Toyota plans to spend $2.8 billion to make sure its system for writing the software for self-driving cars will be just as efficient as the factories that build them, according to Bloomberg.
The company needs faster and more reliable methods for writing software because self-driving cars require “millions and millions’’ of lines of computer code, according to James Kuffner, who’ll lead the new effort. That compares with tens of thousands of lines of code in cars just a generation ago.
The Japanese automaker is seeking an edge over rival car giants as well as newcomers such as Waymo as the industry charts a path toward self-driving vehicles. Kuffner said he plans to hire 1,000 programmers as soon as he can find them, seeking to lure global talent.
For the effort, Toyota is setting up a new company in Tokyo with two of its suppliers. On Friday, Kuffner was named chief executive officer of the venture, called Toyota Research Institute - Advanced Development.
Toyota had already allocated $1 billion to start a free-standing unit called Toyota Research Institute in 2015 to study self-driving, robotics and artificial intelligence. Kuffner, 47, has been serving as chief technology officer for TRI, which now has about 250 employees. Before that, he was the leader of robotics and cloud computing research at Alphabet’s Google unit.
Toyota’s two biggest suppliers, Denso and Aisin Seiki, will invest in the new venture, each taking a five percent stake, the carmaker said. Currently, Kuffner said, teams of programmers work in isolation to solve portions of a big problem like self-driving and then spend “years and years’’ piecing their work together and testing it with AI and other tools. Toyota plans to streamline this process by validating each chunk of software as it’s written to make sure it’s robust enough for the cars and trucks that Toyota sells to the public.
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Siniša Krajnović, PhD, President of the Management Board of ENT, sees the transformation brought about by artificial intelligence through products, internal processes, and changes in the way work itself is performed, while Jelena Jurišić, Director of Technology of the ENT Group (CTO), explains how specialized AI agents are now part of analysis, design, implementation, testing, and verification. In such a model, autonomy increases gradually, with quality control and human decision-making at critical points. At the same time, the change does not diminish the importance of engineers, but increasingly shifts their role toward architecture, domain understanding, and the management of complex automated systems.
