Brain vs. Deep Learning (2015)
Long, and fascinating. I can see why this made the front page. I oscillated between 20% strident disagreement and 60% strident agreement. (The rest -- no strong feelings, or I feel that the questions are too ill-formed to answer.)<p>To pick one point of disagreement,<p><i>“We do not need as much computational power as the brain has, because our algorithms are (will be) better than that of the brain.”</i><p><i>I hope you can see after the descriptions in this blog post that this statement is rather arrogant.</i><p>Machines are already better than brains at many cognitive tasks of practical interest. Believing that we'll continue to find "tricks" to allow computers to outperform brains on useful cognitive tasks, despite the brains' much greater complexity, seems like a perfectly sober and conservative prediction.<p>If I had to advance my own pet reasons for discounting the likelihood of a technological singularity, here are my top two:<p>1) It's a more challenging case of the general Fermi paradox. Show me the Hubble images of the computronium Dyson swarms. If it takes less than a century to go from the first transistorized computers to superintelligence, and superintelligence is as prone to run amok as Bostrom/Yudkowsky think, signs should already be visible from Earth.<p>2) You need experiments to validate scientific models. Even if a machine-intelligence could think a billion times faster than a biological intelligence, it couldn't complete experiments a billion times faster. Technologies that act on the material world will improve sublinearly with respect to thinking/computing power, for at least this reason and probably others as well.