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Google unveils custom chip for machine learning

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Mark Moore
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The chip needs fewer transistors to perform operations.

Google has developed a custom chip to improve machine learning capabilities used by its own teams in various applications.

Google's distinguished hardware engineer Norm Jouppi said: "This is roughly equivalent to fast-forwarding technology about seven years into the future three generations of Moore's Law ."

Jouppi said: "Because of this, we can squeeze more operations per second into the silicon, use more sophisticated and powerful machine learning models and apply these models more quickly, so users get more intelligent results more rapidly."

In February, it had launched its TensorFlow Serving as open source to help developers in taking their machine learning models into production.

The TensorFlow Serving system, which was made available on GitHub under the Apache 2.0 license, was aimed at enabling developers to easily implement new algorithms and experiments.

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