Our simulation platform generates synthetic data to help businesses improve their machine learning algorithms.
HOW AI WORKS
To understand the world, AI must first learn about the world.
How it works
Machine learning enables AI to be trained directly from images, sounds, text and other data. It is what enables driverless cars to see the roads, smart devices to listen and respond to voice commands, and digital services to offer recommendations on what to watch.
The success of deep learning, a way to approach machine learning, has brought an insatiable hunger for data. The performance of deep learning often correlates with the amount of data used in training.
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.
With synthetic data, a fully scalable data solution is now at our fingertips — at a fraction of the cost. By simulating the real world, virtual worlds create synthetic data that is as good as, and sometimes better than, real data.
The Value of Synthetic Data
- Gives Control: Easily creates customized datasets based on unique objects, varying perspectives, rare scenarios and custom sensors.
- Lower Costs: Avoids the expensive process of annotating data by hand by generating annotations automatically in real time.
- Provides Scale: Delivers unlimited training data needed to get the best level of performance.
- Accelerates Development: Removes barriers to entry by providing easy access to training data needed to start training AI applications.
- Enhances Data: Overcomes bias found in real data by adding diversity to help with generalization.
Power AI Applications
We provide data and vision APIs to improve machine learning algorithms.
What We Offer
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.
Diverse Objects & Scenarios
We offer diverse images and scenarios to help algorithms generalize well.
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.
We provide fully annotated synthetic data- at scale and error free- that saves time, lowers costs, and be used to immediately train AI.
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.
"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