Platinum
D-Wave Quantum
About D-Wave Quantum
D-Wave is the first commercial supplier of quantum computers, and the first and only to offer dual-platform quantum computing products and services, spanning both annealing and gate-model quantum computing. We help customers realize the value of quantum today through enterprise-grade systems available on-premises and via our Leap™ quantum cloud service.
Product types
- AI Hardware GPUs
- AI Software ML Ops Platform
- Analytics BI Tools
- Cloud Services
- Core AI Infrastructure
Sessions at Ai4 2026
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.
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.
