Why is this, I wonder? Aren't the models trained on about the same blob of huggingface web scrapes anyway? Does one tool do a better job of pre-parsing the web data, or pre-parsing the prompts, or enhancing the prompts? Or a better sequence of self-repair in an agent-like conversation? Or maybe more precision in the weights and a more expensive model?
their products are just just good enough to allow them to put a checkbox in a feature table to allow it to be sold to someone who will then never have to use it
but not even a penny more will be spent than the absolute bare minimum to allow that
this explains Teams, Azure, and everything else they make you can think of
How do you QA adding weird prediction tool to say Outlook. I have to use Outlook at one of my clients and have switched to writing all emails in VS Code and then pasting it to Outlook as “autocomplete” is unbearable… Not sure QA is possible with tools like these…
Part of QA used to be evaluating whether a change was actually helpful in doing the thing it was supposed to be doing.
... why, it's almost like in eliminating the QA function, we removed the final checks and balances on developers (read: PMs) from implementing whatever ass-backwards feature occurs to them.
Just in time for 'AI all the things!' directives to come down from on high.
exactly!! though evaluating whether a change was actually helpful in doing the thing it was supposed to be doing is hard when no one knows what it is supposed to be doing :)
