• How can quantum generative models outperform classical generative models? • How can quantum generative models propose novel, high-quality solutions to complex optimization problems? • How are these methods compatible with future quantum hardware? This session will discuss—and demonstrate—the potential impact of quantum generative models on optimization and other enterprise use cases. Jeffrey Grover, Research Scientist, MIT Christopher Savoie, CEO & Co-Founder, Zapata Computing Christopher Savoie is a published scholar in medicine, biochemistry, and computer science, and his research and business interests over the years have focused on the intersection of machine learning, biology, and chemistry. Christopher is the original inventor of AAOSA, the A.I.-based natural language interface technology used to develop Apple’s Siri. He has led big data analytics efforts at Nissan and has previously founded and served as CEO of technology companies that have been acquired or exited via IPO. He currently sits on the board of the US Quantum Economic Development Consortium (QED-C). Christopher is also a licensed attorney and has served as the Vice-Chairman of the Big Data Committee of the American Bar Association. He is a published legal expert on liability issues surrounding Artificial Intelligence, Big Data, Information Security and Data Privacy. He has also lectured and taught continuing legal education courses on these subjects.  Yudong Cao, CTO & Co-Founder, Zapata Computing Yudong Cao has a background in Mechanical Engineering and Computer Science. He obtained his Ph.D. in Computer Science from Purdue University in 2016, and after graduation, he joined the Aspuru-Guzik group at Harvard University. Yudong’s work at Harvard mainly focused on developing and deploying algorithms for noisy intermediate-scale quantum devices. This work has been the foundation for the applications and solutions that Zapata can offer their enterprise clients today. Today, Yudong continues developing quantum and quantum-inspired algorithms for near-term applications.