The State of AI Font Generation | Font and Text Technology

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The State of AI Font Generation

Two disclaimers: First, this article was entirely human generated; no AI was involved in the writing. Second, I have spent a lot of time this year attempting to train a glyph generation model. I want to be up front about this because I know that for certain people, this will discredit me entirely, and I don’t want you to find out afterwards and feel betrayed. But then, would you rather read an article about AI font generation written by someone who didn’t have any experience of it?

There’s been a lot of discussion recently about the ability of machine learning models to generate new fonts, or “fill in” existing fonts (by expanding the glyphset or design space), much of it prompted by this thread on Typedrawers. As part of that thread, Dave Crossland wrote:

Impallari appears to have been the first. Eric’s become second. I hope there’ll be a third.

I’m not going to talk here about the ethical or legal side of font generation, about whether you should or shouldn’t do this. These are important questions, but not for here; but my reaction when I read that was “Eric wasn’t the second; he wasn’t even the twenty-second - it just that all the others aren’t in your face right now.”

So the point of this article is to try to survey some of the development in font generation research, to present a clear-eyed view of what’s out there, how it works, and what I expect coming down the line. Because more will be coming down the line. People are going to work on this problem, whether we want them to or not. So whether your instinct is to welcome it or critique it (or of course both), let’s make sure we’re aware of it and we understand it.

But let’s also use it as an opportunity to understand ourselves as well. During my investigations, I noticed a couple of factors, a couple of gaps, and I think perhaps talking about these gaps is going to be the real takeaway from this post, rather than the technical stuff. I’m talking about the gaps between type designers and ML engineers, and also the gaps between Western type designers and Chinese/Japanese/Korean type designers.

The obligatory Two Cultures reference

One feature I’ve noticed is a very obvious lack of collaboration across disciplines, between ML researchers and type designers. I’ve certainly noticed a lack of collaboration between ML researchers and type engineers - as I look into the code for some of the models, I shudder to read how glyph outlines and rasterizations are being extracted from fonts; it’s clear that nobody from type-world has had any input into this at all. But more generally, I can see that there is also a lack at the quality control level; what ML engineers consider a typographic success would be something that a type designer would never dare share in public. I’m not just thinking of this thread, but also stuff like Neural Axis Variations - a genuinely interesting idea which probably could be well implemented, but clearly needed a type designer to review it before publication.

This is not “a fully functional variable font”.

I don’t say this to mock people’s work. The whole point is that you don’t know what you don’t know. I have a theory about why this is: when it comes to collaboration with type designers, I think there is an obvious question of perceived need.

ML researchers are really used to working with computer graphics. It’s something that they do all the time and do really well. And, as I argued in the big TypeDrawers thread, “type design is very deceptive because it’s easy to draw a series of recognisable letter forms” and that makes it hard for you to realise that you need feedback. If your ML model outputs a long string of amino acids, you know that you’re going to need a biologist to tell you whether it makes sense or not. Collaboration across disciplines is so obviously necessary in such a situation that you wouldn’t think not to.

But if you’re a researcher used to working with computer graphics and your task is to draw the letter ‘a’… well, everyone knows what an ‘a’ looks like. You don’t need professional input for that. (Spoiler alert: turns out you do!)

And at the same time… how can I put this delicately? Even if ML researchers did reach out to the typographic community in order to collaborate on AI-assisted font generation, they may not necessarily receive a warm and hearty welcome. It’s kind of a touchy subject. Type people have a habit of asking awkward questions about ethics and legality. And on top of that, nobody wants to be the one responsible for putting themselves and their peers out of work. You know, I get that.

So there is a paradox here: that AI generated font design can only come out of deep engagement with the typographic community if it’s going to be effective and high quality, and...