spujb

“similar”

lol. a massive growth in real, human, users is not “similar” to a massive growth in fake undependable data with zero to negative value.

i miss when we had kept gpt unpublished because it was “too dangerous”. i wish we could have released it in a more mature way.

because we were right. we couldn’t be trusted and immediately ruined the biggest wonder of humanity by having it generate thousands to millions of articles for a quick buck. toothpaste is out of the tube now and it can never go back in.

oh interesting that could be an explanation

heartbreaking that that is the popular understanding. more people without homes = more criminals obviously! and of course the solution must be more police and enforcement! not more accessibility to homes that would be ridiculous. hashtag border crisis. (/s)

okay? so i am quite aware of all of this already; none of this info is new.

my question is still, “what’s wrong with lumping all of these technologies together as ‘AI’ when all of them are ineffective at identifying mushrooms (and certain other tasks)?”

edit: oops accidental post

what’s wrong with lumping a lot of things with different substrate together if, as you admit yourself, there’s still no evidence any of them work well?

yeah cuz what is “disorder”? i don’t even have a guess at what that is referring to

but i see media coverage of crime fearmongering all the time

edit: and USA politicians are more than complicit. they are leveraging and amplifying this narrative intentionally because it is the right wing platform of choice this election cycle.

yes!

close, more like, anybody allowing ChatGPT to be marketed as though it can answer life or death questions should be held accountable for lying to the public for profit

cough cough OpenAI cough cough

true to your name you kind of put my comment into less words, nice 👍

you have sort of a weird take on this? like here are our premises, what we know with certainty:

• all mycology apps tested to date are known to be poor (highest accuracy less than 50%)
• all LLMs are known to be fairly poor

and the author is deriving the conclusion:

• mycology apps that happen to be LLM-based have a high likelihood of being poor, so be careful

like yes, it’s not an empirical conclusion because someone still needs to do the work of testing the LLM mycology apps. i’d call it maybe an evidence based hypothesis that the average consumer should heed rather than find out the hard way and get poisoned.

but i think you condeming it as “biased,” “misinformation” or “misleading” is unnecessarily harsh. to me this looks like basic pattern recognition and forming hypotheses based on real evidence.

maybe i am missing a hole in the logic here and if so let me know.

now i have to know, was it wells fargo?

either way thanks for the laugh 😂 no hard feelings