Delbert Murphy joins Scott Hanselman to show how quantum-inspired algorithms mimic quantum physics to solve difficult optimization problems.
Quantum-Inspired optimization (QIO) takes state-of-the-art algorithmic techniques from quantum physics and makes these capabilities available in Azure on conventional hardware, and callable from a Python client. You can use QIO to solve problems with hundreds of thousands of variables, combined into millions of terms, in a few minutes, with this easy-to-consume Azure service.
- 0:00 – Introduction
- 0:40 – What problems can you solve with quantum-inspired optimization?
- 5:35 – A concrete example: Secret Santa
- 8:52 – Demo, Part I: Solving Secret Santa with QIO
- 17:58 – Demo, Part II: Running the code
- 21:12 – Quantum-inspired algorithms
- 24:33 – Wrap-up
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