Le projet THINK

Developer Spotlight: Akash Agrawal proposed an Object Detection Model for Autonomous Vehicles

Developer Spotlight: Rohit Sroch, in his blog proposed a Learning Enhancement and Assistance Platform

Intel Liftoff for Startups presents the AI Innovation Bridge: An onsite LLM and Gen AI hackathon during the Intel Innovation 2023 conference, fostering groundbreaking advancements. The event promises a transformative experience for AI startups. Set for September 19-20 in San Jose, the hackathon aims to unleash developers’ creative prowess with access to cutting-edge Intel resources.

Intel® oneAPI Threading Building Blocks: open-source library on GitHub supports parallelism on CPUs.

Using oneDNN for Improved Efficiency and Sustainability

Developer Spotlight: Arnab Das in his blog proposed a solution to Heart Disease Risk Prediction

The case for nimble, targeted, retrieval-based models as the best solution for generative AI applications deployed at scale.

Intel Labs had five papers accepted at the 40th International Conference on Machine Learning (ICML) 2023, happening now through July 29. Two papers were selected as spotlight oral papers at the conference: ProtST, which uses a ChatGPT-style design interface for protein design, and MOTO, which solves long-horizon robot manipulation tasks completely from images by using a combination of offline data and online interactions.

The 4th gen Intel® Xeon® Scalable Processor, formerly codenamed Sapphire Rapids is a balanced platform for Graph Neural Networks (GNN) training, accelerating both sparse and dense compute. In this article, Intel CPU refers to 4th gen Intel® Xeon® Scalable Processor with 56 cores per socket.

Intel is democratizing AI inference by delivering a better price and performance for
real-world use cases on the 4th gen Intel® Xeon® Scalable Processors, formerly codenamed Sapphire Rapids. In this article, Intel® CPU refers to 4th gen Intel® Xeon® Scalable Processors. For protein folding of a set of proteins of lengths less than a thousand, using DeepMind’s AlphaFold2 inference based end-to-end pipeline, a dual socket Intel® CPU node delivers 30% better performance compared to our measured performance of an Intel® CPU with an A100 offload.