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Scott Aaronson: Quantum Computing | Lex Fridman Podcast #72

Scott Aaronson is a professor at UT Austin, director of its Quantum Information Center, and previously a professor at MIT. His research interests center around the capabilities and limits of quantum computers and computational complexity theory more generally. This episode is presented by Cash App. Download it & use code "LexPodcast": Cash App (App Store): https://apple.co/2sPrUHe Cash App (Google Play): https://bit.ly/2MlvP5w This episode is also supported by the Techmeme Ride Home podcast. Get it on Apple Podcasts: https://apple.co/2vIbh1k or find it by searching "Ride Home" in your podcast app. PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4 Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41 OUTLINE: 0:00 - Introduction 5:07 - Role of philosophy in science 29:27 - What is a quantum computer? 41:12 - Quantum decoherence (noise in quantum information) 49:22 - Quantum computer engineering challenges 51:00 - Moore's Law 56:33 - Quantum supremacy 1:12:18 - Using quantum computers to break cryptography 1:17:11 - Practical application of quantum computers 1:22:18 - Quantum machine learning, questinable claims, and cautious optimism 1:30:53 - Meaning of life CONNECT: - Subscribe to this YouTube channel - Twitter: https://twitter.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/LexFridmanPage - Instagram: https://www.instagram.com/lexfridman - Medium: https://medium.com/@lexfridman - Support on Patreon: https://www.patreon.com/lexfridman

Lex FridmanhostScott Aaronsonguest
Feb 16, 20201h 33mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Scott Aaronson Demystifies Quantum Computing, Supremacy, and Real-World Impact

  1. Scott Aaronson and Lex Fridman explore why big philosophical questions matter to working scientists and how math and physics make progress by reframing them into tractable sub-questions (“Q‑primes”).
  2. Aaronson then gives an accessible but technically grounded tour of quantum mechanics as a generalization of probability, introducing amplitudes, interference, qubits, decoherence, and quantum error correction.
  3. They discuss the current “noisy intermediate-scale quantum” (NISQ) era, Google’s quantum supremacy experiment, what supremacy does and does not prove, and why breaking today’s cryptography is still far off.
  4. The conversation closes on realistic applications (especially quantum simulation for chemistry and materials), common hype and charlatanism in the field, and Aaronson’s personal views on meaning, purpose, and scientific progress.

IDEAS WORTH REMEMBERING

5 ideas

Use ‘Q‑prime’ questions to make philosophical riddles scientifically tractable.

Aaronson argues that progress on big questions (free will, consciousness, machine intelligence) usually comes from carving off precise, answerable sub-questions—like how well physical laws allow us to predict human behavior—rather than attacking the metaphysical question head-on.

Quantum mechanics is best viewed as modified probability with complex amplitudes.

Instead of just nonnegative probabilities, quantum states assign complex amplitudes to possibilities; when these amplitudes evolve and interfere (constructively or destructively), we get counterintuitive phenomena like the double-slit experiment and the power behind quantum computation.

The power of quantum computing comes from choreographing interference, not ‘trying all answers in parallel.’

A quantum computer can put exponentially many potential answers into superposition, but naïve measurement yields only a random one; useful algorithms carefully arrange interference so that wrong answers cancel out while right answers’ amplitudes reinforce.

Decoherence is the central engineering obstacle to scalable quantum computers.

Any unwanted interaction with the environment effectively ‘measures’ qubits and destroys superposition, so practical quantum hardware must balance isolating qubits from the universe while still controlling and coupling them precisely.

Quantum error correction enables reliability from unreliable qubits, but at huge overhead.

Theory shows that if physical error rates are below a threshold, logical qubits can be encoded across many physical qubits to suppress errors; however, current schemes would require millions of high-fidelity physical qubits to do tasks like breaking RSA, far beyond today’s 50‑ish‑qubit devices.

WORDS WORTH SAVING

5 quotes

The entire trick with quantum computing is that you try to choreograph a pattern of interference of amplitudes.

Scott Aaronson

Anything that quantum computers can do can also be done by classical computers, albeit exponentially slower in some cases.

Scott Aaronson

Quantum supremacy is already enough by itself to refute the skeptics who said a quantum computer will never outperform a classical computer for anything.

Scott Aaronson

We know how to do in theoretical computer science... we don’t know how to prove that most of the problems we care about are hard, but we know how to pass the blame to someone else.

Scott Aaronson

Again and again, I’ve undergone the humbling experience of first lamenting how badly something sucks, then only much later having the crucial insight that its not sucking wouldn’t have been a Nash equilibrium.

Scott Aaronson, as quoted by Lex Fridman

The role of philosophy and “Q‑prime” questions in science and computer scienceFoundations of quantum mechanics: amplitudes, superposition, interference, and measurementWhat qubits are, physical implementations, and the problem of decoherence and noiseQuantum error correction, fault tolerance, and the NISQ (noisy intermediate-scale quantum) eraQuantum supremacy and Google’s 53‑qubit sampling experimentQuantum computing’s impact on cryptography and post‑quantum cryptographyRealistic applications (especially quantum simulation) versus hype, including quantum machine learning

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