Keith adds that Intel will aim to use its hardware expertise to develop the increasingly sophisticated fusion systems—combining cameras, radar, and possibly laser sensing, or lidar—needed bring fully automated vehicles to market.

If your car is capable of identifying a road sign or a pedestrian on the road ahead, there’s a good chance it already uses one of Mobileye’s chips for the task. The company’s vision systems are a simple, low-cost solution that offers surprisingly sophisticated sensing.

The company therefore offers Intel a good way into the automated driving market, which promises to grow as the technology matures in the coming years.

For its vision system, Mobileye employs deep learning, a machine-learning technique that has given computers powerful new capabilities in recent years. This involves capturing images as cars drive around, and annotating them to identify things like road markings, traffic signs, other vehicles, and pedestrians. The images are fed into a big neural network, which is tweaked until it can reliably recognize the relevant elements of an image. If Mobileye’s system is unable to identify something, it’s usually possible to simply annotate some new images and add them to the learning data set.

This isn’t to say that it’s perfect, or all that’s needed for automated driving. Tesla had been using Mobileye’s vision technology for its Autopilot semi-automated driving system until last year. The companies ceased working together after a fatal accident involving a car controlled by Autopilot. In the fallout from the crash, the carmaker criticized the vision system provided by Mobileye. Executives from Mobileye countered that its technology was never meant to be used in this way.

Technology now under development at Mobileye could help automated cars drive more safely in the future. In December, I met with Amnon Shashua, Mobileye’s CTO, and Shai Shalev-Shwartz, VP for technology. They explained how Mobileye is now using reinforcement learning, a technique inspired by the way animals learn through experience, to teach computers how to drive safely in complex and subtle situations (see “10 Breakthrough Technologies 2017: Reinforcement Learning”).

As part of this effort, Mobileye is developing a simulated driving environment to enable learning. It hopes this will become the standard environment for testing automated driving software. They also explained that Mobileye is working with several carmakers on a way for them to share the data collected with other companies for a price. This could help accelerate (no pun intended) progress toward fully automated driving.

The result could be a transformation of transportation as we know it. Indeed, the prospect of profound disruption has caused a stampede for technology and talent among automakers, suppliers, and startups.

Stephen Zoepf, executive director of the Center for Automotive Research at Stanford, agrees that Intel’s acquisition of Mobileye shows how critical data and machine learning are to the auto industry’s future. But he adds, “It’s also evidence of the degree to which demand for talent is outstripping supply in the autonomous vehicle space.”