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Articles récents
- 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
- Argonne’s Aurora Supercomputer Helps Power Breakthrough Simulations of Quantum Materials
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Neural networks news
Intel NN News
- 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® […]
- AutoRound Meets SGLang: Enabling Quantized Model Inference with AutoRound
We are thrilled to announce an official collaboration between SGLang and AutoRound, enabling […]
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
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Archives mensuelles : août 2025
Intel® Xeon® Processors: The Most Preferred CPU for AI Host Nodes
Today’s AI workloads are not purely offloaded to GPU accelerators. Host CPUs such as the Intel® Xeon® 6 processors play a significant role in maximizing the performance of AI-accelerated systems.
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Building AI With Empathy: Sorenson’s Mission for Accessibility
For Sorenson Senior Director of AI Mariam Rahmani, the future of AI isn’t about building the flashiest models—it’s about creating solutions that close communication gaps and empower people, especially the Deaf and Hard of Hearing community. With a third of … Continuer la lecture
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Multi-node deployments using Intel® AI for Enterprise RAG
As enterprises scale generative AI across diverse infrastructures, Intel® AI for Enterprise RAG solution delivers a modular, hardware-aware framework for Retrieval-Augmented Generation (RAG) optimized for Kubernetes and Intel platforms. With intelligent scheduling, NUMA-aware resource isolation, and dynamic scaling, it ensures predictable, … Continuer la lecture
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Connected Data is the Future: How Neo4j Is Enabling the Next Generation of AI
In the evolving landscape of artificial intelligence, connected data is becoming a core competitive advantage.
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Orchestrating AI for Real Business Value: Google Cloud’s Approach to Scalable Intelligence
In the race to operationalize AI, success hinges not on hype, but on clarity, customization, and speed to value. According to Riyaz Habibbhai, Director of Product Marketing at Google Cloud, truly effective AI product marketing focuses on one simple but … Continuer la lecture
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Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
Researchers from the University of Texas at Austin and Intel Labs investigated chain-of-thought reasoning structures in large language models to identify and calibrate flawed reasoning pathways
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Intel Labs Works with Hugging Face to Deploy Tools for Enhanced LLM Efficiency
Large Language Models are revolutionizing AI applications; however, slow inference speeds continue to be a significant challenge. Intel researchers, along with industry and university partners, are actively working to address this issue and accelerate the efficiency of LLMs. In a … Continuer la lecture
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AI’s Next Frontier: Human Collaboration, Data Strategy, and Scale
Ramtin Davanlou, CTO of the Accenture and Intel Partnership, explores what it really takes for enterprises to move from AI experimentation to scaled success, revealing how data quality, strategic partnerships, and AI factories are reshaping the way businesses operate.
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