On Thu, Feb 10, 2005 at 10:15:25AM -0500, Brad Wyble wrote: > >Evolution is limited by mutation rates and generation times. Mammals > >need from 1 to 15 years before they reach reproductive age. Generation > > That time is not useless or wasted. Their brains are acquiring > information, molding themselves. I don't think you can just skip it.
Most lower organisms are genetically determined. Even so, at a speedup rate of 1:10^6 a wall clock-day is worth 3 kiloyears simulation time. > 10^ 9 generations per second? This rate depends(inversely) on the 10^9 generations/second is absurdly high. 10^9 rate is about the top of event rate in the simulation you could hope to achieve, given what we know of computational physics. Fitness testing seconds to minutes on very large populations looks very doable, though. Some complex behaviour can be evaluated in some 10-100 ms with massively parallel molecular hardware. Of course, current state of the art is pathetic: <http://darwin2k.com>. People would laugh if you'd say plausible fake physics simulators could scale O(1). Then, would Sutherland expect Nalu, or Dawn? http://www.nzone.com/object/nzone_downloads_nvidia.html > complexity of your organism. No. The simulation handles virtual substrate, and that's O(1) if you match organism size with volume of dedicated hardware, assuming local signalling (which is ~ms constrained in biology, and ~ps..~fs constrained relativistically). > And while fitness functions for simple ant AI's are (relatvely) simple to > write and evaluate, when you start talking about human level AI, you need People can be paid or volunteer to judge organism performance from interactive simulation. Co-evolution has a built-in drive and has no intrinsic fitness function but the naturally emergent one. > a very thorugh competition, involving much scoial interaction. This takes > *time* whether simulated time or realtime, it will add up. > > A simple model of interaction between AI's will give you simple AI's. We > didn't start getting really smart until we could exchange meaningful > ideas. What I'm interested in an efficient, robustly evolvable framework. It doesn't take more than insect equivalent complexity to achieve that. This implies full genetic determinism and simple fitness testing. > I'd be careful throwing around guesses like that. You're dealing with so > many layers of unknown. > > Before the accusation comes, I'm not saying these problems are unsolvable. > I'm just saying that (barring planetoid computers) sufficient hardware is Are you seeing any specific physical limits in building systems hundreds of km^3 large? And why do you think you need systems of nontrivial size for evolutionary bootstrap of intelligence? Buckytronics are just molecules. > a tiny fraction of the problem. But I'm hearing a disconcerting level of > optimism here that if we just wait long enough, it'll happen on all of our > desktops with off-the shelf AI building kits. > > Let me defuse another criticism of my perspective, I'm not saying we need > to copy the brain. However, the brain is an excellent lesson of how Hard > this problem is and should certainly be embraced as such. Constraints on biological tissue are very different from constraints of electron or electron spin distributions in solid state circuits switching in GHz to THz range. While the overall architecture definitely contains lots of components necessary for hitting a fertile region in problem space, slavishly copying the microarchitecture is likely to only lead you astray. -- Eugen* Leitl <a href="http://leitl.org";>leitl</a> ______________________________________________________________ ICBM: 48.07078, 11.61144 http://www.leitl.org 8B29F6BE: 099D 78BA 2FD3 B014 B08A 7779 75B0 2443 8B29 F6BE http://moleculardevices.org http://nanomachines.net ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
pgppJwj3lcM0l.pgp
Description: PGP signature
