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A thread recommending the optimal order to read CUDA books, starting with CUDA by Example to build intuition before diving into more advanced texts.
The number of AI-generated books has skyrocketed in just three years, highlighting a significant trend in publishing.
A personal reflection on preferring pre-2022 books because they were written without AI assistance, questioning the value of human effort in the age of LLMs.
A curated collection of must-use resources for building AI systems, including books, courses, and landmark papers.
A list of 10 recommended books for becoming a 10x AI engineer, covering LLMs, machine learning, deep learning, and data-intensive systems.
A personal collection of public domain books freely available online, with references to Anna's Archive, LibGen, and torrents for additional materials.
Elad Gil and Ivanka Trump are launching the Alexandria project, using AI to translate 1,000 great public-domain books into every major language, making them freely accessible with text, audiobook, and chat features.
A curated list of Lean 4 books for learning the theorem prover, covering functional programming, metaprogramming, and logical verification, with opinions on each resource.
A curated list of major books on CUDA programming covering beginner to advanced topics, including C++ and Python, with focus on practical resources for NVIDIA GPU parallel computing.
A curated collection of must-use, actively maintained resources for building and shipping AI systems, covering AI engineering topics like RAG, agents, evals, guardrails, and deployment, along with recommended books, courses, and landmark papers.