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Carl Kolon, an engineering leader, shares his curated 'required reading' list of software engineering articles, covering coding practices, platform design, and frontend development, with personal notes on why each matters.
A tweet recommending Arvind Narayanan's annotated slides from his talk 'AI as Normal Technology' as a high-level overview of the concept.
Ilya Sutskever shared a reading list of influential machine learning papers with John Carmack, recommending them as essential knowledge covering 90% of what matters today.
A Twitter thread recommending ten foundational papers and works to understand LLMs, from the original Transformer to DPO.
This tweet introduces 'Awesome LLM Books', a curated GitHub list of 22 high-quality books for LLM development, evaluated by strict criteria including relevance, content quality, and social proof. Each book entry includes author, publisher, rating, and links, helping developers quickly find suitable resources.
A list of 10 books that serious AI researchers actually recommend, covering topics from probability theory and information theory to reinforcement learning and cognitive science, providing deeper insights beyond popular reading lists.
A list of essential research papers for LLM engineers, including key works on transformers, scaling laws, and fine-tuning techniques.
LLMSys-PaperList is a curated reading list on GitHub that organizes LLM systems research papers and resources into practical categories such as training systems, serving systems, and multi-modal coverage, helping AI/ML engineers and researchers stay updated.
A curated reading list of foundational and modern resources for understanding agentic architecture, blending classic distributed systems concepts with current AI agent patterns.
Tweet promoting the reading list for Stanford's CS153 Frontier Systems course, which features talks from industry leaders and a project on scaling one's capabilities.