No, of course a broken spar is A Very Bad Thing when it happens in midair.

Is this changing-the-timing-chains-in-an-Audi difficult, or is this replacing-your-spinal-cord-without-killing-you impossible?

Are these planes repairable? I think it's a reasonable question.

(Of course, with the Audi, if has anything more than a loose gas cap it's not economically feasible to repair, but that's what you get with European engineering.)

Woah... Dumb question, but would a wing spar be repairable or replaceable?

May be true, but 100% irrelevant. Trademark infringement claim seems very clear cut to my non-lawyerly eyes.

A lot of the audio production in individual videos is really bad. This isn't anything to do with YouTube per se, not their compression algorithms or other features. A lot of YouTubers have absolutely no concept of microphone placement, of using audio compression, of reducing background noise. All of which are things which will drastically affect audio quality and the ability of a speech-to-text model to create subtitles.

It would be nice if YouTube would normalize all the uploaded videos to one set standard. Note I'm not suggesting that they compress the videos as that might change the intended presentation of professional audio productions. I just mean peak-finding normalization which could be implemented losslessly and without breaking existing video links.

Having said that, when I look at my own channel - and I am not claiming to have great audio; I have a host which would destroy a lavalier microphone in mere seconds. YouTube's subtitling is really good. It automatically switches between English and French and Hebrew, and even with a fair bit of background noise (welding, grinding, cooking, crowd noise, music) it generally gets the text correct. So I don't know what the original complaint is, except that it's not perfect. Well, guess what, neither is human hearing. How about that famous Jimi Hendrix line, "Excuse me while I kiss this guy."

Side mirrors almost always leave a large blind spot directly behind and close to the vehicle. There's a reason that when firefighters are reversing their appliances they always have at least one of the crew physically get out and watch the area behind the vehicle.

Even a rear window and rear view mirror almost always leave a significant blind spot low and close behind the vehicle, which is why reversing cameras became a thing. When they're done well, they really are significantly safer, as well as sometimes making it a lot more reliable for most people to park the vehicle in difficult spaces.

One of the modern innovations I really would like to have is full AR on my windscreen. I want unexpected hazards highlighted in real time, particularly those that are more easily detectable by non-visual sensors, like big potholes or animals obscured by vegetation near the side of a country road. I want the actual driving line I need to take to follow my planned route through complex junctions overlaid slightly on my view of the road ahead. I want light amplification for night driving, ideally combined with some other technology that can reduce the glare from oncoming headlights to prevent dazzle.

Although I only want all of this if (a) it's implemented well and (b) any additional data it uses is reliably up-to-date and (c) there's an emergency shut-off that instantly clears everything off the windscreen in case anything goes wrong.

Don't worry. You probably have funky modern door handles that don't work when the power goes out anyway. Not that the power in an EV is likely to go out if it's underwater or on fire or anything.

Oh, don't be silly. Next you'll be making even more absurd claims, like that car theft was already a solved problem 20 years ago thanks to immobilisers, or that having separate physical controls for essential functions that you can find and use without taking your eyes off the road for several seconds to mess around with a touchscreen is safer, or that no-one ever hacked 100,000 cars at once from 1,000 miles away back when they didn't have always-on remote connectivity and allow OTA updates to their essential control systems.

Yes, as long as you're the one in the big, heavy car, it's great. Shame if you're the kid it's reversing over though.

Do you ever use reverse gear? What's behind you is pretty important when you're going backwards...

Yes, Apple's shared RAM model really works for them in the context of running LLMs locally. It's a huge advantage. As you say, not much use for those running other platforms, though.

I'm impressed that anyone can afford a new development PC in 2026. I'd need a second mortgage with the price of the RAM, SSD and GPU these days!

Google learned to embrace, extend and extinguish right out of Microsoft's playbook. They were excellent students and you can see the results in how email and web "standards" work today.

The difference is that when Microsoft did it the authorities eventually started getting in their way to promote more openness and competition again. So far there is little sign that anyone intends to challenge the way a few tech giants have recently been capturing long-established standards that we rely on for what have become vital services and effectively taking ownership for their own purposes. The governments and their regulators are either asleep at the wheel or, if you're a bit less trusting, bought and paid for.

Do you often use VeraCrypt on a company-managed device? I'm sure if you do then it's with the knowledge and consent of your IT department and they'll be responsible for managing any consequences of the VeraCrypt issue according to their official policy as well.

Yes. So far, the LLM tools seem to be much more useful for general research purposes, analysing existing code, or producing example/prototype code to illustrate a specific point. I haven't found them very useful for much of my serious work writing production code yet. At best, they are hit and miss with the easy stuff, and by the time you've reviewed everything with sufficient care to have confidence in it, the potential productivity benefits have been reduced considerably. Meanwhile even the current state of the art models are worse than useless for the more research-level stuff we do. We try them out fairly regularly but they make many bad assumptions and then completely fail to generate acceptable quality code when told no, those are not acceptable and they really do need to produce a complete and robust solution of the original problem that is suitable for professional use.