Energy-Efficient, Annealing Quantum Computers for Machine Learning [RSVP REQUIRED]

This event requires an RSVP; to attend, submit form here

Significant machine learning progress has been realized in the past decade---from performing simple classification tasks to the advent of large language models. The accelerated adoption of deep neural networks can be partly accredited to the computational efficiency and accessibility of graphical processing units (GPUs). This success has resulted in an increased demand for compute-resource alternatives to GPUs.


With the maturation of energy-efficient annealing quantum computing, research is being realized to place annealing quantum processing units (QPUs) as viable technology for machine learning applications. In this workshop, I will introduce annealing quantum computers and its applications in optimization, generative modelling, and general machine learning computations.