Comment by steveBK123
1 month ago
An issue in the chat format is that all these models seem bad at recognizing when they have extraneous information from user that can be ignored, or insufficient information from the user to answer the question fully.
This issue is compounded by the lack of probabilities in the answers, despite the machines ultimately being probabilistic.
Notice a human in a real conversation will politely ignore extra info (the distance to car wash) or ask clarifying questions (where is the car?).
Even non-STEM people answer using probabilistic terms casually (almost certainly / most likely / probably / possibly / unlikely).
I suspect some of this is to minimize token usage in the fixed monthly price chat models, because back&forth would cost more tokens.. but maybe I'm too cynical.
The systems recognized the pattern that it looks like a generic article on the internet asking whether someone should walk or drive and answered it exactly as expected based on their training data. None of this should be surprising.
We are the ones fooling ourselves into believing there's more intelligence in these systems than they really have. At the end of the day, it's just an impressive parlor trick.
In that sense the google AI summary search results are a better UX for this type experience
The better UX is that the google ai search summary is easy to ignore.