Transformers are a type of neural network architecture that was first developed by Google in its DeepMind laboratories. The tech was introduced to the world in a 2017 white paper called 'Attention is ...

an open source implementation of an accelerator platform for AI and traditional image processing workloads. Ztachip (pronounced “zeta-chip”) contains an array of custom processors, and is not ...

Discover how Google's LiteRT enhances on-device inference with GPU and NPU acceleration, making AI applications faster and more efficient. Learn more!

Learn More Maker of the popular PyTorch-Transformers model library, Hugging Face today said it’s bringing its NLP library to the TensorFlow machine learning framework. The PyTorch version of the ...

PyTorch’s popularity in the past few years is almost certainly tied to the success of Hugging Face’s Transformers library. Yes, Transformers now supports TensorFlow and JAX too, but it started ...

TensorFlow, which emerged out of Google in ... the team set about combining techniques to create an image processing workflow for drill core imagery. This involved developing a series of deep ...

Google has revealed new benchmark results for its custom TensorFlow processing unit ... of this model is that it creates an intuitive image of overall performance. The flat roofline represents ...