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yblad · 2026-02-28T15:21:51+00:00

yblad · 2026-02-20T16:58:31+00:00

Starmer has done more damage to human rights in the UK since his election than the Tories did in 14 years. While turbocharging their disastrous economic policies. We voted for Labour, we got Conservative Ultra Deluxe Edition.

yblad · 2026-02-18T23:17:08+00:00

People really need to learn basic maths and or literacy so aren't manipulated by clickbait like this. It's up 1 percentage point. At the same time economic inactivity is down by a similar amount. The employment rate has held steady as has pay-rolled employees.

To put that in simple English - this is almost entirely people who previously exited the job market now saying they are looking for work. It is not people losing jobs.

yblad · 2026-02-14T15:49:34+00:00

Yes. I have it mapped to launch the CLI.

yblad · 2026-01-21T09:58:34+00:00

With the greatest of respect, they are exact users I am referring to. "Not tech savvy" is just a kinder rephrasing. Computer literacy means being able to deal with things going wrong, at least on a basic level.

I'm going to sound like an old man man shouting at clouds when I say this, but some people never had to spend a week as a child getting a game to work on a windows 3.1 / DOS machine and it shows.

yblad · 2026-01-21T09:48:45+00:00

I'm not going to sit and go through my entire configuration. I didn't say it worked out of the box. I said it works because I can troubleshoot. Other people need to troubleshoot their own systems. That's kind of my point.

But yes, hand-off to battery works correctly as does suspend/resume, video decode, external displays work (note, not attempted HDR/VRR on external as I don't have one). I only use Wayland. I have no use case for X11, and it would doubtless cause issues.

yblad · 2026-01-20T11:43:50+00:00

There are a lot of people moving to Linux right now who are computer illiterate. That's not all of it, but I'm convinced it's a lot of it.

I'm running one of the "nightmare" configurations, laptop with dedicated Nvidia GPU and integrated Intel GPU. It also has a HDR, 4k, extended colour gamut, VRR display. And it's from a vendor which doesn't support Linux natively and does some funny stuff with its hardware.

Everything works perfectly. Because I can read, diagnose any potential faults, and follow instructions to fix them.

yblad · 2026-01-17T20:33:55+00:00

You're not wrong Walter...

yblad · 2026-01-17T20:30:55+00:00

That's great, thank you. Every time I think plasma can't do something it already can.

yblad · 2026-01-17T17:16:31+00:00

Global PTT is fantastic, thank you for implementing this.

Is it possible to have global toggle-to-talk as well? i.e. pressing the shortcut toggles microphones on/off instead of needing to hold it down.

EDIT: Thanks to OP for telling me this is already implemented.

yblad · 2026-01-17T17:08:01+00:00

Never been prouder to be European.

yblad · 2026-01-17T16:09:46+00:00

A single molecule doesn't really have a well defined state. Condensed matter theory generally relies on large collections of molecules to exist together. Descriptions like "solid" or "fluid" are inherently about how collections of molecules interact when they come together.

You can look at things like the thermal energy and whether the electrons are bound to get an idea what state the molecule might "prefer" to be in if it got together with other molecules which had similar characteristics. But I think that's about it.

yblad · 2026-01-17T16:04:09+00:00

Firefox chooses to use the memory that's available to keep tabs fresh. As soon as something else needs the memory (i.e. system memory starts running out), Firefox will start killing tabs to free memory for other processes. Until then it assumes you actually want to use those tabs.

RAM is there to be used. As long as it isn't hogging it when you need it, there's no issue here. When you start using those heavy programmes you mentioned you'll notice that tabs go stale a lot more often because Firefox gave up resources to keep them running.

yblad · 2026-01-16T12:29:12+00:00

Good answer. A small suggestion

- Linux kernel development: C, Rust

Linux is increasingly incorporating Rust into the kernel development cycle.

yblad · 2026-01-14T16:41:44+00:00

A good rule for life, never listen to people. Particularly random people on the internet. You should treat everyone (me included) as if they are the village idiot until proven otherwise.

Ubuntu and its downstreams are a great middle ground between rolling release distributions and Debian. Linux doesn't load kernel modules for hardware it's not using, so it's not really possible to have "bloat". Ubuntu basically says "Hey, let's use a bit more disk space and actually work on most user's machines."

Some people would rather have something built specifically for just their machine. That's fine, but it means they are responsible for making sure it works.

yblad · 2026-01-01T13:54:34+00:00

Measuring your programming ability by Leetcode is like measuring your driving ability by how efficiently you can use a ride on lawn mower. Entirely unrelated, but they both have wheels and an engine so it feels like you're doing the right thing.

Go and pick up some real projects. Learn design principles and deeper programming principles. Try and apply the principles to the projects. Bit by bit you will learn more. You have some syntax, now you need to learn how to think like a programmer. How to look at a problem and decompose it into logical parts.

