The term "flow" refers to this movement of data through the various stages of model training or inference. Graphs: One of the reasons for TensorFlow’s popularity is its graph-based architecture.

Whereas the existing TensorFlow runtime was initially built for graph execution and training workloads, the new runtime will make eager execution and inference first-class citizens. Graph ...

You’ll see terms like “sea-of-MACs,” “systolic array,” “dataflow architecture,” “graph ... and inference rate.” Fig. 1: A block diagram for devices using Syntiant’s second-generation core. The ...

With tight integration with Kubeflow, the Kubernetes ecosystem is taking advantage of the scale of containers for training and inference of TensorFlow models. 5. Backed by Google’s research ...

Google has revealed new benchmark results for its custom TensorFlow processing unit, or TPU. In inference workloads, the company's ASIC positively smokes hardware from Intel, Nvidia. Share on ...

TensorFlow can be used for a type of artificial intelligence called deep learning, which involves training artificial neural networks on lots of data and then getting them to make inferences about ...

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