A better title would be: "all of human ingredients compressed into 1,800 primitives"
There is little to substantively nothing about the actual cooking: preparation methods, proportions, etc.
But the idea that tomato goes well with beef the whole world over is very interesting and useful for creating flavors that will go together, perhaps surprisingly. It will be a nice resource in the future.
The flavor bible.
I can assure you that it does not contain 1800 ingredients in all of there combinations, but it does a remarkable job of covering a widely used selection of herbs spices vegetables and meats. I doubt a compressed version of the text would even be very large.
The trouble I find with LLM generated recipes is they miss the nuance of the technique. Often the success of a depends on a single step or ratio. For instance “fried chicken” has a million incarnations the world over, but you can’t just average out the recipes and end up with tasty fried chicken.
https://www.simonandschuster.com/books/Ratio/Michael-Ruhlman...
I saved a beef stew I was making for twelve people once by adding tomato sauce.
Beef hardens if stewed incorrectly and tomato acid tenderises it again.
EDIT: removed incorrect information about store bought tomatoes.
I'm trying to compress recipes into little schematics https://leontrolski.github.io/recipes.html
For a while I expected there could be a good return on a good implementation of this, but now as soon as a strong interface itself is created it seems easy to copy.
And I don't know why, but "Beans (green)" is really tickling my funny bone.
This would help coordinate two cooks to make prepping more independent.
I’m trying to figure out if an landscape Ipad, with interactive elements for extra details if needed, would be a good UI for this.
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Edit: Showed it to my non-Engineer wife and she said ”this is horrible” after staring at it for 10 seconds. Maybe not for everyone…
Great job!
So hardly "all of human cooking"...
They do quickly acknowledge it, but definitely not a balanced set.
It's got some adventurous ingredients such as juniper berry, macadamia nut, nigella seed, orange blossom water and lemon verbena. It even separates sesame oil and toasted sesame oil. Even though the ingredients list only has "rice", "black rice", "brown rice" and "glutinous rice", when you select "rice" as an ingredient, the recipes it generates are smart enough to advise of chilling cooked jasmine rice before using in a fried rice, and smart enough to soak and rinse Basmati rice before using in a pilaf. If selecting "lamb" as an ingredient, the recipes it generates will choose the cut as shoulder or shank if you select vegetables normally associated with braising.
It doesn't know of grapeseed oil, orzo, mangosteen, lemon myrtle, and of course anything that only Peter Gilmore might use in a recipe and most chefs would have never heard of (karkalla as an example). I don't see this being too much of a limitation because such ingredients are quite localised or speciality. It knows of "pumpkin seeds" but not "pumpkin"--that is "squash", so there are some localisation improvements which could be made to improve British and American English use. I tried pairing "lamb" and "avocado" together in the hope it'd generate a recipe with a salad, but this failed. I then realised the ingredients list doesn't include lettuce or rocket, but has "salad greens" instead (American English) and no matter what I tried (other salad ingredients, chicken or no protein), it would not give me a salad. It kept generating wannabe-fancy dishes of a chunk of protein surrounded by tomato gel (agar agar) and a smear of avocado, or similar.
It is sort of like saying here is a 1GB model that can do tool calling and coding and then you try it out and it barely functions. Yes, it technically is a 1GB coding model, but it isn't a good one.
The triangle of flour - milk and egg- held eggnog, but eggnog contains alcohol, which is made of starches, usually flour.. thus being percentage-wise closer to flour then displayed. Yes, so much on the spectrum..
Not that it matters much in this context, but low-temperature is not the same thing as deterministic.
Getting you to click is the ultimate goal.
That being said, I'm not excited about the idea of this being used to automate cooking somehow.
Food, to me, is part of what makes us human, where we express our soul for lack of a better word.
The idea of taking that away feels like robbing us of our humanity.
It's another book for Zach Weinersmith.
Numerical instability can introduce randomness especially on GPU like hardware unless you’re very careful about how you write your algorithms.