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Watch · Deep learning from first principles

How I use LLMs

Chapters

  1. 0:00Intro into the growing LLM ecosystem
  2. 2:54ChatGPT interaction under the hood
  3. 13:12Basic LLM interactions examples
  4. 18:03Be aware of the model you're using, pricing tiers
  5. 22:54Thinking models and when to use them
  6. 31:00Tool use: internet search
  7. 42:04Tool use: deep research
  8. 50:57File uploads, adding documents to context
  9. 59:00Tool use: python interpreter, messiness of the ecosystem
  10. 1:04:35ChatGPT Advanced Data Analysis, figures, plots
  11. 1:09:00Claude Artifacts, apps, diagrams
  12. 1:14:02Cursor: Composer, writing code
  13. 1:22:28Audio (Speech) Input/Output
  14. 1:27:37Advanced Voice Mode aka true audio inside the model
  15. 1:37:09NotebookLM, podcast generation
  16. 1:40:20Image input, OCR
  17. 1:47:02Image output, DALL-E, Ideogram, etc.
  18. 1:49:14Video input, point and talk on app
  19. 1:52:23Video output, Sora, Veo 2, etc etc.
  20. 1:53:29ChatGPT memory, custom instructions
  21. 1:58:38Custom GPTs
  22. 2:06:30Summary
Show the full video description ›

The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series on LLMs. In this more practical followup, I take you through the many ways I use LLMs in my own life. Chapters 00:00:00 Intro into the growing LLM ecosystem 00:02:54 ChatGPT interaction under the hood 00:13:12 Basic LLM interactions examples 00:18:03 Be aware of the model you're using, pricing tiers 00:22:54 Thinking models and when to use them 00:31:00 Tool use: internet search 00:42:04 Tool use: deep research 00:50:57 File uploads, adding documents to context 00:59:00 Tool use: python interpreter, messiness of the ecosystem 01:04:35 ChatGPT Advanced Data Analysis, figures, plots 01:09:00 Claude Artifacts, apps, diagrams 01:14:02 Cursor: Composer, writing code 01:22:28 Audio (Speech) Input/Output 01:27:37 Advanced Voice Mode aka true audio inside the model 01:37:09 NotebookLM, podcast generation 01:40:20 Image input, OCR 01:47:02 Image output, DALL-E, Ideogram, etc. 01:49:14 Video input, point and talk on app 01:52:23 Video output, Sora, Veo 2, etc etc. 01:53:29 ChatGPT memory, custom instructions 01:58:38 Custom GPTs 02:06:30 Summary Links - Tiktokenizer https://tiktokenizer.vercel.app/ - OpenAI's ChatGPT https://chatgpt.com/ - Anthropic's Claude https://claude.ai/ - Google's Gemini https://gemini.google.com/ - xAI's Grok https://grok.com/ - Perplexity https://www.perplexity.ai/ - Google's NotebookLM https://notebooklm.google.com/ - Cursor https://www.cursor.com/ - Histories of Mysteries AI podcast on Spotify https://open.spotify.com/show/3K4LRyMCP44kBbiOziwJjb - 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/1DN3LU3MbKI00udxoS-W5ckCHq99V0Uqs/view?usp=sharing - Discord channel for Eureka Labs and this video: https://discord.gg/3zy8kqD9Cp Educational Use Licensing This video is freely available for educational and internal training purposes. Educators, students, schools, universities, nonprofit institutions, businesses, and individual learners may use this content freely for lessons, courses, internal training, and learning activities, provided they do not engage in commercial resale, redistribution, external commercial use, or modify content to misrepresent its intent.