Earlier quoted context omitted.
I am asking a lot here, but school needs to be training people what AI is and what it's weaknesses are and how to use it... My school taught me to use a calculator. It also taught me how to check my work when I relied on the calculator. AI is a very complicated calculator - you give it an input, magic happens, it gives you an output. Really no different, to a layman.
To be fair, this should probably be covered by basic physics/maybe cooking classes. “You can’t determine the calories in food by looking at it” isn’t really ML specific.
He asked AI to count carbs 27000 times. It couldn't give the same answer twice
101–110 of 329 posts
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#102Earlier quoted context omitted.
Curious, why it was easier to use an LLM vs a non-AI app with a DB of foods? Seems that in this case a traditional approach would be more precise and more environmentally efficient to get to the same results.
Any app I have used before has asked me to look up the foods and add them manually and usually there has been ads or subscriptions involved. Much easier for me to take pictures of the packets while making the food, the weight the final bulk product and then when I eat just weight the plate and say “500g of casserole” and the LLM spits out the calories and keeps track of the daily consumption
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#103There'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…
I feel like you didn't understand the goal of this study > The DTN-UK stated earlier this year that generic LLMs must never be used as autonomous advisory calculators for insulin delivery. This data is the quantitative evidence base for that statement. This study is to prove that you should not rely on LLMs
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#104> You’d expect the same answer each time. It’s the same photo, the same model, the same question. But you won’t get the same answer. Not even close — and the differences are large enough to cause a hypoglycaemic emergency. Already the first paragraph highlights the issue; unless you set temperature=0.0 and the model can actually do reproducible inference, none of the "answers" you get are deterministic! But it's a ve…
i'd be ok with it if i was generating a picture of X, or some word salad about Y, but not for code. Never for code.
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#105Earlier quoted context omitted.
The average person has no idea this is true. And the average person cannot tell when this is the case. So we have a bunch of people, going their way through school, and then when they get stuck relying on AI. The future is gonna be wild.
Here's technical literacy of population on display. I love these prank examples which show the true education of populace. https://www.youtube.com/shorts/B7c9qJcRnVk
Even if you _know_ the debit card transaction is safe, there’s no reason to risk it when a weirdo is filming you with some wild contraption.
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#106There'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…
I feel like you didn't understand the goal of this study > The DTN-UK stated earlier this year that generic LLMs must never be used as autonomous advisory calculators for insulin delivery. This data is the quantitative evidence base for that statement. This study is to prove that you should not rely on LLMs
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#107I am surprised that people believe that calories can be counted correctly from a single photo
Issue is there are many apps claiming they can do that, and for many people are “magic”. We should not allow companies to lie blatantly to the customers. Edit: r/blame/lie/
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#108Earlier quoted context omitted.
It’s worse, I bet there are apps in the App Store that do this, the users just have no idea on the accuracy
There is a very popular app for macro counting called Cal AI that was reported to have been written by a high school student with over $1M in revenue. Looks like it was just acquired by MyFitnessPal
https://techcrunch.com/2025/03/16/photo-calorie-app-cal-ai-d...
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#109Earlier quoted context omitted.
But nothing prevents llms from being RLed to do this right? But does training llms to be better at this, improves their world model or does it only make changes at the surface?
Yes, something prevents llms from being RLed to do this: You can't see through something opaque to determine whether there's something high calorie or low calorie out of sight. The problem itself is unsolvable given the data provided. You could conceivable make it better at making guesses, but they will inherently always be guesses that will sometimes be wildly off.
https://www-users.york.ac.uk/~ss44/joke/3.htm "There is at least one field, containing at least one sheep, of which at least one side is black."
Re: He asked AI to count carbs 27000 times. It couldn't give the same answer twice
#110There'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 is a shocking amount of Computer Vision tasks where the scientists claim you can get X info from a picture of Y and it's like, even with ML/AI you can't extract data where there isn't any. The fact I can add an arbritrary amount of high-calorie fat to a meal without changing the appearance by defintion shows it's pointless. A 1000 calorie and 100 calorie milkshake can look identical, and you'd have no way of working that out via an image even if it was a super-intelligent system.
Similarly I see it in things like extracting material of an object from an image of it in serious research papers, which for the same reason cannot be done, since how an object looks has very little to do with what its made of, else painting and other art would clearly be impossible. The information is just not there within the data.