I have so many questions, none of which are answered by the article. Was the flavor really picked by an AI? If so, how did they train the AI? What kind of AI was this? What other flavors did it come up with? Did they try a bunch of them and this was the best one they could get?
This whole thing just screams marketing stunt to me, and not a particularly good one. I can’t wait for this whole AI thing to just die out already. How is it that every tech fad seems to somehow end up being even dumber than the previous one (although I think the whole NFT thing might have set a new low bar)?
“Unsurprisingly, ‘Diarrhea Sasquatch Xtreme’ hit the mark yet failed to wow test groups,” is likely one of many test flavors removed from the article for PR reasons.
Yeah, I’m guessing it was as as much an “AI” thing as everything was “i-something” about 20 years ago, or a bunch of stuff, even video game consoles, were the “something something computer” 40 years ago
The press release they link to is not especially forthcoming with information either and all they can get in terms of details is from that press release and tasting it themselves.
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.
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.
So, basically what people who are decent at cooking do all the time. Groundbreaking.
I’m a little bit of a cooking nerd, and a pretty adventurous eater. There are some flavor combinations that, when they’re explained to me, make a lot of sense, and I can see how they would work well together, but I would never think of putting together myself in a million years unless I saw some high-end chef on a cooking show or fancy restaurant do it first.
Off the top of my head, I remember someone on iron chef making some sort of fish ice cream, and someone on some other cooking show making some sort of liver pate and jelly donut, and both were very well received by the judges. I’d never think of putting those ingredients together in those ways, my first gut instinct if you just told me that those foods existed without further explanation was that they sound gross, but after thinking about it or having the chefs or judges explain them, I can totally see how they can work.
There’s only so many chefs cooking at a high level like that though, whose brains are wired in such a way that they really understand how the flavors can work together and can work around the biases that most of us have and put together ingredients in new and unexpected ways.
AI often won’t have the same biases we do (though it may be biased in other ways) so it could lower the barrier to entry for those of us who have the hands-on skills to put those sorts of dishes together, but maybe aren’t quite creative enough to come up with them by ourselves, and for the more creative types it could potentially become a useful sounding board for them to bounce ideas off of.
And yet the example soda flavor wasn’t well received because randomly putting shit together isn’t something that is inherently better when a computer does it.
Even though it’s apparently a pretty lackluster soda, I think it’s pretty notable that I haven’t seen any reviews saying that it’s outrightbad, it’s just not great. That’s better than I would expect from just randomly mixing ingredients.
Now we don’t know how many iterations it took to get them to that point, what kind of prompts or human handholding it took to get it to that point. It very well might be that the computer gave them a thousand bad formulas and this was the only one that was remotely palatable, but we don’t know and probably never will know if that was the case.
Not that I think coke will do it, but personally I think it would be cool for them to take the feedback they get from this soda, feed it back into the ai and have the computer design a version 2.0 based on that feedback and see how well it goes, and keep iterating it that way and see where they end up.
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.
Companies using AI in a stupid way will die out, but the models themselves are far too useful for certain job fields (probably not yours or you wouldn’t be comparing it to NFT’s) for them to ever die. They’re going to expand and become integrated into the data environment.
Well, on the label of the ones I tried it said co-developed by AI.
So yeah, probably marketing stunt
That said, if it hadn’t been artificially sweetened, I would probably have preferred it to the normal one. Felt like it had more flavor. Similar to Fritz Cola from Germany.
Deep Learning at least can produce useful tools here or there. No one has yet to come up with a good idea for why NFTs should be a thing. Though I’m sure someone will come along with their niche use that, on further consideration, doesn’t actually solve anything after all.
It will absolutely die out in that it will go back to what it was previously. We’ve been using “AI” for decades now, only it’s better known under the name machine learning. This latest surge in interest is just a bunch of marketing hype and a bunch of executives too stupid to realize they’re being fed a line of bullshit by contractors promising if they hire them to make an “AI” they’ll be able to fire their entire workforce and dump their salaries into fat executive bonuses. Just like all the previous tech fads this will stop being the hot thing once enough of these douche-bags get burned and even the dumbest of them learns that no, you can’t just replace your entire workforce with “AI” and call it a day.
