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[1hr Talk] Intro to Large Language ModelsAndrej Karpathy

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Andrey Karpathy introduces Large Language Models (LLMs) as next-word predictors, explaining their training, fine-tuning into assistants, and current capabilities like tool use. He discusses their inscrutable nature, future improvements like self-improvement, and security vulnerabilities such as jailbreaks and prompt injection. The talk concludes by framing LLMs as an emerging operating system kernel, highlighting both their potential and the ongoing security challenges.

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How large language models are trained, what they can do today, and where agents are heading — in 4 chapters.

00:00What an LLM actually is

07:42Training: from internet text to assistant

18:15Tool use, multimodality and agents

32:08What to watch over the next year

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The hardest part of understanding is knowing what still needs context.理解内容最难的部分，是知道哪里还需要上下文。

07:42 / 20:14

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Read the summary, turn on bilingual subtitles, and ask Lumi anything.

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FAQ

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All core features are free to try. Free accounts receive 200,000 Lumi AI tokens, while Pro includes 10,000,000 tokens each month. Bringing your own API key is always unmetered.

YouTube and Bilibili are supported now. Vimeo, Coursera, and other course platforms are next on the roadmap.

You can use Lumi AI with zero setup, or bring your own key for DeepSeek, OpenAI-compatible, Anthropic and Gemini models — pick whichever fits you in extension settings.

No. Lumi only sends subtitle text to AI providers when you trigger a feature. Your watch history stays in local browser storage.

Yes. When the platform provides captions Lumi uses them; for videos with no captions at all, Lumi generates subtitles from the audio first, then translates, summarizes and chats over them.

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