Quantum Machine Learning Using PennyLane – with Nathan Killoran from Xanadu

Quantum machine learning, or QML, is one of the three major application categories for quantum computing, along with optimization and simulation. As we’re working with customers at Protiviti to find advantageous use cases in QML, we rely daily on a tool called PennyLane from Xanadu. Join host Konstantinos Karagiannis, and special cohost Emily Stamm, for a chat with Nathan Killoran from Xanadu to learn about this powerful, free software.For more on Xanadu, visit https://www.xanadu.ai/.For more on PennyLane, visit https://pennylane.ai/.To read the paper “Is quantum advantage the right goal for quantum machine learning?” visit https://arxiv.org/abs/2203.01340.Visit Protiviti at www.protiviti.com/postquantum to learn more about how Protiviti is helping organizations get post-quantum ready.Follow host Konstantinos Karagiannis on Twitter and Instagram: @KonstantHacker and follow Protiviti Technology on LinkedIn and Twitter: @ProtivitiTech. Questions and comments are welcome! Theme song by David Schwartz, copyright 2021.Visit Protiviti at www.protiviti.com/US-en/technology-consulting/quantum-computing-services to learn more about how Protiviti is helping organizations get post-quantum ready.  Follow host Konstantinos Karagiannis on all socials: @KonstantHacker             Questions and comments are welcome!  Theme song by David Schwartz, copyright 2021.  The views expressed by the participants of this program are their own and do not represent the views of, nor are they endorsed by, Protiviti Inc., The Post-Quantum World, or their respective officers, directors, employees, agents, representatives, shareholders, or subsidiaries.  None of the content should be considered investment advice, as an offer or solicitation of an offer to buy or sell, or as an endorsement of any company, security, fund, or other securities or non-securities offering. Thanks for listening to this podcast. Protiviti Inc. is an equal opportunity employer, including minorities, females, people with disabilities, and veterans.