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Articles récents
- Starting with Production in Mind: A Blueprint for Affordable Enterprise-Grade RAG on VMware Tanzu
- Running the AI Factory: How Enterprises Operationalize AI Placement at Scale
- Intel® Xeon® 6 Processors: The Ultimate Host CPU Solution for AI-Accelerated Systems and Agentic AI
- Agentic Code Execution: A Leaner Way to Build AI Agents with Open Models
- CPU Overload Despite Having iGPU: Here’s Why?
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Neural networks news
Intel NN News
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Survival of the Fittest: Compact Generative AI Models Are the Future for Cost-Effective AI 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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Can we Improve Early-Exit Transformers? Novel Adaptive Inference Method Presented at ACL 2023
Intel Labs and the Hebrew University of Jerusalem present SWEET, an adaptive Inference method for text classification at this year’s ACL conference.
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Are all Transformer Layers Necessary? Novel Adaptive Inference Method Presented at ACL 2023
Intel Labs and the Hebrew University of Jerusalem present SWEET, an adaptive Inference method for text classification at this year’s ACL conference.
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Chronic Kidney Disease Risk Prediction using Modin and scikit-learn* (sklearn): Developer Spotlight
Developer Spotlight: Arnab Das proposed a solution to Chronic Kidney Disease Risk Prediction
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