Explorer #18: Quantum Computers and A.I. with Scott Aaronson

Dr. Scott Aaronson is Schlumberger Centennial Chair of Computer Science at The University of Texas at Austin, and director of its Quantum Information Center. His research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

For the 2022-2023 and 2023-2024 academic years, he is on leave to work at OpenAI on the theoretical foundations of AI safety.

In this interview, Dr. Aaronson discussed a quantum computer, its comparison to classical computers, and its use cases. He also shared his take on the potential role of quantum computers in Artificial Intelligence.

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TIMESTAMPS
01:45 Misconceptions about Quantum computing
03:00 Quantum Computer vs Classical Computer
08:30 The Schrodinger equation
18:00 What is Quantum Computer good for?
28:45 The look of Quantum computers
43:40 Quantum Error Correction
46:50 Quantum computing in AI
55:25 Would you choose Machin Learning or Quantum Computer for a major
57:50 Take on Michio Kaku’s book Quantum Supremacy….(oh, well)

#quantumcomputer #ScottAaronson

[suzannecarter]

I've been waiting for months for Scott to talk on this subject (QC & AI) - may have missed in Shtetl Optimized. Thanks!

[chrisfarrell]

If Quantum Computing and/or A.I. accomplished but one thing; the solution to the mass production of graphene for industrial scale applications, either or both of them individually or jointly would enormously change the world for the better.
The possibilities for either or both of them changing the world for the worse tragically exists as well.

[chrisfarrell]

I wonder if A.I. and Quantum Computing can together resolve the FRACTAL. Or if there exists an end to the Fibonacci sequence. Then there's Pi....

[snarkyboojum]

Summary: In this conversation, Scott Aaronson discusses the common misconceptions and core concepts of quantum computing. He clarifies that quantum computing is not a magical solution that can solve any problem instantaneously, but rather requires a deeper understanding and problem-solving approach. Aaronson explains the concepts of quantum mechanics, qubits, interference, and the comparison between classical and quantum computing. He also discusses the potential applications of quantum computing in fields such as quantum mechanics, AI, and cryptography. The conversation covers the physical implementation of quantum computers, different approaches to building them, and the concept of quantum supremacy. Aaronson emphasizes the need for better quantum supremacy experiments, the pursuit of error-corrected qubits, and the challenges of integrating quantum computing with AI.

Themes:
1. Core concepts and misconceptions of quantum computing: This theme encompasses the discussion on the concepts of quantum mechanics, qubits, interference, and the common misconceptions surrounding quantum computing, such as the idea that it can solve any problem instantaneously.
2. Potential applications of quantum computing: This theme includes the exploration of the potential applications of quantum computing in fields such as quantum mechanics, AI, and cryptography. It also addresses the question of whether quantum computers can be useful for problems unrelated to quantum mechanics.
3. Quantum supremacy and error correction: This theme focuses on the concept of quantum supremacy, the limitations of current experiments, and the pursuit of error-corrected qubits. It also discusses the challenges in achieving quantum supremacy and the need for better experiments to solidify the quantum victory.

Follow-up questions:
1. Can you provide more examples of potential applications of quantum computing in fields other than quantum mechanics, AI, and cryptography?
2. What are the current challenges in achieving error-corrected qubits, and what advancements are being made in this area?