Google claims new AI training tech is 13x faster and 10x more power efficient – DeepMind's new JEST optimizes training data for big gains.

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Google DeepMind, Google's AI research lab, has published new research on training AI models that claims to speed up both training speed and energy efficiency by orders of magnitude, compared to other models. Gives 13 times more performance and 10 times more power efficiency than conventional methods. The new JEST training method comes timely as the conversation about the environmental impact of AI data centers is intensifying.

DeepMind's method, called JEST or joint instance selection, departs from traditional AI model training techniques in a simple way. Conventional training methods focus on individual data points for training and learning, while JEST trains based on entire batches. The JEST method first builds a small AI model that classifies data quality from the highest quality sources, classifying batches by quality. It then compares this ranking to a larger, lower-quality set. The smaller JEST model determines the most suitable batches for training, and then a larger model is trained from the results of the smaller model.

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