Deep Dive into LLMs like ChatGPT

Andrej Karpathy · Intermediate ·🧠 Large Language Models ·1y ago
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 (201…
Watch on YouTube ↗ (saves to browser)

Chapters (24)

introduction
1:00 pretraining data (internet)
7:47 tokenization
14:27 neural network I/O
20:11 neural network internals
26:01 inference
31:09 GPT-2: training and inference
42:52 Llama 3.1 base model inference
59:23 pretraining to post-training
1:01:06 post-training data (conversations)
1:20:32 hallucinations, tool use, knowledge/working memory
1:41:46 knowledge of self
1:46:56 models need tokens to think
2:01:11 tokenization revisited: models struggle with spelling
2:04:53 jagged intelligence
2:07:28 supervised finetuning to reinforcement learning
2:14:42 reinforcement learning
2:27:47 DeepSeek-R1
2:42:07 AlphaGo
2:48:26 reinforcement learning from human feedback (RLHF)
3:09:39 preview of things to come
3:15:15 keeping track of LLMs
3:18:34 where to find LLMs
3:21:46 grand summary

Playlist

Uploads from Andrej Karpathy · Andrej Karpathy · 16 of 17

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