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Deep Dive into LLMs like ChatGPT

Andrej KarpathyYouTube ↗

Further reading 2

Caption notes

Follow language models from tokenization and pretraining to supervised tuning and reward optimization, including hallucinations and ways a learned reward can be exploited.

Original passages · 7
it doesn't have to recall it it just has access to it
Deep Dive into LLMs like ChatGPT · ▶ 101:20–101:27
distribute our reasoning and our computation across many tokens
Deep Dive into LLMs like ChatGPT · ▶ 110:34–110:41
the models they don't see the characters they see tokens
Deep Dive into LLMs like ChatGPT · ▶ 121:29–121:37
we're going to check them and we're going to do more of what worked
Deep Dive into LLMs like ChatGPT · ▶ 145:32–145:40
optimization will start to game it and you basically crop it
Deep Dive into LLMs like ChatGPT · ▶ 184:45–184:56
this process of converting from raw text into these symbols
Deep Dive into LLMs like ChatGPT · ▶ 11:52–12:10
labelers are asked to come up with prompts
Deep Dive into LLMs like ChatGPT · ▶ 70:47–71:00

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