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Synthetic data for computer vision and perception
Open for applications
Synthetic data for computer vision and perception
21-100 employees
Open for applications
More information about location
21-100 employees
To bridge the gap between simulation and the real world, ensuring autonomous systems perform flawlessly when it counts most.
Desirable
Autonomous vehicles are fast making the leap from science fiction to reality. However, there are huge safety implications that need to be addressed. Parallel Domain has developed software for training autonomous vehicles in a virtual setting, reducing the risks associated with real-world testing and giving vehicle manufacturers the ability to identify problems and put them right, before the vehicle ever hits the road.
Founded in 2017, Parallel Domain leverages synthetic data to train and test the vision and perception systems for AVs. Clients can customise training environments with parameters such as weather, lighting, and distribution of agents, allowing them to model specific situations, including rare ones that would be unlikely to occur in real-world training. This results in AIs that behave better and more safely in novel situations.
Parallel Domain has seen significant investment that is fuelling operational expansion and increase business reach. With the value of synthetic data quickly becoming apparent, the company is positioned well to benefit from those wishing to train their autonomous vehicle AIs faster and more efficiently.

Steph
Company Specialist at Welcome to the Jungle
62% employee growth in 12 months
Nov 2022
$30m
SERIES B
Dec 2020
$11m
SERIES A
Financial District, San Francisco, CA
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