ai

Celine Nguyen in Asterisk, on what Silicon Valley means when it talks about taste. She goes back to the Victorians, who had a near-identical panic about automation and answered it by founding design schools, and to the Bauhaus, which taught aesthetic perception as a skill rather than an innate gift. Both sit somewhat awkwardly against the current line that taste is the one thing a model can’t do.

She also describes teaching herself typography by collecting a large scraped dataset of images and learning to categorise them, a comparison she makes on purpose.

George London on how AI coding tools can ensure open and free software regains a practical edge over closed services, like much SaaS. I have cancelled two iOS app subscription and one SaaS subscription in the last month after I realised I could make my own versions that meet my specific needs rather than those of the mass market. This article is an interesting counterpoint to some of what Anil Dash argues in “Endgame for the Open Web”.

Anil Dash on how the open web is being eroded. At the end he talks about building “good AI” and alternative infrastructures. I wonder what concrete coordination, funding models and incentive structures would enable those projects to scale and compete with Big Tech before the open web’s critical institutions collapse?

Researchers at the company are trying to understand their A.I. system’s mind—examining its neurons, running it through psychology experiments, and putting it on the therapy couch.