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Behind the painstaking process of creating Chinese computer fonts

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Behind the painstaking process of creating Chinese computer fonts


But there are tens of thousands of Chinese characters, and a 5-by-7 grid was too small to make them legible. Chinese required a grid of 16 by 16 or larger—i.e., at least 32 bytes of memory (256 bits) per character. Were one to imagine a font containing 70,000 low-resolution Chinese characters, the total memory requirement would exceed two megabytes. Even a font containing only 8,000 of the most common Chinese characters would require approximately 256 kilobytes just to store the bitmaps. That was four times the total memory capacity of most off-the-shelf personal computers in the early 1980s.

As serious as these memory challenges were, the most taxing problems confronting low-res Chinese font production in the 1970s and 1980s were ones of aesthetics and design. Long before anyone sat down with a program like Gridmaster, the lion’s share of work took place off the computer, using pen, paper, and correction fluid.

Designers spent years trying to fashion bitmaps that fulfilled the low-memory requirements and preserved a modicum of calligraphic elegance. Among those who created this character set, whether by hand-drawing drafts of bitmaps for specific Chinese characters or digitizing them using Gridmaster, were Lily Huan-Ming Ling (凌焕銘) and Ellen Di Giovanni.

Draft bitmap drawings of Chinese characters for the Sinotype III font.

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

The core problem that designers faced was translating between two radically different ways of writing Chinese: the hand-drawn character, produced with pen or brush, and the bitmap glyph, produced with an array of pixels arranged on two axes. Designers had to decide how (and whether) they were going to try to re-create certain orthographic features of handwritten Chinese, such as entrance strokes, stroke tapering, and exit strokes.

In the case of the Sinotype III font, the process of designing and digitizing low-resolution Chinese bitmaps was thoroughly documented. One of the most fascinating archival sources from this period is a binder full of grids with hand-drawn hash marks all over them—sketches that would later be digitized into bitmaps for many thousands of Chinese characters. Each of these characters was carefully laid out and, in most cases, edited by Louis Rosenblum and GARF, using correction fluid to erase any “bits” the editor disagreed with. Over top of the initial set of green hash marks, then, a second set of red hash marks indicated the “final” draft. Only then did the work of data entry begin.

A close-up of a draft bitmap drawing of bei (背, back, rear) showing edits made using correction fluid.

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

Given the sheer number of bitmaps that the team needed to design—at least 3,000 (and ideally many more) if the machine had any hopes of fulfilling consumers’ needs—one might assume that the designers looked for ways to streamline their work. One way they could have done this, for example, would have been to duplicate Chinese radicals—the base components of a character—when they appeared in roughly the same location, size, and orientation from one character to another. When producing the many dozens of common Chinese characters containing the “woman radical” (女), for example, the team at GARF could have (and, in theory, should have) created just one standard bitmap, and then replicated it within every character in which that radical appeared.

No such mechanistic decisions were made, however, as the archival materials show. On the contrary, Louis Rosenblum insisted that designers adjust each of these components—often in nearly imperceptible ways—to ensure they were in harmony with the overall character in which they appeared.

In the bitmaps for juan (娟, graceful) and mian (娩, to deliver), for example—each of which contains the woman radical—that radical has been changed ever so slightly. In the character juan, the middle section of the woman radical occupies a horizontal span of six pixels, as compared with five pixels in the character mian. At the same time, however, the bottom-right curve of the woman radical extends outward just one pixel further in the character mian, and in the character juan that stroke does not extend at all.

The bitmap characters for juan (娟, graceful) and mian (娩, to deliver) from the Sinotype III font, recreated by the author.

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

Across the entire font, this level of precision was the rule rather than the exception.

When we juxtapose the draft bitmap drawings against their final forms, we see that more changes have been made. In the draft version of luo (罗, collect, net), for example, the bottom-left stroke extends downward at a perfect 45° angle before tapering into the digitized version of an outstroke. In the final version, however, the curve has been “flattened,” beginning at 45° but then leveling out.

A comparison of two draft versions of the character luo (罗, collect, net).

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

Despite the seemingly small space in which designers had to work, they had to make a staggering number of choices. And every one of these decisions affected every other decision they made for a specific character, since adding even one pixel often changed the overall horizontal and vertical balance.

The unforgiving size of the grid impinged upon the designers’ work in other, unexpected ways. We see this most clearly in the devilish problem of achieving symmetry. Symmetrical layouts—which abound in Chinese characters—were especially difficult to represent in low-resolution frameworks because, by the rules of mathematics, creating symmetry requires odd-sized spatial zones. Bitmap grids with even dimensions (such as the 16-by-16 grid) made symmetry impossible. GARF managed to achieve symmetry by, in many cases, using only a portion of the overall grid: just a 15-by-15 region within the overall 16-by-16 grid. This reduced the amount of usable space even further.

Symmetry and asymmetry in the characters shan (山, mounting), zhong (中, middle), ri (日, sun), and tian (田, field).

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

The story becomes even more complex when we begin to compare the bitmap fonts created by different companies or creators for different projects. Consider the water radical (氵) as it appeared in the Sinotype III font (below and on the right), as opposed to another early Chinese font created by H.C. Tien (on the left), a Chinese-American psychotherapist and entrepreneur who experimented with Chinese computing in the 1970s and 1980s.

A comparison of the water radical (氵) as it appeared in the Sinotype III font (right) versus an early Chinese font created by H.C. Tien (left).

LOUIS ROSENBLUM COLLECTION, STANFORD UNIVERSITY LIBRARY SPECIAL COLLECTIONS

As minor as the above examples might seem, each represented yet another decision (among thousands) that the GARF design team had to make, whether during the drafting or the digitization phase.

