Archives de catégorie : Non classé

When it comes to scaling AI, the conversation isn’t only about the cloud—it’s about the edge. According to Matthew Formica, Senior Director and Head of Edge Product Marketing & AI PC/Edge AI Software Developer Relations at Intel, the edge represents … Continuer la lecture →

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.

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 →

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 →

In the evolving landscape of artificial intelligence, connected data is becoming a core competitive advantage.

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 →

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

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.

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 →

In this blog, we demonstrate how to build and run a PDF Summarizer Agent using Intel® XPU-optimized tooling for efficient inference, leveraging CrewAI’s orchestration, PyPDF2 for text extraction, and a T5-based model for summarization.