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Source channel @githubtrending · Post #14926 · Jul 8

#jupyter_notebook#artificial_intelligence#book#large_language_models#llm#llms#oreilly#oreilly_books You can learn how to use Large Language Models (LLMs) effectively through the book *Hands-On Large Language Models* by Jay Alammar and Maarten Grootendorst. This book uses nearly 300 custom illustrations to explain key concepts and practical tools for working with LLMs, including tokenization, transformers, prompt engineering, fine-tuning, and advanced text generation. It also provides runnable code examples in Google Colab, making it easy to practice and apply what you learn. This resource helps you understand and build your own LLM applications confidently, saving you time and effort in mastering complex AI technology. It’s highly recommended for anyone wanting hands-on experience with LLMs. https://github.com/HandsOnLLM/Hands-On-Large-Language-Models

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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