Deep learning, an advanced form of artificial intelligence and dynamic way of computerized decision-making, is driving significant change for autonomous cars and for the automotive and transportation industry. In fact, a new KPMG report projects that by 2030 a new mobility services segment tied to products and services related to autonomy, mobility, and connectivity will be worth well over $1 trillion globally.
The new KPMG report titled "I see. I think. I drive. (I Learn)," notes that the direct impacts of deep learning will revolutionize the nature of doing business for automakers. Deep learning is a critical enabler of building a self-driving vehicle that can operate without human intervention. Underlying those efforts is the need for the vehicle to "see," "think," "drive," and "learn." It is through this last "learning" step where deep learning will be critical to achieving fully autonomous cars.
"Deep learning is accelerating autonomy faster than anyone could've imagined, and it has far-reaching implications for the industry and societal mobility as a whole," said Gary Silberg, KPMG's national automotive leader. "If a car can't learn, then it's still reliant on millions and millions of lines of code, with such complexity and ambiguity, that full autonomy wouldn't be achievable for many years to come."
Silberg feels that "it is a new era in automotive product development and manufacturing—one that emphasizes the car's nervous system, which includes computer "brain," sensors, controls, driver interaction and data storage even more than the powertrain. This is an enormous shift in organizational structure, talent acquisition, and operating model for most car manufacturers."
According to KPMG, this is a critical juncture in the history of the auto industry - as OEMs and tech companies face off in a war for specialized talent. People with deep learning expertise are in short supply, and the pool of experts among those specialists is even smaller. This makes it difficult for traditional automakers to compete with tech leaders. In addition, universities cannot keep pace with the autonomous driving market demands for talent.
"Automakers always owned the "secret sauce" of the vehicle," said Tom Mayor, Industrial Manufacturing Strategy Practice Leader at KPMG. "But with deep learning, somebody else has it, and for car companies to control the algorithms driving the vehicle, they will need the people who design them. The problem is, deep learning specialists are not exactly flocking to the auto industry."
In the research, KPMG identifies the key developments for automakers to contemplate if they are to survive:
For more information, download the full report below.
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