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Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding
Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
Every day, various types of sensory information fromthe external environment are transferred to the brainthrough different modalities and then processed to generate a series of coping behaviors. Among ...
A recent paper from Friedrich-Alexander University benchmarks energy consumption and compression efficiency for six video codecs across software and hardware decoders. While the study uses VP9 as a ...
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