A theme surfaced when Apple’s director of neural networks research outlined results from several of the company’s recent AI projects on the sidelines of a major convention Friday. Each involved uttering software abilities needed for self-driving cars.
Ruslan Salakhutdinov addressed roughly 200 AI professionals who had signed up for a free lunch and peek at how Apple employments Machine Learning, a proficiency for analyzing big accumulations of data. He discussed assignments using data from cameras and other sensors to spot cars and pedestrians on metropolitan streets, navigate in unfamiliar cavities, and build detailed 3-D planneds of cities.
The talk offered brand-new penetration into Apple’s reticent endeavors around autonomous-vehicle engineering. Apple received a permit from the California DMV to experiment self-driving vehicles in April, and CEO Tim Cook confirmed his interest in such technology in June.
The scale and scope of any vehicle assignment at Apple remains unclear. Salakhutdinov didn’t say how development projects he discussed Friday fit into any wider attempt in automated driving, and a company spokesman declined to elaborate.
Salakhutdinov pictured data from one project previously disclosed in a research paper posted online last-place month. It improved software to identify walkers and cyclists using 3-D scanners called lidars used only for most autonomous vehicles.