Apple is still interested in self-driving cars as it explores ‘revolutionary’ LIDAR sensor design
Apple’s automotive initiative, unofficially dubbed Project Titan, appears to still be alive and kicking. According to a report from Reuters, Apple is currently looking into advanced lidar sensor technology that “would be smaller, cheaper and more easily mass produced than current technology.”
What’s more, the report relays that Apple, in addition to exploring third-party solutions, also has a team of engineers working on developing an Apple-branded lidar sensor.
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While it remains to be seen if anything comes of Apple’s exploration, the larger point here is that Apple still has grand ambitions in the automotive space. This may come as something of a surprise given the series of layoffs Apple’s Project Titan has endured over the past few years.
Just about three months ago, for instance, word surfaced that Apple cut upwards of 200 employees from the Project Titan team. Far more than a rumor, Apple at the time confirmed the cuts and issued the following statement to various media outlets:
We have an incredibly talented team working on autonomous systems and associated technologies at Apple. As the team focuses their work on several key areas for 2019, some groups are being moved to projects in other parts of the company, where they will support machine learning and other initiatives, across all of Apple.
We continue to believe there is a huge opportunity with autonomous systems, that Apple has unique capabilities to contribute, and that this is the most ambitious machine learning project ever.
At this point, it will be fascinating to see what, if anything, ever comes out of Project Titan. As far as we can tell, Apple has abandoned any desire to design and release a car from the ground-up and has instead opted to focus on self-driving car technologies.
To this end, Tim Cook himself acknowledged this nearly two years ago when he told Bloomberg: “We’re focusing on autonomous systems. It’s a core technology that we view as very important. It’s probably one of the most difficult A.I. projects actually to work on.”
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