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Source channel @githubtrending · Post #14747 · May 25

#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch

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Venture Village Wall 🦄

@venturevillagewall · Post #4266 · 02/28/2025, 07:00 AM

AI Predictions: From Vacuums to Real Impact AI-powered prediction platforms are gaining traction, with a focus on forecasting reactions based on content and audience. Initial predictions using tools like ChatGPT yield 17% accuracy, but considering audience interactions can boost accuracy to 83%. This innovative approach helped a startup refine its pitch to enter Y Combinator. Discover more insights on enhancing prediction accuracy in various fields here. #AI#Startup#Prediction#YCombinator#Marketing#Innovation#Tech#Growth#Entrepreneurship#Forecasting#AudienceAnalysis#DataScience#MachineLearning#Success#Business#Trends#Platforms#Metrics#Investment#VC