Source: Wired, Jul 2015
Hassabis decided to take a PhD in cognitive neuroscience at University College London, focusing on memory and imagination. “I thought that would be a good thing to study because computers do episodic memory badly. My work was investigating imagination as a process — how do we visualise the future?”
He tested the imagination of amnesiac patients with a damaged hippocampus and found that their descriptions of, say, being on a beach were impoverished, suggesting that the hippocampus incorporated a visualisation engine.
On DeepMind’s website, the company’s mission is explained simply as to “solve intelligence”. As Hassabis describes it, it comes down to a multi-decade Apollo-style project to crack artificial general intelligence (AGI): rather than teach the machine to understand language, or recognise faces, or respond to voice commands, he wants machine learning and systems neuroscience to teach the network to make decisions — as humans do – in any situation whatsoever.
“The dream of AI is to make machines smart,” he explains in the new six-storey King’s Cross building that houses 150 DeepMind staff. “Most AI today is about preprogramming a machine. Our way is to program them with an ability to learn for themselves. That’s much more powerful; that’s the way biological systems learn.
why do we need a general form of AI at all? “I think we’re going to need artificial assistance to make the breakthroughs that society wants,” Hassabis says. “Climate, economics, disease — they’re just tremendously complicated interacting systems.
It’s just hard for humans to analyse all that data and make sense of it. And we might have to confront the possibility that there’s a limit to what human experts might understand. AI-assisted science will help the discovery process.”
We’ll have things that can start being creative in 20 years. A lot of things that look very complex, when you break them down it becomes clear how the apparatus works.
I studied imagination. We did brain scans, found areas of the brain involved, built models. That made me think that most processes can be understood, including creativity.” An AI making an entertaining movie? “I’m thinking more on a basic level — putting disparate things together to make a new hypothesis.