11–20 of 148 posts
This argument is disingenuous. Hyperparameter optimization is not in the same category as prompt engineering, like at all. Also no one claims like half of the things the article claims people clain.
I can walk and chew bubble gum at the same time: on one hand, yes, there's certainly a lot of Kool-Aid being drank by the AI folks. Even on HN, I constantly argue with people that genuinely think LLMs are some kind of magical black box that contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain. And on the other hand, I think that language interfaces are probably the n…
These are not mutually exclusive. If you have a Markov chain that 100% of the time outputs "A cat is an animal", then it has knowledge that a cat is an animal.
See Also: Scrum certification.
I can walk and chew bubble gum at the same time: on one hand, yes, there's certainly a lot of Kool-Aid being drank by the AI folks. Even on HN, I constantly argue with people that genuinely think LLMs are some kind of magical black box that contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain. And on the other hand, I think that language interfaces are probably the n…
>contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain These are not mutually exclusive. If you have a Markov chain that 100% of the time outputs "A cat is an animal", then it has knowledge that a cat is an animal.
$ yes "a cat is an animal"
I can walk and chew bubble gum at the same time: on one hand, yes, there's certainly a lot of Kool-Aid being drank by the AI folks. Even on HN, I constantly argue with people that genuinely think LLMs are some kind of magical black box that contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain. And on the other hand, I think that language interfaces are probably the n…
>contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain These are not mutually exclusive. If you have a Markov chain that 100% of the time outputs "A cat is an animal", then it has knowledge that a cat is an animal.
I can walk and chew bubble gum at the same time: on one hand, yes, there's certainly a lot of Kool-Aid being drank by the AI folks. Even on HN, I constantly argue with people that genuinely think LLMs are some kind of magical black box that contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain. And on the other hand, I think that language interfaces are probably the n…
>contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain These are not mutually exclusive. If you have a Markov chain that 100% of the time outputs "A cat is an animal", then it has knowledge that a cat is an animal.
If I understand correctly, the meat of the argument is "that is a system for every (∀) task, there exists (∃) a setting that gives the correct answer for that one task." My understanding of this (correct me if I'm wrong) is that the scam is convincing users that GPT-X can do anything with say, the correct prompts. This argument misses the mark for me. It's not that it solves all the problems, it's that the problems i…
Earlier quoted context omitted.
>contain "knowledge" or "intelligence" or "meaning" when in reality, it's just a very fancy Markov chain These are not mutually exclusive. If you have a Markov chain that 100% of the time outputs "A cat is an animal", then it has knowledge that a cat is an animal.
I think you are operating with a different definition of "knowledge" that the parent does.
If I understand correctly, the meat of the argument is "that is a system for every (∀) task, there exists (∃) a setting that gives the correct answer for that one task." My understanding of this (correct me if I'm wrong) is that the scam is convincing users that GPT-X can do anything with say, the correct prompts. This argument misses the mark for me. It's not that it solves all the problems, it's that the problems i…
#1 it’s not clear that this ∃ ∀ construction is a fair representation of what is being ‘sold’ by GPT-x
#2 it’s also not clear what this proposed inverted formulation (∀ ∃) that describes what the author thinks GPT actually is even means. For every setting there exists a task that it answers? Does that even make sense?