There’s also PeerTube, the Fediverse counterpart to YouTube. Unfortunately, while there’s some good stuff you can find (and some re-uploads of YouTube), there’s just not as much content. I’d imagine the userbase is pretty small, too.
There’s also PeerTube, the Fediverse counterpart to YouTube. Unfortunately, while there’s some good stuff you can find (and some re-uploads of YouTube), there’s just not as much content. I’d imagine the userbase is pretty small, too.
I use a cheap VPS to host my email server. It’s a bit easier than running it solely at home, but there’s a lot of annoying work to “verify” yourself. Once you get your DNS records good, you shouldn’t be blocked after that (unlike a home server). It only costs me $5/month plus the domain, which I think is money well spent. Doing the admin work to make sure I’m secure still needs to happen, but I don’t mind that work and find it fun.
I got a laptop back in 2018, and it shipped really fast. It’s not my daily driver, but it works well when I’m on the road, and the battery life is pretty good. Granted, I replaced the OS with a distro I prefer and customized the hell out of it, so that might contribute to my experience. Tbh, I was pretty impressed with it (still am), and I was going to buy a Librem 5 when they came out. I wanted to wait and not just throw money at them because I didn’t want to get burned. After all the horror stories and crap reviews, I passed on that and won’t touch the company with a 10 foot pole, and I thank past me for not throwing money at them.
I think that the company started with noble intentions and made a decent product at first, but they got in way over their heads and now they’re floundering.
However, the name “Arthur Grand Technologies” will always be synonymous to racism.
For now. This will be memory-holed in a couple weeks. A couple grand is nothing, maybe just a slightly down quarter. They should have been completely annihilated. Crimes like this shouldn’t be fixed dollar amounts; it should be percentages of average annual gross earnings, and in this case, something like 300% annual gross earnings. Let them sell everything off.
The original paper itself, for those who are interested.
Overall, this is really interesting research and a really good “first step.” I will be interested to see if this can be replicated on other models. One thing that really stood out, though, was that certain details are obfuscated because of Sonnet being proprietary. Hopefully follow-on work is done on one of the open source models to confirm the method.
One of the notable limitations is quantifying activation’s correlation to text meaning, which will make any sort of controls difficult. Sure, you can just massively increase or decrease a weight, and for some things that will be fine, but for real manual fine tuning, that will prove to be a difficulty.
I suspect this method is likely generalizable (maybe with some tweaks?), and I’d really be interested to see how this type of analysis could be done on other neural networks.
My thoughts exactly. Growth is a byproduct of quality. Similarly, if the Fediverse grows too much and quality starts to slip, we should also let it shrink until quality comes back. I think our aim should be quality, and anything else is just a side effect.
What I think is even sadder is that even if a local small business makes a good, honest product and values consumers and employees and even if it miraculously doesn’t get decimated by cheap>quality and becomes successful. It will still get destroyed because private equity or another large soulless corporation will swoop in and make an offer the owner can’t refuse which then starts the the good business down the road of being sucked dry by the corporate vampires.
I do my best to go out of my way to patronize small businesses first, but too many times I’ve seen this happen. Every time it’s so depressing. What’s more depressing is that it really doesn’t need to be this way, and yet we continue as is.
You’re getting downvoted, but you’re right. And that is the reason that using proprietary software and SaaS is a problem. If I’m only buying the right to use a copy of something as a company sees fit, then I’m not really buying anything. I’m essentially paying a company a tribute to use their software in their way.
Decades ago, it was the same way, but it felt different. We got physical media, and we could do what we wished with the files: modify them, delete them, etc. Hell, the EULAs for some '90s and early '00s software even said you could use the software in perpetuity, and we could use software in anyway we saw fit. The biggest constraint was on selling copies. Back then, and even now, that seems pretty reasonable. (Though, as an aside, it would have been better to also get access to the source code, but I digress.)
Now, we have to use company’s software exactly how they want us to use it. Personally, I refuse to go along with this (as much as I can), so I have migrated most of my digital life to FLOSS.
Not necessarily. The Free and Libre Open Source Software (FLOSS) movement is a thing. Most of the Fediverse is FLOSS, and I doubt there’s anyone who can take Lemmy or Mastodon closed source and buy every instance and then stop pop-up instances. It does require quite a bit of work, though, so it is difficult.
I think the real challenging thing is that a great FLOSS service needs to attract attention and care. When I bring up Fediverse/FLOSS alternatives to software my friends complain about, I’m met with lukewarm-at-best reactions, generally due to networking effects (I think).
