A year ago, ZDNet spoke with Google Brain director Jeff Dean about how the company is using artificial intelligence to advance its internal development of custom chips to accelerate its software. Dean noted that deep learning forms of artificial intelligence can in some cases make better decisions than humans about how to lay out circuitry in a chip. This month, Google unveiled to the world one of those research projects, called Apollo, in a paper posted on the arXiv file server , “Apollo: Transferable Architecture Exploration,” and a companion blog post by lead author Amir Yazdanbakhsh. Apollo represents an intriguing development that moves past what Dean hinted at in his formal address a year ago at the International Solid State Circuits Conference, and in his remarks to ZDNet . In the example Dean gave at the time, machine learning could be used for some low-level design decisions, known as “place and route.” In place and route, chip designers use software to determine the layout of the circuits that form the chip’s operations, analogous to designing the floor plan of a building. In Apollo, by contrast, rather than a floor plan, the program is performing what Yazdanbakhsh and colleagues call “architecture… Read full this story
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