make room for German settlers." Or such logical solutions as communism. Sure, on paper it's perfectly sound and logical, if you assume that you can change humans overnight. Maybe sometimes being able to understand humans actually helps, eh?
That said, most of the stellar job performance that OCPD cases claim exists only in their own mind.
They tend to never get a job done because it's not yet perfect, for example. I have one two rooms from me at the office, who's taken three fucking years just to get a build script done because everything wasn't perfect enough for him. No exaggeration. Literally. Well, in parallel with building a convoluted unit testing environment, because the existing one didn't satisfy his purist view of the matter. (The old tests had some functional testing too. So his perfect version actually tests less, but is _pure_ unit testing, by his own definitions of it.) Of course, he's convinced that he's done a stellar, uncompromising job, but for everyone else he's just wasted some time and didn't even achieve more than what we already had.
Do I really want that even in a computer? Nope, not really. _The_ problem with most programs nowadays is just that: that they're OCPD nutcases. Workflows that were a lot more flexible (even if not as fast) with a pen and paper, get shoehorned into some lobotomized set of rules that allows no exceptions. The problem is that most often the rules aren't actually what the user wants to do: e.g., you end up unable to save a new client's data until you know their fax number, whereas with a paper form you'd fill in the data you have and leave the rest for later. Often it's more annoyance for the users and more work in workarounds, than doing it without a computer in the first place. (Of course, the equally OCPD-ridden creator will then bitch and moan about "idiot lusers" and how everyone should change to fit his perfect tool, instead of his tool changing to do what the user actually needs done.)
No real qualms with autism on its own, though. They tend to be very good with a computer, or any kind of abstract problem for that matter. (If sometimes difficult to deal with in a team.)
Combine it with OCPD, though, and... well, let's just say that they mix like Ammonium Nitrate and Fuel Oil. You get some of the most obnoxious personalities that way, and it's no fun for anyone involved, not even the geek. The poor bugger can't even tell that he's the one who offended the whole room, and proceeds to imagine that he's the victim of unwarranted cruelty.
A polar bear is a cartesian bear after a coordinate transform.
- I've created the following constants for my cats, their sibling and parents:
- #$Comet-TheCat
- #$Rocket-TheCat
- #$Packet-TheCat
- #$Mama-TheCat
- #$GhostDad-TheCat
- I've asserted (#$isa [cat] #$Cat) about all of them.
- I've asserted (#$biologicalMother [cat] #$Mama-TheCat) about Comet, Rocket and Packet
- I've asserted (#$biologicalFather [cat] #$GhostDad-TheCat) about Comet, Rocket and Packet as well.
- I even created #$ConceptionOfKitties, asserted (#$isa #$ConceptionOfKitties #$BiologicalReproductionEvent), (#$parentActors #$ConceptionOfKitties #$Mama-TheCat) and (#$parentActors #$ConceptionOfKitties #$GhostDad-TheCat).
So why can't Cyc infer that (#$siblings #$Comet-TheCat #$Packet-TheCat)? Is it a limitation in the public subset of the ontology, or some more fundamental issue with my data?The joke will be on us when the first real AI wakes up, spends some time contemplating the Internet, downloading terabytes of information, and finally communicates with its creators...
...only to ask for more pr0n.
Taken as criticisms, the allusions to 'bloat' and 'database' are both significantly wide of the mark: if Cycorp has been guilty of anything, it's historically underestimating the size and technical complexity of the knowledge base indicated for the common sense reasoner the company aspires to build. OpenCyc is not a database except in the most attenuated sense: it encodes, not instance-level facts, but quantified and contextually parameterized rules for reasoning about the everyday world, and it is, if anything, far too small for this purpose. The number and complexity of the rules needed for this is fairly staggering and too-little-appreciated, even by many in the AI community though not Minsky and McCarthy, both of whom are on the record as having recognized Cyc as one of the very few efforts in the field that was on anything like the right track). It's also fair to say that efficient and suitably flexible inference over a knowledge base of this size and complexity, and automated induction of new reasoning rules on the basis of experience - both obvious prerequisites for what Cycorp has been trying to do - present significant and partly unsolved theoretical challenges. The company's surprising willingness to tackle such weighty and potentially intractable issues head-on is a thing greatly to be commended in the present season of intellectual and commercial timidity, and even though they may not have always been able to deliver on every promissory note, one can't help but admire their spirit. And the fact remains that OpenCyc is now being used by an enthusiastic community of unaffiliated developers who are busily laying the groundwork for a new suite of open source applications. Judgement should not be pronounced on the basis of their efforts before they have been given the chance to see what they can deliver.