Technicians analyze data following the trial of an autonomous self-driving vehicle in a pedestrianised zone, during a media event in Milton Keynes, north of London, on October 11, 2016. Suburbs have largely been dismissed by environmentalists and urban planners as bad for the planet, a form that ne...
In the coming decades, artificial intelligence (AI) and machine learning technologies are going to transform many aspects of our world. Much of this change will be positive; the potential for benefits in areas as diverse as health, transportation and urban planning, art, science, and cross-cultural understanding are enormous. We've already seen things go horribly wrong with simple machine learning systems; but increasingly sophisticated AI will usher in a world that is strange and different from the one we're used to, and there are serious risks if this technology is used for the wrong ends.
One of the curious features of the deep neural networks behind machine learning is that they are surprisingly different from the neural networks in biological systems. While there are similarities, some critical machine-learning mechanisms have no analogue in the natural world, where learning seems to occur in a different way.
In February of 2011, NASA launched Robonaut 2 to the International Space Station. It was a huge achievement for the robotics team at NASA's Johnson Space Center in Houston. There had been other robots in space, but Robonaut was the first advanced humanoid to ever go on a mission beyond Earth. On board the ISS, the robot was intended to eventually work side by side with astronauts, performing some of the dull and repetitive tasks that take up a significant amount of time that the humans on the station could instead be spending on science and discovery.