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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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Crypto M - Crypto News

@CryptoM · Post #64782 · 04/09/2026, 11:03 PM

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🚀 AI TRENDS | Anthropic Reportedly Considering In-House Chip Development According to Jin10, sources indicate that Anthropic is exploring the possibility of developing its own chips. This move could potentially enhance the company's capabilities in artificial intelligence and reduce reliance on external suppliers. The decision to consider in-house chip production aligns with a broader trend among tech companies seeking greater control over their hardware components. Anthropic's initiative reflects the growing importance of customized hardware in advancing AI technologies. #AI#Anthropic#ChipDevelopment#InHouseChips#ArtificialIntelligence#TechTrends#CustomHardware

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