Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
On Dec 3, 2007 7:19 PM, Ed Porter [EMAIL PROTECTED] wrote: Perhaps one aspect of the AGI-at-home project would be to develop a good generalized architecture for wedding various classes of narrow AI and AGI in such a learning environment. Yes, I think this is the key aspect, the meta-problem whose solution would enable piecemeal solutions to the other problems: Create an architecture within which procedural knowledge can flow like water, the way text does on the Web. It would also need to scale well across a slow, unreliable network the way the Web does; once that's in hand, P2P [EMAIL PROTECTED] follows fairly naturally. - 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/?member_id=8660244id_secret=71759601-2c1ca5
Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
On Dec 3, 2007 11:03 PM, Bryan Bishop [EMAIL PROTECTED] wrote: On Monday 03 December 2007, Mike Dougherty wrote: Another method of doing search agents, in the mean time, might be to take neural tissue samples (or simple scanning of the brain) and try to simulate a patch of neurons via computers so that when the simulated neurons send good signals, the search agent knows that there has been a good match that excites the neurons, and then tells the wetware human what has been found. The problem that immediately comes to mind is that neurons for such searching are probably somewhere deep in the prefrontal cortex ... does anybody have any references to studies done with fMRI on people forming Google queries? ...and a few dozen brains from which we can extract the useful parts? :) - 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/?member_id=8660244id_secret=71797586-08a419
[agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
My suggestion, criticized below (criticism can be valuable), was for just one of many possible uses of an open-source P2P AGI-at-home type system. I am totally willing to hear other proposals. Considering how little time I spent coming up with the one being criticized, I have a relatively low ego investment in it and I assume there will be better suggestions from others. I think the hard part of AGI will be difficult to address on a P2P system with low interconnect bandwidth. I do because I believe the hard part of AGI will be learning appropriate dynamic controls for massively parallel systems computing over massive amounts of data, and the creation of automatically self organizing knowledge bases derived from computing from such massive amounts of knowledge in a highly non-localized way. For progress on these fronts at any reasonable speed you need massive bandwidth, which a current P2P system would lack, according to the previous communications on this thread. So a current P2P system on the web is not going to be a good test bed for anything approaching human-level AGI. But interesting things could be learned with P2P AGI-at-Home networks. In the NL example I proposed, the word senses and parsing were all to be learned with generalized AGI learning algorithms (although bootstrapped with some narrow AI tools) I think they could be a good test bed for AGI learning of self organizing gen-comp hierarchies because the training data is plentiful and easy to get, many of the gen-comp hierarchy of patterns that would be formed would be ones that we humans could understand, and the capabilities of the system would be ones we could compare to human level performance in a somewhat intuitive manner. With regard to the statement that The proper order is: lexical rules first, then semantics, then grammar, and then the problem solving. The whole point of using massive parallel computation is to do the hard part of the problem I have the following two comments: (1) As I have said before, the truly hard part of AGI is almost certainly going to be beyond a P2P network of PCs. And (2) with regard to the order of NL learning, I think a child actually learns semantics first (words associated with sets of experience), since most young children I have met start communicating first in single word statements. The word sense experts I proposed in the P2P system would be focusing on this level of knowledge. Unfortunately, they would be largely limited to experience in the form of a textual context, resulting in a quite limited form of experiential grounding. The type of generalized AGI learning algorithm I proposed would address lexical rules and grammar as part of both its study of grammar and word senses. I have only separated out different forms of expertise because each PC can only contain a relatively small amount of information, so there has to be some attempt to separate the P2P's AGI representation into regions with the highest locality of reference. In and ideal world this should be done automatically, but to do this well automatically would tend to require high bandwidth, which the P2P system wouldn't have. So at least initially it probably makes sense to have humans decide what the various fields of expertise are (although such decisions could be based on AGI derived data, such as that obtained from data access patterns on singe PC AGI prototypes, or even on an initial networked system). Also, I think we should take advantage of some of the narrow AI tools we have, such as parsers, WordNet, dictionaries, and word-sense quessers, to bootstrap the system so that we could get more deeply into the more interesting aspect of AGI such as semantic understanding faster. These narrow AI tools could be used in conjunction with AGI learning. For example, the output of a narrow AI parser or word sense labeler could be used to provide initial data used to train up AGI models, which could then replace or run in conjunction with the narrow AGI tools in a set of EM cycles, with the AGI models hopefully providing more consistent labeling at time progresses, and increasingly getting more weight relative to the narrow AI tools. Perhaps one aspect of the AGI-at-home project would be to develop a good generalized architecture for wedding various classes of narrow AI and AGI in such a learning environment. Narrow AI's are often very efficient, but they have very limitations which AGI can often overcome. Perhaps learning how to optimally wed the two could create systems that had the best features of both AGI and narrow AI, greatly increasing the efficiency of AGI. But there are all sorts of other interesting things that could be done with an AGI-at-home P2P system. I am claiming no special expertise as to what is the best use of it. For example, I think it would be interesting to see what sort of AGI's could be built on current PCs with up to 4G or RAM. It would be interesting to see just what
