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That's super cool, thanks for sharing! I will share this as an easy to follow example of what we can with AI.
> Allowing a Q&A interface using these embeddings over the post contents could speed up research over the community posts (if you know the right questions to ask :P). Let's view some posts similar to this one complaining about function calling
That's indeed a great thing to surface, and that's exactly how the the OpenAI forum selects the "Related Topics" to show at the end of every topic. We use embeddings for this feature, and the entire thing is open-source: https://github.com/discourse/discourse-ai/blob/main/lib/embe...
We also embeddings for suggesting tags, categories, HyDE search and more. It's by far my favorite tech of this new AI/ML gen so far in terms of applicability.
> Using Twitter-roBERTa-base for sentiment analysis, we generated a post_sentiment label (negative, positive, neutral) and post_sentiment_score confidence score for each post.
We do the same, with even the same model, and conveniently show that information on the admin interface of the forum. Again all open source: https://github.com/discourse/discourse-ai/tree/main/lib/sent...
Disclaimer: I'm the tech lead on the AI parts of Discourse, the open source software that powers OpenAI's community forum.