Apple recently published details of system called VolexNet, which is capable of recognizing pedestrians and vehicles from a 3-D data.

At a private workshop held this week for AI researchers, Apple researchers gave a rare glimpse of some machine-learning technology they’re building for self-driving cars.

Speaking to an exclusive audience of researchers in the field, Ruslan Salakhutdinov, Apple’s director of AI, discussed several projects apparently related to automated driving.

The technical talks were given Friday during the Neural Information Processing Systems conference, the largest AI-focused academic event of the year, which was held in Long Beach, California. The event attracted thousands of researchers, including many from rival tech companies. The talks were designed to showcase Apple’s technical prowess and to woo potential recruits.

Salakhutdinov, who joined Apple in 2016 but still holds a post as a professor at Carnegie Mellon University, showed off a project previously disclosed in a paper posted online by Apple last month. This project trained a system to recognize pedestrians and other vehicles from 3-D point cloud information.

Other projects not previously revealed included a method for classifying different objects on the road using cameras placed on top of a vehicle, and a method of using camera footage to track its position very precisely. This technique, known as visual SLAM (simultaneous location and mapping), could be used for autonomous driving but also for augmented and virtual reality.