jbird11
Joined 3 years ago
Joined 3 years ago
I initially started by offering the service for free, but it eventually became too expensive to handle by myself. I then decided to switch to a paid and free tier and by that point I had amassed enough of a user base that a decent handful signed up to the paid tier. I optimized for user growth > revenue in the beginning because I kept thinking, "if people are not going to use this for free then they surely are not going to pay for it".
Anyhow, it's called Proseable and it also supports English, Italian, German, and Spanish!
Let's say you have a chatbot and stored in its database is the usual info like session id, timestamp, message etc. To "vectorize" this db then would be to vectorize all the messages. Is this too simple an understanding?
Once the db has been vectorized then we can do semantic search on the messages and create more informative graphs based off the semantic similarity for messages within a given timeframe or other criteria.
Experimental setup - https://www.nobelprize.org/uploads/2023/10/fig5_fy_en_23.pdf
Light / gas interaction - https://www.nobelprize.org/uploads/2023/10/fig4_fy_en_23.pdf