A user requested adding wrapping hex grids to Sylves. That is, a grid that is a collection of hexagons, and the collection itself is also hexagonal shaped. When you exit from one side, you re-enter on the opposite side.
The maths for this turned out to be surprisingly fiddly, and not listed by RedBlobGames, so I thought I’d share it here.
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I met a scholar from an English class
Who said: In dusty archives, seldom passed,
There lies a sonnet, once of mighty fame.
Near it, on yellowed pages, time-worn, lame,
The dedication reads: “Percy Bysshe Shelley,
Who spoke to power through his burning hymns,
Few now recall, save students, grudgingly.
He wrote of Ozymandias, King of Kings;
Look on his verse, ye readers, and despair!”
Round the decay of that poetic feat,
Bare margins stretch, and in the desert there
His words drift forgotten, like windblown heat.
I did a short hackathon “Building Tools for Community Organisers with Matrix” sponsored by Campaign Lab, working in a team with Ben Dunn Flores.
Our tool is a prototype for summarizing a chat log, and publishing the result to Matrix (an instant message platform) and gitbooks.
Recently, I’ve quit my job, and have been trying to learn a new field, with plans towards a bit of a lateral career shift after 16 years as a Financial Software Engineer.
This has caused a fair bit of soul searching, because as it turns out, learning new things is hard.
The first things to conquer were the fear of looking stupid, and persevering without that feeling of mastery. It’s frustrating, but not unexpected, when it comes to learning something new.
Today, I wanted to talk about another roadblock that I’m coming to grips with. I remember when I was much younger, I would absorb new material with ease. Now that I’m doing it as a mini-mid-life crisis, it feels like I’m forcing it, and it takes much more effort. There was a time when I thought I’d lost my “spark”, or at least had replaced fluid intelligence with crystalized intelligence. I eventually realized though that’s not true. I’m basically as sharp as ever, but instead I have a differe a mental roadblock to deal with:
The thing is, I’m more complete a person right now. As a youngster, I was far more willing to obsess over something or make it a core part of my identity. Then work on it far more than is healthy or sensible. Now, I feel I have ties to a dozen different areas – my career, my hobbies, my relationships. Each of these demands time and focus.
I see the same pattern when it comes to learning languages. Children learn languages very well, even outside of the critical period. There have been studies showing this is is because they simply sink ungodly amounts of time into learning. I’ve been revising German as an adult via Duo Lingo for 3 years. But 5 minutes a day for that period adds up to a term or two of school lessons, excluding any homework. It’s no surprise that I’ve made no progress with that sort of dedication.
I’ll probably never be cracked at something new, same as how I’ll never reach native level fluency at German.
So am I essentially arguing for a form of agism, then applying it against myself? That I’m saying that even if you have the same energy, intellect and time as a youth, you are unlikely to be as devoted to something new? That I’ve become cynical, instead of passionate?
I think not. Instead, my mental model is that of a super-tanker. Now that I am a bit older (though not that old!), my hull is stocked with precious resources. I’m used to spending on time on things, and that gives a certain momentum to winding down one thing and doing another. Turning is not something to be taken lightly when you’ve spent so much fuel getting up to speed in one direction. But perhaps it is more valuable to arrive with goods at the right destination, but late, than it is to arrive elsewhere, or arrive empty handed.
Recently I’ve been playing around more with gen AI techniques. I thought I’d try to generate a set of tiles that all connect together. It’s harder than it sounds – Stable Diffusion is hard to control, so there’s no easy way to get a set of images that are fully consistent with one another.
I’ve developed a technique for doing it that I’ll call Non-Manifold Diffusion as it involves doing diffusion over a set of patches that interlock to form a non-manifold surface.
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For many years, I always gifted people books for birthdays. It took a long time to realize that most people see them more as obligations than anything. I guess I was trying to recapture some of the magic they have always brought me.
The following books are not necessarily the best ones I’ve read or even the ones that have absorbed deepest into my personality. But they’ve had a distinct impact. Let’s begin.
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I went to some lectures on the future of science in games recently, and the keynote speaker was Tommy Thompson, an well-known AI expert in the game dev space.
Of course, by AI, he didn’t mean the modern sort that dominates the news. His focus is AI for games, which is algorithmic and rarely involves any ML component. Still, he spoke about the challenges the industry faces regarding Image Generators, LLMs and so on. He specifically called LLMs “stochastic parrots”, which I found disappointing. Imho it’s an incredibly misleading model of what LLMs are capable of and is usually deployed to downplay their abilities and belittle them. But it’s a common view, particularly in creative industries.
So what is a better model? It’s clear that they are not that smart in most ways we consider important, but they do have some interesting capabilities. Here’s model I use that I feel give a better intuition for what they can and cannot do.
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I’ve been working on adding aperiodic grids to Sylves.
Aperiodic tilings are made tilings are made of a fixed set of tiles, rotated and translated to fully cover the plane.But they are not periodic – there’s no way to rotate/translate the whole grid onto itself.
This makes them almost hypnotic in their balance of regularity and chaos. A classic example is the penrose tiling.
Back in the early days of computer animation, the technology at the time really struggled with realism. The first cartoons were necessarily abstract, or cartoony.
As time progressed, the technology caught up. CGI now can be all but indistinguishable from real life. But there was a brief period, as seen in films like The Polar Express or Final Fantasy: The Spirits Within, when the artists aimed for realism and didn’t quite get there.
These films were often critically panned. Eventually, it became clear that the cause was quite deep in the human psyche. These films were realistic enough that we’d mentally classify the characters as real humans, but not so realistic that they actually looked normal. On an instinctive level, people reject these imposters far harder than more stylised graphics that don’t have the pretence of reality.
This phenomenon is known as the Uncanny Valley and has influenced visual design of fake people in films, robots, games etc.
For a time, the recent crop of image generators and LLMs fell into the same boat. Twisting people with the wrong number of fingers or teeth was a common source of derision. People are still puzzling over chatbots that can speak very coherently and yet make wild mistakes with none of the inner light you might expect from a real conversationalist.
Now, or at least very soon, AI threatens to cross that valley and advance up the gentle hills on the opposite side. Not only are we faced with a disinformation storm like nothing before, but AI is going to start challenging exactly how we consider personhood itself.
This is something we need to fight, in addition to all the other worries about AI. I don’t want to get into philosophical weeds about whether LLMs could be considered moral patients. But I think our society and thinking are structured around a clear human/non-human divide. Chatbots threaten to unravel that.
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