RE: [agi] Teaching AI's to self-modify
Title: Message Hello Ben, Is there a prototype of Novamente I can download and run on a PC, for NLP purposes?.. Thanks, Shai. -Original Message-From: Ben Goertzel [mailto:[EMAIL PROTECTED] Sent: Saturday, July 31, 2004 7:05 PMTo: [EMAIL PROTECTED]Subject: Re: [agi] Teaching AI's to self-modify Hi Dennis, Sorry for the long delay in reply, I've been on vacation and am now plowing through a big pile of backed-up emails To answer your three questions... 1) We have an NLP framework that uses a variation of the carnegie-mellon "link parser" together with a bunch of special "semantic algorithms" for mapping syntactic links into semantic ones, and some probabilistic inference based algorithms for semantic disambiguation reference resolution. Given a sentence this framework makes a number of prioritized guesses regarding the correct interpretation of the sentence. The user gets to view these guesses and correct them via a UI; for instance, they can select from several possible parses, they can change the selected meaning of a word to a different one (choosing from a menu of known meanings or defining a new one), etc. The overall process is much slower than just freely typing in natural language, but much faster than entering knowledge using an expert system, formal logic based approach. This will go into commercial use for one of our customers as of early september. 2) Of course, I agree that ambiguity can never be fully eliminated from natural language. NOvamente internally can deal with ambiguity. 3) As for an example of a program generated by Sasha In language processing, an example would be an algorithm for reference resolution --- normally one would code such a thing in C++ and stick it in a Novamente MindAgent, but if one codes it in Sasha then Novamente can not only execute it but also study and modify it, because it will be represented in the form of Novamente nodes and links. In a vision context, an example would be an algorithm for edge detection. This is less far along than INLINK. Right now we are using Sasha to generate programs doing simple math stuff and list manipulations etc.Over the next couple months we will hook it into the rest of Novamente and start using it for applications like the ones described above. The point is, it's a way of getting procedural knowledge into the system in a precise yet learnable/adaptable way. Whereas INLINK is a way of getting declarative knowledge into the system. Not very much like the process of teaching a human infant, of course. I think that kind of experiential interactive learning is going to be critical to teaching Novamente, BUT, I think it makes sense to augment it with these kinds of tricks like INLINK and Sasha, as a way of overcoming the deficit Novamente has, compared to humans, in terms of its lack of an evolved cognitive endowment. I plan to write a document on this stuff during the next few days (or perhaps the next week if things go slowly), and I'll post it to the list when I do... --Ben G Dennis Gorelik [EMAIL PROTECTED] wrote: Ben,1) Could you describe what is the architecture of you INLINKinteractive framework?How is it going to handle natural language?2) I doubt that it's possible to communicate in natural languagecompletely unambiguously. There always will be some uncertainty.Intelligent system itself will have to decide how to interpretincoming message.3) Could you give an example of a program which will be generated bySasha programming framework?Sunday, July 4, 2004, 8:58:01 AM, you wrote:BG We're developing two powerful methods for communicating with Novamente:BG 1) the INLINK interactive NL framework, which allows naturalBG language to be communicated to Novamente correctly andBG unambiguouslyBG 2) the Sasha programming framework, which allows the easyBG construction of software programs that manipulate Novamente nodesBG and links [and, rapid executable versions of these programs willBG be produced via supercompilation, www.supercompilers.com]. RightBG now, Novamente MindAgents, the processes that guide NovamenteBG cognition, are coded as C++ objects which are opaque to NovamenteBG cognition; but with the advent of Sasha, we'll be able to codeBG MindAgents as Novamente nodes and links which can in principle beBG modified/improved/replaced by Novamente cognition.---To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] __
RE: [agi] Teaching AI's to self-modify
Title: Message Shai, I'm sorry, but we don't currently provide the Novamentesystem except to members of our RD team, or to firms that have licensed Novamente-based products to use for some specific purpose (such as natural language processing). This may change in the future but probably not in the near future. As an aside, Novamente doesn't normally run on a single PC, it runs on a network of PC's, each of which must be running Linux (latest versions of SUSE or RedHat). Our simple test configuration for language processing using Novamente uses 3 machines, with a separate instance of the Novamente core software process on each of them. -- Ben -Original Message-From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]On Behalf Of Ophir ShaiSent: Monday, August 16, 2004 7:31 AMTo: [EMAIL PROTECTED]Subject: RE: [agi] Teaching AI's to self-modify Hello Ben, Is there a prototype of Novamente I can download and run on a PC, for NLP purposes?.. Thanks, Shai. -Original Message-From: Ben Goertzel [mailto:[EMAIL PROTECTED] Sent: Saturday, July 31, 2004 7:05 PMTo: [EMAIL PROTECTED]Subject: Re: [agi] Teaching AI's to self-modify Hi Dennis, Sorry for the long delay in reply, I've been on vacation and am now plowing through a big pile of backed-up emails To answer your three questions... 