3 ms·
I don’t agree. RAG works just fine for this use case if you have a decent chunking methodology, good prompt design and some secondary safety rails. We do just t
by dbuxton 3y ago
I don’t agree. RAG works just fine for this use case if you have a decent chunking methodology, good prompt design and some secondary safety rails. We do just this in our product (https://hrharriet.com https://hrharriet.com).
The challenge Microsoft have set themselves however is that their problem domain is very large. They have to accommodate many different types of queries. We do benefit from having a specific type of usage pattern and much smaller data than a “real” Onedrive.
That said I am baffled that this product has performed as badly as it did in the review. These seem like pre-alpha type issues. I guess we should congratulate MS for being willing to put these things out to test at early stage but… come on!
- rmccue 3y agoAs an aside, I think your product site could be a bit more precise on some of the language; your homepage states "Harriet never trains on your data.", but your FAQ states "She is powered by LLMs [...] but trained on your company info" and "Harriet is trained on your documents" :) I assume what you're meaning is that the generic model itself is not trained on company data, but is using retrieval techniques with the actual company data when used.