https://github.com/dethos/confwisdom
This repository contains the notes generated by LLMs for multiple conference presentations.
https://github.com/dethos/confwisdom
Last synced: 4 months ago
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This repository contains the notes generated by LLMs for multiple conference presentations.
- Host: GitHub
- URL: https://github.com/dethos/confwisdom
- Owner: dethos
- Created: 2024-07-11T17:04:18.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2024-10-25T14:00:28.000Z (over 1 year ago)
- Last Synced: 2025-06-04T16:23:07.959Z (about 1 year ago)
- Homepage:
- Size: 188 KB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Conf Wisdom
The main idea behind this repository is that a person cannot watch all the presentations of any big conference, not to mention of all the interesting conferences that happen during the year. Based on experience, picking the videos by the title isn't as efficient as it seems, since the content will likely differ from the expectations, and we will likely miss other great content.
One alternative is to ask some LLM (in this case `llama3:8b`) to extract the key insights, ideas, references and recommendations in an easily and quickly digestible way. We can learn from these notes, if the content is worth, watch the talk later.
[For a more detailed explanation of the reasoning behind this experiment, please check my blog post.](https://blog.ovalerio.net/archives/2900)
## Contents
This repository contains the generated notes for the videos of multiple conferences. Soon, the code to generate these notes from any YouTube playlist will be added to the repository.
### Notes
You can find all the notes in the `data` directory, organized by conference (aka YouTube playlist). All of them are generated locally by running the models, instead of relying on online APIs.
### Tools
This repository relies on [ollama](https://ollama.com/) and [fabric](https://github.com/danielmiessler/fabric/) to achieve its goal. Especially the `extract_wisdom` pattern created by [Daniel Miessler](https://github.com/danielmiessler)