Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

He asked AI to count carbs 27000 times. It couldn't give the same answer twice

diabettech.com

Post reply on HN
Print view View original

201–210 of 329 posts

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#201

Post by bcjdjsndon »

harperlee wrote: post #53

There is a lot of hate in the comments but there is some merit to the post existing: 1. Even if the task is unreasonable, it is good to showcase that the LLM will perform poorly - warning not to be used for diabetes. 2. As it is a probabilistic model, the approach was to execute it multiple times and look at the distribution. They also tried to minimize variance: "All at the lowest randomness setting these models off…

Re: 2... I think it's interesting they add arbitrary randomness in the algorithm. The problem of wildly varying outputs to the same input wouldn't exist in the first place

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#202

Post by bcjdjsndon »

ozgung wrote: post #196
jaccola wrote: post #6

It’s just an impossible problem. Photons don’t provide sufficient information to determine calories (at least not in any way they could practically be captured). Inside that sandwich could be drenched with olive oil or it could be hollow cheese with lettuce. It’s impossible to tell.

As a human, in the photo of that sandwich I see 4 slices of bread and 4 slices of cheese (distributed unevenly). I have no idea about the weight of the bread, flour type or its sugar content. I don't know the type of the cheese, dimensions of the slices or total amount of cheese inside the bread. I don't know if there is butter or anything else inside. I can guess the size of the plate as a size reference but I can't…

But why would the same llm give you wildly different answers EACH TIME you ask?

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#203

Post by umvi »

Food companies try every trick to make carb counting difficult. Companies will tout "zero sugar" in the label even though the first ingredient is maltodextrin or maltitol or some other thing that quickly turns into sugar the moment you ingest it. The only way to get good at it is to wear a CGM and then see how your body reacts to things and then keep a mental list after that. A company may claim some product only has 2 net carbs, but I've found those claims to be false a lot of the time, with bigger companies being the biggest offenders.

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#204

Post by therobots927 »

pohl wrote: post #60
therobots927 wrote: post #51

Earlier quoted context omitted.

Why is the AI answering questions without answers then?

could be because, at the end of the day, it's just predicting the next likely token

The paper millionaires did NOT like your comment.

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#205

Post by nvahalik »

Man. I built an AI food system at my previous company and it was tough: we ended up just using it as a way to look up foods in a real DB and allowed guestimation but ultimately the win was "I don't have to search for everything on this place" we surface _what_ and then allowed the user to enter the real weights.

And this... really was and (will be) the only way for this to ever work.

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#208

Post by chromacity »

endymion-light wrote: post #43

There's an incredibly serious lack of education with how LLMs & carb-counting works. This entire article would be better suited to astrology.com than hackernews. When I opened it up, I assumed the author would have at least attempted a calculation service, maybe even placed something like the size of the meal into an actual model, using the integration of pre-existing tools that are (slightly more) accurate. Hell - m…

> There's an incredibly serious lack of education with how LLMs & carb-counting works

Oh! Do the vendors offer trainings to make sure the users understand how LLMs work? If not, surely, the LLM itself is trained to know its limitations and politely decline in situations like that?...

The #1 use case for this tech is "here's a problem I don't feel like solving, let's have a computer do magic". It's how it's advertised on TV, it's how it promoted in the software I already use. Food preparation? Travel planning? Shopping? Tutoring your children? You can do anything now!

I just talked to a realtor who will make a killing on a real estate transaction. Instead of offering human insights, they sent me "AI reviews" of several properties. The AI has never been to any of these properties and has no idea how they actually look like. But I guess it's how we operate now as a society.

If you go to eBay, every other listing description for used items is AI-generated. This is an official platform feature for sellers. The AI doesn't know the condition of the item or what's included or missing. Doesn't matter, it's magic. It's AGI, it will figure it out.

Most of the uses of AI I encounter as a consumer are like that, and the companies selling this tech are 100% complicit.

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#209

Post by Ukv »

professoretc wrote: post #163
Ukv wrote: post #133

Earlier quoted context omitted.

> Then the correct answer is “I can’t tell.” From the paper they're using structured JSON schema mode opposed to freeform answers, so it can't. Models do typically caveat their answer for questions like this, in my experience.

They'll qualify their answers in English but as the article mentions, if your prompt asks for a confidence score, that "uncertainty" doesn't translate into low numerical confidence.

Quantifying their own confidence is also something they're not good at, and which the format would prevent them from refusing to do or preceding with a caveat if that's what you'd want of them. Particularly since the response format seems backwards - giving confidence, then carbs estimate, then observations/notes, rather than being able to base carbs estimate off of observations/notes and then confidence estimate off of both of those.

> They'll qualify their answers in English but [...]

That the default user-facing chat as a normal user would use it gives a warning is the key part IMO. I don't think expectations of there being no "wrong way" to use the model can necessarily extend to API usage with long custom system prompt and restricted output format.

Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice

#210

Post by endymion-light »

datsci_est_2015 wrote: post #197
endymion-light wrote: post #43

There's an incredibly serious lack of education with how LLMs & carb-counting works. This entire article would be better suited to astrology.com than hackernews. When I opened it up, I assumed the author would have at least attempted a calculation service, maybe even placed something like the size of the meal into an actual model, using the integration of pre-existing tools that are (slightly more) accurate. Hell - m…

The obvious meme to invoke here is: - AI will solve all of our problems - No not like that! Are the trillion dollars sloshing around the AI economy well-invested if the refrain is always “you’re holding it wrong”? So we’re trying to define, through trial and error, what problems “AI” will actually solve, and this paper is one of the many cobblestones on that road.

i mean it's more like

"AI can solve this one problem, but it needs X, Y, Z, because it's not a omnipotent god entity"

"I tried it without any of those things and it didn't work - this is worthless tech!"

I don't know if more accurate calorie counting using AI exists - but it's like being upset that the screwdriver isn't gluing wood. AI is far more than frontier LLMs.

Post reply on HN