On 22 Oct 2006 at 17:22, Samantha Atkins wrote: > It is a lot easier I imagine to find many people willing and able to > donate on the order of $100/month indefinitely to such a cause than to > find one or a few people to put up the entire amount. I am sure that has > already been kicked around. Why wouldn't it work though?
There have been many, many well funded AGI projects in the past, public and private. Most of them didn't produce anything useful at all. A few managed some narrow AI spinoffs. Most of the directors of those projects were just as confident about success as Ben and Peter are. All of them were wrong. No-one on this list has produced any evidence (publically) that they can succeed where all previous attempts failed other than cute powerpoint slides - which all the previous projects had too. All you can do judge architecture by the vauge descriptions given, and the history of AI strongly suggests that even when full details are available, even so-called experts completely suck at judging what will work and what won't. The chances of arbitrary donors correctly ascertaining what approaches will work are effectively zero. The usual strategy is to judge by hot buzzword count and apparent project credibility (number of PhDs, papers published by leader, how cool the website and offices are, number of glowing writeups in specialist press; remember Thinking Machines Corp?). Needless to say, this doesn't have a good track record either. As far as I can see, there are only two good reasons to throw funding at a specific AGI project you're not actually involved in (ignoring the critical FAI problem for a moment); hard evidence that the software in question can produce intelligent behaviour significantly in advance of the state of the art, or a genuinely novel attack on the problem - not just a new mix of AI concepts in the architecture, /everyone/ vaguely credible has that, a genuinely new methodology. Both of those have an expiry date after a few years with no further progress. I'd say the SIAI had a genuinely new methodology with the whole provable-FAI idea and to a lesser extent some of the nonpublished Bayesian AGI stuff that immediately followed LOGI, but I admit that they may well be past the 'no useful further results' expiry date for continued support from strangers. Setting up a structure that can handle the funding is a secondary issue. It's nontrivial, but it's clearly within the range of what reasonably competent and experienced people can do. The primary issue is evidence that raises the probability that any one project is going to buck the very high prior for failure, and neither hand-waving, buzzwords or powerpoint (should) cut it. Even detailed descriptions of the architecture with associated functional case studies, while interesting to read and perhaps convincing for other experts, historically won't help non-expert donors make the right choice. Radically novel projects like the SIAI /may/ be an exception (in a good or bad way), but for relatively conventional groups like AGIRI and AAII insist on seeing some of this supposedly already-amazing software before choosing which project to back. Personally if I had to back an AGI project other than our research approach at Bitphase, and I wasn't so dubious about his Friendliness strategy, I'd go with James Rogers' project, but I'd still estimate a less-than-5% chance of success even with indefinite funding. Ben would be a little way behind that with the proviso that I know his Friendliness strategy sucks, but he has been improving both that and his architecture so it's conceivable (though alas unlikely) that he'll fix it in time. AAII would be some way back behind that, with the minor benefit that if their architecture ever made it to AGI it's probably too opaque to undergo early take-off, but with the huge downside that when it finally does enter an accelerating recursive self-improvement phase what I know of the structure strongly suggests that the results will be effectively arbitrary (i.e. really bad). As noted, hard demonstrations of both capability and scaling (from anyone) will rapidly increase those probability estimates. I understand why many researchers are so careful about disclosure, but frankly without it I think it's unrealistic verging on dishonest to expect significant donated funding (ignoring the question of why the hell /companies/ would be fishing for donnations instead of investment). Michael Wilson Director of Research and Development Bitphase AI Ltd - http://www.bitphase.com ----- 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/[EMAIL PROTECTED]
