henrythe9th/AI-Crash-Course 排名第 18,477，此处有 8 个同类条目；PRML/PRMLT 排名第 18,483。

AI-Crash-Course AI Crash Course to help busy builders catch up to the public frontier of AI research in 2 weeks **Intro:** I’m Henry Shi and I started Super. com in 2016 and grew it to $150MM+ in annual revenues and recently exited. As a traditional software founder, I needed to quickly catch up to the frontier of AI research to figure out where the next opportunities and gaps were. I compiled a list of resources that were

essential for me and should get you caught up within 2 weeks. For more context, checkout the original twitter thread **Start Here:** Neural Network \-\> LLM Series **Then get up to speed via Survey papers:** Follow the ideas in the survey paper that interest you and dig deeper LLM Survey \- 2024 Agent Survey \- 2023 Prompt Engineering Survey \- 2024 Context Engineering Survey \- 2025 **AI Papers:** (prioritize ones with star \*) **Foundational Modelling:** **Transformers**\* (foundation, self-attention) \- 2017 Scaling Laws/**GPT3**\* (conviction to scale

up GPT2/3/4) \- 2020 LoRA (Fine tuning) \- 2021 Training Compute-Optimal LLMs \- 2022 **RLHF**\* (InstructGPT-\>ChatGPT) \- 2022 DPO (No need for RL/Reward model) \- 2023 LLM-as-Judge (On par with human evaluations) \- 2023 MoE (MIxture of Experts) \- 2024 **Planning/Reasoning:** AlphaZero/**MuZero**\* (RL without prior knowledge of game or rules) \- 2017/2019 **CoT**\* (Chain of Thought)/ToT (Tree of Thoughts)/GoT (Graph of Thoughts)/Meta CoT \- 2022/2023/2023/2025 ReACT (Generate reasoning traces and task-specific actions

in interleaved manner) \- 2022 Let’s Verify Step by Step (Process \> Outcome) \- 2023 **ARC-Prize**\* (Latest methods for solving ARC-AGI problems) \- 2024 **DeepSeek R1**\* (Building OSS o1-level reasoning model with pure RL, no SFT, no RM) \- 2025 Recursive Language Models (Simple REPL + basic tools → models emergently learn adaptive strategies without explicit prompting) \- 2026 **Applications:** Toolformer (LLMs to use tools) \- 2023 GPT4 (Overview of GPT4, but fairly high level) \- 2023 **Llama3**\* (In depth details of how Meta built Llama3

and the various configurations and hyperparameters) \- 2024 Gemini1. 5 (Multimodal across 10MM context window) \- 2024 Deepseekv3 (Building a frontier OSS model at a fraction of the cost of everyone else) \- 2024 SWE-Agent/OpenHands (OpenSource software development agents) \- 2024 **Benchmarks:** BIG-Bench (First broad & diverse collaborative OSS benchmark) \- 2022 SWE-Bench (Real world software development) \- 2023 Chatbot Arena (Live human preference Elo ratings) \- 2024 **Videos/Lectures:** 3Blue1Brown on Foundational Math/Concepts Build a Large Language Model (from Scratch) \#1 Bestseller

Build a Reasoning Model (From Scratch) Andrej Kaparthy: Zero to Hero Series Yannic Kilcher Paper Explanations Noam Brown (o1 founder) on Planning in AI Stanford: Building LLMs Foundations of LLMs Why You’re Not Too Old to Pivot Into AI (motivation) **Helpful Websites:** History of Deep Learning \- summary timeline of deeplearning with major breakthroughs and key concepts Full Stack Deep Learning \- courses for building AI products Prompting Guide \- extensive list of prompting techniques and examples a16z AI Cannon \- similar list

of resources, but longer (slightly dated) 2025 AI Engineer Reading List \- longer reading list, broken out by focus area State