Qualcomm’s answer to Nvidia’s dominance in the artificial acceleration market is a pair of new chips for server racks, the A1200 and A1250, based on its existing neural processing unit (NPU) ...
A new technical paper titled “PICNIC: Silicon Photonic Interconnected Chiplets with Computational Network and In-memory Computing for LLM Inference Acceleration” was published by researchers at the ...
Apple and NVIDIA shared details of a collaboration to improve the performance of LLMs with a new text generation technique for AI. Cupertino writes: Accelerating LLM inference is an important ML ...
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 ...
RENO, Nev.--(BUSINESS WIRE)--Positron AI, the premier company for American-made semiconductors and inference hardware, today announced the close of a $51.6 million oversubscribed Series A funding ...
With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale. High inference latency and ...
ByteDance's Doubao AI team has open-sourced COMET, a Mixture of Experts (MoE) optimization framework that improves large language model (LLM) training efficiency while reducing costs. Already ...
In a blog post today, Apple engineers have shared new details on a collaboration with NVIDIA to implement faster text generation performance with large language models. Apple published and open ...
Dell has just unleashed its new PowerEdge XE9712 with NVIDIA GB200 NVL72 AI servers, with 30x faster real-time LLM performance over the H100 AI GPU. Dell Technologies' new AI Factory with NVIDIA sees ...
Even an older workstation-class eGPU like the NVIDIA Quadro P2200 delivers dramatically faster local LLM inference than CPU-only systems, with token-generation rates up to 8x higher. Running LLMs ...
Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...
A new technical paper titled “Architecting Long-Context LLM Acceleration with Packing-Prefetch Scheduler and Ultra-Large Capacity On-Chip Memories” was published by researchers at Georgia Institute of ...
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