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diff --git a/2023/talks/matplotllm.md b/2023/talks/matplotllm.md index 453eb114..4117374b 100644 --- a/2023/talks/matplotllm.md +++ b/2023/talks/matplotllm.md @@ -31,6 +31,39 @@ the future or such work could look like. The package is called MatplotLLM and lives here <https://github.com/lepisma/matplotllm> +About the speaker: + +I am a Programmer and Machine Learning Engineer who has been in love +with Emacs' extendability from the moment I pressed M-x. Since then, I +have been doing as many things inside Emacs as I can. In this talk, I +will cover a recent attempt at automating one of my workflows inside +Emacs. + +# Discussion + +## Questions and answers + +- Q: What is the license of <https://github.com/lepisma/matplotllm> + project ? Sjo + - A: GPLv3 or later. Sorry, I didn't put this in the repository, + You can refer to + <https://github.com/lepisma/matplotllm/blob/main/matplotllm.el#L18C12-L29> + though. +- Q: Sometimes LLMs hallucinate. Can we trust the graph that it + produces? + - A: Not always, but the chances of hallucinations impacting + 'generated code' that causes a harmful but not identifiable + hallucinations are a little lower. Usually hallucination in code + show up as very visible bug so you can always do a retry. But I + haven't done a thorough analysis here yet. +- Q: What are your thoughts on the carbon footprint of LLM useage? + - (not the speaker): to add a bit more to power usage of LLMs, it is not inherent that the models must take many megawatts to train and run. work is happening and seems promising to decrease power usage +## Notes + +- Repository link <https://github.com/lepisma/matplotllm> . A + connected blog post here + <https://lepisma.xyz/2023/08/20/matplotllm:-an-llm-assisted-data-visualization-framework/index.html> + [[!inline pages="internal(2023/info/matplotllm-after)" raw="yes"]] |