Hi Robin. In part it depends on what you mean by "fast". 1. "Fast" -> less than 10 years. I do not believe there are any strong arguments for general-purpose AI being developed in this timeframe. The argument here is not that it is likely, but rather that it is *possible*. Some AI researchers, such as Marvin Minsky, believe that we already have the necessary hardware commonly available, if we only knew what software to write for it. If, as seems likely, there is a large economic incentive for the development of this software, it seems reasonable to grant the possibility that it will be developed. Following that line of reasoning, a computation of "probability * impact" yields a large number for even small probabilities since the impact of a technological singularity could be very large. So planning for the possibility seems prudent. 2. "Fast" -> less than 50 years. For this timeframe, just dust off Moravec's old computer speed chart. On such a chart I think we're supposed to be at something like mouse level right now -- and in fact we have seen supercomputers beginning to take a shot at simulating mouse-brain-like structures. It does not feel so wrong to think that the robot cars succeeding in the DARPA challenges are maybe up to mouse-level capabilities. It is certainly possible that once computers surpass the raw processing power of the human brain by 10, 100, 1000 times, we will just be too stupid to keep up with their capabilities for some reason, but it seems like a more reasonable bet to me that the economic pressures to make somewhat good use of available computing resources will win out. AI is often called a perpetual failure, but from this view that is not true at all; AI has been a spectacular success. It's very impressive that the early researchers were able to get computers with nematode-level "nervous systems" to show any interesting cognitive behavior at all. At worst, AI is keeping up with the available machine capabilities admirably. Still, putting aside the "brain simulation" route, we do have to build models of mind that actually work. As Pei Wang just pointed out, we are beginning to see models such as Ben Goertzel's Novamente that at least seem like they might have a shot at sufficiency. That is not proof, but it is an indication that we may not be overmatched by this challenge, once the machinery becomes available. If something like Moore's law continues (I suppose it's a cognitive bias to assume it will continue and a different bias to assume it won't), who wants to bet that computers 10,000, 100,000, or 1,000,000 times as powerful as our brains will go to waste? Add as many zeros as you want... they cost five years each. ----- Having written that, I confess it is not completely convincing. There are a lot of assumptions involved. I don't think there *is* an objectively convincing argument. That's why I never try to convince anybody... I can play in the intersection between engineering and wishful thinking if I want, simply because it amuses me more than watching football. Hopefully some folks with more earnest beliefs will have better arguments for you.
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