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 ...
Application discovery, algorithms, error correction, resource estimation, hardware execution, and classical components are ...
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