TensorFlow is the default back-end for Keras, and the one recommended for many use cases involving GPU acceleration on Nvidia hardware via CUDA and cuDNN, as well as for Tensor Processing Unit ...

TensorFlow Lite is an open-source deep learning framework for on-device inference. The new tool is designed to adapt machine learning models to datasets with transfer learning.

A team of researchers from the University of British Columbia have grabbed Google’s XLA compiler which can spit out LLVM code directly from th e TensorFlow specifications and then be used to realize ...

In the release of TensorFlow 2.9, the performance improvements delivered by the Intel oneAPI Deep Neural Network Library are turned on by default.

“Nobody ever got fired for buying IBM” was the rallying cry of computing in the 1970s and 1980s, and the same could be said about using TensorFlow in the 2010s for deep learning.

When it comes to training deep learning models, NVIDIA may be getting all the attention. However, Intel is not sitting quietly, just staring at the massive AI opportunity. It is moving fast in ...

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker ...

While PyTorch is an excellent deep learning framework, there are other options worth exploring. TensorFlow , developed by Google, is a strong alternative, particularly for large-scale AI ...

Training deep learning models is costly and hard, but not as much as deploying and running them in production. Deci wants to help address that. Bringing Deep Learning to your hardware of choice ...

Wave Computing accelerates deep learning by using dataflow technology to eliminate the need for a host and co-processor in the processing of a neural network.. In November, 2018, Wave Computing closed ...