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- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
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Neural networks news
Intel NN News
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
The latest Intel® Xeon® 6 processors deliver performance advantages across key enterprise […]
- Next-Gen AI Inference: Intel® Xeon® Processors Power Vision, NLP, and Recommender Workloads
Intel® Xeon® processors can deliver a CPU-first platform built for modern AI workloads without […]
- Document Summarization: Transforming Enterprise Content with Intel® AI for Enterprise RAG
Transform enterprise documents into insights with Document Summarization, optimized for Intel® […]
- Intel® Xeon® 6 Processors: The Smart Total Cost of Ownership Choice
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Archives de catégorie : Non classé
Accelerating the performance of AI applications on Windows Subsystem for Linux with Intel’s iGPU and
Configure Windows system to get the most out of Intel® Integrated Graphics Processing Unit (iGPU)
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Optimize Inference with Intel CPU Technology
Enjoy improved inferencing lower overall total cost of ownership (TCO) across an integrated AI platform
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Deploy AI Inference with OpenVINO™ and Kubernetes
In this blog, you will learn how to use key features of the OpenVINO™ Operator for Kubernetes
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Artificial Intelligence-Driven Discovery of Novel Material Systems
Intel Labs creates new research effort to investigate and develop advanced AI algorithms and technologies to accelerate the discovery of new material systems more economically.
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Thrill-K: A Blueprint for The Next Generation of Machine Intelligence
Thrill-K will be introduced as the AI systems architecture blueprint that implements 3LK principles for next-generation AI.
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Intel® Labs Uses AI and Audio Anomaly Detection to Prevent Semiconductor Manufacturing Malfunctions
Research in anomalous sound detection to improve semiconductor manufacturing production for both Intel and its partners by using artificial intelligence (AI) and audio detection to monitor machine condition and health.
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OpenVINO™ Execution Provider + Model Caching = Better First Inference Latency for your ONNX Models
Developers can now leverage model caching through the OpenVINO™ Execution Provider for ONNX Runtime
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AttentionLite: Towards Efficient Self-Attention Models for Vision
Intel Labs has created a novel framework for producing a class of parameter- and compute-efficient models called AttentionLite, which leverages recent advances in self-attention as a substitute for convolutions.
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NEMO: A Novel Multi-Objective Optimization Method for AI Challenges
Neuroevolution-Enhanced Multi-Objective Optimization (NEMO) for Mixed-Precision Quantization delivers state-of-the-art compute speedups and memory improvements for artificial intelligence (AI) applications.
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Best Practices for Text-Classification with Distillation Part (3/4) – Word Order Sensitivity (WOS)
In this post, I introduce a metric for estimating the complexity level of your dataset and task, and I describe how to utilize it to optimize distillation performance.
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