Google uses AI to design next-generation AI chips faster than humans can.

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Google uses machine learning to help design the

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next generation of machine learning chips. The design of the algorithm It's "comparable to or superior" to human-made ones, Google engineers say, but can be built much faster. According to the tech giant, a month-long task for humans can be accomplished by AI in less than six hours.

Google has been working on how to use machine learning to build chips for years. But this latest effort Described in an article this week in the journal Nature, it appears to be the first time research has been applied to a commercial product: Upcoming. A version of Google's TPU (tensor processing unit) chip optimized for AI computing.


“Our method was used in manufacturing to design the next-generation Google TPU,” the authors of the article, led by Azalia Mirhoseini, head of ML for Systems at Google.


In other words, AI is accelerating the future of AI development.


In this report, Google engineers noted that the work was "significant" for the chip industry. should help companies Explore possible architectural areas for designs to happen faster. and easier to customize the chip for specific workloads.


An editorial in Nature calls the research "a study in the field of research." He noted that such work could help offset the predicted end of Moore's Law. This is a chip design axiom from the 1970s that states that the number of transistors on a chip doubles every two years. AI doesn't have to solve the physical problem of squeezing more transistors on a chip. But it can help find other routes to optimize at the same rate.

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