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Articles récents
- Unlocking AI Inference Performance with Intel® Xeon® 6 Processors with Priority Core Turbo
- 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
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Microsoft Azure Cognitive Service Containers on-premises with Intel Xeon Platform
Microsoft Azure Cognitive Services based AI Inferencing on-premises with Intel Xeon Platforms
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Art Generation with PyTorch Stable Diffusion and Habana Gaudi
In this post, we will learn how to run PyTorch stable diffusion inference on Habana Gaudi processor, expressly designed for the purpose of efficiently accelerating AI Deep Learning models.
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Responsible AI: The Future of AI Security and Privacy
Intel Innovation 2022: Jason Martin, Principal Engineer leading Intel Labs Secure Intelligence Team
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Intel Labs Introduces SPEAR: An Open-Source Photorealistic Simulator for Embodied AI
Intel Labs collaborated with the Computer Vision Center in Spain, Kujiale in China, and the Technical University of Munich to develop the Simulator for Photorealistic Embodied AI Research (SPEAR).
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End-to-End Azure Machine Learning on-premises with Intel Xeon Platforms
Azure Machine Learning on-premises with Intel Xeon Platforms and Kubernetes
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Intel Labs Presents Natural Language Processing Research at EMNLP 2022
Intel Labs presents latest research in Natural Language Processing at EMNLP.
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Writing training scripts that can run either on Gaudi, GPU, or CPU
In this tutorial we will learn how to write code that automatically detects what type of AI accelerator is installed on the machine (Gaudi, GPU or CPU), and make the needed changes to run the code smoothly.
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Intel Labs Introduces the Open MatSci ML Toolkit
Intel Labs has set several works in motion to further the development and application of advanced artificial intelligence technologies to scientific challenges, particularly in the field of materials science.
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Intel Co-Sponsors New Phase of MIT DSAIL Program for Instance-Optimized Data Systems Research
Nesime Tatbul is a senior research scientist in the Parallel Computing Lab at Intel Labs and acts as Intel’s lead PI for DSAIL. Highlights: Intel co-sponsors a new phase of the Data Systems and Artificial Intelligence Lab (DSAIL) university research program at the Massachusetts Institute of … Continuer la lecture
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CUMULATIVE_THROUGHPUT Enables Full-Speed AI Inferencing with Multiple Devices
OpenVINO™ has enabled automatic selection of the most suitable target device for AI inferencing
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