Like @Crack0n7uesday@lemmy.world said, it’s on government phones. The thinking goes that TikTok, which is a Chinese company, is exporting too much data from US government devices. In other words, the government is worried the Chinese are spying. Given the amount of data that the TikTok app actually collects, the fear is probably not unreasonable. All corporate-owned social media collects way too much data, but TikTok really is next level from what I’ve read.
I think a big difference, though, is that there is political force to ending TikTok. The US government has no major issues with Twitter, Facebook, Reddit, etc. existing. Remember, there’s actual legislation banning TikTok. Whether that makes a real difference or not, well, I guess we just wait and see. Personally, I think they all should go down in flames.
It’s not just convenient for them to do it; it’s how they are able to evade anti-trust action (not that the U.S. is great at it anyway but still). I also run my own mail server. It’s not impossible, and I wouldn’t even say it’s even hard. It’s just time consuming to set up (if it’s the first time), and there are a lot of hurdles to make it so impractical that it’s virtually impossible to the average person. Only the most patient or those who have a real desire to run their own mail server will even attempt it. Anyone can set up their own mail server, but most won’t because it’s not worth it compared to using something that just works from Google.
I agree with this in general, but you still may want to consider using Windows or Mac if there’s university only software that is Windows/Mac-based and doesn’t play nicely with VMs, which is really common in test-taking software (since it’s essentially spyware). An alternative would be dual-booting if you want to deal with that.
The reason I say this is that when I went back to school and started course work, there was an online class that mandated the use of certain test-taking software. I tried to get it to work in a VM (by masking the clues of being in a VM), and it kept shutting me down. I ultimately had to borrow a friend’s laptop to take all of my quizzes and tests, which was a real pain. Thankfully, I only had that one class like that, but any others would have driven me to get a cheap throw-away Windows-only box.
In the end, I’d stay away from bleeding-edge for school work, so Fedora is probably your better bet, but there may come a time that you will need to use Windows (much to your chagrin).
I work/study in AI, and it is completely over-hyped. For one thing, the C-suite can’t wrap it’s head around the fact that AI != LLM; they all seem to think all AI is just LLMs. On top of that, they are way too eager to throw humans out of the loop.
That said, I think LLM applications, even in their current form, are super useful in development and business practices. I myself use it to increase my productivity in coding. But, I use it as an augmentation rather than a replacement. One of my friends put it best the other day, “LLMs are like a junior dev to your senior dev. You need to be hyper-specific, and you need to check it’s output.” In other words, it’s great for off-loading some work, but it isn’t going to completely replace humans.
With that said, I’m a bit annoyed that other AI fields are being over-shadowed by LLMs. There’s a ton of other interesting work being done in those fields that is super useful and important. All of them, though, are not going to replace humans but rather augment and make humans more productive. I’ve found that an AI-Human team is most effective.
Building a signup wizard to use that information to select a instance would seem to be the best approach.
That’s actually not a bad idea. I’m not on board with mining contacts, but I think there’s a simple, transparent way to do this that can actually be fun: a personality quiz. Sure, if someone knows what instance to join already, they can override this. But if they don’t, they get like five questions, and then they are matched to an instance.
Except that scaling alone won’t lead to AGI. It may generate better, more convincing text, but the core algorithm is the same. That “special juice” is almost certainly going to come from algorithmic development rather than just throwing more compute at the problem.
I mean, that’s more-or-less what I said. We don’t know the theoretical limits of how good that text generation is when throwing more compute at it and adding parameters for the context window. Can it generate a whole book that is fairly convincing, write legal briefs off of the sum of human legal knowledge, etc.? Ultimately, the algorithm is the same, so like you said, the same problems persist, and the definition of “better” is wishy-washy.
Cool, Bill Gates has opinions. I think he’s being hasty and speaking out of turn and only partially correct. From my understanding, the “big innovation” of GPT-4 was adding more parameters and scaling up compute. The core algorithms are generally agreed to be mostly the same from earlier versions (not that we know for sure since OpenAI has only released a technical report). Based on that, the real limit on this technology is compute and number of parameters (as boring as that is), and so he’s right that the algorithm design may have plateaued. However, we really don’t know what will happen if truly monster rigs with tens-of-trillions of parameters are used when trained on the entirety of human written knowledge (morality of that notwithstanding), and that’s where he’s wrong.
Yeah, I’m in the same boat.