Startup improves AI training procedures for autonomous cars: Page 2 of 2

April 10, 2019 //By Christoph Hammerschmidt
Startup improves AI training procedures for autonomous cars
The startup company (Karlsruhe, Germany) has developed a procedure to improve the training algorithms for self-driving cars; the training thus can be done faster and with better quality. The procedure developed by the startup is also based on artificial intelligence.

Although the image processing process is largely highly automated, the final quality control requires the use of human labor. Kessler emphasizes that the combination of technology and human care is particularly important in safety-critical topics such as autonomous driving. The markings in the image and video representations, also known as annotations, must match the real environment with pixel accuracy. The better the quality of the processed image data, the better the algorithm that trains with it.

"Since it is not possible to provide training images for all situations - accidents, for example - we also create simulations from real data," says Kessler.

For the initial phase, the company wants to focus on the topic of autonomous driving. In the future, also plans to process image data that will be used to train algorithms for tumor recognition or the evaluation of aerial photos. Leading automobile manufacturers and suppliers in Germany and the USA are among the customers of the start-up founded by Kessler together with Marc Mengler in 2017. In addition to its headquarters in Karlsruhe, the young company has more than 50 employees in Berlin and San Francisco. In 2018, a round of private investors provided it with start-up financing amounting to 2.8 million US dollars.

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