Eugen> Groan. The whole network computes. The synapse is just an Eugen> element. Also: you're missing on connectivity, Eugen> reconfigurability, synapse type and strength issues.
I'll definitely grant you reconfigurability. Might be fairer to compare to a programmable array. >> On a related subject, I argued in What is Thought? that the hard >> problem was not processor speed for running the AI, but coding the software. Eugen> Trust me, the speed is. Your biggest problem is memory Eugen> bandwidth, actually. Well, on this we differ. I can appreciate how you might think memory bandwidth was important for some tasks, although I don't, but I'm curious why you think its important for planning problems like Sokoban or Go, or a new planning game I present your AI on the fly, or whether you think whatever your big memory intensive approach is will solve those. Ben> However, evolution is not doing software design using anywhere Ben> near the same process that we human scientists are. So I don't Ben> think these sorts of calculations [of evolution's computational power] Ben> are very directly relevant... As you know, I argued that the problem of designing the relevant software is NP-hard at least, so it is not clear that it can be cracked without employing massive computation in its design, anymore than a team of experts could solve a large TSP problem by hand. However, I have an open mind on this, which I regard as the critical issue for AGI. Mark> VERY few Xeon transistors are used per clock tick. Many, many, Mark> MANY more brain synapses are firing at a time. How many Xeon transistors per clock tick? Any idea? I recall estimating .001 of neurons were firing at any given time (although I no longer recall how I reached that rough guesstimate.) And remember, the Xeon has a big speed factor. ------- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/[EMAIL PROTECTED]
