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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 #65372 · 04/13/2026, 02:55 AM

🚀 Asian Markets Show Resilience Amid Geopolitical Tensions Asian stock markets continued their 'low open-recovery' trend on April 13, with Japan's Nikkei 225 and South Korea's KOSPI initially experiencing significant declines before quickly narrowing their losses. According to BlockBeats, this pattern reflects a decreasing sensitivity to geopolitical conflicts, such as the ongoing tensions involving Iran. Since the escalation of the Iran conflict, the market's Monday corrections have shown a consistent reduction in magnitude, moving from near double-digit losses to more moderate adjustments. This indicates a diminishing impact of geopolitical shocks on market sentiment. In trading dynamics, the 'Trump model' is being systematically priced in. This involves creating uncertainty through policy signals or strong statements during the week, followed by a softening stance or 'victory' outcomes over the weekend, which helps to restore expectations and drive a rebound in risk assets. As this framework is repeatedly validated, investors' willingness to trade on early-week volatility has decreased, leading to reduced selling pressure and a convergence in volatility patterns. #AsianMarkets#GeopoliticalTensions#Nikkei225#KOSPI#IranConflict#MarketResilience#TrumpModel#Volatility#RiskAssets#MarketSentiment#TradingDynamics#InvestorBehavior