A task that might have taken five hours assisted by AI, and perhaps ten hours without it, is now more commonly taking seven or eight hours, or even longer.
What kind of work do they do?
in my role as CEO of Carrington Labs, a provider of predictive-analytics risk models for lenders. My team has a sandbox where we create, deploy, and run AI-generated code without a human in the loop. We use them to extract useful features for model construction, a natural-selection approach to feature development.
I wonder what I have to imagine this is doing and how. How do they interface with the loop-without-a-human?
Either way, they do seem to have a (small, narrow) systematic test case and the product variance to be useful at least anecdotally/for a sample case.
I have a feeling that their test case is also a bit flawed. Trying to get index_value instead of index value is something I can imagine happening, and asking an LLM to ‘fix this but give no explanation’ is asking for a bad solution.
I think they are still correct in the assumption that output becomes worse, though
What kind of work do they do?
I wonder what I have to imagine this is doing and how. How do they interface with the loop-without-a-human?
Either way, they do seem to have a (small, narrow) systematic test case and the product variance to be useful at least anecdotally/for a sample case.
I have a feeling that their test case is also a bit flawed. Trying to get index_value instead of index value is something I can imagine happening, and asking an LLM to ‘fix this but give no explanation’ is asking for a bad solution.
I think they are still correct in the assumption that output becomes worse, though
It just emphasizes the importance of tests to me. The example should fail very obviously when you give it even the most basic test data.
Yeah, if only QA vere not the first ‘replaced’ by AI 😠