Scott Aaronson is a theoretical computer scientist at the University of Texas at Austin, known for his pioneering work on quantum computing and computational complexity. He writes the widely read blog Shtetl-Optimized and has shaped how researchers and the public understand both the possibilities and limits of quantum technology.
We talk about the reality of quantum computing, cryptography, AI progress, large language models, and what the future might look like when these technologies converge. Topics are outlined in the timestamps below.
Watch on YouTube. Listen on Apple Podcasts, Spotify, or wherever you get your podcasts.
Support my work here and follow me on Twitter here
Timestamps
00:00 – Intro
03:25 – How computer science views quantum mechanics today
06:50 – Superconducting qubits and how quantum machines are built
10:15 – The rules of quantum probability explained
13:41 – Quantum error correction and protecting fragile states
17:06 – When quantum algorithms provide a speed-up (and when they don’t)
20:31 – Skepticism and testing the limits of quantum hype
23:56 – Why Scott is optimistic about scalable quantum computing
27:22 – Potential applications: materials, chemistry, and beyond
30:47 – Shor’s algorithm and breaking classical encryption
34:12 – Bitcoin, cryptography, and the risks of a working quantum computer
37:37 – Grover’s algorithm and the reality of search speedups
41:03 – Large language models vs hard computational problems
44:28 – What tasks AI still can’t solve (and how to test them)
47:53 – GPT-4 vs GPT-3: progress, hype, and possible limits
51:18 – How companies train and deploy models responsibly
54:44 – The pace of change since ChatGPT launched
58:09 – Power and danger: capability without aligned goals
1:01:34 – Why AI is not just another technology but a civilizational shift
Share this post