James (“Brad”) DeLong - Quantum Country interview - 2019-11-22

https://quantum.country/debug/userJourney?email=brad.delong@gmail.com
brad.delong@gmail.com
delong@econ.berkeley.edu

Brad has been using Quantum Country since March. He’s finished the 2 months level for QCVC and almost in search. James is a prominent economist blogger and a Patreon, who found us via Tyler. He’s done 34 review sessions!

Highlights

  • Brad feels the proof is in the pudding: he can remember all the details of the quantum material he read on Quantum Country, and that lets him discuss the material more deeply than other material (e.g. Feynman’s QED lectures) he thought he’d understood.
    • “I think I know this shit, but of course I don’t know this shit. All I know are Feynman’s wiggly lines, which allow me to make fairly accurate qualitative predictions. I have a simple mental model, … but when someone asks me a more complex question […] you get stuck with what it is to have a ‘good enough’ mental model”
  • Berkeley has a new division of data science which he thinks should fun us.
  • He likens the mnemonic medium to a “catechism.” A striking comparison.

Raw notes

  • mnemonic medium as “catechism”
  • the Primer
    • “the ideal combination of book and reference library and tutor and AI aid” “the ideal educational process” “very little hardware, very little expense"
    • “individuals think they have agency but they don’t”
    • “to give people victories”
    • “to make people well aware that the answer is not necessarily out there”
  • What’s the relationship between “the problems to be solved are not ones which they can do by memorizing a bunch of stuff from some book” and enthusiasm about "the catechism"
    • Berkeley is the CostCo of universities; Stanford is the Whole Foods
    • “your business in the lecture is to get as much info as possible through to the ears and eyes… then you realize that if you say something in the lecture, their retention is shit"
  • why memorize? why not just let people look it up?
    • “at the moment, they still can’t really remember what the Pauli matrices are”
    • …then Brad recites lots of details from the teleportation essay…
    • “that’s a deeper understanding of what’s going on than ‘you have to do some widgy widely QM stuff’”
    • thinks the catechism was very important to being able to recite in all that detail “otherwise it wouldn’t stick”
    • before he had a vague understanding about QM’s “action at a distance”
    • “now I have a fairly deep understanding of the system”
    • produced a fair amount of detail about QED from Feynman, even though there wasn’t a catechism
    • “I think I know this shit, but of course I don’t know this shit. All I know are Feynman’s wiggly lines, which allow me to make fairly accurate qualitative predictions. I have a simple mental model, … but when someone asks me a more complex question […] you get stuck with what it is to have a ‘good enough’ mental model”
    • example of new tax code:
    • thinks he knows what will happen based on the tax code, but “in fact I don’t know,” just draws models, “it works most of the time, and sometimes it doesn't work"
    • mental models acquired while playing war games wasn’t real understanding—instead, it meant I understood what was possible in the system that the creator made. it feels like you did it but you didn’t
    • but the detailed understanding he’s absorbed about QC feels different: it feels like a real understanding
  • what does progress feel like?
    • “well, it does work.” how do you know?
    • “I can see in my mind’s eye: [long description etc]”
    • “if you asked me about my understanding about teleportation before this, I would not have had that in my mind’s eye”
    • how does it feel as concepts become more durable?
    • “there was a time when I didn’t know that the derivative of log(x) was 1/x … but then it became something obvious, something I don’t even have to think about"
  • so what? why does this matter?
    • “why do anything? I have tenure!!”
    • “I do it because I think it’s fun”
  • there’s a new division of data science which Brad thinks should fund us
Last updated 2023-07-13.