Some of McCarthy's colleagues in neighboring departments, however, were more interested in how intelligence is implemented in humans (and other animals) first. Noam Chomsky and others worked on what became cognitive science, a field aimed at uncovering the mental representations and rules that underlie our perceptual and cognitive abilities. Chomsky and his colleagues had to overthrow the then-dominant paradigm of behaviorism, championed by Harvard psychologist B.F. Skinner, where animal behavior was reduced to a simple set of associations between an action and its subsequent reward or punishment. The undoing of Skinner's grip on psychology is commonly marked by Chomsky's 1959 critical review of Skinner's book Verbal Behavior, a book in which Skinner attempted to explain linguistic ability using behaviorist principles. Skinner's approach stressed the historical associations between a stimulus and the animal's response -- an approach easily framed as a kind of empirical statistical analysis, predicting the future as a function of the past.

First there was TensorFlow, Google's machine learning framework. Then there was SyntaxNet, a neural network framework Google released to help developers build applications that understand human language. What comes next is anyone's guess, but one thing is clear: Google is aggressively open-sourcing the smarts behind some of its most promising AI technology. Despite giving it away for free, however, Google is also apparently betting that "artificial intelligence will be its secret sauce," as Larry Dignan details. That "sauce" permeates a bevy of newly announced Google products like Google Home, but it's anything but secret.

The artificial-intelligence routine is far from perfect, of course. Google says Parsey McParseface reaches about 94 percent accuracy identifying the root of an English sentence taken from a newspaper. As for the competition, you can play with a version of the Stanford NLP parser here. A simpler, but much faster parser is spaCy, which has a demo here. You have todownload Parsey McParseface to your computer; it's a little tricky.)

Google has designed and deployed a custom chip for driving its machine learning technologies. The chips are custom made to work with TensorFlow, Google's machine learning platform. The technology was stealthily developed, and is already deployed for Street View, Inbox Smart Reply and RankBrain, which is the brains behind delivering more relevant search results. The chips are named Tensor Processing Units (TPU). It delivers better performance optimisation per unit of electricity consumption, an order of magnitude better than any other product in the market.

Teaching the machines involve a structural process where every stage builds a better version of the machine.

It happens hundreds of times a day: We press snooze on the alarm clock, we pick a shirt out of the closet, we reach for a beer in the fridge. In each case, we conceive of ourselves as free agents, consciously guiding our bodies in purposeful ways. But what does science have to say about the true source of this experience? In a classic paper published almost 20 years ago, the psychologists Dan Wegner and Thalia Wheatley made a revolutionary proposal: The experience of intentionally willing an action, they suggested, is often nothing more than a post hoc causal inference that our thoughts caused some behavior. The feeling itself, however, plays no causal role in producing that behavior. This could sometimes lead us to think we made a choice when we actually didn't or think we made a different choice than we actually did.

At the Stanford shopping center in Palo Alto, California, there is a new sheriff in town – and it's an egg-shaped robot. Outside Tiffany & Co, an unfortunate man holding a baby finds himself in the robot's path. It bears down on him, a little jerkily, like a giant Roomba. The man dodges but the robot's software is already trying to avoid him, so they end up on a collision course. "I've seen Terminator," the man says, half to himself and half to the amused crowd, "and that is some Skynet-ass shit."

An internet pioneer who first taught the world how to find friendship, love, and sex online a quarter century ago is trying to determine at what point artificial intelligence develops emotional intelligence, and he thinks he can do it with an art contest. About 31 different robots competed for 100,000 in prizes at the first annual International Robot Art Competition. The vote was based on 2,200 votes cast on Facebook as well as judgment from six art critics who have experience working with technology. The fan and judge favorite was TAIDA from the National Taiwan University. TAIDA won first place and 30,000 for several Pointillism-style works, including a still life of fruit, landscape of the Taiwan coast, and a portrait of Albert Einstein.

The artificial intelligence revolution is clearly happening. A.I. will transform medicine, give us all super-smart virtual assistants, fight crime and a thousand things more. In order for A.I. to work its miracles, it's going to need data. And I'm predicting that we'll willingly give that data. Do you use Siri, Google Now, Cortana or Alexa?

Spring may finally have arrived for artificial intelligence, Google executives said Friday. Speaking at the Google I/O developers conference in Mountain View, executives said that artificial intelligence and machine learning have advanced to the point where they are proving genuinely useful, through such technologies as speech recognition and language translation. But there remains great room for improvement. "We've seen extraordinary results in fields that hadn't really moved the needle for many years," said John Giannandrea, vice president of engineering for Google. "I think we're in an AI spring right now."