The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Pragmatic Quantum Machine Learning with Peter Wittek - TWiML Talk #245
Apr 1, 2019
In this engaging discussion, Peter Wittek, an Assistant Professor at the University of Toronto and a leading expert in quantum-enhanced machine learning, shares insights into the current state and future of quantum computing. He explores the transition from theoretical mathematics to practical applications in machine learning. Peter also highlights the fundamental differences between quantum and classical computers, the promise of hybrid algorithms, and the significance of his new online course for practical learning in this revolutionary field.
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Digital Computing Basics
- Digital computers decompose algorithms into elementary operations like addition and multiplication.
- These operations are deterministic, transforming bit strings in a universal manner.
Quantum Computing Basics
- Quantum computers operate on probability distributions over bit strings, not directly on bit strings.
- This makes quantum computation inherently probabilistic, yielding slightly different results each run.
Qubits vs. Bits
- Digital CPUs use 64-bit registers for localized operations, limiting problem size.
- Quantum computers use thousands of qubits, enabling global problem consideration.