The Nintendo way of adapting technology is not to look for the state of the art but to utilize mature technology that can be mass-produced cheaply.
This is the reason a Nintendo console never has the fastest chips or the beefiest specs of its generation; instead, its remixes components in an interesting and generative way. Think of the Gameboy’s monochrome screen, the Wii’s motion controller, the Switch’s smartphone form.
[Gunpei Yokoi] is talking about reliability and predictability, in performance and supply alike. He wants the components to be boring, so their application can be daring.
This visualization takes the current New York Times Best Sellers list for combined print and e-book fiction and scales each title according to the demand for its e-book edition at a collection of U.S. public libraries, selected for their size and geographic diversity.
This is a kind of manifesto about the difference between liking something on the internet and loving something on the internet.
It’s also an experiment in a new format: a “tap essay,” presenting its argument tap by tap, making its case with typography, color, and a few surprises.
Like a programming language interpreter, GPT-3 translates the designer’s intent from a language they’re already familiar with (English) to one they need to learn (Figma’s information architecture, as manifested in its UI.) This can be easier for a new/busy designer, much like Python is easier and faster to work with than assembly language.
But that’s not “designing” — at least not any more than compiling Python code is “programming.” In both cases, all the system does is translate human intent into a lower level of abstraction. Sure, the process saves time — but the key is getting the intent part right. I’ll be convinced the system is “designing” when it can produce a meaningful output to a directive like “change the product page’s layout to increase conversions.”