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Autonomous cars need data. Lots of data. According to research conducted by the Rand Corporation, they’ll have to drive hundreds of millions or even billions of miles to demonstrate their safety. Companies like Waymo are well on their way; the average self-driving vehicle is projected to generate more than 300 terabytes per year. But collecting data isn’t the only technical hurdle. Labeling it — that is, adding the markup that allows cars’ computer models to recognize and learn from it — is another.

That’s where Scale comes in. The San Francisco-based company, which was founded in 2016 by 21-year-old MIT computer scientist Alexandr Wang, supplies an API that autonomous car manufacturers use to accelerate the data-labeling process. It today announced an $18 million funding round led by Index Ventures, Accel, and Y Combinator.

“Our [new funding] enables Scale to rapidly advance how human intelligence and machine learning can work together to make the once arduous and manual process of creating training data a breeze,” Wang said in a statement. “The success of AI-based applications is inherently dependent on the caliber of the data inputted, and we believe our human and machine integrated system provides customers with the precision needed to power AI applications. We’re proud that leaders in autonomous vehicles (as well as other industries) have made Scale an integral and trusted part of their pioneering work.”

Scale employs a combination of human data labelers and machine learning algorithms to sort through raw, unlabeled streams from clients like Lyft, General Motors, Zoox, Voyage, nuTonomy, and Embark, which it returns as scalable datasets. Its contract workers review image, radar, and lidar data from cars (among other sensor data), ensuring that pedestrians, bicyclists, and other objects on the road are correctly identified and making corrections as needed.

Altogether, Scale’s system has annotated more than 200,000 million miles collected by self-driving cars, and recently expanded its work into robotics, drones, virtual assistants, and “other solutions” that depend heavily on AI.

“Scale has the potential to become the fabric that connects and powers the Artificial Intelligence world,” Mike Volpi, general partner at Index Ventures, said. “For autonomous vehicles in particular, Scale is well-positioned to take over an emerging field of data annotation regardless of which players ultimately come out on top.”

Scale faces stiff competition from the likes of Mighty AI, Appen, Cloud Factory, Samasource, and Amazon’s Mechanical Turk, but Wang believes that it’s well-positioned for growth. It’s raised $22.7 million in funding to date and reports that revenue has grown 15x over the past 12 months.


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