The car industry went through something similar seemingly ages ago. The Japanese (Toyota mostly) aligned processes such that average or even mediocre operators would result in quality cars. The American and European car industries traditionally based their setup on highly qualified people with a brain and brilliant people developing things. When they realised they couldn't scale and had trouble finding highly qualified people, they tried to solve things by going on the hunt for more brilliant engineers.

Fast forward to today and the whole world is getting their processes right.

You seem to think that it's a plus to have high requirements for software developers, Greg KH sees in his reality that it makes more sense to lower the threshold.

You're completely right if the amount of work that needs doing is exceeded by the available qualified resources. Otherwise, your way will be limited to not achieve the goals or break in other ways.

Problem is, no way to be sure if that story was actually AI slop with hallucinated numbers... It might be over 95% already.

Thanks a million, I'll have to do a bit of reading to catch up there. Your link is but the start.

Thanks a lot for the information. I don't see the single litho for the whole stack in there, though I couldn't read the IEEE link (haven't had access in ages) and just browsed the other two, just enough to read that they talk about stacking fully developed silicon. Do you have a link for that single exposure for nand 3d flash?

If by 3D the idea that more devices are stacked for a higher density, that actually won't help. It's not wafer material that is in short supply, it's fab capacity. And for such (imaginary) stacked devices wafers, the production run would just have more litho processes, so you still don't get really more out.

Just connect your smartphone. Over USB-C, with a docking station, taking the display output from the phone, putting it on HDMI which then gets connected to the not so smart TV. You did get a phone with display out, right?

That reminds me of a colleague who was doing a PhD parallel to working, and another colleague asked how his MBA was going, to which he answered: "why would I do an MBA? They make you dumber... "

The reason Redhat and others chose Gnome was due to licensing issues of QT way back when, and apparently they didn't get back from that.

I fail to see the relevance, I take 5 minutes on any fresh KDE installation and it behaves exactly the way I want, minus the things that have been undone since KDE 3 for reasons (virtual desktops with a different backdrop on each, for instance), which no other major system can do.

I don't know what UI things I should beg the KDE team to improve, I'm not aware of any glaring things. Do you have any examples?

When my kids were small, I got a new phone number, but out of a selection I chose one that had meaning to me, not the easier one that my wife told me to take. (She got that one.... Long story... Not doing that again...)

So in reverse social engineering, to get my kids to remember that somewhat harder number, I configured the family tablet to have that as a passcode. What do you know, it took the kids about a day and they had it memorized. Hmmm, I'll have to check if they still remember...

Wow, a Gnome fan...! Still have to meet one in real life, but even online they're not plentiful except in the usual places. Or are you a dev?

I've used Linux professionally, on the desktop, and literally everybody and his dog around me also switched to KDE due to not getting along with Gnome, which was the default (Redhat). We didn't get offered many other choices, but boy were we glad we could get away from Gnome.

In terms of usability, I think the KDE defaults are okay, but with some tweaks, KDE surpasses all of the most used ones (Windows, any version, and MacOS, at least the ones I've seen). It starts with focus follows mouse and goes on from there...

Right, then, let me raise that to "Gobbledybook".

AI is great for things you know a bit about, it can fill in the gaps. It's not a true expert, so all experts try to tone down the hype.

Essentially, since LLMs are trained on data that has a level often somewhat above the average (stack exchange and such) people who would need loads of searches can be more effective with AI. This group typically includes the bosses.

The specialists who read the most liked answer on stack exchange (and such) and go, yes, but also X y z, and if it were slightly different, the answer z would be the way to go, etcetera, won't really benefit that much from AI. Or sometimes be hampered or slowed down, unless they find ways where AI can support their tasks.

So there are two different situations. Whenever you're in the first, go for it, but question the results. In the second, you don't really need my advice, just that you should regularly check if AI skills have improved to do more for you yet.

Anyway, if bosses have mediocre workers, AI might be a benefit. I've rarely experienced bosses who knew who their good staff were and who were just liked.

Please correct me if I'm wrong, but I thought this social game called Slashdot was supposed to be played without reading the summary? You're literally admitting to, and advocating, cheating! Shame on you!

Your response seems the best place for me to add my story of a few weeks ago, about one of my first interactions with Claude.

The topic was something language related, which I used before as a litmus test for AI.

At some point, Claude calculated that its answers weren't what I was looking for. It then started to, seemingly, insinuate that it had hunches, feelings about where the answer might be, ideas about me having more answers, etcetera.

I was very close to accepting that, wow, Claude is an intelligent being.

Then it dawned on me. So I asked, is it programmed to answer to my questions in a specific way. And indeed, it bluntly stated that its answers aren't answers to my questions but cooked up word salads that are aimed at keeping my interest and engagement.

It's apparently the case that plenty of training data is about academics mulling ideas and trying to keep their discussion partners engaged.

Which then the AI just mimicks, as it's programmed to do. But it comes across as more humble and human, instead of the sycophantic, self assured, idiotic semi savant. An easy thing to fall for.

Great how you turned the ambiguity into the other direction, well played!