Low resolution did not stay “low” for long, of course. Computing advances gave rise to ever denser bitmaps, ever faster processing speeds, and ever diminishing costs for memory. In our current age of 4K resolution, retina displays, and more, it may be hard to appreciate the artistry—both aesthetic and technical—that went into the creation of early Chinese bitmap fonts, as limited as they were. But it was problem-solving like this that ultimately made computing, new media, and the internet accessible to one-sixth of the global population.

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The Download: AI films, and the threat of microplastics

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Welcome to the new surreal. How AI-generated video is changing film.


The Frost nails its uncanny, disconcerting vibe in its first few shots. Vast icy mountains, a makeshift camp of military-style tents, a group of people huddled around a fire, barking dogs. It’s familiar stuff, yet weird enough to plant a growing seed of dread. There’s something wrong here.

Welcome to the unsettling world of AI moviemaking. The Frost is a 12-minute movie from Detroit-based video creation company Waymark in which every shot is generated by an image-making AI. It’s one of the most impressive—and bizarre—examples yet of this strange new genre. Read the full story, and take an exclusive look at the movie.

—Will Douglas Heaven

Microplastics are everywhere. What does that mean for our immune systems?

Microplastics are pretty much everywhere you look. These tiny pieces of plastic pollution, less than five millimeters across, have been found in human blood, breast milk, and placentas. They’re even in our drinking water and the air we breathe.

Given their ubiquity, it’s worth considering what we know about microplastics. What are they doing to us? 

The short answer is: we don’t really know. But scientists have begun to build a picture of their potential effects from early studies in animals and clumps of cells, and new research suggests that they could affect not only the health of our body tissues, but our immune systems more generally. Read the full story.

—Jessica Hamzelou

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Microplastics are everywhere. What does that mean for our immune systems?

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Microplastics are everywhere. What does that mean for our immune systems?


Here, bits of plastic can end up collecting various types of bacteria, which cling to their surfaces. Seabirds that ingest them not only end up with a stomach full of plastic—which can end up starving them—but also get introduced to types of bacteria that they wouldn’t encounter otherwise. It seems to disturb their gut microbiomes.

There are similar concerns for humans. These tiny bits of plastic, floating and flying all over the world, could act as a “Trojan horse,” introducing harmful drug-resistant bacteria and their genes, as some researchers put it.

It’s a deeply unsettling thought. As research plows on, hopefully we’ll learn not only what microplastics are doing to us, but how we might tackle the problem.

Read more from Tech Review’s archive

It is too simplistic to say we should ban all plastic. But we could do with revolutionizing the way we recycle it, as my colleague Casey Crownhart pointed out in an article published last year. 

We can use sewage to track the rise of antimicrobial-resistant bacteria, as I wrote in a previous edition of the Checkup. At this point, we need all the help we can get …

… which is partly why scientists are also exploring the possibility of using tiny viruses to treat drug-resistant bacterial infections. Phages were discovered around 100 years ago and are due a comeback!

Our immune systems are incredibly complicated. And sex matters: there are important differences between the immune systems of men and women, as Sandeep Ravindran wrote in this feature, which ran in our magazine issue on gender.

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Welcome to the new surreal. How AI-generated video is changing film.

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Welcome to the new surreal. How AI-generated video is changing film.


Fast and cheap

Artists are often the first to experiment with new technology. But the immediate future of generative video is being shaped by the advertising industry. Waymark made The Frost to explore how generative AI could be built into its products. The company makes video creation tools for businesses looking for a fast and cheap way to make commercials. Waymark is one of several startups, alongside firms such as Softcube and Vedia AI, that offer bespoke video ads for clients with just a few clicks.

Waymark’s current tech, launched at the start of the year, pulls together several different AI techniques, including large language models, image recognition, and speech synthesis, to generate a video ad on the fly. Waymark also drew on its large data set of non-AI-generated commercials created for previous customers. “We have hundreds of thousands of videos,” says CEO Alex Persky-Stern. “We’ve pulled the best of those and trained it on what a good video looks like.”

To use Waymark’s tool, which it offers as part of a tiered subscription service starting at $25 a month, users supply the web address or social media accounts for their business, and it goes off and gathers all the text and images it can find. It then uses that data to generate a commercial, using OpenAI’s GPT-3 to write a script that is read aloud by a synthesized voice over selected images that highlight the business. A slick minute-long commercial can be generated in seconds. Users can edit the result if they wish, tweaking the script, editing images, choosing a different voice, and so on. Waymark says that more than 100,000 people have used its tool so far.

The trouble is that not every business has a website or images to draw from, says Parker. “An accountant or a therapist might have no assets at all,” he says. 

Waymark’s next idea is to use generative AI to create images and video for businesses that don’t yet have any—or don’t want to use the ones they have. “That’s the thrust behind making The Frost,” says Parker. “Create a world, a vibe.”

The Frost has a vibe, for sure. But it is also janky. “It’s not a perfect medium yet by any means,” says Rubin. “It was a bit of a struggle to get certain things from DALL-E, like emotional responses in faces. But at other times, it delighted us. We’d be like, ‘Oh my God, this is magic happening before our eyes.’”

This hit-and-miss process will improve as the technology gets better. DALL-E 2, which Waymark used to make The Frost, was released just a year ago. Video generation tools that generate short clips have only been around for a few months.  

The most revolutionary aspect of the technology is being able to generate new shots whenever you want them, says Rubin: “With 15 minutes of trial and error, you get that shot you wanted that fits perfectly into a sequence.” He remembers cutting the film together and needing particular shots, like a close-up of a boot on a mountainside. With DALL-E, he could just call it up. “It’s mind-blowing,” he says. “That’s when it started to be a real eye-opening experience as a filmmaker.”

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