Unfortunately, you still need a level of trust with Proton. Even aside from trusting that they will not bend to pressure to terminate your service, you’re also trusting them with your network of contacts, because metadata (including the sender, recipient, and subject line) are not end-to-end encrypted in Proton.
Just wear disposable faces.
You humans wear the same face your entire life and then get upset when people recognize it?! Get over yourself! Aside from the obvious privacy issue, let’s be real: it’s also gross.
That can’t be good. But I guess it was inevitable. It never seemed like Arc had a sustainable business model.
It was obvious from the get-go that their ChatGPT integration was a money pit that would eventually need to be monetized, and…I just don’t see end users paying money for it. They’ve been giving it away for free hoping to get people hooked, I guess, but I know what the ChatGPT API costs and it’s never going to be viable. If they built a local-only backend then maybe. I mean, at least then they wouldn’t have costs that scale with usage.
For Atlassian, though? Maybe. Their enterprise customers are already paying out the nose. Usage-based pricing is a much easier sell. And they’re entrenched deeply enough to enshittify successfully.
Why? It’s Japanese and your browser should display it as マリウス. But I don’t know what that means.
Yeah, that’s true for a subset of code. But for others, the hardest parts happen in the brain, not in the files. Writing readable code is very very important, especially when you are working with larger teams. Lots of people cut corners here and elsewhere in coding, though. Including, like, every startup I’ve ever seen.
There’s a lot of gruntwork in coding, and LLMs are very good at the gruntwork. But coding is also an art and a science and they’re not good at that at high levels (same with visual art and “real” science; think of the code equivalent of seven deformed fingers).
I don’t mean to hand-wave the problems away. I know that people are going to push the limits far beyond reason, and I know it’s going to lead to monumental fuckups. I know that because it’s been true for my entire career.
If I’m verifying anyway, why am I using the LLM?
Validating output should be much easier than generating it yourself. P≠NP.
This is especially true in contexts where the LLM provides citations. If the AI is good, then all you need to do is check the citations. (Most AI tools are shit, though; avoid any that can’t provide good, accurate citations when applicable.)
Consider that all scientific papers go through peer review, and any decent-sized org will have regular code reviews as well.
From the perspective of a senior software engineer, validating code that could very well be ruinously bad is nothing new. Validation and testing is required whether it was written by an LLM or some dude who spent two weeks at a coding “boot camp”.
XMPP is still around! Despite Google’s best efforts to kill it.
The “free market” solution is for malpractice suits to be so ruinously expensive that insurance companies will apply sufficient pressure to medical practices to actually do their fucking jobs.
Same in the legal field, plus we should see a wave of disbarments already.
I’m not holding my breath. AI is shaping up to be history’s greatest accountability sink and I’ve yet to see any meaningful pushback.
All major browser engines are FOSS.
Chrome and Edge are proprietary wrappers around Chromium (BSD license). Firefox and derivatives are FOSS (Mozilla Public License). Safari is built around WebKit (LGPL/BSD).
The problem, however, is governance. These projects are all too big for anyone to realistically fork and maintain independently. So in practice, they are under control of Google, Mozilla, and Apple — all of which have questionable priorities (especially Google).
Wireless card readers are relatively new tech. I see them more and more as time goes on. New places usually give their waitstaff mobile readers, but there’s little motivation for older restaurants to upgrade their whole POS systems. POS systems have pretty long life expectancy. At least the older ones do.
Nobody should feel a strong need to upgrade after only two generations. Same deal with most tech like GPUs and CPUs.
I use my phone a lot and my Pixel 7 is fine. The primary factors driving my last couple upgrades were battery degradation and software support. Neither should be a big problem with a Fairphone.
I’m also trying to decide whether to stick with the Pixel/GrapheneOS ecosystem or go for Fairphone.
How hard/expensive was it to replace your battery? I looked on iFixIt and it seemed a lot harder than my orevious phones.
