Google (the real Google, within Alphabet) has announced a new, open-source machine learning platform called TensorFlow(Opens in a new window), one which could greatly accelerate the pace at which ...
While you can train simple neural networks with relatively small amounts of training data with TensorFlow, for deep neural networks with large training datasets you really need to use CUDA-capable ...
It's possible to create neural networks from raw code. But there are many code libraries you can use to speed up the process. These libraries include Microsoft CNTK, Google TensorFlow, Theano, PyTorch ...
Google is rebranding TensorFlow Lite to LiteRT (as in “lite runtime”). This lets you deploy ML and AI models on Android, iOS, and embedded devices. Basically, for on-device AI at the Edge. Google ...
TensorFlow Lite (TFLite) was announced in 2017 and Google is now calling it “LiteRT” to reflect how it supports third-party models. TensorFlow Lite for mobile on-device AI has “grown beyond its ...
This is new: TensorFlow 2.18 integrates the current version 2.0 of NumPy and, with Hermetic CUDA, will no longer require local CUDA libraries during the build. The ...
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