Building A.I. That Can Build A.I.

Building A.I. That Can Build A.I.
Jean-François Gagné, the chief executive of an independent machine-learning lab called
Element AI, refers to the process as “a new kind of computer programming.”
In building a neural network, researchers run dozens or even hundreds of experiments across a vast network of machines,
testing how well an algorithm can learn a task like recognizing an image or translating from one language to another.
“We are following the same path that computer science has followed with every new type of technology,” said Joseph Sirosh, a vice president at Microsoft, which recently unveiled a tool to help coders build deep neural networks, a type of computer algorithm
that is driving much of the recent progress in the A. I.
With it, Google may soon find a way to create A. I.
technology that can partly take the humans out of building the A. I.
systems that many believe are the future of the technology industry.
Google is investing heavily in cloud-computing services — services
that help other businesses build and run software — which it expects to be one of its primary economic engines in the years to come.
Eventually, the Google project will help companies build systems with artificial
intelligence even if they don’t have extensive expertise, Mr. Dean said.