>Evaluators validate each tag individually — for example, protein, preparation, or health, individually rather than judging the item as a whole.
Am I reading this right that the jury is multiple LLMs each iterating through each tag and voting on each? Why wouldn't you tune one LLM to be really competent at a single tag? Like a single "spicy evaluator LLM" or "protein evaluator LLM"?
I am sorry to be harsh but I find it amateurish that they would use an AI generated hero image for this and presumably fabricated LLM output -- fabricated by an AI image generator no less
Whenever I create an image like this for the purpose of a demo, I make certain that it demonstrates either real input/output or at least is exemplary of real input/output because the whole point is to instill confidence in the tool. Sure, if the raw outputs aren't clean/comprehensible enough for presenting to stakeholders or others, fine, clean them up to make them comprehensible or add explainers, but there shouldn't be any need to fabricate the inputs.
I feel obligated to respond to the hypothetical "But they don't want to tie it to a particular restaurant or brand" -- you don't have to! Doordash has taken generic food photos for this exact purpose.
I'm guessing that if it is a real tag, then consumers have a "know it when I see it" feeling for certain kinds of food that they'd describe as "healthy." As a word that could be consistently well-defined, it's garbage. But that doesn't mean it's not useful for real-world consumers to find what they believe they want.
I am taking from their hero image that something like a gluten allergy would have to be verified by the merchant, but I’m just guessing that’s true.
Feeding failure cases into an AI-led prompt tuning agent to solve them seems prone to a lot of problems though.
despite having multibillion dollar valuation and a real product and service doordashes tech blogs have always been surprisingly simplistic and borderline elementary or in this case, kind of just slop. I remember reading their early data science ones and they were all sort of comically limited or discussing tradeoffs between outdated methods.
Am I reading this right that the jury is multiple LLMs each iterating through each tag and voting on each? Why wouldn't you tune one LLM to be really competent at a single tag? Like a single "spicy evaluator LLM" or "protein evaluator LLM"?