That mugshot of from 2011, probably before he was “declared a Non-Jurisdictional Sovereign Entity under the strict protocols of the Monti Act of God Phenomenon.”

I’m sure it will protect him next time. I mean, it’s irrevocable!

If I can’t play it in MPV, I don’t wanna play it.

Everything else feels like going back to the stone age. No offense to VLC fans. VLC is cool too, and I still recommend it because of its simpler GUI. But MPV is the MVP.

Atkinson Hyperlegible would be a good starting point but I don’t know how you could extend it to all of Unicode.

What I’m gathering is that “wave” can refer to a behavioral pattern that is substrate independent — it refers to a logical function more than it does an ontological presence

I think that’s a good way of putting it.

As for what counts as a “substrate”, I have no idea! In the old days, the idea of a substance that permeated seemingly-empty space was common. See: https://en.wikipedia.org/wiki/Aether_theories

Nowadays, the idea of aether has been discarded for the most part. But that said, there’s still plenty we don’t understand, like dark matter. There’s no consensus on what dark matter is exactly; there are many competing theories. What we know is that there are observable phenomena that can’t be explained without something that acts (roughly, at least) like matter in terms of its effect on gravity, but doesn’t interact with electromagnetism like normal matter. That “something” is called dark matter, but its fundamental nature is an open question.

Now we’re getting into linguistics with the question of “what is a wave?”

In quantum physics, basically everything is waves, in the sense that the same mathematical formulae used to describe waves are used to describe quantum phenomena. The intuitive human-scale dynamics of waves don’t necessarily apply though.

For example, sound waves can’t propagate through a vacuum, but light waves can. Aside from that, they follow mostly the same rules. You can use the same math the describe interference of sound waves and light waves, for example.

People talk about the “particle/wave duality” of photons because in some ways they behave like waves and in some ways they behave like particles. But both of those words are stretched a little from their everyday plain-english usage, and the precise reality would require years of study to understand.

Plain English wasn’t made to be that precise or objective. That’s why we use math. :)

I’m no expert in quantum physics so take this all with a grain of salt.

With a million tokens you can get it to rewrite the script to remove this guardrail. OMG we’ve reached the singularity!!

The coolest, and often most confusing thing about computer science, information theory, and perhaps reality in general, is how everything becomes more or less equivalent if you boil it down and twist it around a little.

Everything is sorting. Everything is compression. Everything is geometry. Everything is language. Everything is music. Everything is, like, waves, man. *puff*

Or more accurately, everything can be expressed in any of those other things’ terms.

These are not new ideas, but computers have made them provably and demonstrably true in many contexts, and I think that’s super cool.

LLMs are soulless.

Marketing and PR people are soulless.

It’s not coincidence they sound alike.

This is cool, but the framing rubs me the wrong way.

The assumption of human-like attributes is a bit of a stretch when you can build an LLM in any substrate

“I can theoretically run arbitrary computer programs inside another computer program” does not hold any philosophical weight.

We’ve known what Turing-completeness means for many decades now. ANY program you run on your computer can theoretically run on ANY Turing-complete substrate, which includes all kinds of ridiculous things. You could do this with PowerPoint or Minecraft, too. Or with a sufficient number of rocks on a beach.

If this is your first time learning about Turing-completeness, then…well, that’s cool! Just don’t let it rock your world too hard. :)

Whether LLMs have any “human-like attributes” has nothing to do with the substrate, beyond the point that different substrates will lead to different levels of performance in practice, and some emergent properties might only manifest at higher levels of performance in practice.

Whether a Turing machine (i.e. conventional computer) can theoretically do the same things as a human body is still an open question. (I say “human body” instead of just “human brain” because the brain is not responsible for all of human cognition and behavior, despite popular belief.) It might be fully impossible (unlikely, IMHO), it might require a completely unrealistic scale (most likely, IMHO), or it might be downright trivial once we figure out how.

The specific examples seem reasonable, but do not support the overall thesis.

The problem with that philosophy is that all the fundamental problems reinforce themselves, generation after generation after generation. Assuming familiarity with Windows as your baseline guarantees that you will be stuck in a rut of horrible UI design “because that’s the way it’s always been”. The lowest-friction choice will always be to carry forward all the bullshit.

I don’t think you can truly call someone “computer literate” if they can’t tolerate moderate friction and learn new things quickly.

This is also why apple’s UI sucks so bad now. They used to have fantastic UI design because they made software with the fewest possible assumptions about the user. Now they design software assuming you are ass-deep in their previous software. It is the design equivalent of inbreeding.

Yeah. The newer versions of Dall-E, GPT-Image, and similar cloud apps seem to have subnetworks specifically for text. They’re worlds better than they were just a year or two ago. Like, you can twist them into generating semi-coherent-looking text logos, or make a cartoon character wearing a T-shirt with some text on it.

I’ve seen some complex pipelines with open models, where people train loras specifically to fix the things the base models suck at, like hands, text, etc.

