oneTBB: A Modern C++ Library for Task-based Parallelism on CPUs

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

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Revolutionizing Recycling: Smart Garbage Classification using oneDNN

Using oneDNN for Improved Efficiency and Sustainability

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Heart Disease Risk Prediction using scikit-learn* (sklearn) and XGBoost: Developer Spotlight

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

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Survival of the Fittest: Compact Generative AI Models Are the Future for Cost-Effective AI at Scale

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

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Intel Labs Presents Five Papers on Novel AI Research at ICML 2023

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.

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Intel® Xeon® trains Graph Neural Network models in record time

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.

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Intel Xeon is all you need for AI inference: Performance Leadership on Real World Applications

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.

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JUMP and Intel Labs Success Story: UCSD Professor Leads HD Computing Research Efforts

For the past five years at the JUMP CRISP Center at UCSD, Professor Tajana Simunic Rosing has led hyperdimensional computing research efforts to solve memory and storage challenges in COVID-19 wastewater surveillance and personalized recommendation systems.

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Democratizing Generative AI for Medicine

Add domain-specific knowledge to foundation AI models without the AI training costs or expertise.

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Accelerate Workloads with OpenVINO and OneDNN

OpenVINO utilizes oneDNN GPU kernels for discrete GPUs to accelerate compute-intensive workloads

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