Musk, who has crossed swords with Mark Zuckerberg and Jack Ma over the role of AI, is giving the tech some space.
Tesla is developing core algorithms that drive car by creating high-fidelity representation of the world
Tesla CEO Elon Musk, who is a staunch critic of unregulated artificial intelligence (AI), has now hired the technology, turning AI into a subordinate that "reports directly" to him daily.
Musk, who has crossed swords with Facebook CEO Mark Zuckerberg and former Alibaba Chairman Jack Ma over the role of AI, is finally giving the technology some space, like in his startup Neuralink that is creating a brain-machine interface.
Tagging Lex Fridman, popular host of the Artificial Intelligence podcast on YouTube, Musk tweeted: "At Tesla, using AI to solve self-driving isn't just icing on the cake, it the cake" @lexfridman
"Join AI at Tesla! It reports directly to me & we meet/email/text almost every day. My actions, not just words, show how critically I view (benign) AI," the Tesla CEO added.
For him, the AI he is using can only do 'benign' tasks and those jobs too are being evaluated critically by him.
Tesla is using advanced AI for vision and planning, supported by efficient use of inference hardware to achieve a general solution to full self-driving.
The company is building silicon chips that power its full self-driving software from the ground up, taking every small architectural and micro-architectural improvement into account while pushing hard to squeeze maximum silicon performance-per-watt.
The company is applying cutting-edge research to train deep neural networks on problems ranging from perception to control.
"Our per-camera networks analyse raw images to perform semantic segmentation, object detection and monocular depth estimation. Our birds-eye-view networks take video from all cameras to output the road layout, static infrastructure and 3D objects directly in the top-down view," says Tesla.
"Our networks learn from the most complicated and diverse scenarios in the world, iteratively sourced from our fleet of nearly 1 million vehicles in real time. A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train. Together, they output 1,000 distinct tensors (predictions) at each timestep," the electric carmaker added.
The company is also developing core algorithms that drive the car by creating a high-fidelity representation of the world and planning trajectories in that space.
During a recent presentation about Neuralink's brain-machine interface technology, he said: "Even in a benign AI scenario, we will be left behind. [..] Hopefully, it is a benign scenario. But I think with a high-bandwidth brain-machine interface we can actually go along for the ride. And we can effectively have the option of merging with AI."
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