Mimicking nature via neural nets has become the prime driver for enabling AI to work in similar fashion to how the brain processes information, something able to be simulated in code without issue but not in practical fashion in hardware, until now.
In what marks a significant step forward for artificial intelligence, researchers at UC Santa Barbara have demonstrated the functionality of a simple artificial neural circuit. For the first time, a circuit of about 100 artificial synapses was proved to perform a simple version of a typical human task: image classification.
"It's a small, but important step," said Dmitri Strukov, a professor of electrical and computer engineering. With time and further progress, the circuitry may eventually be expanded and scaled to approach something like the human brain's, which has 1015 (one quadrillion) synaptic connections.
For all its errors and potential for faultiness, the human brain remains a model of computational power and efficiency for engineers like Strukov and his colleagues, Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins and Gina Adam. That's because the brain can accomplish certain functions in a fraction of a second what computers would require far more time and energy to perform.
What are these functions? Well, you're performing some of them right now. As you read this, your brain is making countless split-second decisions about the letters and symbols you see, classifying their shapes and relative positions to each other and deriving different levels of meaning through many channels of context, in as little time as it takes you to scan over this print. Change the font, or even the orientation of the letters, and it's likely you would still be able to read this and derive the same meaning.
In the researchers' demonstration, the circuit implementing the rudimentary artificial neural network was able to successfully classify three letters ("z", "v" and "n") by their images, each letter stylized in different ways or saturated with "noise". In a process similar to how we humans pick our friends out from a crowd, or find the right key from a ring of similar keys, the simple neural circuitry was able to correctly classify the simple images.
"While the circuit was very small compared to practical networks, it is big enough to prove the concept of practicality," said Merrikh-Bayat. According to Gina Adam, as interest grows in the technology, so will research momentum.
Where it gets interesting.
The image above show how neural nets work, the part that get interesting is how Google, Facebook, IBM, among significant others, are mining enormous amounts of data from the net to train NNs to become smarter, a thought that makes yours truly quietly uneasy as it does Musk, Hawking, Rees and Joy, guys that know a little bit about tech, science and the potent unknowns that AI brings to the table.
Not all future technology meets with his approval, though. In a speech in October at the Massachusetts Institute of Technology, Mr Musk described artificial intelligence (AI) as “summoning the demon”, and the creation of a rival to human intelligence as probably the biggest threat facing the world. He is not alone. Nick Bostrom, a philosopher at the University of Oxford who helped develop the notion of “existential risks”—those that threaten humanity in general—counts advanced artificial intelligence as one such, alongside giant asteroid strikes and all-out nuclear war. Lord Rees, who used to run the Royal Society, Britain’s foremost scientific body, has since founded the Centre for the Study of Existential Risk, in Cambridge, which takes the risks posed by AI just as seriously.
Such worries are a mirror image of the optimism suffusing the field itself, which has enjoyed rapid progress over the past couple of years. Firms such as Google, Facebook, Amazon and Baidu have got into an AI arms race, poaching researchers, setting up laboratories and buying start-ups. The insiders are not, by and large, fretting about being surpassed by their creations. Their business is not so much making new sorts of minds as it is removing some of the need for the old sort, by taking tasks that used to be things which only people could do and making them amenable to machines.
As often stated in BRT, AI is going to happen whether we like it or not, the question to ask now is, are we ready for it?
"No one knows, do one?" - Fat Waller