全部/社媒/Substack Newsletter/Ahead of AISubstack Newsletter · Ahead of AI9小时前更新ARCHIVE近 30 天历史柱高表示当天的文章数← 更早 30 天更近 30 天 →实时榜0160170180190200210220231240250260270280290300310010020030040050060070080090100110120130今天10/16—11/14 有历史数据10-2419:14Building Reasoning Models from the Ground Up: A Full Video CourseOver 11 hours of coding videos on evaluation, inference-time scaling, reinforcement learning, and distillation, with Python and PyTorch.09-2918:50Language Models for Text Classification: From Bag-of-Words to JevA Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency09-0919:14GPT-6 Astra, Looped Transformers, and Hidden ReasoningA Look at Recurrent Depth, Hidden Chains of Thought, and Recent Research on Looping Transformer Blocks08-2219:11How Claude Watermarks AI-Generated TextA 48-minute video walkthrough of token sampling, watermark detection, and removal08-1519:54Building an AI Text Detector From ScratchAn End-to-End Project With Dataset Construction, Model Training, Local Deployment, and RLVR07-1819:16Controlling Reasoning Effort in LLMsHow LLMs Learn Low-, Medium-, and High-Effort Reasoning Modes06-2719:21Using Local Coding AgentsUsing Open-Weight Models in Local Coding Harnesses as an Alternative to Claude Code and Codex Subscriptions06-0619:16LLM Research Papers: The 2026 List (January to May)A curated roundup of notable LLM research papers that came out this year05-1619:33Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed AttentionFrom Gemma 4 to DeepSeek V4, How New Open-Weight LLMs Are Reducing Long-Context Costs04-1819:24My Workflow for Understanding LLM ArchitecturesA learning-oriented workflow for understanding new open-weight model releases04-0419:45Components of A Coding AgentHow coding agents use tools, memory, and repo context to make LLMs work better in practice03-2219:55A Visual Guide to Attention Variants in Modern LLMsFrom MHA and GQA to MLA, sparse attention, and hybrid architectures02-2521:26A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026A Round Up And Comparison of 10 Open-Weight LLM Releases in Spring 202601-2419:23Categories of Inference-Time Scaling for Improved LLM ReasoningAnd an Overview of Recent Inference-Scaling Papers202512-3020:22The State Of LLMs 2025: Progress, Problems, and PredictionsA 2025 review of large language models, from DeepSeek R1 and RLVR to inference-time scaling, benchmarks, architectures, and predictions for 2026.202512-3020:15LLM Research Papers: The 2025 List (July to December)In June, I shared a bonus article with my curated and bookmarked research paper lists to the paid subscribers who make this Substack possible.202512-0320:03From DeepSeek V3 to V3.2: Architecture, Sparse Attention, and RL UpdatesUnderstanding How DeepSeek's Flagship Open-Weight Models Evolved202511-0421:06Beyond Standard LLMsLinear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers202510-0519:12Understanding the 4 Main Approaches to LLM Evaluation (From Scratch)Multiple-Choice Benchmarks, Verifiers, Leaderboards, and LLM Judges with Code Examples202509-0619:10Understanding and Implementing Qwen3 From ScratchA Detailed Look at One of the Leading Open-Source LLMs202508-0919:23From GPT-2 to gpt-oss: Analyzing the Architectural AdvancesAnd How They Stack Up Against Qwen3202507-1919:11The Big LLM Architecture ComparisonFrom DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design202507-0119:11LLM Research Papers: The 2025 List (January to June)A topic-organized collection of 200+ LLM research papers from 2025202506-1718:55Understanding and Coding the KV Cache in LLMs from ScratchKV caches are one of the most critical techniques for efficient inference in LLMs in production.202505-1019:03Coding LLMs from the Ground Up: A Complete CourseWhy build LLMs from scratch? It's probably the best and most efficient way to learn how LLMs really work. Plus, many readers have told me they had a lot of fun doing it.202504-1919:02The State of Reinforcement Learning for LLM ReasoningUnderstanding GRPO and New Insights from Reasoning Model Papers
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