Youtor
Deep Dive into LLMs like ChatGPT
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=7xTGNNLPyMI
This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their psychology , and how to get the best use them in practical applications. I have one Intro to LLMs video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version. • Instructor • Andrej was a founding member at OpenAI (2015) and then Sr. Director of AI at Tesla (2017-2022), and is now a founder at Eureka Labs, which is building an AI-native school. His goal in this video is to raise knowledge and understanding of the state of the art in AI, and empower people to effectively use the latest and greatest in their work. • Find more at https://karpathy.ai/ and https://x.com/karpathy • Chapters • 00:00:00 introduction • 00:01:00 pretraining data (internet) • 00:07:47 tokenization • 00:14:27 neural network I/O • 00:20:11 neural network internals • 00:26:01 inference • 00:31:09 GPT-2: training and inference • 00:42:52 Llama 3.1 base model inference • 00:59:23 pretraining to post-training • 01:01:06 post-training data (conversations) • 01:20:32 hallucinations, tool use, knowledge/working memory • 01:41:46 knowledge of self • 01:46:56 models need tokens to think • 02:01:11 tokenization revisited: models struggle with spelling • 02:04:53 jagged intelligence • 02:07:28 supervised finetuning to reinforcement learning • 02:14:42 reinforcement learning • 02:27:47 DeepSeek-R1 • 02:42:07 AlphaGo • 02:48:26 reinforcement learning from human feedback (RLHF) • 03:09:39 preview of things to come • 03:15:15 keeping track of LLMs • 03:18:34 where to find LLMs • 03:21:46 grand summary • Links • ChatGPT https://chatgpt.com/ • FineWeb (pretraining dataset): https://huggingface.co/spaces/Hugging... • Tiktokenizer: https://tiktokenizer.vercel.app/ • Transformer Neural Net 3D visualizer: https://bbycroft.net/llm • llm.c Let's Reproduce GPT-2 https://github.com/karpathy/llm.c/dis... • Llama 3 paper from Meta: https://arxiv.org/abs/2407.21783 • Hyperbolic, for inference of base model: https://app.hyperbolic.xyz/ • InstructGPT paper on SFT: https://arxiv.org/abs/2203.02155 • HuggingFace inference playground: https://huggingface.co/spaces/hugging... • DeepSeek-R1 paper: https://arxiv.org/abs/2501.12948 • TogetherAI Playground for open model inference: https://api.together.xyz/playground • AlphaGo paper (PDF): https://discovery.ucl.ac.uk/id/eprint... • AlphaGo Move 37 video: • Lee Sedol vs AlphaGo Move 37 reactio... • LM Arena for model rankings: https://lmarena.ai/ • AI News Newsletter: https://buttondown.com/ainews • LMStudio for local inference https://lmstudio.ai/ • The visualization UI I was using in the video: https://excalidraw.com/ • The specific file of Excalidraw we built up: https://drive.google.com/file/d/1EZh5... • Discord channel for Eureka Labs and this video: / discord
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