I feel like the technique recommendations are probably the most valuable element, but I'm getting rave reviews like 85% of the time now?
There have been a couple times where I was out of an ingredient and it proposed an adjustment that sounded a little wild to me, but it almost always is well received.
Unfortunately, one does not exist.
The Internet, however, is full of garbage cooking advice, and while AI is quite happy to parrot that garbage, it's not significantly worse than it's sources.
The physical ones have indices, and the digital ones usually do as well (plus string search).
I often find their contents to be both incredibly broad, and incredibly shallow, and often lead to dishes that don't quite suit my tastes.
I have generally had more success with the internet than I have with them.
I usually just find recipes that are close to something I like and then modify them until I like them
I feel like cooking recipes should always be full of little notes from past attempts, to tweak them to your personal taste
And we aren't talking about something esoteric. How To Cook Everything. (4.5 rating on Amazon, 4.0 on Goodreads), one of the most popular cookbooks in the world...
Has its first recipe for chicken cutlets produce undercooked chicken (15 minutes at 325F has not resulted in 165F internally).
Worse yet, its chile recipe for some weird reason involves boiling and simmering an onion with the beans before throwing it out (WTF). It then has you drain the beans only to add that drained water right back (WTF?), unless you optionally replace it with tap water (WTF was the point of boiling the onion then?), so that you could bring them to boil again. The recipe barely has any spices besides actual chile peppers.
This... Is not good or helpful, but is incredibly opinionated with a bunch of bullshit steps.
Fuck. Does nothing good survive on the internet anymore.
I mostly don’t even need a recipe from AI, just the title and a 1-2 sentence description.
I feel like it can only be successful by luck. Either it's reproducing a recipe verbatim that was tried and validated and tasted by a human, in which case, we didn't need AI for that, just a searchable cookbook. Or, it's making one up. I understand that using RLHF has helped improve the quality of questions about history, programming, or TV show recommendations, but I do not believe that there has been some kind of training regime where people prompt the models for "a recipe that uses X, Y, Z random ingredients," follow the recipe, and then score it. And even if they do, I don't see how a model can learn enough from that besides "this exact recipe is good/bad." '1/2 tsp cumin' may be a great addition to one recipe and not enough for another, so improving the output based on a bunch of scored recipes... I just don't believe cooking is an LLM job.
Maybe some other kind of model that I don't know about.