1) We have an NLP framework that uses a variation of the carnegie-mellon "link parser" together with a bunch of special "semantic algorithms" for mapping syntactic links into semantic ones, and some probabilistic inference based algorithms for semantic disambiguation reference resolution. Given a sentence this framework makes a number of prioritized guesses regarding the correct interpretation of the sentence. The user gets to view these guesses and correct them via a UI; for instance, they can select from several possible parses, they can change the selected meaning of a word to a different one (choosing from a menu of known meanings or defining a new one), etc. The overall process is much slower than just freely typing in natural language, but much faster than entering knowledge using an expert system, formal logic based approach. This will go into commercial use for one of our customers as of early september. 2) Of course, I agree that ambiguity can never be fully eliminated from natural language. NOvamente internally can deal with ambiguity. 3) As for an example of a program generated by Sasha In language processing, an example would be an algorithm for reference resolution --- normally one would code such a thing in C++ and stick it in a Novamente MindAgent, but if one codes it in Sasha then Novamente can not only execute it but also study and modify it, because it will be represented in the form of Novamente nodes and links. In a vision context, an example would be an algorithm for edge detection. This is less far along than INLINK. Right now we are using Sasha to generate programs doing simple math stuff and list manipulations etc.Over the next couple months we will hook it into the rest of Novamente and start using it for applications like the ones described above. The point is, it's a way of getting procedural knowledge into the system in a precise yet learnable/adaptable way. Whereas INLINK is a way of getting declarative knowledge into the system. Not very much like the process of teaching a human infant, of course. I think that kind of experiential interactive learning is going to be critical to teaching Novamente, BUT, I think it makes sense to augment it with these kinds of tricks like INLINK and Sasha, as a way of overcoming the deficit Novamente has, compared to humans, in terms of its lack of an evolved cognitive endowment. I plan to write a document on this stuff during the next few days (or perhaps the next week if things go slowly), and I'll post it to the list when I do... --Ben G Dennis Gorelik [EMAIL PROTECTED] wrote: Ben,1) Could you describe what is the architecture of you INLINKinteractive framework?How is it going to handle natural language?2) I doubt that it's possible to communicate in natural languagecompletely unambiguously. There always will be some uncertainty.Intelligent system itself will have to decide how to interpretincoming message.3) Could you give an example of a program which will be generated bySasha programming framework?Sunday, July 4, 2004, 8:58:01 AM, you wrote:BG We're developing two powerful methods for communicating with Novamente:BG 1) the INLINK interactive NL framework, which allows naturalBG language to be communicated
Re: [agi] Teaching AI's to self-modify
Hi Dennis, Sorry for the long delay in reply, I've been on vacation and am now plowing through a big pile of backed-up emails To answer your three questions... 1) We have an NLP framework that uses a variation of the carnegie-mellon "link parser" together with a bunch of special "semantic algorithms" for mapping syntactic links into semantic ones, and some probabilistic inference based algorithms for semantic disambiguation reference resolution. Given a sentence this framework makes a number of prioritized guesses regarding the correct interpretation of the sentence. The user gets to view these guesses and correct them via a UI; for instance, they can select from several possible parses, they can change the selected meaning of a word to a different one (choosing from a menu of known meanings or defining a new one), etc. The overall process is much slower than just freely typing in natural language, but much faster than entering knowledge using an expert system, formal logic based approach. This will go into commercial use for one of our customers as of early september. 2) Of course, I agree that ambiguity can never be fully eliminated from natural language. NOvamente internally can deal with ambiguity. 