{"id":7101,"date":"2024-02-09T18:20:26","date_gmt":"2024-02-09T18:20:26","guid":{"rendered":"http:\/\/learningaloud.com\/blog\/?p=7101"},"modified":"2024-02-10T21:23:45","modified_gmt":"2024-02-10T21:23:45","slug":"ai-tutoring-based-on-retrieval-generated-augmentation","status":"publish","type":"post","link":"https:\/\/learningaloud.com\/blog\/2024\/02\/09\/ai-tutoring-based-on-retrieval-generated-augmentation\/","title":{"rendered":"AI tutoring based on retrieval generated augmentation"},"content":{"rendered":"\n

Here is a new phrase to add to your repertoire – retrieval generated augmentation<\/a> (RAG). I think it is the term I should have been using to explain my emphasis in past posts to my emphasis on focusing AI on notes I had written or content I had selected. Aside from my own applications, the role for retrieval generated augmentation I envisioned is as an educational tutor or study buddy<\/a>.<\/p>\n\n\n\n

RAG works in two stages. The system first retrieves information from a designated source and then uses generative AI to take some requested action using this retrieved information. So, as I understand an important difference, you can interact with a large language model based on the massive corpus of content on which that model was trained or you can designate specific content to which the generative capabilities of that model will be applied. I don\u2019t pretend to understand the specifics, but this description seems at least to be descriptive. Among the benefits is a reduction in the frequency of hallucinations. When I propose using AI tools in a tutoring relationship with a student, suggesting to the tool that you want to focus on specific information sources seems a reasonable approximation to some of the benefits a tutor brings. <\/p>\n\n\n\n

I have tried to describe what this might look like in previous posts, but it occurred to me that I should just record a video of the experience so those with little experience might see for themselves how this works. I found trying to generate this video an interesting personal experience. It is not like other tutorials you might create in that it is not possible to carefully orchestrate what you present. What the AI tool does cannot be perfectly predicted. However, trying to capture the experience as it actually happens seems more honest.<\/p>\n\n\n\n

A little background. The tool I am using in the video is Mem.ai<\/a>. I have used Mem.ai for some time to collect notes on what I read so I have a large collection of content I can ask the RAG capabilities of this tool to draw on. To provide a reasonable comparison to how a student would study course content, I draw some parallels based on the use of note tags and note titles. Instead of using titles and tags in the way I do, I propose a student would likely take course notes and among the tags label notes for the next exam with something like \u201cPsych1\u201d to indicate a note taken during the portion of a specific course before the first exam to which that note might apply. I hope the parallels I explain make sense.<\/p>\n\n\n\n

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