Alpha1
Well-known member
AI / LLM's can be used to make threads and other content more useful and better organized. For better usability, SEO, content discovery and readability.
One of the challenges of using forums is reading through mega-threads with thousands of replies. Especially if high quality replies and useless comments are mixed. For this reasons there have been many requests for a summary feature over the years. Now with the advent of AI the technology to create good summaries for large amounts of text is possible.
Some other challenges for forums are:
Some forum platforms like Discourse and Quora have already implemented some LLM solutions. For example:
meta.discourse.org
meta.discourse.org
Once an LLM understands the meaning of the thread, the LLM can create the following with the data:
Please consider to add LLM functionality to let AI / LLM suggest the above.
As there are costs for the use of AI / LLM, it would require various limits on when analysis takes place. For example generate x,y,z only after x posts have been made. Or add a budget for AI credits.
As LLM generated data can be erroneous, methods of correct are needed like community editing of summaries or admin view of new tags.
One of the challenges of using forums is reading through mega-threads with thousands of replies. Especially if high quality replies and useless comments are mixed. For this reasons there have been many requests for a summary feature over the years. Now with the advent of AI the technology to create good summaries for large amounts of text is possible.
Some other challenges for forums are:
- Correcting useless thread titles. i.e. 'HELP ME NOW!!!' or 'Dumb question'.
- Optimal SEO meta tags.
- Useful thread tags.
- Correct thread prefix.
- Correct thread type. i.e. a Question posted as a Discussion Type.
- Making forum threads look better with images.
- Making unreadable posts readable. When users post broken English, chat speak, mobile t9 autocomplete suggests wrong words, ALL CAPS, no punctuation, no line breaks wall of text, no formatting, then it can make posts completely unreadable to others.
- Link to related content from other content types for better content discovery. For example if XFRM has a resource that addresses the topic in a thread.
Some forum platforms like Discourse and Quora have already implemented some LLM solutions. For example:
Discourse AI Topic Summary 🤖
ℹ Summary Uses a remote AI language model to prepare and post a summary of a topic. 🛠 Repository Link GitHub - merefield/discourse-ai-topic-summary: Uses a remote AI language model to prepare and post a summary of a Topic 📖 Install Guide How to install plugins in Discourse Enjoying this...
meta.discourse.org
Discourse AI
:discourse2: Summary Integration between AI features and Discourse 🌐 Website Discourse AI Features | Discourse - Civilized Discussion 🛠 Repository Link GitHub - discourse/discourse-ai 📖 Install Guide How to install plugins in Discourse Discourse AI Discourse AI is our one-stop...
meta.discourse.org
Once an LLM understands the meaning of the thread, the LLM can create the following with the data:
- A thread summary. (widget)
- A better thread snippet.
- Suggest a better thread title.
- SEO meta tags: Meta title, Meta Description, Meta Keywords, etc.
- Thread tags.
- Select Thread prefix.
- Select Thread Type.
- Thread cover, caption and thumb. This would make forum content look much better.
- Making unreadable posts readable. (correct spelling mistakes)
- Display related content. (Widget to display related content from all content types)
Please consider to add LLM functionality to let AI / LLM suggest the above.
As there are costs for the use of AI / LLM, it would require various limits on when analysis takes place. For example generate x,y,z only after x posts have been made. Or add a budget for AI credits.
As LLM generated data can be erroneous, methods of correct are needed like community editing of summaries or admin view of new tags.
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