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 they don’t matter with outrage, because of how 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”.
“illegal” is overrated, anyway. Trump did a ton of illegal stuff and yet, here we are.
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
deleted by creator
About 20 new cases of gender violence arrive every day, each requiring investigation. Providing police protection for every victim would be impossible given staff sizes and budgets.
I think machine-learning is not the key part, the quote above is. All these 20 people a day come to the police for protection, a very small minority of them might be just paranoid, but I’m sure that most of them had some bad shit done to them by their partner already and (in an ideal world) would all deserve some protection. The algorithm’s “success” in defined in the article as reducing probability of repeat attacks, especially the ones eventually leading to death.
The police are trying to focus on the ones who are deemed to be the most at risk. A well-trained algorithm can help reduce the risk vs the judgement of the possibly overworked or inexperienced human handling the complaint? I’ll take that. But people are going to die anyway. Just, hopefully, a bit less of them and I don’t think it’s fair to say that it’s the machine’s fault when they do.
I have to admit It was a solid idea, though. Dick pics should be one of the best training sets you can find on the internet and you can assume that the most prolific senders are the ones with the lowest chance of having an STI (or any real-life sexual activity).
Agree, it definitely rocks!
“Spectacular custom built oceanback, home, impressive land views & only a 5 minutes swim to the beach!”
The medical field is ripe for some intrusive ads to boost revenues! Possibilities are endless:
Ad-supported heating aids ("what were you sa… "; “this conversation will resume after a quick message from our sponsors!”)
Pacemakers - want to watch an ad for 100 more free heartbeats?
Surgery - this scar will unfortunately be in a visible spot, but how about we make the cut look like the Amazon logo ?
Implants - click the nipple and watch an ad to re-inflate your left breast for 10 more days
we are doing this, now?
printing all that paper in order to sue them probably ended up costing more than their fine
he doesn’t even make TEN billions a year? Ha, what a loser!
Just wanted to point out that the Pinterest examples are conflating two distinct issues: low-quality results polluting our searches (in that they are visibly AI-generated) and images that are not “true” but very convincing,
The first one (search results quality) should theoretically be Google’s main job, except that they’ve never been great at it with images. Better quality results should get closer to the top as the algorithm and some manual editing do their job; crappy images (including bad AI ones) should move towards the bottom.
The latter issue (“reality” of the result) is the one I find more concerning. As AI-generated results get better and harder to tell from reality, how would we know that the search results for anything isn’t a convincing spoof just coughed up by an AI? But I’m not sure this is a search-engine or even an Internet-specific issue. The internet is clearly more efficient in spreading information quickly, but any video seen on TV or image quoted in a scientific article has to be viewed much more skeptically now.
I do. Right now I’m listening to music on my phone through wired headphones. I have too many smart things already connected via bluetooth to my phone: 2 different wireless speakers, an electronic drumset, smart TV, car, fitness tracker (I’m sure I’m forgetting something) and I came to like the idea of physically plugging something in order for sound to be played through it, especially if both phone and external device are physically close to me during the whole interaction, like with a headset.
Have seen that too. The canned press release from all of them is something like "as part of our continued effort to make the org more efficient we have aggregated tram X with team Y and as a result a handful of roles were no longer needed. Our company remains focused and confident in our growth". Has AI taken over the PR department too?
From what I can see, this is not even about individual performance. It looks like a continuous game of musical chair where an entire team here and there is suddenly decimated or completely removed with non-existent internal communication.
there’s an old joke about this:
man goes to doctor saying “I keep farting, doc; my farts aren’t smelly and luckily they are also silent but I am worried because I fart all day long. Even now, as I was talking to you, I kept farting the whole time”.
“I see”, says the doctor. “I will prescribe you this pill, to be taken twice a day for a week”.
“And will that help with the farting?”
“No, but it should help you with your sense of smell. Then come to see me after one week and we’ll try to fix your hearing”
Thank you, I was just making a bad joke about OP being deleted by his creator for being an atheist. Sorry, I’ll show myself out …
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?