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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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🦅 [ perspective ix ]

@perspectiveix · Post #1686 · 12/03/2018, 10:30 AM

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🔈Most Common Smart Speaker Usage People are doing plenty of things with voice commands on their #SmartSpeakers, but shopping isn’t really one of them. Only about a quarter to a third of U.S. smart speaker owners have ever purchased something using voice. Very few do so on a regular basis. An Information article this summer said just 2 percent of #Alexa owners had made a purchase via Alexa in 2018. 🚀@PerspectiveIX via Recode. ❓Do you own a Smart Speaker, like Apple HomePod, Google Home, Amazon Echo, etc?

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@perspectiveix · Post #1512 · 09/01/2018, 08:00 AM

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🗣The State of Chinese Voice Assistants China is the second-largest consumer market in the world, hitting $4.3T in consumer expenditure in 2016 alone (for reference, the US ranked first with $12.5T, and Japan third with $2.7T). The Chinese smart home market will reach nearly $23B in 2018, according to Juniper Research. #SmartSpeakers and #AI voice assistants are becoming an integral part of that. Now that smart speakers are becoming commonplace, the early entrant, #Amazon, is losing its market share — and not just to its rival #Google, but to newer players emerging in China. 🚀@PerspectiveIX via CBInsights. ❓ Do you own a smart speaker?

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