Unity accelerates AI training with the release of synthetic datasets

Unity accelerates AI training with the release of synthetic datasets
Ryan is an editor at TechForge Media with over a decade of experience covering the latest technology and interviewing leading industry figures. He can often be sighted at tech conferences with a strong coffee in one hand and a laptop in the other. If it's geeky, he’s probably into it. Find him on Twitter: @Gadget_Ry

Real-time 3D content creation platform Unity is releasing synthetic datasets with the aim of accelerating AI training.

The new Unity Computer Vision Datasets contain synthetic data which is generated to meet specific demands. Unity aims to break down the cost barrier typically faced in obtaining high-quality synthetic datasets.

Dr Danny Lange, SVP of Artificial Intelligence & Machine Learning at Unity, said:

“By creating a synthetic version of datasets that mirror validated privacy rules and accurately reflect real-world data, we enable these groundbreaking datasets to get into the hands of more innovators.

Essentially, these datasets empower companies to plan for and simulate scenarios they haven’t yet experienced, with a sizable increase in user data that mimics what they’d find over time in the real world.

As a result, we’re seeing smarter indoor environments, such as cashier-less grocery stores, and more as our customers discover new applications.”

A technique called ‘domain randomisation’ is used to generate Unity’s datasets. The process outputs permutations of how objects of interest are positioned and orientated, including variances in lighting and camera angles as well as the many other countless configurations Unity enables.

Traditional methods of real-life data collection are labour-intensive and carry a greater risk of privacy issues and biases we’ve seen repeatedly over recent years. Unity’s datasets aim to meet strict privacy and regulatory standards.

“Synthetic data is revolutionising the training of machine learning models as it overcomes many of the shortcomings of manually collected and labelled real-world data,” explains Lange. 

Datasets can either be created by a developer using free access to the Unity Perception SDK – and a library of labelling and randomisation tools – or purchased from Unity’s computer vision experts.

Purchasing datasets is based on a tiered pricing model where the price per image decreases proportionally to the demand for more synthetic images.

“Exploring what’s possible, and connecting creators with the affordable data they need to make the right decisions continues to drive Unity, no matter the industry,” adds Lange.

“This is why our team will be available to assist customers in ensuring that the datasets produced meet the right criteria for their needs.”

More information about Unity’s AI datasets can be found here.

(Image by Comfreak from Pixabay)

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