This is the 2nd launch from Dish Dragon. View more
Dish Dragon AI
Data science based ingredient pairing
The results of a survey of 150,000+ online recipes. Find ingredients that combine well or poorly or follow the 3d graph of interlinked ingredients. Also: find recipes based on the Dish Dragon's own scoring system, rather than questionable online review scores.
I really love the idea of this!
@matseinarsen, I'm curious if you've personally used it to make any dishes, or figured out what to make from an obscure ingredient?
Have you also thought about sorting the pairings into flavour profiles of the combination of ingredients, or of the linked recipes themselves? I'm just wondering if say, you had an ingredient like Truffles, it might be quite interesting to see if there was a clever recipe for a sweet dessert or something, which involved truffles.
@calum Hey! Thanks for the enthusiasm :) Yes - I've found quite a few things that I've liked. The combination of maple syrup and lime juice was really surprising to me, but now I use that in everything from Indian curries to cocktails. Another thing I recently enjoyed was having red onion on blue cheese. I also have it high on my list to splash some honey into my adobo sauce next time I make that. I use it quite a lot myself, actually, but i guess often it's more a reminder of things I already knew, like adding parsley or a chunk of butter to a dish to give it something extra.
Yes on the second :) I already have category meta data for most ingredients and recipes, so that's more an interface thing to add... But it would be interesting to also use a clustering algorithm to identify other kinds of flavour profiles. Definitively pondering that :)
All things considered, D5 Render is a fantastic tool for architectural visualization, especially if you're looking for ease of use and high-quality results. While it’s not perfect, it’s certainly a strong contender in the world of 3D rendering.
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