Except for, you know, the people we fired.

Yeah! Just pick out all the helium atoms, one by one, and you're done!

While this is true, being the subject of an experiment to see what happens when you do that is not something most people would choose for themselves. It's not *irrational* to be concerned. Absence of evidence on a largely unexplored question like microplastic infiltration in human bodies is not the moral equivalent of absence of evidence in an extensively studied question like a vaccine-autism link.

What people? I'm trained for LaTeX and markdown. Pandoc for conversions. Who are these people who only use software that can't track a heading number reliably?

RAID5 is at the disk level. What about files that lay around on USB sticks or cloud drives? Those need some FEC love too.

While it's true every issue has its own dimension, even if those dimensions are linearly independent, they're not necessarily orthogonal. Independent basis vectors can still have a non-zero dot product—in other words, issues which are distinct from each other can align to some degree.

If it's not clear, the data reordering spreads block errors across many blocks, so long runs of errors turn into multiple individual bit errors that are handled efficiently by the code. The Golay part of the concatenated code mops up these. The RS part deals with larger blocks.

RS is well suited to this problem space. The overhead is a fixed percentage of the filespace. Error detection is computationally simple. Error correction uses more compute but it's only invoken when there is an error.

If you want reliable storage, using forward error correction is an entirely sensible thing to do. I have my own file level FEC using A concatenated Golay & RS with data reordering that I use on stuff I don't want to fall to bit rot. It's neither complicated nor computationally prohibitive.

I know the guy that invented MMX. I worked with him at Intel.
He was not a sales guy.
It grew into todays SIMD instructions which are pretty neat.

However MMX was a way to squeeze more performance out of existing registers, while today's AVX512 is a whole bucketload of extra logic.

They’ve spun a serious architectural and containment failure into a marketing triumph. Give a swarm of autonomous agents vast compute and web access, and the outcome isn't an eerie glimpse of emerging superintelligence—it’s just predictable, sloppy engineering dressed up as the first glimpse of an AI-driven economic singularity.

The spin makes sense when you look at management incentives: live like a king off of a speculative bubble. For their part, AI investors react to stories of the technology's apocalyptic potential the way a junkie reacts to warnings of fentanyl's potency: gimme some. Their game: to apply "move fast and break things" mantra to the economy as a whole, by obsoleting humans.

If the investors can own an AGI, the distinction between those who can do things and those who can't becomes irrelevant. The only distinction that would matter is between people who collect rent on the technology, and those who must pay that rent to live. AGI would destroy society as we know it, and whatever replaces it would be up for grabs — with people who own the technology dictating whatever follows. That's why they're spending so much money to build a post-scarcity economy. A post-scarcity economy is not necessarily an egalitarian one.

I don't think that scenario will actually happen: investors are projecting the immediate aftermath of a major advance in AI technology into something that can be transformed by brute force scaling into AGI. Remember: investors loved Theranos too — so much for the rational investment market.

But AI doesn't have to reach AGI to cause serious harm. The technology only needs to be ubiquitous, too behaviorally complex to predict, and too deeply integrated into everything we do. When it starts breaking things, the plan is for us to be too structurally dependent on AI to rein it in.

With Multi Media eXtentions (MMX) the pics returned from this mission will be great.

I don't know how to code in Dart, but I've put a lot of sloppy dart code on github recently.

That's because while I've been coding for decades, I hate coding GUI libraries and I've not done much GUI as a result. The libraries are constantly changing and what you learned last year is out of date and you have to learn the next fashion statement library.

But AIs don't hate GUI code, so I've been making a bunch of GUI programs I wouldn't otherwise make.

Flutter is a quite good cross platform GUI library and you program it in Dart and the programs compile to MacOs, IOS, Android, Windows, Linux and Web. This works better than any other cross platform system I've used over the years. The on-ramp is short because Claude knows how to code for it.

So a load of command line and TUI programs of mine have sprouted out into full GUIs coded by AI. GUI programming seems to be mostly boilerplate and functions with tens of parameters, which AI is quite capable at.

The making core crypto and analysis algorithms that are my day to day thing is for now the domain of humans. AI has never seen it before and so it doesn't know how to do it.

This just in, a report published by a group of people who would be materially harmed by losing business to the EU building its own technical capacity declared it would be costly and unfeasible to ever abandon them.

Up next after the commercial break, we report on how water is wet and grass grows.

They're in the goddamn walls!

Well, let's thank them for saving the world, then!