OUR MISSION
Our simulation platform generates synthetic data to train and improve machine learning algorithms.
The success of deep learning, a way to approach machine learning, has brought an insatiable hunger for data. However, data at scale is often proprietary, expensive, and laborious for people to manually prepare. The best way to deal with these challenges is with synthetic data — data created in virtual worlds rather than collected from the real world.
Video Demo: AI.Reverie Simulation Platform
Our Services
We partner with businesses across industries to support their unique training data needs.
scale
We build photorealistic virtual worlds to closely mimic any real location where our client's services are being used.
Photorealism ensures that our synthetic data is effective in training AI to operate in the physical world. Because simulations are easier to control, these virtual worlds are the best place to test, train, and improve AI.
DIVERSITY
We offer diverse images and scenarios to help algorithms generalize well and reduce bias.
Photorealistic objects, difficult to reach places such as underwater locations, hard to replicate scenarios like extreme weather, varying perspectives from top down to bottoms up, costly real world tests like crashes all become easily simulated in virtual worlds.
ACCURACY
We provide fully annotated synthetic data that can be used to immediately train machine learning algorithms.
Annotations such as 2D and 3D bounding boxes, semantic and instance level segmentations, surface normals, depth masks, edge masks, velocity annotations are all automatically generated in real time.
Synthetic data is a powerful method for training AI because of its scalability and flexibility.
Implementing solutions to narrow AI problems is expensive, but there is great potential in overcoming them using a synthetic data approach — data derived from a virtual photorealistic world that we’ve been pioneering at AI.Reverie.
Preview: The Value Of Synthetic Data (5:00 minutes)
Our Talks
Unreal Engine in Autonomous Vehicle Simulation
Nvidia GTC DC, Washington, D.C., October 22, 2018
How to Augment Sparse Training Data Sets With Synthetic Data
O’Reilly AI Conference, London, UK, October 10, 2018
Fake It To Make It: Augmenting Sparse Training Sets with Synthetic Data
UX+Data Meet Up, New York, NY, July 9, 2018
View Video (45 minutes).
Our Investors
"AI.Reverie will be able to accelerate the performance of vision algorithms across many vertical markets, at scale and low cost and we are excited to be their partners."
Raanan Bar-Cohen, Co-Founder at Resolute Ventures
Tell us about your data needs.
