I don’t know what their ai process looks like, what kind of data they trained it on, etc.
But annecdotally, I’ve played around a bit with chatgpt making cocktail recipes, and it’s been surprisingly good at it. They sometimes need a little fine-tuning but they tend to get you in a pretty close ballpark, it’s made some interesting suggestions I probably wouldn’t have thought of, but nothing that turned out to be bad.
A lot of recipes tend to follow some pretty well-established ratios which means they can be broken down into some sort of mathematical formula which is something computers can actually do pretty well, and it’s often just a matter for swapping out one ingredient or combination of them for another that is similarly salty/sweet/bitter/sour/umami.
For example a standard recipe for punch is 1 part sour, 2 of sweet, 3 of strong (liquor of your choice), 4 of weak (tea, juice, soda, water, etc.) and you can mix and match just about any ingredients that fit those profiles and get a drinkable punch.
I’m sure a company like coke probably has a long list of flavorings with known and well-documented flavor profiles that an ai trained on a list of proven recipes could mix and match with all day long.
That’s not how a LLM like Chatgpt works. It’s not referencing cocktail recipes, compiling their ingredients, seeing commonalities, figuring out mathematical formulas, and then experimenting with the variables. That kind of thing is still probably a decade or more away, if not decades.
If you’re curious, see what people have tried to do with AI generated recipes that fit nutrition guidelines and how they never add up correctly.
From what I’ve seen of cocktails and recipe books, there’s probably a lot more of them than you realize. I guarantee you there are thousands of cocktail recipes you’ve never heard of that have been written into published recipe books.
All of that to say that Chatgpt is basically just making up arrangements of words that based on its training should go together.
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I don’t know what their ai process looks like, what kind of data they trained it on, etc.
But annecdotally, I’ve played around a bit with chatgpt making cocktail recipes, and it’s been surprisingly good at it. They sometimes need a little fine-tuning but they tend to get you in a pretty close ballpark, it’s made some interesting suggestions I probably wouldn’t have thought of, but nothing that turned out to be bad.
A lot of recipes tend to follow some pretty well-established ratios which means they can be broken down into some sort of mathematical formula which is something computers can actually do pretty well, and it’s often just a matter for swapping out one ingredient or combination of them for another that is similarly salty/sweet/bitter/sour/umami.
For example a standard recipe for punch is 1 part sour, 2 of sweet, 3 of strong (liquor of your choice), 4 of weak (tea, juice, soda, water, etc.) and you can mix and match just about any ingredients that fit those profiles and get a drinkable punch.
I’m sure a company like coke probably has a long list of flavorings with known and well-documented flavor profiles that an ai trained on a list of proven recipes could mix and match with all day long.
That’s not how a LLM like Chatgpt works. It’s not referencing cocktail recipes, compiling their ingredients, seeing commonalities, figuring out mathematical formulas, and then experimenting with the variables. That kind of thing is still probably a decade or more away, if not decades.
If you’re curious, see what people have tried to do with AI generated recipes that fit nutrition guidelines and how they never add up correctly.
From what I’ve seen of cocktails and recipe books, there’s probably a lot more of them than you realize. I guarantee you there are thousands of cocktail recipes you’ve never heard of that have been written into published recipe books.
All of that to say that Chatgpt is basically just making up arrangements of words that based on its training should go together.