Men, can you name five...

Can you name:

Five things you're likely to find under the hood of a car?

Five plays in football.

Five components of a pistol?

Five members of the X-Men?

Five kinds of dice used in D&D?

Five brands of beer.

Five items found in a toolbox.

Five movies where lots of stuff gets blow up.

Five electronic gadgets you wish you owned.

Five parts of a woman's vulva.

If the last one was hard, tell me again how much you like sex.

PacMan doesn't need AI

The other day, I was reading through the course syllabus for a second-year AI class, as one does, when I noticed that the assignment for the sixth week was to turn in a working version of PacMan. Which is kind of weird, because the actual algorithm for PacMan involves more or less zero AI. It involves something else, and one of my favorite words: stigmergy.

Alright, so, here’s the algorithm in a nutshell: PacMan is played on a 29-by-26 square grid of cells. Everything else is special effects. There is a clock cycle: every cycle, the characters move from one square of the grid to another. If PacMan and a ghost share the same cell in a cycle, PacMan loses a life. There’s an animation engine running to make it look smoother than it is, but that’s the basic game.

The grid is actually three different grids layered together: One grid constrains movement by providing the walls. One grid tracks the dots that have been eaten. (The actual end-of-round tracking is done with a counter.)

The last grid is the stigmergy grid: every clock cycle, PacMan moves forward in a direction. The grid he just left is given a number: 255. Every clock cycle, the stigmergy grid is scanned for these numbers, and they’re reduced according to some formula until they reach zero. A ghost wandering the maze has a few rules: when it reaches a cell that has more than one neigbor, it chooses a direction based on a formula, and part of that formula includes adding in the stigmergy number of the neighboring cells. Blue ghosts use a reverse strategy; “dead” ghosts use a simple vector-weight strategy to go back to the center room.

In short, the ghosts are following PacMan’s scent, in much the same way ants follow a trail laid down by other ants.

There’s also a clock-cycle counter that causes the ghosts to reverse themselves from time to time, but that’s the basic gist of it. Unfortunately, the random number generator is seeded with the same number every level, so it became possible to master the game and play infinitely long. As smooth as the game looks, you actually have half a second of leeway time between moves, which is well within the average video gamer’s skill to master. Ms. PacMan fixed the seeding issue, and the game is significantly harder to play for a long time.

That’s it. You could implement PacMan in a few hundred lines of Javascript and HTML. Some animate CSS using the FLIP trick would be awesome. There’s no magic, and certainly no AI about it.

Which skills? What disciplines? The pundits don't say.

So, Spectrum IEEE has a “The sky is falling! The sky is falling!” article claiming that in 2016 tech layoffs have been nasty and that in 2017 it’s going to get even nastier. This is one of many articles on this theme, but it’s a little disheartening to see it in Spectrum. Worse, none of the articles I’ve read on this theme list the skills are going to be out-of-date. Which skills? What disciplines?

In 2008, I was laid off after 8 years at a large company, and I’d been using the same tools for those 8 years. As a front-end developer for dev-ops shops, my skills were woefully out-of-date: We’d been using Sencha (JS) and Webware (PY), with some Python 2 Python-to-C libraries. I knew nothing about what the cool kids were doing. I sat down and in a few days taught myself Django and jQuery; I rebooted by SQL knowledge from my 90s-era experience with Oracle and taught myself the ins and outs of Postgresql.

And then, in the bottom of the recession, I took shit contracts that paid very little (in one mistake, nothing) but promised to teach me something. I worked for a Netflix clone startup; I traded my knowledge of video transcoding for the promise of learning AWS. I worked for a genetic engineering startup, trading my knowledge of C++ for the promise of learning Node, Backbone, SMS messaging, and credit card processing; a textbook startup, trading my knowledge of LaTeX for the promise of learning Java; an advertising startup trading my basic Django skills to learn modern unit testing; a security training startup, trading my knowledge of assembly language in order to learn Websockets.

The market improved. I never stopped learning. I gave speeches at Javascript and Python meet-ups. Recruiters sought me out. I’ve been at another big company for four years now.

Will things go to hell in March? I don’t care. I have the one skill that matters.