Le projet THINK

As generative and agentic AI use cases proliferate across nearly every industry, improving the reliability, availability, and serviceability (RAS) of AI clusters is becoming increasingly important. Intel® Xeon® 6 processors offer an impressive set of RAS features that can help improve the stability and performance of AI computing clusters. Intel’s collaboration with Internet technology company ByteDance demonstrated that using the RAS features of Intel Xeon CPUs reduced server downtime by up to 50%

Fine-tuning an LLM doesn’t have to require massive infrastructure. With Unsloth now supporting Intel® GPUs, developers can efficiently customize models like Llama 3 and Qwen across Intel Core Ultra–based AI PCs, Intel Arc graphics, and the Intel Data Center GPU Max Series.

This blog walks through key techniques like SFT, PEFT, and RLHF—and shows how Intel-optimized libraries such as oneDNN and Triton accelerate training while reducing memory use. Build faster, smarter, and more personalized AI—all within the Intel ecosystem.

In real-world vector search performance tests, Intel® Xeon® server architectures outperform AMD EPYC processors when running two commonly used vector search frameworks.

Less Gold Rush and more Boring Factory – The evolving AI mindset.

From community curiosity to real-world inference – showing how local language models run with day-zero Intel hardware support.

In this post, we’ll dicuss how to run responsive, CPU-only applications using a quantized SLM in the GPT-Generated Unified Format (GGUF). 

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

Intel® Xeon® processors can deliver a CPU-first platform built for modern AI workloads without added complexity or overhead.

Transform enterprise documents into insights with Document Summarization, optimized for Intel® Xeon® and Intel® Gaudi® with automated NUMA-aware scheduling.