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Source channel @githubtrending · Post #15428 · Jan 22

#cplusplus FlashMLA is DeepSeek's optimized attention library that makes AI models run faster and use less memory. It works with advanced NVIDIA GPUs to speed up how language models process information, achieving up to 660 trillion floating-point operations per second. The library supports both dense and sparse attention modes, meaning it can focus on important tokens while skipping less relevant ones, reducing computational waste. For you, this means faster AI responses, lower costs for running large language models, and better performance on tasks like chatbots and code generation. The technology is open-source and integrates with popular AI frameworks like PyTorch and Hugging Face, making it accessible for developers building next-generation AI applications. https://github.com/deepseek-ai/FlashMLA

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@kejiqu · Post #4272 · 03/19/2026, 01:39 AM

2026 图灵奖授予量子密码学发明者 计算机协会 (Association for Computing Machinery) 于周三宣布,Charles Bennett 博士和 Gilles Brassard 博士因其在量子密码学及相关技术方面的开创性工作而共同荣获 2026 年图灵奖。该奖项通常被称为计算机领域的诺贝尔奖,奖金为 100 万美元。两位科学家于 1983 年发表研究,证明了量子地铁票无法伪造,并于 1984 年提出了 BB84 系统,该系统利用光子创建加密密钥,通过量子力学原理实现安全加密。Slashdot 🏷#Turing#Award#Quantum#Cryptography#BB84 📢频道👥群组📝投稿