{"id":2187,"date":"2021-01-10T13:00:24","date_gmt":"2021-01-10T13:00:24","guid":{"rendered":"https:\/\/thenextweb.com\/?p=1333500"},"modified":"2021-01-10T13:00:24","modified_gmt":"2021-01-10T13:00:24","slug":"apples-self-driving-car-plans-could-change-the-entire-company","status":"publish","type":"post","link":"https:\/\/www.londonchiropracter.com\/?p=2187","title":{"rendered":"Apple\u2019s self-driving car plans could change the entire company"},"content":{"rendered":"\n

What would an Apple-made self-driving car look like? We don\u2019t know yet, but what we do know is that the company has serious plans to roll out its own <\/span>electric self-driving car by 2024<\/a>.<\/p>\n

Apple hasn\u2019t officially confirmed any of the information disclosed in the Reuters reports that broke the news last week. And we are still missing many details on the company\u2019s self-driving plans. Nonetheless, the news is significant, both for Apple and the self-driving car industry.<\/p>\n

Depending on how the situation unfolds in the next months and years, the fact that there\u2019s a concrete date for Apple\u2019s self-driving car plans can indicate the company is making a fundamental change to its product-development strategy.<\/p>\n

The current state of self-driving car technology<\/h2>\n

The history of self-driving cars is very much reflective of the decades-long search for <\/span>artificial general intelligence<\/a> <\/span>(AGI): the finish line always seems to be around the corner. But the closer we get to it, the harder it becomes.<\/p>\n

Like many of today\u2019s AI technologies, self-driving cars have their roots in the 1970s and 80s. But until recent years, they were only limited to academic and military research labs and science contests. In the 2010s, advances in <\/span>deep learning<\/a> <\/span>have led to great improvements in <\/span>computer vision<\/a>, one of the key technologies powering self-driving cars. We\u2019re finally seeing cars that can drive themselves in real streets.<\/p>\n

[Read: Meet the 4 scale-ups using data to save the planet<\/span><\/a>]<\/em><\/p>\n

Deep learning algorithms have helped self-driving cars come a long way toward navigating challenging environments. But the <\/span>technology is far from perfect<\/a>. Deep learning models are only as good as their training data. If the data is representative of all the situations the self-driving car will face, then it will have a robust performance. But the AI\u2019s actions will become unpredictable when faced with edge cases, novel situations that happen rarely, such or a fire truck parked at <\/span>an odd angle<\/a> <\/span>or an overturned car.<\/p>\n

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