Archives mensuelles : juillet 2025

An in-depth look at building lightweight, tool-augmented AI agents using hybrid retrieval and local LLMs for high-performance document QA.

Shadow AI is rising fast. Intel® Liftoff startups are building secure, scalable tools to protect data, ensure compliance, and bring AI safely into enterprise workflows.

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 →

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 →

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 →

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

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 →

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.

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

Industrial enterprises need more than just AI to scale technology across diverse environments. They need open, flexible, and interoperable platforms.