3 ms·

The compound I was researching was [edit: removed]. Problem is it's not FDA approved, only prescribed by compounding pharmacies off label. Experimental compou

by cj 1y ago

The compound I was researching was [edit: removed]. Problem is it's not FDA approved, only prescribed by compounding pharmacies off label. Experimental compound with no official guidelines. The first result on Google for "[edit: removed] dosing guidelines" is a random word document hosted by a Telehealth clinic. Not exactly the most reliable source. Edit: Jeesh, what’s with the downvotes?

BeetleB 1y ago
> Experimental compound with no official guidelines. > The first result on Google for "GHK-Cu dosing guidelines" is a random word document hosted by a Telehealth clinic. Not exactly the most reliable source. You're making my point even more. When doing off label for an unapproved drug, you probably should not trust anything on the Internet. And if there is a reliable source out there on the Internet, it's very much on you to be able to discern what is and what is not reliable. Who cares that the LLM is wrong, when likely much of the Internet is wrong? BTW, I'm not advocating that LLMs are good for stuff like this. But a better example would be asking the LLM "In my state, is X taxable?" The Google AI summary was completely wrong (and the helpful link it used as a reference was correct, and in complete disagreement with the summary). But other than the AI summary being wrong, pretty much every link in the Google search results was correct. This is a good use case for not relying on an LLM: Information that is widely and easily available is wrong in the LLM.
- cj 1y ago
  > You're making my point even more What exactly is your point? Is your point that I should be smarter and shouldn’t have asked ChatGPT the question? If that’s your point, understood, but I don’t think you can assume the average ChatGPT user will have such a discerning ability to determine when and when not using a LLM is appropriate. FWIW I agree with you. But the “you shouldn’t ask ChatGPT that question” is a weak argument if you care about contextualizing and broadening your point beyond me and my specific anecdote.
  - BeetleB 1y ago
    My point is that if you're trying to demonstrate how unreliable LLMs are, this is a poor example, because the alternatives are almost equally poor. > If that’s your point, understood, but I don’t think you can assume the average ChatGPT user will have such a discerning ability to determine when and when not using a LLM is appropriate. I agree that the average user will not, but they also will not have the ability to determine that the answer from the top (few) Google links is invalid as well. All you've shown is the LLM is as bad as Google search results. Put another way, if you invoke this as a reason one should not rely on LLMs (in general), then it follows one should not rely on Google either (in general).
nonameiguess 1y ago
I think this actually points at a different problem, a problem with LLM users, but only to the extent that it's a problem with people with respect to any questions they have to ask any source they consider an authority at all. No LLM, nor any other source on the Internet, nor any other source off the Internet, can give you reliable dosage guidelines for copper peptides because this is information that is not known to humans. There is some answer to the question of what response you might expect and how that varies by dose, but without the clinical trials ever having been conducted, it's not an answer anyone actually has. Marketing and popular misconceptions about AI lead to people expecting it to be able to conjure facts out of thin air, perhaps reasoning from first principles using its highly honed model of human physiology. It's an uncomfortable position to be in trying to biohack your way to a more youthful appearance using treatments that have never been studied in human trials, but that's the reality you're facing. Whatever guidelines you manage to find, whether from the telehealth clinic directly, or from a language model that read the Internet and ingested that along with maybe a few other sources, are generally extrapolated from early rodent studies and all that's being extrapolated is an allometric scaling from rat body to human body of the dosage the researchers actually gave to the rats. What effect that actually had, and how that may or may not translate to humans, is not usually a part of the consideration. To at least some extent, it can't be if the compound was never trialed on humans. You're basically just going with scale up a dosage to human sized that at least didn't kill the rats. Take that and it probably won't kill you. What it might actually do can't be answered, not by doctors, not by an LLM, not by Wikipedia, not by anecdotes from past biohackers who tried it on themselves. This is not a failure of information retrieval or compression. You're just asking for information that is not known to anyone, so no one can give it to you. If there's a problem here specific to LLMs, it's that they'll generally give you an answer anyway and will not in any way quantify the extent to which it is probably bullshit and why.
- cj 1y ago
  > a problem with LLM users I think the flaw here is placing blame on users rather than the service provider. HN is cutting LLM companies slack because we understand the technical limitations making it hard for the LLM to just say “I don’t know”. In any other universe, we would be blaming the service rather than the user. Why don’t we fix LLMs so they don’t spit out garbage when it doesn’t know the answer. Have we given up on that thought?

