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.
I have a wonderful book that explores this idea of an atlas of flavours that work together.
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.
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..
a lot of the schematics have avoidable edge crossings, that could improve intuitive readability enormously, theres entire subfields of graph theory that consideres rendering of graphs and planar embeddings.
I really like these. I went through a phase a couple years ago where I got really into cooking new fancy recipes, and having to scroll around on recipe pages, or try and read my own chicken scratch notes or understand the context I was trying to imply when I wrote the notes weeks ago was a struggle.
Having everything more or less right there in front of your face seems really nice.
And I don't know why, but "Beans (green)" is really tickling my funny bone.
Ahh - the dependency graph recipe card. These are excellent. I've imagined something like this forever. Always annoyed that recipes put ingredients in a giant undifferentiated list and then give an instruction like "mix the dry ingredients in a deep bowl".
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.
Feels like one might be able to get an llm to convert an annoying to read recipe into a mermaid dependency graph following this example. Might be worth a try!
I love this! I bet you could make a successful recipe book based on this concept, with large schematics that a cook can read from a distance while working in the kitchen.
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.
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.
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").
It's an appeal to the attention economy. "All of human cooking compressed into 2 MB" is(mentally) palatable relative to "Navigating the Emergent Geometry of Food Ingredient Embeddings".
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.nature.com/articles/srep00196
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.
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..
I'm trying to compress recipes into little schematics https://leontrolski.github.io/recipes.html
And I don't know why, but "Beans (green)" is really tickling my funny bone.
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.
— Carl Sagan
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 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.
Not that it matters much in this context, but low-temperature is not the same thing as deterministic.
Numerical instability can introduce randomness especially on GPU like hardware unless you’re very careful about how you write your algorithms.
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.
Getting you to click is the ultimate goal.
It's another book for Zach Weinersmith.