What Is Tensor Processing Unit (TPU)?

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In a world where the future is more machine than human, Google has been working tirelessly to create a processor that can keep pace with the demands of artificial intelligence, and it looks like they've finally done it. The tensor processing unit (TPU) is a proprietary type of processor designed by Google in 2016 for use with neural networks and in machine learning projects. Experts talk about these TPU processors helping achieve more significant amounts of low-level processing simultaneously. They are also said to be able to process data faster than GPUs (graphics processing units), which have traditionally been used for such tasks. Google has been using this new processor for its machine learning software since 2016, but it's also available for sale. It comes in three different sizes: 16 GB, 32 GB, and 64 GB. The search engine giant is known to be a master at innovation. Google started as a simple search engine running on 8-bit processors, but today it has become one of the world's leading innovators in AI technology. Google's next step in its evolution was to increase the memory and bandwidth of its systems so that they could execute CISC instructions. Experts point out that Google uses a mix-and-match approach rather than using tensor processing units exclusively. The company still promotes using CPUs and other resources along with the TPU. The TPUs are designed for machine learning, which can be used to help run everything from search algorithms to language translation. They'll be able to process vast amounts of data at once and handle complex problems more efficiently than traditional computers. We're incredibly excited about these new TPUs and want to share them with the world so that everyone can access their benefits," reads part of an announcement from Google. "By offering the functionality of TPUs as part of a proprietary system, Google can keep control of the TPUs and still offer use to clients.

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