When people write blog posts about how LLMs failed for some particular task, the responses from boosters invariably fall along the lines of "just use this other model/just tweak your prompt like so/you're just not skilled enough—you can't make fundamental arguments about AI by citing specific examples."
So we can't make arguments by citing specific examples, and also can't make arguments by not citing specific examples. Whelp, I guess that's the ball game.
(yes yes, I'm committing a group attribution error, but still)
I think we should investigate the backgrounds of those making claims one way or another and rely on those backgrounds for determining credibility. I suspect that we'd find that those who are saying LLMs write great, bulletproof code with "100% unit test coverage" (true story- a coworker was bragging about 100% unit test coverage) are not really qualified to be software engineers. This is a trend I have noticed in my org. Those drinking the most LLM kool aid do NOT have an engineering/comp sci degree, have relatively little experience, resumes are incredibly weak (e.g., generic stuff that we've all done as software engineers).
We no longer have the luxury of welcoming bootcamp engineers into our field with open arms. We need to protect our craft. Call these fools out or they'll keep spreading hype/FOMO.
The Supreme Court is not the ultimate decider of what the layman's document means. It was wrong when it decided, for instance, Plessy v. Ferguson. The law that the Court upheld patently violated the Fourteenth Amendment and was unconstitutional. The Supreme Court was simply wrong.
By definition, the Supreme Court does decide what is Constitutional. It doesn't decide what is right or moral, but it does, according to the Constitution, decide what laws conform to the Constitution.
That is their job, yes. But they don't always do their job, especially in a compromised government. Let's not pretend that Trump didn't stack the courts.
... yes, that's the complaint. The prompt engineering they did made it spew neo-Nazi vitriol. They either did not adequately test it beforehand and didn't know what would happen, or they did test and knew the outcome—either way, it's bad.
Do you think that Tay's user-interactions were novel or perhaps race-based hatred is a consistent/persistent human garbage that made it into the corpus used to train LLMs?
We're literally trying to shove as much data as possible into these things afterall.
What I'm implying is that you think you made a point, but you didn't.
The big digital music stores are DRM-free these days (iTunes and Amazon both are). There's also Qobuz if you want to avoid the tech giants (though most of your money ends up going to record labels, so does it really matter?).
the verge has always identified themselves as reporting on the intersection of tech and culture. sometimes that swings more towards culture than tech, but this feels completely outside technology.
A beanbag is a chair? Perhaps a chair should be something on which one can comfortably sit without breaking that has a back and four legs. I suppose then a horse would be a chair.
So we can't make arguments by citing specific examples, and also can't make arguments by not citing specific examples. Whelp, I guess that's the ball game.
(yes yes, I'm committing a group attribution error, but still)