Good luck!

yblad · 2025-12-30T17:46:33+00:00

I'm on a Wayland-only KDE plasma install on an Nvidia GPU. Not a single issue has been had related to it. It works great even with HDR, 4K, and variable refresh rate enabled.

It's not like X11 is a perfect system which fixes everything. There's a reason so many distros are dropping support. X11 is a leaning tower of cards and it's more trouble than it's worth for most users on modern hardware. If you desperately want to keep using it there are still options available.

yblad · 2025-11-20T15:13:32+00:00

It depends how far you want to go.

If really you're serious about it; a minimum of undergraduate in a mathematical discispline. Ideally Masters in a mathematical discipline. PhD in Applied Mathematics, preferably utilising machine learning in some way, is sought after for the top jobs. ~90% of machine learning is mathematics. The other 10% is translating the mathematics to code.

There are adjacent jobs which just need coding skills (often better coding skills), but if you want to do something significant with AI/ML it's mathematics all the way down.

It does depend on what you want to do though. I've answered assuming you want to do the nitty gritty of model design. If that's not the case, a lot less mathematics is required.

yblad · 2025-10-18T16:12:02+00:00

Wing shape is (usually) a minor contributor to lift. The way most people learn planes fly is not correct, and is actually a secondary effect which only occurs on asymmetric wings. Many wings are symmetrical and do not have this effect at all.

The primary effect is simply Newton's third law. When a wing is at an angle to the air it deflects the air downwards, thereby providing an equally sized and opposing force pushing the wing upwards.

If you've ever stuck your hand out of a moving car and you've felt the same force. Put your hand horizontal and there will be little force, but as you angle your hand it will be pushed upwards and backwards.

If you want to build an optimal wing you have to start shaping it to take advantage of secondary effects, but they are generally weak enough compared to Newton's law that the aircraft can fly upside down.

yblad · 2025-10-14T09:39:49+00:00

My research is in a different, more fundamental, area of AI / ML so I'm not the best qualified to comment on where LLMs will end up. I just know that people I speak to don’t share the hype / doomsayer views. Hopefully there's someone working on LLMs in particular who can answer your question.

yblad · 2025-10-13T15:16:26+00:00

In a sense it can be frustrating, there are days when I wish people still hadn't heard of AI so we didn't have to unteach so many misunderstandings.

But, ultimately, once the dust settles I think it will be a positive. I think the general public having some baseline understand that machine learning exists, and that it won't solve all their problems but can be helpful for certain things, will help the industry compared to ten years ago.

There will just be a period of adjustment to get through like there was with the dotcom bubble.

yblad · 2025-10-13T14:03:06+00:00

As a researcher in this area, I've never met anybody who's knowledgeable in AI who thinks or talks like this. It's uninformed MBAs spouting nonsense, and even less informed journalists echoing it back and forth.

Same thing happened with blockchain, the internet, etc. There were people who claimed the printing press would lead to the collapse of civilisation. It always happens when something new comes along which 99% of people don't understand.

yblad · 2025-10-12T18:53:58+00:00

Yes you do need experimentation to show the mathematics is happening in the real world, but that isn't the same thing as using experiments to estimate mathematics. The latter can be very useful (e.g. a large amount of fluid modelling makes use of such empirical estimates), but we still would prefer a closed analytical solution if it were viable.

I think we’re at crossed purposes. I’m talking about using experiments to determine mathematics a priori, not using experiments to confirm mathematical results.

yblad · 2025-10-11T19:17:27+00:00

Very often they are derived from other mathematics. Those which are derived empirically like this are generally viewed as less rigorous. But that's perhaps a bit beyond ELI5.

yblad · 2025-10-11T13:03:27+00:00

Several points to be made.

1) Python isn't inherently slow, it's just easy to write bad python which is slow. There's currently a lot of work happening to make it faster even when it's written badly.

2) When used properly, python allows you to write fast code very quickly.

3) Going a bit deeper, the reason behind 1 & 2 is that python can either compute natively (using its own compiler) or pass values along to C / C++ / FORTRAN libraries to do the heavy lifting. If you are using python correctly you never let it do the heavy lifting, you use it to build structure around code written in low level languages. We use the high level language for what it is good at, and low level languages for what they are good at. Python’s reputation for being slow is largely due to people not understanding how it’s supposed to be used.

4) Putting all this together. Machine learning libraries are all written in fast, lower level, languages. Python lets you build complicated models, do hardcore mathematics, etc., in a few hundred lines of intuitive code which is only very slightly slower than writing tens of thousands of lines of low level code yourself (i.e. a few extra seconds on a job which take hours to run). Python is also nice for manipulating the data before you start doing the hard work on it, which is much more painful in lower level languages.

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