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Articles récents
- Give Your RAG a Voice: Building an Audio Q&A Experience with Intel® AI for Enterprise RAG
- Reduce Downtime Up To 50% by Utilizing AI-Ready RAS Features of Intel® Xeon® Processors
- How to Fine-Tune an LLM on Intel® GPUs With Unsloth
- Intel® Xeon® Processors Set the Standard for Vector Search Benchmark Performance
- From Gold Rush to Factory: How to Think About TCO for Enterprise AI
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Neural networks news
Intel NN News
- Give Your RAG a Voice: Building an Audio Q&A Experience with Intel® AI for Enterprise RAG
Turn your RAG into a voice-powered assistant with Intel® AI for Enterprise RAG.
- Reduce Downtime Up To 50% by Utilizing AI-Ready RAS Features of Intel® Xeon® Processors
As generative and agentic AI use cases proliferate across nearly every industry, improving the […]
- How to Fine-Tune an LLM on Intel® GPUs With Unsloth
Fine-tuning an LLM doesn’t have to require massive infrastructure. With Unsloth now supporting […]
- Give Your RAG a Voice: Building an Audio Q&A Experience with Intel® AI for Enterprise RAG
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Archives de catégorie : Non classé
Document Summarization: Transforming Enterprise Content with Intel® AI for Enterprise RAG
Transform enterprise documents into insights with Document Summarization, optimized for Intel® Xeon® and Intel® Gaudi® with automated NUMA-aware scheduling.
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AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
We are thrilled to announce an official collaboration between SGLang and AutoRound, enabling low-bit quantization for efficient LLM inference.
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In-production AI Optimization Guide for Xeon: Search and Recommendation Use Case
In this guide, you’ll learn multiple aspects of optimizing the Search and Recommendation model deployed in Production using Intel Xeon CPU servers.
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Argonne’s Aurora Supercomputer Drives Simulations to Explore How Light Shapes Quantum Materials
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.
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Argonne’s Aurora Supercomputer Helps Power Breakthrough Simulations of 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.
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AERIS Earth Systems Model Pushes AI for Science to New Heights
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.
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Leveraging Edge AI for Business Innovation
Discover how Intel Edge AI merges computing and intelligence to drive automation, real-time decisions, and business transformation.
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Intel® AI for Enterprise Inference as a Deployable Architecture on IBM Cloud
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
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Scaling Intel® AI for Enterprise RAG Performance: 64-Core vs 96-Core Intel® Xeon®
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
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Comprehensive Analysis: Intel® AI for Enterprise RAG Performance
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
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