The tools now are far better. You can slap together something useful with some basic Python knowledge. Hardest part is mixing up the data into giving you good results.
It’ll hang around, but I don’t think Nvidea’s market cap is justified. It’ll crash hard, but it could be tomorrow or three years from now.
I don’t think it’s going to end up impacting most industries all that much. Low end call centers will probably be impacted, but they were already being displaced by automated call trees and such even before this latest fad. At some point trucking will be displaced by self driving trucks, but that tech is looking to be further off than it initially seemed as well thanks in part to some pretty high profile accidents and renewed scrutiny from various governments. Beyond that the impact in other industries is looking to be fairly minimal. You’ll see smarter tools being rolled out to let people do the things they were already doing faster, but just like the “magic clone” tool in Photoshop while it will make some tedious time consuming activities much faster, it won’t really fundamentally change things.
Honestly the biggest impact is most likely to be on crime, with these various tools being leveraged by criminals to make increasingly convincing scams, phishing attacks, and even worse things.
In biology we’ve been using machine learning for a long time now so the AI super hype out there is pretty funny to me. It’s for sure useful with stuff like predicting protein folding and analyzing genes and stuff, but it’s all hyper-specific stuff just like it has its always been. Good for removing tedium for sure as its the reason we can even know the human genome because it would take literally forever to sequence it without modern tech, which we did in the in the 90s and finished in 2003.
My big hope is that all this hype will get people to invest in proteonomic technology which is 100% a great use case for AI and also the future.
I have so many questions, none of which are answered by the article. Was the flavor really picked by an AI? If so, how did they train the AI? What kind of AI was this? What other flavors did it come up with? Did they try a bunch of them and this was the best one they could get?
This whole thing just screams marketing stunt to me, and not a particularly good one. I can’t wait for this whole AI thing to just die out already. How is it that every tech fad seems to somehow end up being even dumber than the previous one (although I think the whole NFT thing might have set a new low bar)?
They probably trained it using data from their Coca-Cola freestyle dispensers if you’ve used one. That’s my guess.
People like Vanilla and people like Grape, so here’s Vanilla-Grape by CokeAI!
Sounds horrifyingly plausible.
I’d drink that tbh
Yeah sounds like a Purple Cow, I’d be all over that
The answer is simple. They’re using blockchain NFTs to reach new market growth using AI to provide flavor solutions to consumers
I can’t wait to get Bored Ape-flavored Coke on the blockchain!
So, ape piss?
“Unsurprisingly, ‘Diarrhea Sasquatch Xtreme’ hit the mark yet failed to wow test groups,” is likely one of many test flavors removed from the article for PR reasons.
Sorry about that. I had taco bell for lunch.
Bad AI
Per an early draft of the Proverbia Grecorum:
Or, if your latin is rusty:
Yeah, I’m guessing it was as as much an “AI” thing as everything was “i-something” about 20 years ago, or a bunch of stuff, even video game consoles, were the “something something computer” 40 years ago
The press release they link to is not especially forthcoming with information either and all they can get in terms of details is from that press release and tasting it themselves.
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.
So, basically what people who are decent at cooking do all the time. Groundbreaking.
I’m a little bit of a cooking nerd, and a pretty adventurous eater. There are some flavor combinations that, when they’re explained to me, make a lot of sense, and I can see how they would work well together, but I would never think of putting together myself in a million years unless I saw some high-end chef on a cooking show or fancy restaurant do it first.
Off the top of my head, I remember someone on iron chef making some sort of fish ice cream, and someone on some other cooking show making some sort of liver pate and jelly donut, and both were very well received by the judges. I’d never think of putting those ingredients together in those ways, my first gut instinct if you just told me that those foods existed without further explanation was that they sound gross, but after thinking about it or having the chefs or judges explain them, I can totally see how they can work.
There’s only so many chefs cooking at a high level like that though, whose brains are wired in such a way that they really understand how the flavors can work together and can work around the biases that most of us have and put together ingredients in new and unexpected ways.
