A breakthrough low-memory technique by Rice University computer scientists could put one of the most resource-intensive forms of artificial intelligence — deep-learning recommendation models (DLRM) — within reach of small companies.
DLRM recommendation systems are a popular form of AI that learns to make suggestions users will find relevant. But with top-of-the-line training models requiring more than a hundred terabytes of memory and supercomputer-scale processing, they’ve only been available to a short list of technology giants with deep pockets.
Rice’s “random offset block embedding…
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News Source: www.sciencedaily.com