Junko Yoshida

With Physical AI now on the agenda, underestimating calibration drift could bring unintended consequences to highly automated vehicles, robotic systems and automated manufacturing processes.

Brain-inspired computing has always been a "five years away" lab project. A startup in San Francisco hopes to change the narrative. Its first product is not a piece of hardware but software.

With the recent NHTSA letter, AV companies are asked to go beyond basic technology (measured in crash rates) and demonstrate tangible social and economic responsibility.

Full autonomy is AV devlopers' holy grail—by human removal. Glidance lives by a different design principle: How well can their intelligent cane know when and how to involve people?

For autonomous vehicle companies, scaling, not safety, is the top priority because it makes—or breaks—their long-term business survival.

A new report compares Waymo's safety record to professional yellow taxi, Lyft and Uber drivers in New York City, adding fresh insights to the AV safety discourse.

What I picked up at my first "Automated Transportation Symposium," where close to 700 AV professionals and stakeholders of the AV ecosystem milled around.

There are hints, rumors and speculations about how good China's self-driving robotaxis are. But how much is true? What do we know?

Lessons to learn from a Dallas crash involving a SUV and a Waymo aren't about how to assign blames but how to hold human driver and AV's computer driver equally "accountable" when they break a law.

As NXP's CEO Rafael Sotomayor succinctly put it last month during NXP's Q2 financial call, “Physical AI is a system problem, not just a compute problem.” If so, what's the company's robotic plan?