xt-89

xt-89 t1_jbt5yyd wrote

Reply to comment by NovelspaceOnly in [P] GITModel: Dynamically generate high-quality hierarchical topic tree representations of GitHub repositories using customizable GNN message passing layers, chatgpt, and topic modeling. by NovelspaceOnly

That’s cool. I assume you’re going to apply this to memories for the agent. There’s already relevant research on how to do that. Here’s one from Facebookresearch: https://ai.facebook.com/blog/retrieval-augmented-generation-streamlining-the-creation-of-intelligent-natural-language-processing-models/

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xt-89 t1_jbsaabf wrote

Reply to comment by [deleted] in [P] GITModel: Dynamically generate high-quality hierarchical topic tree representations of GitHub repositories using customizable GNN message passing layers, chatgpt, and topic modeling. by NovelspaceOnly

I also plan on applying the basic idea of a GNN with prompting to the thought loop of an cognitive entity (basically open assistant). I believe if you take the tree your outputting for code, but use it to aid CoT reasoning, that could be pretty powerful

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xt-89 t1_jbs8od5 wrote

Reply to comment by [deleted] in [P] GITModel: Dynamically generate high-quality hierarchical topic tree representations of GitHub repositories using customizable GNN message passing layers, chatgpt, and topic modeling. by NovelspaceOnly

Yeah you’ve definitely setup a good representation bias for modeling entire software architectures.

I had a thought a while back that GitHub Copilot is eventually going to offer a feature where they suggest improvements to entire software architectures… and then eventually just write whole projects from a text description alone. I think that the solution for that would be pretty similar to what you’ve done if scaled up and applied that way.

If your plan is to scale up the system for more advanced features, that would be awesome.

Another suggestion is that if you integrated your tool with GitHub, it would be pretty useful for enterprise software development. Most companies are pretty crappy at documentation. Even with good documentation, a chatbot is better than a static document.

Good job!

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xt-89 t1_jbrx1ss wrote

Reply to [P] GITModel: Dynamically generate high-quality hierarchical topic tree representations of GitHub repositories using customizable GNN message passing layers, chatgpt, and topic modeling. by NovelspaceOnly

This project is interesting. The description however is hard to parse through. I’d suggest going over your README and cleaning up some things.

If I could also suggest a feature, if you could use this to generate UML diagrams that’d be great.

You mention that the code base can improve itself. I don’t see where that functionality is. Do you mean that if a person uses this tool for software analysis, productivity increases?

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xt-89 t1_j2ezvam wrote

Reply to comment by TheTomatoBoy9 in Game Theory of UBI by shmoculus

There’s also renewables. When the entire supply chain for wind mills or solar panels become fully automated, energy prices will quickly trend to zero without any new technology beyond AI. Even if you are concerned about rare earth minerals there’s undersea mining that would become more reasonable at that point in time

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xt-89 t1_j2dxg0p wrote

Reply to comment by currentscurrents in [R] LAMBADA: Backward Chaining for Automated Reasoning in Natural Language - Google Research 2022 - Significantly outperforms Chain of Thought and Select Inference in terms of prediction accuracy and proof accuracy. by Singularian2501

I’ve been thinking that we’re really leaving the domain of ‘Machine learning’ and entering the domain of ‘artificial cognition’. It seems like more of these expert system algorithms will be used going forward

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