Tesla sues former employee for theft of trade secrets and attempted cover-up

Tesla is suing a former employee. The man would have stolen secrets concerning the Dojo supercomputer project.

You’re here has decided to sue a former employee whom it accuses of stealing industrial secrets in connection with its supercomputer project, according to an article by Bloomberg. According to the case filed with the San Jose District Court, engineer Alexander Yatskov had resigned on May 2 after only a few months with the company. According to Tesla, the man admitted to transferring confidential information to his personal devices and later to a fake laptop when confronted about the theft.

Tesla sues former employee

In addition to breaking a non-disclosure clause, specifically aimed at protecting its industrial secrets, Bloomberg reports that Tesla is also accusing Alexander Yatskov of having lied about his experience and skills in his resume. Also according to the American daily, Alexander Yatskov declined to comment.

“It is a case of illicit retention of trade secrets by an employee who, with a short stint at Tesla, has already shown his propensity to lie, and to lie again by providing a ‘fake’ device to try to cover his tracks” , Tesla wrote in the filing.

The man allegedly stole secrets about the Dojo supercomputer project

CEO Elon Musk has been teasing a supercomputer project called Dojo since 2019. Last summer, the company unveiled this project in more detail, with the aim of using artificial intelligence to analyze vehicle data, which should allow for an even safer and more successful autonomous driving experience. The computer, which offers 1.8 exaflops of computation and has 10 petabytes of NVME storage at 1.6 terabytes per second, learns itself using video from the eight cameras in Tesla vehicles, at 36 frames per second.

Tesla said last year that while this approach generates huge amounts of data, it’s still more usable than high-definition mapping of the entire world. At the same time, the manufacturer also indicated that the system was more effective in sparsely populated areas where cars can move almost without being interrupted. And even then, the company had shown several very interesting successes in dense areas, including Dojo’s ability to learn new traffic warnings, detect collisions with pedestrians and misuse of pedals – accidental pressing on the accelerator pedal instead of the brake -.

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