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Articles récents
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Archives de catégorie : Non classé
Tackling Network Security: AI Agents at the Edge with Red Hat AI on Intel® Processors and Graphics
Executive Summary: The cybersecurity landscape is evolving rapidly, with organizations facing increasingly sophisticated threats that traditional security measures struggle to counter. As enterprise networks grow in complexity and scale, fueled by 5G, edge computing, and AI workloads, so do the … Continuer la lecture
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Practical Deployment of LLMs for Network Traffic Classification – Part 1
Additional contributing authors: Rui Li, Vishakh Nair, Mrittika Ganguli Executive Summary The integration of Generative AI and Large Language Models (LLMs) into network security and operational management presents transformative opportunities for enhancing application identification and traffic classification. Traditional methods that … Continuer la lecture
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Practical Deployment of LLMs for Network Traffic Classification
EXECUTIVE SUMMARY The integration of Generative AI and Large Language Models (LLMs) into network security and operational management presents transformative opportunities for enhancing application identification and traffic classification. Traditional methods that rely on literal matching and regex-based software flows face … Continuer la lecture
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Intel Labs Presents Latest Machine Learning Research Among Eight Papers at ICML 2025
Intel Labs is excited to present six works at this year’s ICML conference in Vancouver Canada, including two spotlight papers, one of which is also an oral presentation. Intel researchers will also present two works at related conference workshops
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Intel Labs Researcher Souvik Kundu Receives DAC Under-40 Innovators Award for Impactful AI Research
Souvik Kundu is a Staff Research Scientist at Intel Labs, leading scalable and efficient AI research to make AI more sustainable, efficient, and deployable across various hardware platforms. Souvik recently received the prestigious IEEE/ACM DAC Under-40 Innovators Award 2025 for … Continuer la lecture
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How Startups Can Benefit from Corporates: Learnings from Intel® Liftoff for AI Startups
Wondering if your AI startup should team up with a big tech company? Here’s what 350+ founders learned from working directly with Intel and how it paid off.
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Mamba-Shedder: Intel Labs Explores Efficient Compression of Selective Structured State Space Models
Utilizing block pruning techniques, Intel Labs researchers developed the Mamba-Shedder solution to remove redundancies in Mamba-based models, improving their computational and memory efficiency
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Driving Industrial Innovation with AI at the Edge: Open Platforms Leading the Way
Industrial enterprises need more than just AI to scale technology across diverse environments. They need open, flexible, and interoperable platforms.
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Deploying Scalable Enterprise RAG on Kubernetes with Ansible Automation
Generative AI is changing how businesses work, and Retrieval-Augmented Generation (RAG) is one of the most exciting tools out there. It helps AI give smarter, more accurate answers by connecting it to your company’s data. But setting it up can be tricky—until … Continuer la lecture
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Scalable Vector Search: Deep Dive Series
Vector search is at the core of the AI revolution, and this blog series is here to teach you all about it. Our blog series introduces scalable vector search and dives deeper into sector compression, dimensionality reduction, and Retrieval-Augmented Generation … Continuer la lecture
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