Re: [agi] Setting up the systems....
With just a little success, you could fund your operation via the stock market predictions, this would also prove your models capability. All you have to do is be able to make more than the losses. The stock market on a macro scale does move according to business and known principles but only small 5-6% returns can be had investing in broad spectrum investing. On the microscopic scale (where the real money is) there are no overriding rules the market follows. Human behavior is *not* particularly rational. It is possible to bet on the irrationality of mankind but just after you place your bet *that* stock will behave rationally. Programs to predict stock prices are all over the place and their presence only makes the market include that fact in it's current price. Playing the stock market by an AGI will not be the way to fund more research IMHO. -- David Clark --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
RE: [agi] Setting up the systems....
About computational finance... I think this is one plausible approach to funding AGI research -- but it's not a surefire route to success, IMO it's just another interesting narrow-AI problem to attack, with the potential to generate a lot of cash and the certainty of absorbing a lot of attention along the way... My experience is that in building any narrow-AI app based on Novamente components, around 80% of the work goes into the application and the domain-engineering and 20% into stuff of general value for Novamente. This is the nature of narrow AI. I'm sure it's the same with financial prediction. The Novamente learning algorithms definitely have the potential to yield powerful financial predictions -- but building, tuning and testing an actual trading system around these predictions is not a trivial matter. It's not something I could do in my spare time (Want to invest $30K so I can pay someone to create a Novamente-based trading system? Send me an e-mail and we'll talk ;-) I would say that, of all the narrow-AI application areas out there, the bioinformatics area interests me most (www.biomind.com), because in addition to having revenue-generation potential and helping to build up Novamente, it involves both -- doing good science -- doing good (e.g. some of our recent work has helped biologists gain new insight into the roots of Parkinson's disease) along the way. Life extension research is important to me, though not as important as AGI, and Biomind's work -- based on some Novamente components wrapped in a lot of bioinformatics code -- has a lot of potential in this area. Computational finance is appealing in terms of its potential for highly rapid revenue generation, but lacks the scientific interest and moral value of biology-related commercial AI work. -- Ben -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of David Clark Sent: Sunday, January 23, 2005 12:34 PM To: agi@v2.listbox.com Subject: Re: [agi] Setting up the systems With just a little success, you could fund your operation via the stock market predictions, this would also prove your models capability. All you have to do is be able to make more than the losses. The stock market on a macro scale does move according to business and known principles but only small 5-6% returns can be had investing in broad spectrum investing. On the microscopic scale (where the real money is) there are no overriding rules the market follows. Human behavior is *not* particularly rational. It is possible to bet on the irrationality of mankind but just after you place your bet *that* stock will behave rationally. Programs to predict stock prices are all over the place and their presence only makes the market include that fact in it's current price. Playing the stock market by an AGI will not be the way to fund more research IMHO. -- David Clark --- 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] Setting up the systems....
On Jan 23, 2005, at 10:01 AM, Ben Goertzel wrote: About computational finance... I think this is one plausible approach to funding AGI research -- but it's not a surefire route to success, IMO it's just another interesting narrow-AI problem to attack, with the potential to generate a lot of cash and the certainty of absorbing a lot of attention along the way... My experience is that in building any narrow-AI app based on Novamente components, around 80% of the work goes into the application and the domain-engineering and 20% into stuff of general value for Novamente. This is the nature of narrow AI. I'm sure it's the same with financial prediction. I would say that general high-quality financial market prediction implementation is more of a generalist domain than many other possible narrow-AI domains, such that really good implementations would only be narrow in an application sense. The abstract classes of data you have to integrate will map directly into most of the sensory fields that are often considered important for general purpose AI. The difficulty is that the financial community is not so interested in funding blue-sky research as they are in acquiring interesting implementations of theory. If you have something that works then money is no object, but most won't pay you to develop your ideas unless you already have a some examples of efficacy in the problem space to show. On the other hand, they are probably more explicitly aware of AI than just about any other business community. j. andrew rogers --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
Re: [agi] Setting up the systems....
Ben said: My experience is that in building any narrow-AI app based on Novamente components, around 80% of the work goes into the application and the domain-engineering and 20% into stuff of general value for Novamente Abdrew said: I would say that general high-quality financial market prediction implementation is more of a generalist domain than many other possible narrow-AI domains, such that really good implementations would only be narrow in an application sense. The abstract classes of data you have to integrate will map directly into most of the sensory fields that are often considered important for general purpose AI. ..(snip) On the other hand, they are probably more explicitly aware of AI than just about any other business community. If financial work or other topic actually has a high demand for general intellligence, then if Novamente or any other AGI project teamed with a narrow AI group maybe the AGI team could develote most of it's time/money to the general AI aspects and the narrow AI team could worry about the 80% of the total task that is narrow. I know that the general and narrow systems have to integrate so each team will have to think about the work the other is doing but presumably the AGI team, under the two team scenario could spend more than 20% of its time on general AI work. Cheers, Philip --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
RE: [agi] Setting up the systems....
Hey Phil, Sounds good to me. Know anyone who wants to collaborate and split the profits? ;-) ben -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Philip Sutton Sent: Sunday, January 23, 2005 7:49 PM To: agi@v2.listbox.com Subject: Re: [agi] Setting up the systems Ben said: My experience is that in building any narrow-AI app based on Novamente components, around 80% of the work goes into the application and the domain-engineering and 20% into stuff of general value for Novamente Abdrew said: I would say that general high-quality financial market prediction implementation is more of a generalist domain than many other possible narrow-AI domains, such that really good implementations would only be narrow in an application sense. The abstract classes of data you have to integrate will map directly into most of the sensory fields that are often considered important for general purpose AI. ..(snip) On the other hand, they are probably more explicitly aware of AI than just about any other business community. If financial work or other topic actually has a high demand for general intellligence, then if Novamente or any other AGI project teamed with a narrow AI group maybe the AGI team could develote most of it's time/money to the general AI aspects and the narrow AI team could worry about the 80% of the total task that is narrow. I know that the general and narrow systems have to integrate so each team will have to think about the work the other is doing but presumably the AGI team, under the two team scenario could spend more than 20% of its time on general AI work. Cheers, Philip --- 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]
