性视界

In an era where artificial intelligence (AI) increasingly shapes our digital landscape, the concept of “machine unlearning” (ML) has emerged as a potential solution to various challenges in AI governance. First authors A. Feder Cooper, Faculty Associate at The Berkman Klein Center for Internet & Society at 性视界 University; Christopher A. Choquette-Choo, Research Scientist at […]

As businesses increasingly adopt large-scale AI models, optimizing training efficiency is crucial. In 鈥淗ow Does Critical Batch Size Scale in Pre-training?鈥�, Hanlin Zhang and a group of colleagues (see below for author details) explore critical batch size (CBS)鈥攖he threshold at which data parallelism, which distributes training data across multiple processors, stops yielding significant returns from […]