you discovered the importance of multiple non-associated fact checking institutions holding one another accountable :)

fiduciary duty requires that directors of corporations protect the interests of shareholders’ investments—including maximizing profits where reasonable and within the bounds of the law.

even if technically illegal on paper (which i’m not sure it is), so long as there is no enforcement or accountability, t-mobile and similar entities have literally no reason do do better. they are literally just holding up their end of the law.

in other words, this unfair treatment isn’t just one of many unfortunate flukes. it is literally baked into the system as a requirement.

only works on purpose built “Copilot” devices and looks to be disabled by default

definitely funky but not as bad as other AI moves that users didn’t get to chose whether it showed up

reading these comments i didn’t realize there was a whole subculture around teslas and how pervasive and trending toward toxic it was. wild.

thank ya!

genuine question: why call the police anyway? say the tesla driver was right and there was no compatibility. what were they thinking the rivian driver is gonna do? worst case scenario is they are gonna realize their mistake and… leave?

like how is this different from me seeing someone accidentally filling a minivan with diesel and calling the fucken cops about it? i feel there is something more malicious going on here than “a need for education” unless i am missing something.

this format of headline needs to die.

“coming to your appliances” no the hell it’s not it’s coming to appliances on the market. which you can choose to buy, or install the app onto.

feels like fatalist manipulation tactics to subconsciously get you to accept that replacing appliances every two years is normal.

also, there are absolutely other ways to regulate technology, especially since it’s a tech that’s being bought and sold.

“monitor every computer” is emphatically not the only solution ? and it’s weird that they suggested that lol

it’s not the “making one” that’s a problem. it’s the making, optimizing and rabid marketing of one in the service of capital instead of humans.

if only a bunch of open source, true non-profits released language models, the landscape might still suck but would be distinctly less toxic.

and if the government (or even a decently sized ngo standards entity) had worked proactively with computer scientists to find solutions like watermarking, labor replacement protections, and copyright protections, things might be arguably perfect. not one of those things happened and so further into the hellscape we descend.

“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.

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?

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.

what material benefit does having a cutesy representation of phrenology, a pseudoscience used to justify systematic racism, bring to this article or discussion?

they’re absolutely correct we will make all of these breakthroughs, but you dear reader? will benefit from none of them

the fact that you explained the problem doesn’t make it not a problem