While I love mathematics and physics, I pretty much never consume audiovisual content (e.g. podcasts and YouTube videos) on math and physics. In practice, it seems that my interest in technical topics is bimodally-distributed. Either I’m interested enough that I will take the time to check out the Wikipedia articles and skim through a recommend textbook. Or I’m not that interested such that even channels with great presentation like Numberphile will fail to hold my attention. I also think that I have some sort of auditory processing disorder whose effects are pronounced when consuming technical material. I can very rarely follow along during scientific talks or when I am in class. I actually managed to get through the entirety of elementary school, middle school, high school, undergrad, my masters, and the coursework of my PhD without learning how to take notes from a lecturer (though I take decentish notes from a textbook).

But there are exceptions. And I want to recommend one of my favorite YouTube channels: The Cartesian Cafe. The Cartesian Cafe is a YouTube channel dedicated to long-form in-depth interviews with some of the leading minds in mathematics, physics, and computer science. It’s hosted by Timothy Nguyen who has a math PhD from MIT and currently works as a machine learning researcher at Google Deepmind. Tim is a talented interviewer with a great selection of guests. Some of them are known quantites among Very Online math & physics nerds (like John Baez and Scott Aaronson). But other guests (like Greg Yang) were obscure to me before the Cartesian Cafe introduced me to their work.

I would say the main strengths of the podcast are twofold. One strength is that Tim’s technical background allows him to engage with the intellectual work of his wide-ranging guests in a substantive way. I mentioned that Tim has a math PhD from MIT, but if you actually look at his Google Scholar page, you will see that he spent his PhD working on the more mathematical aspects of quantum field theory. And after his PhD, he transitioned to machine learning. Due to working on some many different STEM fields in his short career, he has a remarkable ability to talk intellegently about different topics.

The second strength of the podcast is its “gimmick” or its hook: the pedagogy. After the introductions and personal background is out of the way, the whiteboard comes out! Rather than just talking about what the guest is working on, Tim invites the guest to walk through some of the basic concepts in their field. So you will be treated to small little mini-lessons like Scott Aaronson giving a mini-crash course on quantum computing.

I would guess the closest analog to Tim’s content is probably Sean Carroll’s podcast. Though here I’m only guessing: I’ve never actually watched Sean Caroll give an interview with any of his more technical guests.

I definitely recommend you check it out!