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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 #64491 · 04/09/2026, 03:01 AM

🚀 Bitcoin Developer Adam Back Addresses Quantum Computing Concerns Bitcoin developer Adam Back has dismissed fears of a quantum computing crisis, asserting that humanity has at least a decade to prepare. According to Bitalk News, Back emphasized that current quantum hardware is still in its infancy, lacking error correction capabilities, and has only achieved basic calculations such as elementary-level factorization. He noted that Google's recent paper merely improved algorithms without any hardware breakthroughs. Back reassured that Bitcoin has ample time to adapt, with Liquid serving as a Layer 2 testing ground that has historically been adopted by the Bitcoin main chain after new signature formats were introduced. He argued that genuine solutions are already in progress, and that media-driven panic is more about selling headlines than reflecting technical realities. #Bitcoin#AdamBack#QuantumComputing#BitcoinDeveloper#Liquid#Layer2#SignatureFormats#ErrorCorrection#QuantumHardware#BitalkNews#Panic#TechnicalRealities#BTC