Notices by Dan Piponi (dpiponi@mathstodon.xyz)

I'm an actual imposter and I get a bit fed up of the people faking it.

1. Yes
2. Sometimes
3. Hmmm...
4. It might not laugh but it was being passive-aggressive to me the other day.
5. Oh man, you could do so much harm...
6. Hey, we're already there!

Before you plug in your new Timex/Sinclair 1000, please take a moment to think about this exciting new adventure. We want to assure you that:

1. You will enjoy computing.

2. You will find it easy as well as enjoyable.

3. You shouldn’t be afraid of the computer. You are smarter than it is. So is your parakeet, for that matter.

4. You will make mistakes as you learn. The computer will not laugh at you.

5. Your mistakes will not do any harm to the computer. You can’t break it by pushing the “wrong” button.

6. You are about to take a giant step into the future. Everyone will soon be using computers in every part of their daily lives, and you will have a head start.

-- Steve Vickers, Timex/Sinclair 1000 Instruction Manual (aka the US ZX81 manual)

@inthehands @kevinriggle And if you're feeling cruel you can ask them to predict where the spirals will be. (There are papers, but I'm not sure there is a nice answer to this specific question.)

@kevinriggle @inthehands Perfect for L-systems I'd have thought.

As good an example as any, I think, of how even the simplest of computer programs can yield surprising results that take significant work to explain.

@glynmoody "What's Concorde?" someone asked me the other day at work. That was also when we had the "we used to have to dial up to get internet" conversation.

Just a minor fact that doesn't seem to be stated in many places - maybe it's too obvious to state:

In the absence of knowledge of what a probability distribution is, people sometimes like to pick the maximum entropy distribution consistent with the knowledge they do have.

More generally you may have some prior idea of what the distribution is. In that case you might pick the distribution with the maximum entropy *relative* to your prior guess consistent with any new knowledge.

A special case is when you draw from a joint distribution on X and Y and observe X. The posterior distribution of Y is given by the conditional distribution P(Y|X). This is precisely the maximum entropy distribution relative to the original distribution with the constraint that Y is known.

So conditional probabilities are in fact maximum (relative) entropy distributions.

@julesh That's what I was thinking

https://bsky.app/profile/dpiponi.bsky.social/post/3lc6o4s2xpk2d

@julesh Orthotope shares inspiration with Matlab, ie. APL. And it was written by Lennart Augustsson so you can guarantee it's going to be interesting to use :)

@julesh Are you using orthotope?

Took them a long time to discover it was disgusting.

@julesh 100% serious. It was such a horrible thing to do to coffee and I couldn't understand why they were promoting it for a long time.

Plant care web sites are all like this:

Here's our handy guide on identifying exactly what's wrong with your plant:

• leaves turning brown? Too much water

• leaves turning brown? Not enough water

• leaves turning brown? Too much sun

• leaves turning brown? Too much shade

• leaves turning brown? Soil too acid

• leaves turning brown? Bacterial infection

• leaves turning brown? This is normal for older leaves

Imagine, if you will, it's 2023, back in the dark ages when nobody had figured out yet how to make computers usable.

There are two of you in an aircraft, one with an Android phone and one with an Apple phone. What's the best way to get a photo from one phone to another?

Bonus points: do it without paying $14.95 to move the files thousands of miles across the world and back again.