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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 ...
As Enterprise AI matures from experimental chatbots to production-grade Agentic workflows, a silent infrastructure crisis is the VRAM bottleneck. Deploying a dedicated endpoint for every fine-tuned ...
The traditional model of memory proposes that different types of long term memory are processed in separate brain modules. New research shows activation of these modules overlaps.
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