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Articles récents
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
- Document Summarization: Transforming Enterprise Content with Intel® AI for Enterprise RAG
- AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
- In-production AI Optimization Guide for Xeon: Search and Recommendation Use Case
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Neural networks news
Intel NN News
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
The latest Intel® Xeon® 6 processors deliver performance advantages across key enterprise […]
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
Intel® Xeon® processors can deliver a CPU-first platform built for modern AI workloads without […]
- Document Summarization: Transforming Enterprise Content with Intel® AI for Enterprise RAG
Transform enterprise documents into insights with Document Summarization, optimized for Intel® […]
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
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Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
The latest Intel® Xeon® 6 processors deliver performance advantages across key enterprise workloads, enabling companies to deploy fewer servers and still deliver a similar aggregate performance level compared to AMD EPYC solutions
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Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
Intel® Xeon® processors can deliver a CPU-first platform built for modern AI workloads without added complexity or overhead.
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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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