{"id":8517,"date":"2018-07-09T07:00:25","date_gmt":"2018-07-09T15:00:25","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=8517"},"modified":"2018-05-11T10:18:34","modified_gmt":"2018-05-11T18:18:34","slug":"artificial-intelligence-chips-google-s-tpu-3-0-offers-8x-performance-boost","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/artificial-intelligence-chips-google-s-tpu-3-0-offers-8x-performance-boost\/","title":{"rendered":"Artificial Intelligence Chips: Google &#8216;s TPU 3.0 Offers 8x Performance Boost"},"content":{"rendered":"<p>In May, Google announced the third generation release of a new chip called a <a href=\"https:\/\/cloud.google.com\/tpu\/\">TPU (Tensor Processing Unit)<\/a>.\u00a0 The first generation of TPUs was release in 2016, followed up shortly afterward with a speed-enhanced TPU version 2.0.\u00a0 The newest TPU 3.0 is 8 times faster than the TPU 2.0 and can handle 100 petaFLOPs or higher, putting it in the range of a supercomputer performance.\u00a0 But all that computational power makes the chips very hot &#8212; they require a special copper-plated cooling system to keep them from overheating.<\/p>\n<p>Google plans to offer TPU processors via a cloud service.\u00a0 Currently users can rent a board of TPUs for their projects.\u00a0 Google expects to start rolling out the TPU version 3.0 in the cloud soon.<\/p>\n<p>TPUs are optimized to run Google&#8217;s TensorFlow algorithm, used primarily for machine learning and artificial intelligence.\u00a0 With this approach, Google is trying to own the entire stack.\u00a0 <a href=\"http:\/\/www.bit-tech.net\/news\/tech\/cpus\/google-announces-100-petaflop-tpu-30-pod\/1\/\">Google recently reorganized and aligned<\/a> a number of projects that it had all under the umbrella that it is now calling &#8220;Google AI.&#8221; If Google&#8217;s platform can become advanced enough to attract users, they can lock developers into it. 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