Ted Chiang and [Terence Tao](https://www.linkedin.com/in/terence-tao-621246/): art, math and AI

There is much I dislike about Ted Chiang's manifesto in The New Yorker two weeks ago (https://lnkd.in/gdXhCQ2K). But his narrow understanding of AI, and specifically gen AI and LLMs, is a topic for another time.

👉 A more positive take relies on a striking parallel between Chiang's (deeply flawed, in my view) main point that art is characterized by the myriad decisions required at all scales, and Terence Tao's observation (https://lnkd.in/gAjs2N7K) that getting to the solution of a really hard math problem requires a lot of decisions about where to go next -with so many dead ends that avoiding them is a key survival skill. The big difference between the two is that Tao can see the potential of AI to support the decision-making, even if the critical forks in the road are defined and decided by the talented human. Chiang thinks it removes meaning. I think the two should talk.

💎 This parallel is not as far-fetched as one might think. The Library of Babel, the quintessential Jose Luis Borges short story from his 1941 collection "The Garden of Forking Paths" (a perfect title for our purpose here!), bridges the two worlds. In the Library of Babel, all books already exist (up to a certain length), buried in an ocean of gibberish. So the decisions Chiang is talking about are akin to routing decisions in the Library: which book, which shelf, which section, which octogonal chamber, which floor, ... at all scales. Similarly, if a solution to a mathematical problem "pre-exists", the right sequence of decisions will lead to it. In both cases, the expert (or artist) is the scout, guided by experience, context, intuition, emotions (even in math).