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 vision to turn its electric vehicles into robotaxis.<\/p>\n
CNBC was the <\/span>first to report<\/a> the acquisition. TechCrunch independently confirmed the deal with two unnamed sources, although neither one would provide more information on the financial terms of the deal.\u00a0<\/span><\/p>\n Tesla vehicles are not considered 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.<\/p>\n Instead, Tesla vehicles are \u201cLevel 2,\u201d and its Autopilot feature is a more advanced driver assistance system than most other vehicles on the road today. 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.<\/p>\n Earlier this year, Musk said Tesla would launch an autonomous ridesharing 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<\/a> in July.<\/p>\n 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. In short, these systems allow vehicles to understand the world around them.<\/p>\n The company 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.<\/p>