RE: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
For some lucky cable folks the BW is getting ready to increase soon: http://arstechnica.com/news.ars/post/20071130-docsis-3-0-possible-100mbps-sp eeds-coming-to-some-comcast-users-in-2008.html I'm yet to fully understand the limitations of a P2P based AGI design or the augmentational ability of a public P2P network on a private P2P network constructed for AGI. I would count out P2P AGI so quickly. John _ From: Ed Porter [mailto:[EMAIL PROTECTED] Sent: Monday, December 03, 2007 12:20 PM To: agi@v2.listbox.com Subject: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...] My suggestion, criticized below (criticism can be valuable), was for just one of many possible uses of an open-source P2P AGI-at-home type system. I am totally willing to hear other proposals. Considering how little time I spent coming up with the one being criticized, I have a relatively low ego investment in it and I assume there will be better suggestions from others. I think the hard part of AGI will be difficult to address on a P2P system with low interconnect bandwidth. I do because I believe the hard part of AGI will be learning appropriate dynamic controls for massively parallel systems computing over massive amounts of data, and the creation of automatically self organizing knowledge bases derived from computing from such massive amounts of knowledge in a highly non-localized way. For progress on these fronts at any reasonable speed you need massive bandwidth, which a current P2P system would lack, according to the previous communications on this thread. So a current P2P system on the web is not going to be a good test bed for anything approaching human-level AGI. But interesting things could be learned with P2P AGI-at-Home networks. In the NL example I proposed, the word senses and parsing were all to be learned with generalized AGI learning algorithms (although bootstrapped with some narrow AI tools) I think they could be a good test bed for AGI learning of self organizing gen-comp hierarchies because the training data is plentiful and easy to get, many of the gen-comp hierarchy of patterns that would be formed would be ones that we humans could understand, and the capabilities of the system would be ones we could compare to human level performance in a somewhat intuitive manner. With regard to the statement that The proper order is: lexical rules first, then semantics, then grammar, and then the problem solving. The whole point of using massive parallel computation is to do the hard part of the problem I have the following two comments: (1) As I have said before, the truly hard part of AGI is almost certainly going to be beyond a P2P network of PCs. And (2) with regard to the order of NL learning, I think a child actually learns semantics first (words associated with sets of experience), since most young children I have met start communicating first in single word statements. The word sense experts I proposed in the P2P system would be focusing on this level of knowledge. Unfortunately, they would be largely limited to experience in the form of a textual context, resulting in a quite limited form of experiential grounding. The type of generalized AGI learning algorithm I proposed would address lexical rules and grammar as part of both its study of grammar and word senses. I have only separated out different forms of expertise because each PC can only contain a relatively small amount of information, so there has to be some attempt to separate the P2P's AGI representation into regions with the highest locality of reference. In and ideal world this should be done automatically, but to do this well automatically would tend to require high bandwidth, which the P2P system wouldn't have. So at least initially it probably makes sense to have humans decide what the various fields of expertise are (although such decisions could be based on AGI derived data, such as that obtained from data access patterns on singe PC AGI prototypes, or even on an initial networked system). Also, I think we should take advantage of some of the narrow AI tools we have, such as parsers, WordNet, dictionaries, and word-sense quessers, to bootstrap the system so that we could get more deeply into the more interesting aspect of AGI such as semantic understanding faster. These narrow AI tools could be used in conjunction with AGI learning. For example, the output of a narrow AI parser or word sense labeler could be used to provide initial data used to train up AGI models, which could then replace or run in conjunction with the narrow AGI tools in a set of EM cycles, with the AGI models hopefully providing more
Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
On Dec 3, 2007, at 12:52 PM, John G. Rose wrote: For some lucky cable folks the BW is getting ready to increase soon: http://arstechnica.com/news.ars/post/20071130-docsis-3-0-possible-100mbps-sp eeds-coming-to-some-comcast-users-in-2008.html I'm yet to fully understand the limitations of a P2P based AGI design or the augmentational ability of a public P2P network on a private P2P network constructed for AGI. I would count out P2P AGI so quickly. Distributed algorithms tend to be far more sensitivity to latency than bandwidth, except to the extent that low bandwidth induces latency. As a practical matter, the latency floor of P2P is so high that most algorithms would run far faster on a small number of local machines than a large number of geographically distributed machines. There is a reason people interested in high-performance computing tend to spend more on their interconnect than their compute nodes. J. Andrew Rogers - 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/?member_id=8660244id_secret=71602529-7ec12e
RE: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
From: J. Andrew Rogers [mailto:[EMAIL PROTECTED] Distributed algorithms tend to be far more sensitivity to latency than bandwidth, except to the extent that low bandwidth induces latency. As a practical matter, the latency floor of P2P is so high that most algorithms would run far faster on a small number of local machines than a large number of geographically distributed machines. There is a reason people interested in high-performance computing tend to spend more on their interconnect than their compute nodes. The P2P public network is not homogenous. Lower quality nodes far outnumber high quality nodes but high quality nodes do exist. High quality meaning both low latency and high bandwidth (example 3ms ping at 44 mbits). For human equivalent AGI a private P2P network MIGHT be required, inexpensive would be 3ms ping on a gig E clustered segment. More pricier could require an external switched fabric of say around a 5+ gigbit interconnect cluster. Lazy processing on low quality P2P - exactly how invaluable is that? Distributed P2P computing for AGI needs to be self-organizing, detect and adapt to resource conditions. It's not a perfect world. John - 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/?member_id=8660244id_secret=71615162-02022c
Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
--- Ed Porter [EMAIL PROTECTED] wrote: And (2) with regard to the order of NL learning, I think a child actually learns semantics first Actually Jusczyk showed that babies learn the rules for segmenting continuous speech at 7-10 months. I did some experiments in 1999 following the work of Hutchens and Alder showing that it is possible to learn the rules for segmenting text without spaces using only the simple character n-gram statistics of the input. The word boundaries occur where the mutual information across the boundary is lowest. http://cs.fit.edu/~mmahoney/dissertation/lex1.html Children begin learning the meanings of words around 12 months, and start forming simple sentences around age 2-3. For example, I think it would be interesting to see what sort of AGI's could be built on current PCs with up to 4G or RAM. I did something like that with language models, up to 2 GB. So far, my research suggests you need a LOT more memory. http://cs.fit.edu/~mmahoney/compression/text.html With regard to distributed AI, I believe the protocol should be natural language at the top level (perhaps on top of HTTP), because I think it is essential that live humans can participate. The idea is that each node in the P2P network might be relatively stupid, but would be an expert on some narrow topic, and know how to find other experts on related topics. A node would scan queries for keywords and ignore the messages it doesn't understand (which would be most of them). Overall the network would appear intelligent because *somebody* would know. When a user asks a question or posts information, the message would be broadcast to many nodes, which could choose to ignore them or relay them to other nodes that it believes would find the message more relevant. Eventually the message gets to a number of experts, who then reply to the message. The source and destination nodes would then update their links to each other, replacing the least recently used links. The system would be essentially a file sharing or message posting service with a distributed search engine. It would make no distinctions between queries and updates, because asking a question about a topic indicates knowledge of related topics. Every message you post becomes a permanent part of this gigantic distributed database, tagged with your name (or anonymous ID) and a time stamp. I wrote my thesis on the question of whether such a system would scale to a large, unreliable network. (Short answer: yes). http://cs.fit.edu/~mmahoney/thesis.html Implementation detail: how to make a P2P client useful enough that people will want to install it? -- 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/?member_id=8660244id_secret=71629115-649a10
Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
On Dec 3, 2007 5:07 PM, Matt Mahoney [EMAIL PROTECTED] wrote: When a user asks a question or posts information, the message would be broadcast to many nodes, which could choose to ignore them or relay them to other nodes that it believes would find the message more relevant. Eventually the message gets to a number of experts, who then reply to the message. The source and destination nodes would then update their links to each other, replacing the least recently used links. I wrote my thesis on the question of whether such a system would scale to a large, unreliable network. (Short answer: yes). http://cs.fit.edu/~mmahoney/thesis.html Implementation detail: how to make a P2P client useful enough that people will want to install it? That sounds almost word-for-word like something I was visualizing (though not producing as a thesis) I believe the next step of such a system is to become an abstraction between the user and the network they're using. So if you can hook into your P2P network via a firefox extension, (consider StumbleUpon or Greasemonkey) so it (the agent) can passively monitor your web interaction - then it could be learn to screen emails (for example) or pre-chew either your first 10 google hits or summarize the next 100 for relevance. I have been told that by the time you have an agent doing this well, you'd already have AGI - but i can't believe this kind of data mining is beyond narrow AI (or requires fully general adaptive intelligence) Maybe when I get around to the Science part of my BS degree (after the Arts filler) I will explore to a greater depth for a thesis. - 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/?member_id=8660244id_secret=71648663-f0a7ee
Re: [agi] RE:P2P and/or communal AGI development [WAS Hacker intelligence level...]
On Monday 03 December 2007, Mike Dougherty wrote: I believe the next step of such a system is to become an abstraction between the user and the network they're using. So if you can hook into your P2P network via a firefox extension, (consider StumbleUpon or Greasemonkey) so it (the agent) can passively monitor your web interaction - then it could be learn to screen emails (for example) or pre-chew either your first 10 google hits or summarize the next 100 for relevance. I have been told that by the time you have an agent doing this well, you'd already have AGI - but i can't believe this kind of data mining is beyond narrow AI (or requires fully general adaptive intelligence) Another method of doing search agents, in the mean time, might be to take neural tissue samples (or simple scanning of the brain) and try to simulate a patch of neurons via computers so that when the simulated neurons send good signals, the search agent knows that there has been a good match that excites the neurons, and then tells the wetware human what has been found. The problem that immediately comes to mind is that neurons for such searching are probably somewhere deep in the prefrontal cortex ... does anybody have any references to studies done with fMRI on people forming Google queries? - Bryan - 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/?member_id=8660244id_secret=71715011-399ee5