But it’s still a really dumb idea to generate a whole presentation slide or infographic that way, for a wide variety of reasons. If you ever get decent results, just consider yourself lucky. I mean, even the people with the skills to do this well (who are few and far between) would find it way more trouble than just, you know, making slides the normal way.

The incompetence we keep seeing from Microsoft is staggering. I can only assume this is malicious compliance. I imagine some exec said “everyone needs to use AI for everything” and everyone below them said “okay you dumb fuck, here you go”.

Oh it’s definitely extra stupid. Looks like the slide was made whole-cloth by an image generator, not like the text was generated by an LLM and pasted in.

Image generators make typos all the time (if you can call them that).

See also: continvoucly morged

Not sure about the licensing, but Adobe’s AI is called Firefly and it’s a few years old now.

Nope. Setting up an ad-blocking DNS server, or installing a web browser with an ad blocker, is as easy (and free) on iOS as it is on Android.

Look up instructions for Mullvad DNS or NextDNS.

whyAreYouUsingCamelCaseInAllYourTitles?

Have you ever wondered why we celebrate Richard Stallman as a visionary prophet of digital freedom while simultaneously abandoning every principle he fought for?

…

This is the Stallman Paradox: the growing chasm between our intellectual reverence for genuine free software principles and our practical convergence on venture capital-optimized extraction models that merely cosplay as “open source.”

I’m not entirely sure who “we” refers to, but it sounds like they are either very confused, or they are liars. Perhaps they have been bamboozled by corporate interests trying to undermine and co-opt the free software movement and philosophy, or perhaps they are agents of those corporate interests trying to bamboozle you.

That’s not new; it’s been happening since the moment free software started picking up steam, decades ago. Consider some of these choice quotes from Stallman himself at his speech at a Web3 conference just last year:

I’d like to say more about the difference between Free Software and open source because it’s a topic of great confusion. I founded the Free Software movement in 1983 with the announcement. The term Open Source was coined fourteen years later in 1998 when Free Software was becoming widely used and starting to be something people knew about. But not everyone who worked on or used or promoted Free Software agreed with the philosophy of freedom behind it. And the people who didn’t agree wanted to get out of connection with it by and many of them were working for businesses or with businesses that didn’t care about freedom at all. So, they found a new term, Open Source, which they defined differently but it overlapped a lot… But the biggest difference is that the term Open Source has never had any implications about right and wrong. It was, that idea was launched that way by people who didn’t see it as a matter of right and wrong. So that’s why I decided I would not start using that term.

And what does Stallman think of cryptocurrency?

I’ve never used cryptocurrency. There were things I found disappointing and worrisome when I learned about BitCoin. And it’s not clear to me that others are much better… I don’t want to do currency speculation myself at all.

He prefers GNU Taler as a distributed payment system. Taler is not a cryptocurrency, but it solves a lot of the problems that cryptocurrency pretends to solve.

Now with Taler the payer is anonymous but the payee is always identified, which means that Taler does not help millionaires hide lots of money from taxation. The world has a tremendous problem with wealth that is hidden and cannot be taxed. It’s part of the way that billionaires have been transferring more and more of the world’s wealth to them leaving less and less for everyone else. And this change is on the order of twenty percent of the world’s wealth. It’s an enormous change that impoverishes people who are not rich but even worse it gives the rich people the power of oligarchy, the power to buy governments and that threatens democracy. That threatens the rights of all of us but if we insist on payment systems that don’t permit the hiding of large amounts of wealth, that problem will get less instead of more.

“How much do you know about Web3?”

Not a tremendous amount, that’s not my field.

So again I wonder who this “we” refers to. Who is so confused as to associate Richard Stallman and Free Software with cryptocurrency and web3? I mean, the fact that he was invited to speak at a web3 conference suggests it’s a lot of people in the field, but god damn.

Kind of the opposite. It takes more effort to make a filesystem case-insensitive. Binary comparison is the laziest approach. (Note that laziness is a virtue.)

I’m on the fence as to which is better. Putting backwards compatibility aside, there’s a perfectly good case to be made for case-insensitivity being more intuitive to the human user.

Apple got into a strange position when marrying Mac OS (case-insensitive) and NeXTSTEP (case-sensitive). It used to be possible to install OS X on case-sensitive HFS+ but it was never very well supported and I think they axed it somewhere down the road.

Geany is a nice GUI option. It’s a bit more capable but still lean.

It’s probably time for me to re-evaluate the host of coding editors out there. For the most part I just use good text editors. Though I do love Spyder, I only use it for a certain subset of tasks.

IPFS content IDs (CID) are a hash of the tree of chunks. Changes to chunk size can also change the hash!

I don’t understand why this is a deal-breaker. It seems like you could accomplish what you describe within IPFS simply by committing to a fixed chunk size. That’s valid within IPFS, right?

Is it important to use any specific hashing algorithm(s)? If not, then isn’t an IPFS CID (with a fixed, predetermined chunk size) a stable hash algorithm in and of itself?