Google researchers recently published a describing a framework — SEED RL — that scales AI model training to thousands of machines. They say that it could facilitate training at millions of frames per second on a machine while reducing costs by up to 80%, potentially leveling the playing field for startups who couldn’t previously compete with large AI labs.

Training sophisticated machine learning models in the cloud remains prohibitively expensive. According to a recent Synced report, the University of Washington’s Grover, which is tailored for both the generation and detection of fake news, cost $25,000 to train over the course of two weeks. OpenAI racked up $256 per hour to train its language model and Google spent an estimated $6,912 training , a bidirectional transformer

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