Tech

Tesla sues former employee for allegedly stealing trade secrets and then trying to cover it up


Tesla sued a former employee for allegedly stealing trade secrets related to its supercomputer project, Bloomberg reported on Friday. According to filings with US District Court in San Jose, thermal engineer Alexander Yatskov quit on May 2 after joining the company just a few months earlier, in January. According to Tesla, Yatskov admitted to transferring confidential information to his personal devices and then handing over a “dummy” laptop computer after company officials confronted him on suspicion of having theft.

In addition to violating a non-disclosure agreement to protect trade secrets, Bloomberg reports that Tesla is also accusing Yatskov of misrepresenting his experience and skills on his resume. Bloomberg also said that Yatskov declined to comment.

“This is a case of the unlawful retention of a trade secret of an employee who, during his brief stint at Tesla, demonstrated a record of lying and then later lied by providing a ‘fake’ device to try and cover his tracks,” Tesla wrote in the filing, reporting Bloomberg.

CEO Elon Musk has been teasing Tesla’s supercomputer project, called “Dojo,” since at least 2019. Last summer, the company’s finally explained The project, in more detail, aims to use AI to analyze large amounts of vehicle data, ideally delivering a safer, more refined autonomous driving experience. The computer delivers 1.8 exaflops of performance and 10 petabytes of NVME memory at 1.6 terabytes per second, training itself using video from eight cameras inside a Tesla vehicle running at 36 fps .

Last year, Tesla stated that while this approach generates large amounts of data, it is still more scalable than building high-definition maps around the world. At the time, Tesla showed that the system was most successful in sparsely populated areas where cars could run almost continuously. Even so, the company has also touted some early success in more congested areas, including Dojo’s ability to learn new types of traffic warnings, detect pedestrian collisions, and apply Using the wrong pedal (accidentally pressing the gas instead of the brake).

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