Google's AI-Building AI Is a Step Toward Self-Improving AI

Reaching the technological singularity is almost certainly going to involve AI that is able to improve itself. Google may have now taken a small step along this path by creating AI that can build AI. Speaking at the company's annual I/O developer conference, CEO Sundar Pichai announced a project called AutoML that can automate one of the hardest parts of designing deep learning software: choosing the right architecture for a neural network. The Google researchers created a machine learning system that used reinforcement learning--the trial and error approach at the heart of many of Google's most notable AI exploits--to figure out the best architectures to solve language and image recognition tasks. Not only did the results rival or beat the performance of the best human-designed architectures, but the system made some unconventional choices that researchers had previously considered inappropriate for those kinds of tasks.