Data success depends on a clearly articulated strategy with defined objectives, data prioritization, and the right analytical tools. With this in place, data projects can secure the impact companies are looking for.
After identifying safety as a core mission, Japanese automotive manufacturer Subaru is pursuing a goal of zero fatal traffic accidents1 by 2030. It is updating its existing EyeSight advanced driver-assistance systems to include artificial intelligence (AI), machine learning (ML), and deep learning technologies.
“We will reduce traffic accidents by using image recognition AI to detect objects around the vehicle more quickly than ever for safer driving,” says Takashi Kanai, infrastructure manager for AI development at Subaru Lab, an AI development base started by the automaker in Tokyo.
Subaru isn’t alone in Japan and the Asia-Pacific (JAPAC) region when it comes to achieving data-driven outcomes through AI, machine learning, and data analysis underpinned by cloud technology. Forward-thinking organizations across the region are using the processing and storage capabilities of cloud platforms to scale innovation across diverse industries to solve not only business problems but societal ones as well.
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