To be headed by Junichi Arahori, the new office will focus on implementing ethical measures related to the research, development, and implementation of AI and other machine learning applications.  “This marks the next step in Fujitsu’s ongoing efforts to strengthen and enforce comprehensive, company-wide measures to achieve robust AI ethics governance based on international best-practices, policies, and legal frameworks,” the company stated. But Fujitsu is not the only Japanese tech giant thinking about AI applications. NEC believes it has developed a control technology that it touts can double the efficiency of autonomous mobile robots (AMR) in warehouses while still maintaining a “high level of safety”. According to NEC, the control technology enables robots to autonomously detect obstacles and therefore determine when to travel at high speed, such as when travelling in low-risk locations without workers, as well as when to travel at low speed when using routes that are determined as high-risk locations. NEC plans to roll out this technology in its AMRs in Japan by March 2024. Separately, NEC has announced the acquisition of US-based software provider Blue Danube Systems to beef up its 5G product portfolio. “Blue Danube’s 5G products complement our Open 5G solutions portfolio, enabling us to meet growing market demands and accommodate diversified use cases,” NEC senior VP Shigeru Okuya said. “This acquisition is a great opportunity for us to expand our 5G offerings and will bring substantial value to our customers. NEC has committed to a leadership position in Open RAN network development and this move extends our physical reach and innovation roadmap to deliver on that commitment.” The deal expected to close March 2022.

QUT and Ford Motor team up in autonomous vehicle research

Researchers at the Centre for Robotics at the Queensland University of Technology (QUT) have been awarded a two-year project to work with Ford Motor to develop localisation and perception techniques for autonomous vehicles. The project will examine how cameras and lidar sensors used in autonomous vehicles can better understand the environment in which they operate. The project will also look at how to decrease the cost of autonomous vehicle technology adoption by reducing the cost of deep learning sensing and computing technology. “We’ll dive deep into research developing the algorithms and artificial intelligence systems that could improve the capabilities of autonomous vehicles. In particular, we’ll be looking at the synergistic relationship between autonomous vehicles and the world around them,” QUT professor Michael Milford said. “If vehicles are able to understand the environment they are in such as in an urban environment, the vehicle can better understand its surroundings such as a pedestrian crossing. We can take that understanding of what is in the environment to then help the vehicle better understand where they are located in it.”

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