You seem to have the assumption that they’re not. And that “helping society” is anything more than a happy accident that results from “making big profits”.

It’s not an assumption. There’s academic researchers at universities working on developing these kinds of models as we speak.

Are you asking me whether it’s a good idea to give up the concept of “Privacy” in return for an image classifier that detects how much film grain there is in a given image?

I’m not wasting time responding to straw men.

It’s a statistical model. Given a sequence of words, there’s a set of probabilities for what the next word will be.

That is a gross oversimplification. LLM’s operate on much more than just statistical probabilities. It’s true that they predict the next word based on probabilities learned from training datasets, but they also have layers of transformers to process the context provided from a prompt to eke out meaningful relationships between words and phrases.

For example: Imagine you give an LLM the prompt, “Dumbledore went to the store to get ice cream and passed his friend Sam along the way. At the store, he got chocolate ice cream.” Now, if you ask the model, “who got chocolate ice cream from the store?” it doesn’t just blindly rely on statistical likelihood. There’s no way you could argue that “Dumbledore” is a statistically likely word to follow the text “who got chocolate ice cream from the store?” Instead, it uses its understanding of the specific context to determine that “Dumbledore” is the one who got chocolate ice cream from the store.

So, it’s not just statistical probabilities; the models’ have an ability to comprehend context and generate meaningful responses based on that context.

If enforcement means big tech companies have to throw out models because they used personal information without knowledge or consent, boo fucking hoo

A) this article isn’t about a big tech company, it’s about an academic researcher. B) he had consent to use the data when he trained the model. The participants later revoked their consent to have their data used.

How is “don’t rely on content you have no right to use” litteraly impossible?

At the time they used the data, they had a right to use it. The participants later revoked their consent for their data to be used, after the model was already trained at an enormous cost.

ok i guess you don’t get to use private data in your models too bad so sad

You seem to have an assumption that all AI models are intended for the sole benefit of corporations. What about medical models that can predict disease more accurately and more quickly than human doctors? Something like that could be hugely beneficial for society as a whole. Do you think we should just not do it because someone doesn’t like that their data was used to train the model?

There’s nothing that says AI has to exist in a form created from harvesting massive user data in a way that can’t be reversed or retracted. It’s not technically impossible to do that at all, we just haven’t done it because it’s inconvenient and more work.

What if you want to create a model that predicts, say, diseases or medical conditions? You have to train that on medical data or you can’t train it at all. There’s simply no way that such a model could be created without using private data. Are you suggesting that we simply not build models like that? What if they can save lives and massively reduce medical costs? Should we scrap a massively expensive and successful medical AI model just because one person whose data was used in training wants their data removed?

The anecdote proves nothing because the model could potentially have known of the McGonagal character without ever being trained on the books, since that character appears in a lot of fan fiction. So their point is invalid and their anecdote proves nothing.

I’m still calling it Twitter because it will piss off Elon Musk if everyone keeps calling it Twitter and I think that’s funny.

Just want to say that this is a fantastic answer. Pay attention to the parts about printing/downloading stuff. There are huge parts of America where you won’t get a reliable cell signal sometimes for hours.

I mean, they need to ramp it way faster. It’s pretty garbage right now and there’s really no excuse. Compare it to Lemmy and it’s very obvious. Lemmy still has problems, but it’s much easier to use and has way fewer bugs and glitches. If you’re used to Reddit, then switching to Lemmy is pretty easy to do, and I can see average users making that jump. But Mastadon isn’t even close to the user experience that Twitter/X offered, and I cannot see the average Twitter user sticking around and waiting for all the issue to be fixed.

It won’t last unless Mastadon gets some serious improvements. It’s buggy, glitchy, feature-poor, and confusing to use. There’s no way in its current state it’s going to compete with the big guys for the average person’s attention.

I wouldn’t say that pirating is user-friendly, only that it can be more user-friendly than logging into and searching through multiple streaming services. That of course pre-supposes that you have some knowledge of how to torrent and where to find torrent files.

The problem with removable batteries is that you sacrifice water-proofness. That’s why iPhone batteries aren’t removable: Apple found that, on average, people prefer a water-proof phone over a replaceable battery. If you make the battery to removable, you can’t use sealants anymore, you’re just relying on a gasket.

Personally, I would rather have a phone that can handle being dropped in a sink full of dishes and am happy to pay $80 every 3 years to have the battery swapped.

I pay for Hulu, Max, Disney+, Prime, and get Netflix for free. Half the time, I still can’t find the show or movie I want to watch. But 99.99% of the time I can find a torrent for it within 20 seconds of searching. Not only is pirating cheaper, but it’s more convenient and more user friendly these days.

That’s a bit over the top. The app only has access to the data you give it permission to access. So TikTok may have access to your contacts (don’t give TikTok access to your contacts, guys), but it won’t have access to your text messages or activity data.

If 100% safety is your criteria, then humans shouldn’t be allowed to drive. Humans suck at it. We’re really, really bad at driving. We get in accidents all the time. Tens of thousands of people die every year, and hundreds of thousands are seriously injured. You are holding self-driving cars to standards that human drivers could never hope to meet.

Their assumptions about what the car can or will do without the need for human intervention makes them an insane risk to everyone around them.

Do you have statistics to back this up? Are Teslas actually more likely to get into accidents and cause damage/injury compared to a human driver?

I mean, maybe they are. My point is not that Teslas are safer, only that you can’t determine that based on a few videos. People like to post these videos of Teslas running a light, or getting into an accident, but it doesn’t prove anything. The criteria for self-driving cars to be allowed on the road shouldn’t be that they are 100% safe, only that they are as safe or safer than human drivers. Because human drivers are really, really bad, and get into accidents all the time.

This same concept is why you can’t make a 100% safe self driving car. Driving safety is a function of everyone on the road. You could drive as safely as possible, but you’re still at the mercy of everyone else’s decisions. Introducing a system that people aren’t familiar with will create a disruption, and disruptions cause accidents.

Again, we don’t need a 100% safe self driving car, we just need a self driving car that’s at least as safe as a human driver.

I disagree with the premise that humans are entirely predictable on the road, and I also disagree that self driving cars are less predictable. Computers are pretty much the very definition of predictable: they follow the rules and don’t ever make last minute decisions (unless their programming is faulty), and they can be trained to always err on the side of caution.

I don’t think we should prosecute the programmer, but I do think the manufacturing company should be liable.