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Building Fixed HW Implementations of Neural Networks (Yale, Cornell et al.)
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Building Fixed HW Implementations of Neural Networks (Yale, Cornell et al.)
Researchers from Yale University, Cornell University, Boston University, and NTT Research have published “Physical Foundation Models: Fixed hardware implementations of large-scale neural networks”. Abstract “Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks — text and code generation, question answering, summarization, image classification, and so …
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