The work is very interesting. The title is misleading.
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.
As someone learning to cook from recipes in multiple languages,
this is really cool. Curious how it handles the same ingredient
called by different names (e.g., "scallion" vs "green onion" vs
"long onion").
I don't really understand, what the Graphs on page 9 and 13 represent, but they look somewhat like a world map with the continents.
I wouldn't be surprised if there's actually a geographic connection. A lot of ingrediants are probably more prevalent in certain world regions.
I saw this on X/Twitter. I do not believe that human cooking, and all of its techniques and ingredients and the various ways that things can be prepared in different cultural contexts can be compressed in to 2 megabytes.
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..
See [1] for a demo, seemingly of an older iteration of what this paper describes. I was curious what ingredients the demo had selected (1032 available vs 1790 this paper selects) so I tried some obscure ingredients from "Organum: Nature, Texture, Intensity, Purity" by Peter Gilmore[2] (known for Quay restaurant in Sydney, Australia).
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.
55 comments
[ 1.9 ms ] story [ 63.6 ms ] threadI'm trying to compress recipes into little schematics https://leontrolski.github.io/recipes.html
This is inspiring. Cooking is this sort of an activity that is simple enough to not be overwhelming but also complex enough to be very interesting.
Both in practice and in modelling :-)
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.
Not that it matters much in this context, but low-temperature is not the same thing as deterministic.
It's another book for Zach Weinersmith.
So hardly "all of human cooking"...
https://epicure.kaikaku.ai/
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 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..
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.
[1] https://epicure.kaikaku.ai/
[2] https://en.wikipedia.org/wiki/Peter_Gilmore_(chef)