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๐Ÿ“š Apple Researchers Propose KV-Runahead: An Efficient Parallel LLM Inference Technique to Minimize the Time-to-First-Token


๐Ÿ’ก Newskategorie: AI Nachrichten
๐Ÿ”— Quelle: marktechpost.com

Large language models (LLMs), particularly Generative Pre-trained Transformer (GPT) models, have demonstrated strong performance across various language tasks. However, challenges persist in their decoder architecture, Specifically in time-to-first-token (TTFT) and time-per-output token (TPOT). TTFT, reliant on extensive user context, and TPOT, for rapid subsequent token generation, have spurred research into memory-bound solutions like sparsification and [โ€ฆ]

The post Apple Researchers Propose KV-Runahead: An Efficient Parallel LLM Inference Technique to Minimize the Time-to-First-Token appeared first on MarkTechPost.

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