In this episode, I sit down with Dr. Nathan Wiebe from the Department of Computer Science at the University of Toronto. Prof. Wiebe specializes in quantum simulation, machine learning, and quantum computing. We talk about the fundamentals of quantum computing, explore Microsoft’s new “Majorana” quantum chip, and discuss what the future holds for quantum machine learning, error correction, and more. Whether you’re a seasoned researcher or just curious about the world of qubits, this conversation offers insights into the rapidly evolving quantum landscape.

Video Chapters:0:00 - Introduction and Episode Overview0:27 - Quantum vs. Classical Computing2:20 - Interference and Negative Probability Amplitudes5:12 - The Microsoft “Majorana” Quantum Chip14:15 - Topological Qubits vs. Google’s Surface Code19:22 - “Transistor of the Quantum Age?”: Reliability and Error Correction26:36 - Qubit Counts, Gate Overheads, and the Error-Correction Challenge30:17 - Quantum Machine Learning: Hype vs. Reality34:53 - AGI, Large Language Models, and Is Quantum Necessary?37:01 - Real-World Applications: Chemistry and Materials Science43:32 - Beyond Classical AI: Where Quantum Might Help45:16 - Life Advice for Aspiring Scientists52:00 - Final Thoughts and Outro

Thanks for listening, and enjoy the conversation!