A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...
Users running a quantized 7B model on a laptop expect 40+ tokens per second. A 30B MoE model on a high-end mobile device ...
Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...
Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Groq now allows you to make lightning fast ...
AWS CEO Matt Garman talks to CRN about its new Trainium3 AI accelerator chips being the ‘best inference platform in the world,’ AI openness being a market differentiator versus competitors, and ...
Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for ...
Cloud infrastructure startup Atlas Cloud today launched a highly optimized artificial intelligence inference service that it says dramatically reduces the computational requirements of even the most ...
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GTC Nvidia's Blackwell Ultra and upcoming Vera and Rubin CPUs and GPUs dominated the conversation at the corp's GPU Technology Conference this week. But arguably one of the most important ...
A new technical paper titled “Efficient LLM Inference: Bandwidth, Compute, Synchronization, and Capacity are all you need” was published by NVIDIA. “This paper presents a limit study of ...