Google’s Tensor Processing Units (TPUs), the company’s custom chips for running machine learning workloads written for its TensorFlow framework, are now available to developers. The promise of ...

Shutterstock. Google Cloud has announced the general availability of TPU virtual machines (VMs) for artificial intelligence workloads. The general availability release includes a new TPU embedding ...

Google CEO Sundar Pichai outlined TPU 3.0, short for the third version of the Tensor Processing Unit. TPUs are Google's custom application specific processor to accelerate machine learning and ...

Today Google announced that its Google Cloud TPU Pods are now publicly available in beta. Designed to help Machine Learning researchers iterate faster and train more capable machine learning models, ...

Google claims the each second-generation TPU can deliver up to 180 teraflops of performance. We will have to wait and see what the average benchmarks look like, but they are a step forward for ...

Google is nothing if not ambitious about its machine learning plans. Around this time last year it unveiled its custom Tensor Processing Unit (TPU) hardware accelerator designed to run its ...

Google also announced the TensorFlow Research Cloud, a 1,000-TPU (4,000 Cloud TPU Chip) supercomputer delivering 180 PetaFlops (one thousand trillion, or one quadrillion, presumably 16-bit FLOPS ...

Google launches powerful new Cloud TPU machine-learning chips for Google Cloud Platform. by Tom Krazit on May 17, 2017 at 10:54 am May 17, 2017 at 12:23 pm. Share 23 Tweet Share Reddit Email.

The TensorFlow-tailored TPU, which has been running inside the firm’s data centers for more than a year now, delivered “an order of magnitude better-optimized performance per watt for machine ...

Unlike TPU v1, which used 3.5-inch drive bays as its form factor, TPU v2 was welded together in groups of four ASIC chips. Google currently deploys TPUs in clusters of up to 64 boards, at 11.5 ...