Archives de catégorie : Non classé

We are thrilled to announce an official collaboration between SGLang and AutoRound, enabling low-bit quantization for efficient LLM inference.

In this guide, you’ll learn multiple aspects of optimizing the Search and Recommendation model deployed in Production using Intel Xeon CPU servers. 

Researchers using the Aurora supercomputer at the U.S. Department of Energy’s Argonne National Laboratory have achieved the largest-ever simulations of light interacting with quantum materials.

Using three U.S. Department of Energy (DOE) supercomputers, researchers from the University of Southern California (USC) and DOE’s Lawrence Berkeley National Laboratory developed new ways to model these complex systems with greater precision than ever before.

Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory introduce AERIS, a breakthrough AI system learning from decades of Earth systems data to deliver fast, high-resolution forecasts.

Discover how Intel Edge AI merges computing and intelligence to drive automation, real-time decisions, and business transformation.

Intel® AI for Enterprise Inference as a Deployable Architecture on IBM Cloud The enterprise AI landscape demands solutions that can scale efficiently while maintaining operational simplicity and cost-effectiveness. Intel® AI for Enterprise Inference (Enterprise Inference), powered by the Open Platform … Continuer la lecture →

This evaluation shows materially higher concurrency and improved latency scaling when moving from a 64-core to a 96-core Intel® Xeon® configuration for Intel® AI for Enterprise RAG inference. The 96-core SKU doubles SLA-compliant concurrency for Llama-AWQ and Mistral-AWQ (32 → … Continuer la lecture →

This comprehensive analysis demonstrates that systems with two 64-core Intel® Xeon® processors can effectively support enterprise-scale RAG deployments, handling up to 32 concurrent users with optimized configurations that comply with targeted SLAs. These results validate Intel® Xeon® as a viable … Continuer la lecture →

Small Language Models (SLMs) are emerging as the nimble, quick-thinking counterparts to LLMs providing specialized knowledge in a way that is lean, fast and cost-effective.