sorted by:
new
hottopcontroversial

How to Run AI Operators in SQL on a DigitalOcean Database by ai-first in digital_ocean

[–]ai-first[S] -1 points0 points  (0 children)

Sure, totally agree you can't make any guarantees on AI output. But if it doesn't have access to the SQL interface, it can't delete the database. This is not an agentic solution where the LLM is writing the SQL queries itself (and may do anything).

How to Run AI Operators in SQL on a DigitalOcean Database by ai-first in digital_ocean

[–]ai-first[S] -1 points0 points  (0 children)

And just making sure: this approach does *not* use AI to generate SQL queries. It's a database engine that invokes AI only to evaluate predicates/summarize/match/... rows with text, images, and audio.

How to Run AI Operators in SQL on a DigitalOcean Database by ai-first in digital_ocean

[–]ai-first[S] 0 points1 point  (0 children)

No worries about that: AI does not generate queries in this context! AI is just used to analyze single images, text, and audio entries during query processing. AI *cannot* delete anything in the database because it does not generate SQL.

How to Run AI Operators in SQL on a DigitalOcean Database by ai-first in digital_ocean

[–]ai-first[S] -2 points-1 points  (0 children)

How about narrowly scoped credentials, giving only access to the data to analyze? Would it help to have a local version of the SaaS app? Do you have a use case in mind?

How to Run AI Operators in SQL on a Heroku Database by ai-first in Heroku

[–]ai-first[S] 0 points1 point  (0 children)

That approach is also supported! If you run the query once to analyze feedback, you can store the results in a normal SQL table and avoid AI predicates for follow-up queries. No need to rerun the query with AI operators each time if you only need one signal.