Description of the author at the end of the article had me howling. I’ll just leave it here for y’all to enjoy.

Amanda Caswell is the AI Editor at Tom’s Guide and one of today’s leading voices in AI and technology. A celebrated contributor to various news outlets, her sharp insights and relatable storytelling have earned her a loyal readership. Amanda’s work has been recognized with prestigious honors, including outstanding contribution to media. Known for her ability to bring clarity to even the most complex topics, Amanda seamlessly blends innovation and creativity, inspiring readers to embrace the power of AI and emerging technologies. As a certified prompt engineer, she continues to push the boundaries of how humans and AI can work together. Beyond her journalism career, Amanda is a long-distance runner and mom of three. She lives in New Jersey.

Or press Ctrl-S and take a nice walk outside

Just remember that lifetime means Plex’s lifetime, not yours.

True, but I’ve noticed that as a change in my personal circle, and as a recent change among people who acted different before becoming heavy AI users. I find it difficult to describe the effect, it’s like a disassociation with their surroundings like what supposedly happens when people join a cult. Quite suddenly it becomes very difficult to get through to them. It’s weird and scary.

I’ve seen people become more introverted and unable to participate in an open discussion. They bring an opinion but refuse to reason with actual arguments. If that doesn’t work out for them (it never does) they are offended and leave. Very odd behaviour.

I switched from Kubuntu to CachyOS last week, after 10 years or so. CachyOS is based on Arch, and did not disappoint so far, extremely fast, makes Ubuntu look old and sluggish. It’s really impressive. The basic installation was easy. The GUI package manager isn’t as polished but works. A little bit of terminal tweaking was required to install some packages (VMM and KRDC gave me some trouble) but the documentation was ok. Absolutely can recommend.

A little bit of reverse psychology might help in breaking the cycle.

Instead of obsessing over the things you think you should do, give yourself a task that is simply to try and do absolutely nothing. For example, go to a park, sit on a bench and do nothing. Drive to a mildly interesting, quiet place. Just observe. Watch the people passing by, the ducks in the pond drifting aimlessly about. Note how the trees are moving in the wind…

Do not use your smartphone. Don’t read or listen to music. No distractions. Whenever your mind goes back to unpleasant thoughts about what you “should” be doing, gently remind yourself that your only task right now is to do absolutely nothing. Just observe. You don’t have to enjoy it, so don’t stress yourself about it not being fun.

This can be very hard in the beginning. It might seem boring and pointless, and there will be a nagging feeling that you ought to do something instead. Let it go.

If you do this every day for at least an hour (ideally as long as possible), you’ll get used to being just fine in that moment. You might notice that the world just goes on whether you do something or not, and that’s fine. Your task is to sit here and do nothing. Take it seriously. It is important to remind yourself about that whenever the thoughts are bubbling up again. Let them go for the moment, it’s not the right time. You have a job to do and that is… doing nothing.

After a few weeks (or months, in my case) you will become good at really doing nothing, and initial boredom gives way to genuine calm. And this will enable you to have an intrinsic motivation to do something again, on your own terms.

You could still be identified by a lot of factors and the combination of those. IP address, email if provided, cookies + referrer on clicked links or loaded external images, browser fingerprint, clues from actual content in comments and posts, … It’s not that hard, a whole industry lives on this kind of surveillance data collection.

While this is good advice it only addresses the sender’s perspective of communication. What’s missing is how to deal with people who communicate with malicious intent. You’ll wear yourself out quickly on social media if you don’t learn how to protect yourself against that, and “THINK” is only half of the equation

Not OP, but the votes being public (not only on comments but also on posts) make it really easy for someone with malicious intent to generate a profile on your interests, political and sexual orientation, health/mental issues, addictions and so on. It’s a goldmine of data that should be protected.

I had a similar situation yesterday, albeit not with 26.04, but the previous version. After a regular update it reverted to software rendering. What fixed it was selecting the non-open Nvidia driver with “sudo software-properties-qt”. Initially the options were greyed out, this was fixed by removing all old Nvidia drivers, and then “sudo ubuntu-drivers install”. The default open driver stopped working for some reason.

That happens when you think you don’t need experienced software devs any more, because the AI can do everything now. A seasoned developer/devOp/admin would have known that the production environment needs to have different credentials from staging and these need to be protected. If that is not possible with railway then it’s simply not a good product to use and (again) a good dev/admin would have seen this in the initial evaluation phase. Not preventing AI access to the production environment from the start is the third grave mistake. However, there’s none of it in the “lessons learned” section of the article. You have learned nothing and are bound to repeat your mistakes.

How bizarre. That’s actually a thing. I’ve read the following quote in another article about tokenmaxxing:

“Scaling compute along with data can increase the size, complexity and therefore value of the result,” said Brian Verkley, director of AI data strategy at VAST Data. “A token represents generated business value. Therefore, I expect business value per token to continue to rise, along with AI usage.”

WTF, dude. Size and complexity does not equal value. You can shit out a massive dump of unmaintainable garbage code that has zero value. Incentivising your devs to like that will only produce exactly that, a massive amount of garbage.

And using a token only represents immediate business value for the providers of the AI, not for the consumer of the token. If the price payed for the token isn’t covering the costs then it’s not even a lot of value for the AI provider, apart from usage stats.

This is a doomsday cult.

Good analogy. I’m gonna steal that :D

I don’t doubt that it is possible to create good code when focusing on programming best practices etc. and taking the time to check the AI output thoroughly. Time however is a luxury most of the devs in those companies don’t have, because they are expected to have a 10x code output. And thats why the shit hits the fan. Bad code gets reviewed under pressure, reviewers burn out or bore out and the codebase deteriorates over time.

This approach to coding is exactly what creates the problem. They will find out the hard way if they can continue to be productive when something breaks and AI is not available for whatever reason. Does anyone know how to fix it? Is the documentation sufficient to understand what the AI did?

It’s just “Copilot” for everything in Windows these days

Dein letzter Punkt wird von Atomkraftbefürwortern häufig und gern übersehen. Z.B. die enormen Rückbaukosten veralteter Kraftwerke. Die Rechnung geht dann nicht mehr auf. Der Lobby ist das allerdings egal, weil sie darauf baut die Gewinne (Bau und Betrieb) zu privatisieren und die Verluste (Rückbau und Lagerung radioaktiven Materials) zu verstaatlichen.

Like a digital piñata

Well… Given that the average person neither knows what data they are effectively giving US and Chinese companies, nor does anything against it, this poll is asking the wrong questions. Massive amounts of data collected for every single individual via ad-based surveillance (US) and IOT devices phoning home (China) is the reality we live in today. But the average person does not know about it and therefore can’t even grasp what is done to them. They don’t trust them, but they hand over the data anyway. This is basically a poll amongst cows in the slaughterhouse.