AI often won’t have the same biases we do (though it may be biased in other ways) so it could lower the barrier to entry for those of us who have the hands-on skills to put those sorts of dishes together, but maybe aren’t quite creative enough to come up with them by ourselves, and for the more creative types it could potentially become a useful sounding board for them to bounce ideas off of.
And yet the example soda flavor wasn’t well received because randomly putting shit together isn’t something that is inherently better when a computer does it.
Even though it’s apparently a pretty lackluster soda, I think it’s pretty notable that I haven’t seen any reviews saying that it’s outrightbad, it’s just not great. That’s better than I would expect from just randomly mixing ingredients.
Now we don’t know how many iterations it took to get them to that point, what kind of prompts or human handholding it took to get it to that point. It very well might be that the computer gave them a thousand bad formulas and this was the only one that was remotely palatable, but we don’t know and probably never will know if that was the case.
Not that I think coke will do it, but personally I think it would be cool for them to take the feedback they get from this soda, feed it back into the ai and have the computer design a version 2.0 based on that feedback and see how well it goes, and keep iterating it that way and see where they end up.
I mean for a machine to do it? Yeah it kind of is.
Like the whole purpose of developing AI is to replace us, it being able to do what we do is literally the metric we are shooting for.
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.
Companies using AI in a stupid way will die out, but the models themselves are far too useful for certain job fields (probably not yours or you wouldn’t be comparing it to NFT’s) for them to ever die. They’re going to expand and become integrated into the data environment.
Well, on the label of the ones I tried it said co-developed by AI.
So yeah, probably marketing stunt
That said, if it hadn’t been artificially sweetened, I would probably have preferred it to the normal one. Felt like it had more flavor. Similar to Fritz Cola from Germany.
Deep Learning at least can produce useful tools here or there. No one has yet to come up with a good idea for why NFTs should be a thing. Though I’m sure someone will come along with their niche use that, on further consideration, doesn’t actually solve anything after all.
AI isn’t going to die out but hopefully it’ll get quieter and more boring/focused.
It will absolutely die out in that it will go back to what it was previously. We’ve been using “AI” for decades now, only it’s better known under the name machine learning. This latest surge in interest is just a bunch of marketing hype and a bunch of executives too stupid to realize they’re being fed a line of bullshit by contractors promising if they hire them to make an “AI” they’ll be able to fire their entire workforce and dump their salaries into fat executive bonuses. Just like all the previous tech fads this will stop being the hot thing once enough of these douche-bags get burned and even the dumbest of them learns that no, you can’t just replace your entire workforce with “AI” and call it a day.
The tools now are far better. You can slap together something useful with some basic Python knowledge. Hardest part is mixing up the data into giving you good results.
It’ll hang around, but I don’t think Nvidea’s market cap is justified. It’ll crash hard, but it could be tomorrow or three years from now.
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I don’t think it’s going to end up impacting most industries all that much. Low end call centers will probably be impacted, but they were already being displaced by automated call trees and such even before this latest fad. At some point trucking will be displaced by self driving trucks, but that tech is looking to be further off than it initially seemed as well thanks in part to some pretty high profile accidents and renewed scrutiny from various governments. Beyond that the impact in other industries is looking to be fairly minimal. You’ll see smarter tools being rolled out to let people do the things they were already doing faster, but just like the “magic clone” tool in Photoshop while it will make some tedious time consuming activities much faster, it won’t really fundamentally change things.
Honestly the biggest impact is most likely to be on crime, with these various tools being leveraged by criminals to make increasingly convincing scams, phishing attacks, and even worse things.
In biology we’ve been using machine learning for a long time now so the AI super hype out there is pretty funny to me. It’s for sure useful with stuff like predicting protein folding and analyzing genes and stuff, but it’s all hyper-specific stuff just like it has its always been. Good for removing tedium for sure as its the reason we can even know the human genome because it would take literally forever to sequence it without modern tech, which we did in the in the 90s and finished in 2003.
My big hope is that all this hype will get people to invest in proteonomic technology which is 100% a great use case for AI and also the future.
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