Abstract: Large language models (LLMs) have achieved significant breakthroughs on machine learning tasks. Yet the substantial memory footprint of LLMs significantly hinders their wide deployment. In ...
Abstract: Compute-in-memory (CIM) is an efficient method for implementing deep neural networks (DNNs) but suffers from substantial overhead from analog-to-digital converters (ADCs), especially as ADC ...
Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex mathematical problems that underpin scientific and engineering challenges.
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Even the best AI models can't reliably do simple math
Artificial intelligence systems can write software and reason through complex problems. Yet even basic arithmetic can expose surprising weaknesses. A new study digs into why modern AI models stumble ...
† Computational Chemistry and Molecular Biophysics Unit, Molecular Targets and Medications Discovery Branch, National Institute on Drug Abuse—Intramural Research Program, National Institutes of Health ...
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