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Google and others think software that learns to learn could take over some work done by AI experts.
Progress in artificial intelligence causes some people to worry that software will take jobs such as driving trucks away from humans. Now leading researchers are finding that they can make software that can learn to do one of the trickiest parts of their own jobs—the task of designing machine-learning software.
In one experiment, researchers at the Google Brain artificial intelligence research group had software design a machine-learning system to take a test used to benchmark software that processes language. What it came up with surpassed previously published results from software designed by humans.
In recent months several other groups have also reported progress on getting learning software to make learning software. They include researchers at the nonprofit research institute OpenAI (which was cofounded by Elon Musk), MIT, the University of California, Berkeley, and Google's other artificial intelligence research group, DeepMind.
If self-starting AI techniques become practical, they could increase the pace at which machine-learning software is implemented across the economy. Companies must currently pay a premium for machine-learning experts, who are in short supply.
(Score: 0) by Anonymous Coward on Friday January 20 2017, @07:47PM
GAs training and selecting GAs? This makes very little sense to me. The evaluator of the 'parent' is presumably optimizing towards the same evaluation as the 'child' (and if not, then what is the point?) in which case you're not actually picking and choosing anything, but just exponentially increasing the timescale of an elementary GA for no real reason since it's basically doing some sort of very complex g(f(a)) to get f(a)! If you can reference any papers or even articles or whatever it would be much appreciated because I have a rather difficult time imagining this was being done, as a thing.