Tesla acquires computer vision startup DeepScale in push towards robotaxis

5 years, 2 months ago - 4 October 2019, Autoblog
Tesla acquires computer vision startup DeepScale in push towards robotaxis
Move helps shore up Autopilot team, which has had departures

Tesla has acquired DeepScale, a Silicon Valley startup that uses low-wattage processors to power more accurate computer vision, in a bid to improve its Autopilot driver assistance system and deliver on CEO Elon Musk's goal to turn its electric vehicles into robotaxis.

CNBC was the first to report the acquisition. TechCrunch independently confirmed the deal with two unnamed sources, although neither would provide more information on the financial terms of the deal.

Tesla vehicles are not fully autonomous, or Level 4, a designation by SAE that means the car can handle all aspects of driving in certain conditions without human intervention. Instead, Tesla vehicles are Level 2, and its Autopilot feature is an advanced driver assistance system. Some Tesla owners have regarded it as more than that — at their peril. Musk has promised that the advanced driver assistance capabilities on Tesla vehicles will continue to improve until eventually reaching that full automation high-water mark.

Earlier this year, Musk said Tesla would launch an autonomous ride-sharing network by 2020. DeepScale, a four-year-old startup based in Mountain View, Calif., appears to be part of that plan. The acquisition also brings much needed talent to Tesla's Autopilot team, which has suffered from a number of departures in the past year, The Information reported in July.

DeepScale has developed a way to use efficient deep neural networks on small, low-cost, automotive-grade sensors and processors to improve the accuracy of perception systems. These perception systems, which use sensors, mapping, planning and control systems to interpret and classify data in real time, are essential to the operation of autonomous vehicles. Unlike other automakers, Musk and Tesla are known for eschewing lidar in favor of camera sensors.

DeepScale argued that its method of using low-wattage and low-cost sensors and processors allowed it to deliver driver assistance and autonomous driving to vehicles at all price points.

The company had raised more than $18 million — in $3 million seed and $156 million Series A rounds — from investors that included Autotech VC, Bessemer, Greylock and Trucks VC.

On Monday, DeepScale's co-founder Forrest Iandola posted an announcement on Twitter and updated his LinkedIn account. The Twitter message read, "I joined the @Tesla #Autopilot team this week. I am looking forward to working with some of the brightest minds in #deeplearning and #autonomousdriving."

I joined the @Tesla #Autopilot team this week. I am looking forward to working with some of the brightest minds in #deeplearning and #autonomousdriving.

— Forrest Iandola (@fiandola) October 1, 2019

In Tesla's push towards "full self-driving," it developed a new custom chip designed to those capabilities. This chip is now in all new Model 3, X and S vehicles. Musk has said that Tesla vehicles being produced now have the hardware necessary — computer and otherwise — for full self-driving. "All you need to do is improve the software," Musk said in April at the company's Autonomy Day.

Others in the industry have balked at those claims. Tesla and Musk have maintained the "improve software" line, and have continued to rollout improvements to the capability of Autopilot. Earlier this month, Tesla released a software update that adds new features to its cars. The update included Smart Summon, an autonomous parking feature that allows owners to use their app to summon their vehicles from a parking space.

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