It goes without saying that the human brain is complex, and would be hard to build from scratch. But researchers are looking to simulate how the brain works so that more human-like artificial intelligence can be created and we can better understand damage to our own brains.
Chris Eliasmith of the University of Waterloo in Ontario, Canada, led research published in the journal Science on a brain model called SPAUN - the Semantic Pointer Architecture Unified Network.
SPAUN lives inside a computer, can view images with a camera-like eye and can draw responses to questions. For example, show it the number "4" and it will write its own "4." It can even mimic the style of the numeral.
Both in the brain and in SPAUN, neurons communicate by changing their voltages, and the pattern of these voltage "spikes" is what carries information from one cell to another, Eliasmith said. The receiving cell generates a voltage of its own if it receives a particular voltage.
SPAUN has 2.5 million spiking neurons. Neurons are the cells - the individual components - that make up the brain. The human brain has about 100 billion neurons, so there's still a long way to go in terms of replicating its full capacity.
It's hard to compare SPAUN to any existing animal. Monkeys can do more general recognition than what this model does, Eliasmith said. But there are tasks SPAUN does that, until now, it was thought only humans could do.
"It's not as smart as monkeys when it comes to categorization, but it's actually smarter than monkeys when it comes to recognizing syntactic patterns, structured patterns in the input, that monkeys won't recognize," Eliasmith said.
All of SPAUN's tasks involve numbers. For instance, give it the pattern: 1, 11, 111; 3, 33, 333; 4, 44, _____." SPAUN could fill in the blank as 444.
"That's actually part of an intelligence test, realizing that everything is increasing by one," Eliasmith said. "Monkeys actually won't figure that out."
A drawback is that SPAUN cannot operate in real time. For every one second in anonline demonstration video, it takes 2.5 hours. The researchers are hoping to be able to get it to do real-time operations. And SPAUN, as a simulation of actual neurons, is not a robot.
But structuring the artificially intelligent brain like a human brain means that the kinds of errors it makes are the kind of that people make, and its reaction time - how long it takes to "think" about problems - would be similar to humans. This could help with the creation of robots.
"All of that kind of thing will make for the possibility of having agents that are more human-like to interact with," Eliasmith said.
Christian Machens, neuroscientist at the Champalimaud Neuroscience Programme in Lisbon, Portugal, points out in an accompanying piece in Science that SPAUN is not able to learn any new tasks. Its knowledge is entirely hard-wired.
Still, Machens writes that the authors offer a "coherent theory" of the workings of the brain (except for learning). And it sets a new goal for simulations: "to not simply incorporate the largest number of neurons or the greatest amount of detail, but to reproduce the largest amount of functionality and behavior."
This research is also useful for modeling brain damage, Eliasmith said. In separate research, he and colleagues looked at what happens when neurons in a simulation get destroyed at the same rate as in humans as they age.
"We can show that the performance on (an) intelligence task mimics the kind of performance that you see in people; it gets worse in the same sort of proportion that you find in humans," he said.
As for whether we'll have a fully cognizant, self-aware artificial intelligence in our lifetimes, Eliasmith isn't sure, but that is the sort of goal that he and his team are working toward. And they've come up with a novel way of approaching the problem.
"It’s hard to know at this point whether this approach is going to hit some wall that we haven’t seen yet, or actually be able to reach that holy grail, as it were, of artificial intelligence.”