The majority of computing devices today process data in a temporal manner that leads to numerous bottlenecks and efficiencies. While AI systems have provided transformative capabilities over the past several years, the computational cost associated with training is extraordinarily large with respect to both computational power and the energy essential to running the hardware. Quantum devices clearly can lead to new computational paradigms that could overcome these limitations. In the case of quantum computation, there are classes of problems where an exponential speedup has been found that could provide both a faster and a more energy efficient solution. However, in addition to general purpose quantum computation there are proposals to build neuromorphic hardware out of quantum devices that would significantly lower both the costs and time required. Today’s sessions will explore the intersection of quantum computing, neuromorphic computing, machine learning and anomaly detection for transformative computation tasks that provide both faster time and far more energy efficient solutions.

Moderator

Mark Wippich CEO MPW (United States)

Panelists

Charina Chou COO Google Quantum AI (United States)

Nicholas Harrigan Marketing Lead Quantum Computing nVidia (United States)

Nathan Gemelke Co-founder, Chief Technology Strategist QuEra (United States)

Jeffrey Shainline Founder and CEO Great Sky (United States)

Michael Förtsch CEO Q.ANT (Germany)

 

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Event Details

FORMAT: Panel discussion followed by audience Q&A.
MENU: Coffee, decaf, and tea will be available nearby.
SETUP: Theater style seating.