Dive into the fundamentals of quantum computing in this 39-minute lecture from MIT's course on TinyML and Efficient Deep Learning Computing. Explore the principles behind this cutting-edge technology and its potential applications in machine learning. Learn how quantum computing differs from classical computing and understand its unique capabilities. Gain insights into quantum bits, superposition, entanglement, and quantum gates. Discover how quantum algorithms can potentially solve complex problems exponentially faster than classical computers. Examine the challenges and opportunities in developing quantum machine learning applications. Access accompanying slides for visual aids and additional information. Part of a comprehensive series taught by Professor Song Han, this lecture provides a solid foundation for understanding the intersection of quantum computing and efficient machine learning techniques.
Overview
Syllabus
Lecture 21 - Basics of Quantum Computing | MIT 6.S965
Taught by
MIT HAN Lab