by cj 1y ago

BeetleB 1y ago

> Experimental compound with no official guidelines. > The first result on Google for "GHK-Cu dosing guidelines" is a random word document hosted by a Telehealth clinic. Not exactly the most reliable source. You're making my point even more. When doing off label for an unapproved drug, you probably should not trust anything on the Internet. And if there is a reliable source out there on the Internet, it's very much on you to be able to discern what is and what is not reliable. Who cares that the LLM is wrong, when likely much of the Internet is wrong? BTW, I'm not advocating that LLMs are good for stuff like this. But a better example would be asking the LLM "In my state, is X taxable?" The Google AI summary was completely wrong (and the helpful link it used as a reference was correct, and in complete disagreement with the summary). But other than the AI summary being wrong, pretty much every link in the Google search results was correct. This is a good use case for not relying on an LLM: Information that is widely and easily available is wrong in the LLM.

cj 1y ago
> You're making my point even more What exactly is your point? Is your point that I should be smarter and shouldn’t have asked ChatGPT the question? If that’s your point, understood, but I don’t think you can assume the average ChatGPT user will have such a discerning ability to determine when and when not using a LLM is appropriate. FWIW I agree with you. But the “you shouldn’t ask ChatGPT that question” is a weak argument if you care about contextualizing and broadening your point beyond me and my specific anecdote.
- BeetleB 1y ago
  My point is that if you're trying to demonstrate how unreliable LLMs are, this is a poor example, because the alternatives are almost equally poor. > If that’s your point, understood, but I don’t think you can assume the average ChatGPT user will have such a discerning ability to determine when and when not using a LLM is appropriate. I agree that the average user will not, but they also will not have the ability to determine that the answer from the top (few) Google links is invalid as well. All you've shown is the LLM is as bad as Google search results. Put another way, if you invoke this as a reason one should not rely on LLMs (in general), then it follows one should not rely on Google either (in general).

nonameiguess 1y ago

I think this actually points at a different problem, a problem with LLM users, but only to the extent that it's a problem with people with respect to any questions they have to ask any source they consider an authority at all. No LLM, nor any other source on the Internet, nor any other source off the Internet, can give you reliable dosage guidelines for copper peptides because this is information that is not known to humans. There is some answer to the question of what response you might expect and how that varies by dose, but without the clinical trials ever having been conducted, it's not an answer anyone actually has. Marketing and popular misconceptions about AI lead to people expecting it to be able to conjure facts out of thin air, perhaps reasoning from first principles using its highly honed model of human physiology. It's an uncomfortable position to be in trying to biohack your way to a more youthful appearance using treatments that have never been studied in human trials, but that's the reality you're facing. Whatever guidelines you manage to find, whether from the telehealth clinic directly, or from a language model that read the Internet and ingested that along with maybe a few other sources, are generally extrapolated from early rodent studies and all that's being extrapolated is an allometric scaling from rat body to human body of the dosage the researchers actually gave to the rats. What effect that actually had, and how that may or may not translate to humans, is not usually a part of the consideration. To at least some extent, it can't be if the compound was never trialed on humans. You're basically just going with scale up a dosage to human sized that at least didn't kill the rats. Take that and it probably won't kill you. What it might actually do can't be answered, not by doctors, not by an LLM, not by Wikipedia, not by anecdotes from past biohackers who tried it on themselves. This is not a failure of information retrieval or compression. You're just asking for information that is not known to anyone, so no one can give it to you. If there's a problem here specific to LLMs, it's that they'll generally give you an answer anyway and will not in any way quantify the extent to which it is probably bullshit and why.

cj 1y ago
> a problem with LLM users I think the flaw here is placing blame on users rather than the service provider. HN is cutting LLM companies slack because we understand the technical limitations making it hard for the LLM to just say “I don’t know”. In any other universe, we would be blaming the service rather than the user. Why don’t we fix LLMs so they don’t spit out garbage when it doesn’t know the answer. Have we given up on that thought?