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Articles récents
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
- Intel Labs Works with Hugging Face to Deploy Tools for Enhanced LLM Efficiency
- AI’s Next Frontier: Human Collaboration, Data Strategy, and Scale
- Efficient PDF Summarization with CrewAI and Intel® XPU Optimization
- Rethinking AI Infrastructure: How NetApp and Intel Are Unlocking the Future with AIPod Mini
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Neural networks news
Intel NN News
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
Researchers from the University of Texas at Austin and Intel Labs investigated chain-of-thought […]
- AI’s Next Frontier: Human Collaboration, Data Strategy, and Scale
Ramtin Davanlou, CTO of the Accenture and Intel Partnership, explores what it really takes for […]
- Intel Labs Works with Hugging Face to Deploy Tools for Enhanced LLM Efficiency
Large Language Models are revolutionizing AI applications; however, slow inference speeds continue […]
- Curious Case of Chain of Thought: Improving CoT Efficiency via Training-Free Steerable Reasoning
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Archives mensuelles : janvier 2023
Getting started with classical Machine Learning Frameworks using Google Colaboratory
Installing major machine learning frameworks optimized by Intel on Google Colaboratory (Colab)
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Training Causal Language Models on SDSC’s Gaudi-based Voyager Supercomputing Cluster
The SDSC Voyager supercomputer is an innovative AI system designed specifically for science and engineering research at scale. Funded by the National Science Foundation, Voyager represents a collaboration with the San Diego Supercomputer Center at UC San Diego, Supermicro, and Intel’s Habana Labs, facilitating … Continuer la lecture
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Top 10 Intel Labs Posts of 2022
Intel Labs presented many exciting research innovations in 2022. Read for a brief description of Intel Labs’ top 10 blogs for 2022.
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Intel Labs at The Winter Conference on Applications of Computer Vision
Intel presents five computer vision papers that detail novel works that include a Dynamic Scene Graph Detection Transformer, a Fast Learnable Once-for-all Adversarial Training method, a method for quantizing convolutional neural networks for efficient training, face access models applied in a hypothetical social network, and a … Continuer la lecture
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