Apple releases forked version of TensorFlow optimized for macOS Big Sur

Apple today released a forked version of TensorFlow, Google's AI and machine learning development environment, optimized for Intel Macs and Macs powered by Apple's new M1 chip. By taking advantage of the ML Compute framework on macOS Big Sur, Apple says, the Mac-optimized release of TensorFlow 2.4 allows developers to take leverage accelerated processor (CPU) and graphics card (GPU) training on hardware like the M1's 8-core CPU and 8-core GPU. Training sophisticated AI models can be prohibitively expensive for developers. For instance, Google spent an estimated $6,912 training BERT, a bidirectional transformer model that redefined the state of the art for 11 natural language processing tasks. While training models like BERT likely remains beyond the reach of commodity hardware like MacBooks, the new Mac-optimized TensorFlow package promises to lower the barrier to entry, enabling enterprises to train and deploy models more easily and cheaply than before.