Consider a toddler navigating her day, bombarded by a kaleidoscope of experiences. How does her mind discover what's normal happenstance and begin building a model of the world? How does she recognize unusual events and incorporate them into her worldview? How does she understand new concepts, often from just a single example? These are the same questions machine learning scientists ask as they inch closer to AI that matches -- or even beats -- human performance.

Elon Musk's 1 billion artificial intelligence group wants to build a robot to clean people's houses. OpenAI – which is funded by the billionaire maker of reusable rockets and electric cars – hopes to build a domestic robot as a test of its research into how to build artificial intelligence that won't kill us. Building such a robot isn't just a way of getting rid of household chores, according to a blog entry posted by the nonprofit research group. It would also be a neat way of testing whether or not its work in artificial intelligence is progressing in the right way. Boston Dynamics describes itself as'building dynamic robots and software for human simulation'.

AI has applications in every area in which data are processed and decisions required. Wired founding editor Kevin Kelly likened AI to electricity: a cheap, reliable, industrial-grade digital smartness running behind everything. He said that it "will enliven inert objects, much as electricity did more than a century ago. Everything that we formerly electrified we will now "cognitize." This new utilitarian AI will also augment us individually as people (deepening our memory, speeding our recognition) and collectively as a species.

Intel's chip arsenal appears to have some glaring weaknesses. One of them is the lack of a high-end graphics processor, which is important for gaming, virtual reality and machine learning. However, the company does have powerful alternatives: two monster chips that will be ammunition to take on GPUs and rival chips in the areas of machine learning and supercomputing, which are important to the company. In 2018, Intel will likely release a faster and more power-efficient Xeon Phi, a supercomputing chip that is already used in some of the world's fastest computers. Intel is also looking beyond CPUs to FPGAs (field programmable gate arrays), which can be faster at key tasks.

Twitter CEO and co-founder Jack Dorsey said: "Our acquisition of Magic Pony builds on other investments we've made in machine learning, beginning with the acquisitions of Madbits in July 2014 and Whetlab in June 2015. "Magic Pony's team will be joining Twitter Cortex, a team of engineers, data scientists, and machine learning researchers dedicated to building a product in which people can easily find new experiences to share and participate in. "Magic Pony's technology – based on research by the team to create algorithms that can understand the features of imagery – will be used to enhance our strength in live and video and opens up a whole lot of exciting creative possibilities for Twitter. "The team includes 11 PhDs with expertise across computer vision, machine learning, high-performance computing, and computational neuroscience, who are alumni of some of the top labs in the world."

The learning that is being done is always based on some sort of observations or data, such as examples, direct experience, or instruction. For instance, you might wish to predict how much a user Bob will like a movie that he hasn't seen, based on her ratings of movies that he has seen. This means making informed guesses about some unobserved property of some object, based on observed properties of that object. Supervised learning is a type of machine learning algorithm that uses a known dataset (called the training dataset) to make predictions. The training dataset includes input data and response values.

IBM's Watson has been getting up to plenty of late, including fighting the likes of the Zika virus, and now the supercomputer has turned its hand to editing a magazine, no less. The Drum, a marketing site and publication, apparently allowed Watson to edit the latest issue of its magazine, effectively benching the human editor for an AI (at least in some respects). Billed as an issue created by artificial intelligence and edited by Watson, the magazine contains an opinion piece by David Kenny, General Manager, IBM Watson, along with a broad debate on the merits of AI. Apparently Watson also made some guesses regarding the winners at Cannes Lions, the international advertising festival which is underway this week. The Drum produced a tongue-in-cheek video of staff members sitting around doing very little except playing Solitaire or smartphone games, and browsing job websites.

In the early 1990s, a Hungarian girl who attended Alexey Turchin's school suddenly died. Turchin, a Muscovite teenager who had a crush on the girl, resolved to bring her back to life. To do this, he decided to interview the girl's classmates and friends in order to collect every bit of information about her. This data, fed into a supercomputer (to be designed, built, and operated by Turchin himself) would then be used to conjure up a digital reproduction of the late girl's self. The plan didn't pan out, partly because there wasn't a supercomputer able to emulate the human brain, and partly because--as Turchin puts it--"that was before social networks and there wasn't much information around about her."

Our inability to read other people has led to some epic high five fails and missed kisses. Even after a lifetime of experience, human interactions are hard to predict. But researchers at MIT's Computer Science and Artificial Intelligence Laboratory think they can help: With a new deep-learning algorithm that can predict when two people will hug, kiss, shake hands, or high five, they've taken a big step toward a future blessedly devoid of those awkward moments. They're hoping their new algorithm -- trained on 600 hours of YouTube videos and TV shows like The Office, Scrubs, Big Bang Theory, and Desperate Housewives -- can be used to program less socially awkward robots and develop Google Glass-style headsets to suggest actions for us before we even have the chance to miss. In the future they're imagining, you'll never again mess up a chance to air high-five with your co-worker.

Humans--most of us, at least--are pretty good at judging what's about to happen when we see two people approach each other. Why Dick's Sporting Goods decided to play its own game in ecommerce Dick's Sporting Goods has long partnered with eBay Enterprise on its e-commerce platform. Learn the benefits and risks of this multi-million dollar IT bet. According to a paper released on Tuesday by MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), its deep learning AI system can accurately predict human interactions. The AI that MIT developed, which will be presented at the International Conference on Computer Vision and Pattern Recognition (CVPR), was able to correctly decide, after just one second of a scene, whether two people would hug, kiss, shake hands, or high-five.