New AI framework autonomously optimizes training data, architectures and algorithms — outperforming human baselines
via arxiv.org
Short excerpt below. Read at the original source.
AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottleneck by automating the full optimization loop for training data, model architectures, and learning algorithms. A new framework called ASI-EVOLVE, developed by researchers at the […]