3) As for an example of a program generated by Sasha In language processing, an example would be an algorithm for reference resolution --- normally one would code such a thing in C++ and stick it in a Novamente MindAgent, but if one codes it in Sasha then Novamente can not only execute it but also study and modify it, because it will be represented in the form of Novamente nodes and links. In a vision context, an example would be an algorithm for edge detection. This is less far along than INLINK. Right now we are using Sasha to generate programs doing simple math stuff and list manipulations etc.Over the next couple months we will hook it into the rest of Novamente and start using it for applications like the ones described above. The point is, it's a way of getting procedural knowledge into the system in a precise yet learnable/adaptable way. Whereas INLINK is a way of getting declarative knowledge into the system. Not very much like the process of teaching a human infant, of course. I think that kind of experiential interactive learning is going to be critical to teaching Novamente, BUT, I think it makes sense to augment it with these kinds of tricks like INLINK and Sasha, as a way of overcoming the deficit Novamente has, compared to humans, in terms of its lack of an evolved cognitive endowment. I plan to write a document on this stuff during the next few days (or perhaps the next week if things go slowly), and I'll post it to the list when I do... --Ben G Dennis Gorelik [EMAIL PROTECTED] wrote: Ben,1) Could you describe what is the architecture of you INLINKinteractive framework?How is it going to handle natural language?2) I doubt that it's possible to communicate in natural languagecompletely unambiguously. There always will be some uncertainty.Intelligent system itself will have to decide how to interpretincoming message.3) Could you give an example of a program which will be generated bySasha programming framework?Sunday, July 4, 2004, 8:58:01 AM, you wrote:BG We're developing two powerful methods for communicating with Novamente:BG 1) the INLINK interactive NL framework, which allows naturalBG language to be communicated to Novamente correctly andBG unambiguouslyBG 2) the Sasha programming framework, which allows the easyBG construction of software programs that manipulate Novamente nodesBG and links [and, rapid executable versions of these programs willBG be produced via supercompilation, www.supercompilers.com]. RightBG now, Novamente MindAgents, the processes that guide NovamenteBG cognition, are coded as C++ objects which are opaque to NovamenteBG cognition; but with the advent of Sasha, we'll be able to codeBG MindAgents as Novamente nodes and links which can in principle beBG modified/improved/replaced by Novamente cognition.---To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
RE: [agi] Teaching AI's to self-modify
The idea is to maintain two versions of each Novamente-internal procedure: -- a version that's amenable to learning (and generally highly compact), but not necessarily rapid to execute -- a version that's rapid to execute (produced by supercompiling the former version) As learning produces new procedures, they may be supercompiled. At present supercompiling a Novamente procedure is slow and takes up to a few seconds or even a few minutes for a large, complex procedure. However, the supercompiler itself is still in a preliminary version and could probably be optimized by an order of magnitude. In the long run there is also the concept of "supercompiling the supercompiler" ;-) This is research that we're just now starting to play around with -- we got the first results supercompiling very simple Novamente procedures just last week. If all goes well, more serious work in this direction will commence in the fall. Of course, this aspect is "just computer science" -- albeit very difficult and advanced computer science. It's the learning of the procedures that's the really subtle part... which is the topic that has taken far more of my attention . Fortunately the Java-Supercompilers team (Andrei and Arkady Klimov) seem to have the supercompilation aspect well in hand... But though it's "just CS", it wil be very useful for Novamente-learned procedures to be faster than, rather than a couple orders of magnitude slower than, Novamente-embedded procedures coded directly in C++ . This is not the hardest part of having Novamente learn to self-improve, but it's a necessarycomponent. -- Ben G -Original Message-From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]On Behalf Of [EMAIL PROTECTED]Sent: Sunday, July 04, 2004 11:11 PMTo: [EMAIL PROTECTED]Subject: Re: [agi] Teaching AI's to self-modify Ben, Aren'toptimizations bysupercompilation going to make the future changes of that code more (maybe a lot more)difficult? Sincerely, Jiri In a message dated 7/4/2004 9:58:41 AM Eastern Standard Time, [EMAIL PROTECTED] writes: http://www.supercompilers.com/ To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
Re: [agi] Teaching AI's to self-modify
