According to a McKinsey study on the state of automation, even today, 31% of the time spent by the world labour force is on performing manual labour task. This is the single largest category of jobs performed.
The technical feasibility of automating these tasks is still below 50% wherever there is any unpredictability in the tasks.
Enabling robots to comprehend and adapt to unpredictability remains elusive.
I think robots that have vision and manipulation as good as humans is a huge milestone that will happen in the next decade and is being underestimated.
I think grasping is going to be a solved problem in the next 10 years. It’s turned out to be an incredibly difficult problem, probably in part because we’re starting to solve it with machine vision, so (that means) machine vision did have to come first.
Vision for object manipulation requires dynamic image acquisition hardware, with the ability to focus, refocus, pan, zoom, move around in real-time, and adaptively acquire at high speeds.
Static 2D color images and 3D depth maps alone are insufficient inputs for neural networks to model the complexities of objects. Our imaging pathway acquires and constructs more than 7 fundamental dimensions of information, dramatically reducing the quantum of data for learning.
Our insights into the manual labor and automation market and the cutting edge advances in robotics.
Industrial automation is on the verge of the next great revolution. We have one significant but often overlooked issue to overcome.Photo by Jason Leung on Unsplash“Look at the world around you. It may seem like an immovable, implacable place. It is not...