71–80 of 150 posts
I found a few months ago that the gpt-4 code interpreter is capable of converting a black and white png of a glyph to an svg https://twitter.com/lfegray/status/1678787763905126400 It would be cool to combine a script like the one gpt-4 gave me with an image generation model to generate fonts. The approach from this blog post is way more interesting though. On a separate note it reminds me of this suckerpinch video :)…
Earlier quoted context omitted.
Time will be freed, ChatGPT, DALL-E, Midjourney and Stable Diffusion has collectively saved countless people billions of hours of time and this will do the same. The big font makers no longer have a hold on extremely pricey fonts that are inaccessible, the general endgame is most software is going free and open source thanks to AI, and that is a good thing.
Creatives will have their hopes and dreams stripped away so that artless and tasteless software engineers can type words into a box and instantly get exactly what they want, with no surprises, no feelings, and no economic upsides for anyone else. A beautiful future indeed.
"Fucking Hell" - first thing I yelled to myself when I saw that headline Kudos for the project, of course, but it just saddens me a bit more. Nothing is sacred anymore.
> To train the model, I assembled a dataset of 71k distinct fonts. I give it a week before Monotype sues your face off.
Font law is almost as complex and fascinating as Tree law. Given how complex font licensing can be, a generative use case that produces usable fonts would be a huge threat to the foundaries and I expect they will be very litigious, just as Getty and others are in the image space.
Earlier quoted context omitted.
You don't know that the time will be freed for other things that are more important. We don't know for sure how this is all going to work out at all. And people who make fonts, create art, and write prose generally do these things because they like doing them, not because they're forced to. These technologies aren't automating drudgery, they're automating things that give people's lives meaning. What's the endgame he…
Time will be freed, ChatGPT, DALL-E, Midjourney and Stable Diffusion has collectively saved countless people billions of hours of time and this will do the same. The big font makers no longer have a hold on extremely pricey fonts that are inaccessible, the general endgame is most software is going free and open source thanks to AI, and that is a good thing.
"Fucking Hell" - first thing I yelled to myself when I saw that headline Kudos for the project, of course, but it just saddens me a bit more. Nothing is sacred anymore.
I mean, looking at the kerning of the second example in particular, there’s still a lot to be done. And something like “extend this latin-1 font to all scripts of the BMP so that is looks stylistically consistent and, within that constraint, the glyphs and their combinations look natural and readable for native readers of each script, assuming Japanese readers for the Han characters” is probably still way off.
More correctable in these models would be the balance between the letterforms. Surely if there was some kind of prompt you could tell it to not make those Ms in that bold serif font to be obnoxiously wide?
Either way, as of now, what this gets us is exactly 90% less useful and probably of lower quality than the stuff you can get for free on dafont.com. I know it will progress, but I imagine the best use case for generative AI and font creation for commercially viable fonts would be to give roughs glyphs to fill out a large character set as an aid for a professional type designer.
And surely there will be a chorus of people insisting that it doesn't matter. Well, you're wrong. If you blindly showed people a headline, book, poster or whatever with properly kerned type and then one without, they will see how much more polished the properly kerned page is, even if they couldn't tell you specifically why. In a lot of situations, that really, really matters, even to people who haven't developed the ability to point out the differences.
Earlier quoted context omitted.
There is an "a" in "lazy"?
Well, I'm stupid.
Making sure it’s ‘the’ lazy dog rather than ‘a’ lazy dog is actually important if you care about completing the lowercase alphabet, as without it there’s only an uppercase ‘T’.
I’ve tried out some work on generating vector fonts too, in the format of Bezier curves and a seq2seq model. The problem was that fonts outputted by ML models were imprecise. Lines were not perfectly parallel, corners were at 89°, and curves were kinked. It’s not too difficult to get fonts that look good enough, but the imperfections are glaring as fonts are normally perfectly precise. These imperfections are evident…
Of course, changing the learning process would be best. One idea which comes to mind is finding a way to embed relationships into the ML training system itself (e.g., output no angles other than 90 degrees or some predefined set). Such an approach is a type of contraint-based ML, where the ML agent identifies a solution given certain constraints on the output. In my experience, the right approach to accomplish this goal is using factor graphs.