Hi Ben, If the AI knows the machine as its natural context (stacks, registers, etc., ie, world), then the supercompiled code should be the only code it can comprehend and self modify. The code produced by the C++ compiler would be orders of magnitude more complex. Imagine an article in your favorite magazine where every noun and verb were indirect references to paragraphs in other articles of the magazine, and you could only aproach comprehension of the article by route of approaching the comprehension of the intersection of all of the articles --- after reading and rereading every article many times --- eg, Foucault's exemplary chapter from 'Les Mots', Las Meninas. This is the situation faced by a self aware (as in the first sentence) AI written in C++. If the product of supercompilation is akin to the most minimal implementation in assembler (machine code), then that's the only thing the AI will be able to understand --- unless you're thinking of the AI as an expert system programmed with knowledge of the product of the C++ compiler. That being said, it's difficult to imagine. Rather, consider the self of the AI, as in itself, is an application in nodes and links and self modification in terms of nodes and links rather than machine code (differentiating terms). The remainder follows. If the application is the knowledge of the machine, etc.. Don't drink, and think about this one! Regards from NJ, John The idea is to maintain two versions of each Novamente-internal procedure: -- a version that's amenable to learning (and generally highly compact), but not necessarily rapid to execute -- a version that's rapid to execute (produced by supercompiling the former version) As learning produces new procedures, they may be supercompiled. At present supercompiling a Novamente procedure is slow and takes up to a few seconds or even a few minutes for a large, complex procedure. However, the supercompiler itself is still in a preliminary version and could probably be optimized by an order of magnitude. In the long run there is also the concept of supercompiling the supercompiler ;-) This is research that we're just now starting to play around with -- we got the first results supercompiling very simple Novamente procedures just last week. If all goes well, more serious work in this direction will commence in the fall. Of course, this aspect is just computer science -- albeit very difficult and advanced computer science. It's the learning of the procedures that's the really subtle part... which is the topic that has taken far more of my attention . Fortunately the Java-Supercompilers team (Andrei and Arkady Klimov) seem to have the supercompilation aspect well in hand... But though it's just CS, it wil be very useful for Novamente-learned procedures to be faster than, rather than a couple orders of magnitude slower than, Novamente-embedded procedures coded directly in C++ . This is not the hardest part of having Novamente learn to self-improve, but it's a necessary component. -- Ben G -Original Message- *From:* [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of [EMAIL PROTECTED] *Sent:* Sunday, July 04, 2004 11:11 PM *To:* [EMAIL PROTECTED] *Subject:* Re: [agi] Teaching AI's to self-modify Ben, Aren't optimizations by supercompilation going to make the future changes of that code more (maybe a lot more) difficult? Sincerely, Jiri In a message dated 7/4/2004 9:58:41 AM Eastern Standard Time, [EMAIL PROTECTED] writes: http://www.supercompilers.com/ To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
RE: [agi] Teaching AI's to self-modify
Hi John, Initially Novamente will not know anything about its underlying hardware architecture. Rather, it will learn procedures that are represented in a fairly abstract mathematical form (combinatory logic) and that manipulate Novamente nodes and links as primitives alongside ints, floats and strings. In a later phase of teaching, we will teach Novamente about computer hardware and its impact on algorithms, etc., but we can get a long way before this is necessary -- perhaps even to the level of superhuman superintelligence ;-) ... math is pretty powerful! -- Ben -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of John Pritchard Sent: Monday, July 05, 2004 2:31 PM To: [EMAIL PROTECTED] Subject: Re: [agi] Teaching AI's to self-modify Hi Ben, If the AI knows the machine as its natural context (stacks, registers, etc., ie, world), then the supercompiled code should be the only code it can comprehend and self modify. The code produced by the C++ compiler would be orders of magnitude more complex. Imagine an article in your favorite magazine where every noun and verb were indirect references to paragraphs in other articles of the magazine, and you could only aproach comprehension of the article by route of approaching the comprehension of the intersection of all of the articles --- after reading and rereading every article many times --- eg, Foucault's exemplary chapter from 'Les Mots', Las Meninas. This is the situation faced by a self aware (as in the first sentence) AI written in C++. If the product of supercompilation is akin to the most minimal implementation in assembler (machine code), then that's the only thing the AI will be able to understand --- unless you're thinking of the AI as an expert system programmed with knowledge of the product of the C++ compiler. That being said, it's difficult to imagine. Rather, consider the self of the AI, as in itself, is an application in nodes and links and self modification in terms of nodes and links rather than machine code (differentiating terms). The remainder follows. If the application is the knowledge of the machine, etc.. Don't drink, and think about this one! Regards from NJ, John The idea is to maintain two versions of each Novamente-internal procedure: -- a version that's amenable to learning (and generally highly compact), but not necessarily rapid to execute -- a version that's rapid to execute (produced by supercompiling the former version) As learning produces new procedures, they may be supercompiled. At present supercompiling a Novamente procedure