Creative Destruction Lab Partners with Xanadu to Accelerate Quantum Machine Learning
Companies in CDL’s Quantum Machine Learning Program will leverage Xanadu’s Strawberry Fields – a machine learning toolbox for quantum computing, powered by TensorFlow.
Xanadu and the Creative Destruction Lab (CDL) at the University of Toronto’sRotman School of Management are pleased to announce a technology partnership. Ventures in CDL’s Quantum Machine Learning (QML) program will receive access and hands-on technical support to Xanadu’s Strawberry Fields, an open-source quantum software package featuring a quantum machine learning toolbox for quantum computing built on TensorFlow.
“CDL brings together the world’s greatest concentration of quantum technologists, software programmers, and investors. We’re thrilled to support the program and its entrepreneurs as they develop real world applications for quantum computers,” said Nathan Killoran, Head of the QML team at Xanadu. “Our built-in TensorFlow backend, machine learning toolbox, and interactive interface allow users to start programming a quantum computer and generating machine learning models without requiring a deep knowledge of quantum circuits.”
“Quantum machine learning is a nascent field, not only as a potential application for quantum computing but also as a tool to develop and program quantum processors,” said Daniel Mulet, CDL’s Associate Director who leads the program. “Xanadu’s dedicated QML team is developing new algorithms leveraging a photonic architecture for deep learning. They will support up to 25 projects this year and we look forward to the scalable, high-growth technology companies that will emerge.”
As CDL’s first photonic-based partner, Xanadu will help expand the options of quantum systems available for algorithm development for start-ups in the program. “Xanadu joins Founding Technology Partner D-Wave Systems, and California-based Rigetti Computing. Alumni from the first cohort of quantum companies are tackling complex challenges such as designing efficient materials for OLEDs and predicting protein folding to create novel drugs,” said Mulet. “It will be interesting to see how our companies will use Strawberry Fields to create innovative solutions to some of the most computationally complex problems.”