Essentially Kurzweil believes that the exponentially doubling trend in computer power will continue indefinitely – and this leads him to make an astonishing prediction: By 2045 he predicts a “technological singularity” will occur. Thus, Kurzweil’s estimate for achieving AGI (artificial general intelligence) by 2029 now seems reasonable to many knowledgeable individuals.Īchieving artificial general intelligence, however, is not Kurzweil’s most famous, nor most controversial, prediction. Additionally, given recent progress in artificial vision (Kinect), speech recognition and generation (Siri, Google Now), deep question answering (IBM’s Watson), and ongoing initiatives in the US and Europe to understand how the human brain works, the software component finally seems to be falling into place.
Regardless of whether 10 petaFLOPS, or 10 exaFLOPS, or something in between turns out to be the magic number necessary to support human level artificial intelligence, we appear to be quite close to achieving the necessary hardware. When he first came out with these predictions, most ‘reputable’ scientists gently shook their heads and smiled. If Kurzweil’s estimate is correct, why haven’t we already constructed an AI? The answer is simple, we haven’t yet figured out how to generate the appropriate software.įor many years, Kurzweil has used the year 2029 as his target for when we will achieve human level intelligence in a machine – a machine capable of passing the Turing Test. Amazingly, since our fastest supercomputers now run at over 33 petaFLOPS (as of 2013), according to Kurzweil we should already possess the necessary supercomputer hardware to support an artificial general intelligence. Kurzweil estimates that 10 petaFLOPS, 1/100 of an exaFLOPS, should be sufficient. Some, such as Ray Kurzweil, believe that human level cognition could eventually be accomplished on less powerful machines. As discussed above, scientists are beginning to converge on an estimate of 1 to 10 exaFLOPS as the amount of raw processing power needed to simulate a human brain in real time.
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