is slow and takes up to a few seconds or even a few minutes for a large, complex procedure. However, the supercompiler itself is still in a preliminary version and could probably be optimized by an order of magnitude. In the long run there is also the concept of supercompiling the supercompiler ;-) This is research that we're just now starting to play around with -- we got the first results supercompiling very simple Novamente procedures just last week. If all goes well, more serious work in this direction will commence in the fall. Of course, this aspect is just computer science -- albeit very difficult and advanced computer science. It's the learning of the procedures that's the really subtle part... which is the topic that has taken far more of my attention . Fortunately the Java-Supercompilers team (Andrei and Arkady Klimov) seem to have the supercompilation aspect well in hand... But though it's just CS, it wil be very useful for Novamente-learned procedures to be faster than, rather than a couple orders of magnitude slower than, Novamente-embedded procedures coded directly in C++ . This is not the hardest part of having Novamente learn to self-improve, but it's a necessary component. -- Ben G -Original Message- *From:* [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of [EMAIL PROTECTED] *Sent:* Sunday, July 04, 2004 11:11 PM *To:* [EMAIL PROTECTED] *Subject:* Re: [agi] Teaching AI's to self-modify Ben, Aren't optimizations by supercompilation going to make the future changes of that code more (maybe a lot more) difficult? Sincerely, Jiri In a message dated 7/4/2004 9:58:41 AM Eastern Standard Time, [EMAIL PROTECTED] writes: http://www.supercompilers.com/ To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED
Re: [agi] Teaching AI's to self-modify
Ben, I hope you are going to keep a human in the loop. Human in the loop scenario: The alpha Novamente makes a suggestion about some change to its software. The human implements the change on the beta Novamente running on a separate machine, and tests it. If it seems to be an improvement, it is incorporated into the alpha Novamente. Human not in the loop scenario: The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The humans wonder what the hell is going on. Mike Deering. To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
RE: [agi] Teaching AI's to self-modify
Hi, Because we use a lot of evolutionary learning methods, it will work more like: A whole populatoin of Novamentes (10 or so for starters, later perhaps much more) repeatedly try out new MindAgents (cognitive-control objects) on some test-cognitive-problems and see how well it does. Another Novamente, the controller, studies which of the new MindAgents work well, and mines patterns among these, creating new MindAgents to try out So there is no human in the learning loop Furthermore, for a human to understand the intricate details of a learned procedure (e.g. an automaticallylearned MindAgent) may be very hard Just as understanding the details of our own adaptively learned neural wiring is very hard -- Ben -Original Message-From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]On Behalf Of deeringSent: Monday, July 05, 2004 2:54 PMTo: [EMAIL PROTECTED]Subject: Re: [agi] Teaching AI's to self-modify Ben, I hope you are going to keep a human in the loop. Human in the loop scenario: The alpha Novamente makes a suggestion about some change to its software. The human implements the change on the beta Novamente running on a separate machine, and tests it. If it seems to be an improvement, it is incorporated into the alpha Novamente. Human not in the loop scenario: The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The Novamente looks at its code. The Novamente makes changes to its code, and reboots itself. The humans wonder what the hell is going on. Mike Deering. To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED] To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
Re: [agi] Teaching AI's to self-modify
Ben, 1) Could you describe what is the architecture of you INLINK interactive framework? How is it going to handle natural language? 2) I doubt that it's possible to communicate in natural language completely unambiguously. There always will be some uncertainty. Intelligent system itself will have to decide how to interpret incoming message. 3) Could you give an example of a program which will be generated by Sasha programming framework? Sunday, July 4, 2004, 8:58:01 AM, you wrote: BG We're developing two powerful methods for communicating with Novamente: BG 1) the INLINK interactive NL framework, which allows natural BG language to be communicated to Novamente correctly and BG unambiguously BG 2) the Sasha programming framework, which allows the easy BG construction of software programs that manipulate Novamente nodes BG and links [and, rapid executable versions of these programs will BG be produced via supercompilation, www.supercompilers.com]. Right BG now, Novamente MindAgents, the processes that guide Novamente BG cognition, are coded as C++ objects which are opaque to Novamente BG cognition; but with the advent of Sasha, we'll be able to code BG MindAgents as Novamente nodes and links which can in principle be BG modified/improved/replaced by Novamente cognition. --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
