Tesla reportedly buys machine-learning startup DeepScale for self-driving car tech

The purchase could help shore up Tesla's autonomous car efforts.

Sean Szymkowski
It all started with Gran Turismo. From those early PlayStation days, Sean was drawn to anything with four wheels. Prior to joining the Roadshow team, he was a freelance contributor for Motor Authority, The Car Connection and Green Car Reports. As for what's in the garage, Sean owns a 2016 Chevrolet SS, and yes, it has Holden badges.
Sean Szymkowski
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Tesla Smart Summon
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Tesla Smart Summon

Tesla is determined to win the autonomous race without lidar.

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Tesla has big plans in store, if we're to follow CEO Elon Musk's timeframe laid out during the Autonomy Investor Day. In an effort to achieve these goals, the electric-car maker may have made a solid purchase.

CNBC reported Tuesday that Tesla has fully acquired a tech startup company called DeepScale. The startup focuses on computer vision and not on lidar, which many other companies and automakers bank out to give their self-driving car prototypes the gift of sight.

Tesla did not comment on the reported purchase, though CNBC also reported DeepScale CEO Forrest Iandola made a curious announcement on LinkedIn. On the social media network, Iandola confirmed he joined Tesla as a senior staff machine learning scientist. CNBC's sources familiar with the deal reported back saying it wasn't a single hire and that Tesla has, in fact, purchased the startup outright.

DeepScale's approach to autonomy fits the bigger picture Musk has promoted for a few years now. Rather than relying on lidar, Musk has consistently believed cameras, radar and ultrasonic sensors will make up a robust system without other hardware. Powering it all is a new artificial intelligence chip Tesla developed in-house. The chip, detailed this past April, uses minimal power for operation and takes in an absolute massive load of information from the hardware package.

Meanwhile, Tesla also detailed a neural network that will help bring autonomy to life. This strategy also appears to sync well with the reported DeepScale acquisition. This neural network pulls video and images from Tesla vehicles in the real world and learns how to read roads more efficiently and accurately. Human annotation and predictive behavior (more machine learning) power the process. Andrej Karpathy, Tesla's head of AI, earlier stated that the neural network and other hardware will be vastly superior to lidar.

If all goes according to plan, Tesla wants to have a 1 million-strong test network of robotaxis on the roads by the end of 2020. DeepScale could, perhaps, help it get there.

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