Ring was an obvious trojan horse from day 1. It’s depressing how many people are only just realizing this, and how many people still don’t even give a shit.
If you have a Ring camera, you are a scourge to your entire community.
This is true almost every time someone says “but without <obviously unethical thing>”, these businesses couldn’t survive! Same deal with all the spyware that’s part of our daily lives now. If it’s not possible for you to make a smart TV without spying on me, then cool, don’t make smart TVs.
If your business model crumbles under the weight of ethics, then fuck your business model and fuck you.
If you like hiking, you might also enjoy indoor rock climbing. It’s more social and fun than a gym and you will have the opportunity to interact with a lot of the same people repeatedly. You might even have some beginners groups in you area to get started. Meetup.com is good for finding groups like that.
Good luck out there!
This is the clearest sign to me that Apple has jumped the shark.
Apple has a long history of waiting until they could do something right rather than rushing to market with some fad. And here they are tripping over themselves to ship something that is obviously half-baked (at best). There’s no vision, there’s no attention to detail, there’s no careful UX design. It’s just “oh shit we need AI right?”
SEO (search engine optimization) has dominated search results for almost as long as search engines have existed. The entire field of SEO is about gaming the system at the expense of users, and often also at the expense of search platforms.
The audience for an author’s gripping life story in every goddamn recipe was never humans, either. That was just for Google’s algorithm.
Slop is not new. It’s just more automated now. There are two new problems for users, though:
Well I’m sorry, but most PDF distillers since the 90s have come with OCR software that can extract text from the images and store it in a way that preserves the layout AND the meaning
The accuracy rate of even the best OCR software is far, far too low for a wide array of potential use cases.
Let’s say I have an archive of a few thousand scientific papers. These are neatly formatted digital documents, not even scanned images (though “scanned images” would be within scope of this task and should not be ignored). Even for that, there’s nothing out there that can produce reliably accurate results. Everything requires painstaking validation and correction if you really care about accuracy.
Even ArXiv can’t do a perfect job of this. They launched their “beta” HTML converter a couple years ago. Improving accuracy and reliability is an ongoing challenge. And that’s with the help or LaTeX source material! It would naturally be much, much harder if they had to rely solely on the PDFs generated from that LaTeX. See: https://info.arxiv.org/about/accessible_HTML.html
As for solving this problem with “AI”…uh…well, it’s not like “OCR” and “AI” are mutually exclusive terms. OCR tools have been using neural networks for a very long time already, it just wasn’t a buzzword back then so nobody called it “AI”. However, in the current landscape of “AI” in 2025, “accuracy” is usually just a happy accident. It doesn’t need to be that way, and I’m sure the folks behind commercial and open-source OCR tools are hard at work implementing new technology in a way that Doesn’t Suck.
I’ve played around with various VL models and they still seem to be in the “proof of concept” phase.
For instance, Mozilla said it may have removed blanket claims that it never sells user data because the legal definition of “sale of data” is now “broad and evolving,” Mozilla’s blog post stated.
Uh huh.
The company pointed to the California Consumer Privacy Act (CCPA) as an example of why the language was changed, noting that the CCPA defines “sale” as the “selling, renting, releasing, disclosing, disseminating, making available, transferring, or otherwise communicating orally, in writing, or by electronic or other means, a consumer’s personal information by [a] business to another business or a third party” in exchange for “monetary” or “other valuable consideration.”
Yes. That’s what “sale of data” means. Everybody understood that. That’s exactly what we don’t want you to do.
The experience of installing and updating GPU drivers can be very different across different distros. Especially if you use secure boot. This was such a pain point for me on Tumbleweed that I just pinned my kernel.
I was about to say this.
If they can’t give me a callback number that is publicly listed on their web site, then they’re most likely a scammer.
With Google, however, this is a scarier proposition than with most companies. If someone from my phone company, or my bank, or my insurance company called me, I could very easily call the actual company and talk to a human to confirm. I have no idea how I could ever talk to a human at Google. I’m not sure they even have a public phone line.