Most things to do with Green Energy. Don’t get me wrong, I think solar panels or wind turbines are great. I just think that most of the reported figures are technically correct but chosen to give a misleadingly positive impression of the gains.
Relevant smbc: https://www.smbc-comics.com/comic/capacity
I think he means “I will give you a child, choose any of them. I don’t know where to put them any longer and they don’t even seem to like me.”
and Trump would just… “your beer? Haven’t seen it. There’s just MY two glasses of beer here. A great beer, the greatest. My uncle invented beer, Fred Budweiser Trump. Great IQ, very good genes!”
like sending Vance literally following her around?
laugh all you want, but YOU are next, former Twitter users who refused to pay for their blue badge and had the gall to move to Mastodon or others!
yes, that was all completely wrong. If Trump had been the one on top of the building and had fallen down (maybe accidentally hitting a stray bullet on his way down)… now THAT would have been closer
I think they don’t matter with outrage, because outrage explodes in ways that are hard to predict. I mean, I can see the problem with the ad now that it has been pointed out to me. After reading about it repeatedly, I now find it bad and ridiculous and what were they thinking? But at a first look, as a test audience I would have probably rated it as “meh, ok”.
It is about fragility, like others said, but It is also about uniqueness, in the sense of “oh, so you think you’re soo special!”
to be fair, he did turn orange
“illegal” is overrated, anyway. Trump did a ton of illegal stuff and yet, here we are.
ah I get what you’re saying., thanks! “Good” means that what the machine outputs should be statistically similar (based on comparing billions of parameters) to the provided training data, so if the training data gradually gains more examples of e.g. noses being attached to the wrong side of the head, the model also grows more likely to generate similar output.
I think you just found a good example to prove his point, though?
AKA “shit, looks like now we need to re-hire some of those engineers”
TBH those same colleagues were probably just copy/pasting code from the first google result or stackoverflow answer, so arguably AI did make them more productive at what they do
I only have a limited and basic understanding of Machine Learning, but doesn’t training models basically work like: “you, machine, spit out several versions of stuff and I, programmer, give you a way of evaluating how ‘good’ they are, so over time you ‘learn’ to generate better stuff”? Theoretically giving a newer model the output of a previous one should improve on the result, if the new model has a way of evaluating “improved”.
If I feed a ML model with pictures of eldritch beings and tell them that “this is what a human face looks like” I don’t think it’s surprising that quality deteriorates. What am I missing?
see? It says it right here: “that thing you just did”
don’t be like that, they are just saying that the two events happened at the same time. “Kamala Harris grins as the world marks new hottest day on record”, “Kamala Harris grins as hundreds more flights get cancelled after huge IT outage”. See? Perfectly innocent journalism!
I’m not sure we, as a society, are ready to trust ML models to do things that might affect lives. This is true for self-driving cars and I expect it to be even more true for medicine. In particular, we can’t accept ML failures, even when they get to a point where they are statistically less likely than human errors.
I don’t know if this is currently true or not, so please don’t shoot me for this specific example, but IF we were to have reliable stats that everything else being equal, self-driving cars cause less accidents than humans, a machine error will always be weird and alien and harder for us to justify than a human one.
“He was drinking too much because his partner left him”, “she was suffering from a health condition and had an episode while driving”… we have the illusion that we understand humans and (to an extent) that this understanding helps us predict who we can trust not to drive us to our death or not to misdiagnose some STI and have our genitals wither. But machines? Even if they were 20% more reliable than humans, how would we know which ones we can trust?