Google DeepMind took a leap forward last year when its artificial intelligence agent mastered 49 Atari 2600 games. The learning system, or "deep Q-network" (DQN), that DeepMind designed achieved this mastery through general experience, rather than specific programming for each game. This milestone is just one step along a grander path toward the general-purpose "smart machine": an AI that can master any task with minimal input. DeepMind's work in this field is groundbreaking, and it's helping advance the field in ways you might not expect. Wojciech Jaśkowski is an assistant professor at the Institute of Computing Science (ICS) at Poznan University of Technology, Poland.

Microsoft Research and a team at Carnegie Mellon University have developed a system that can train machines to examine an image and seek to answer questions the way a human might ask them. Microsoft's latest effort in developing the tools for artificial intelligence focus on the field of so-called'image-question answering', which aims to automatically answer natural-language questions about the content of a given image. 'Building AI is like launching a rocket': Meet the man fighting to stop artificial intelligence destroying humanity Skype's co-founder wants to keep humankind safe from the existential threats of artificial intelligence. That's easier than it sounds, even for a seemingly simple image of a dog sitting in a bike basket. To answer the question, 'What's sitting in the basket on a bicycle?' requires multi-step reasoning, the researchers from Carnegie Mellon and Microsoft Research noted.

Geoffrey Hinton was in high school when a friend convinced him that the brain worked like a hologram. To create one of those 3-D holographic images, you record how countless beams of light bounce off an object and then you store these little bits of information across a vast database. While still in high school, back in 1960s Britain, Hinton was fascinated by the idea that the brain stores memories in much the same way. Rather than keeping them in a single location, it spreads them across its enormous network of neurons. This may seem like a small revelation, but it was a key moment for Hinton -- "I got very excited about that idea," he remembers.

Facebook needs machines that can understand the way we humans behave and write and even feel. In January -- after the company rolled out a limited public trial of Graph Search, a way of searching activity on the popular social network -- Facebook engineers were forced to tweak their algorithms so they could translate slang like "pics of my homies" into more straightforward language like "pictures of my friends" and convert expressions like "dig," "off the chain," and "off the hook" into that standard Facebook word: "Like." Like Google and Apple and other tech giants, Facebook is exploring a new field called "deep learning," which will allow its machines to better understand all sorts of nuanced language and behavior that we humans take for granted. In short, deep learning teaches machines to behave more like the human brain. Facebook's effort only recently got off the ground -- "we're just getting started," a company spokesperson says -- but its importance will expand as time goes on.

Chinese search giant Baidu has served up its first ever visual search engine, which allows users to finally query the web using only images as input instead of keywords. Google has long offered this sort of thing, but Baidu continues to show that it's determined to keep pace with Larry Page and company. "We didn't have any similar kind of product in China because we didn't have the sufficient technology to handle this," says Baidu's Kai Yu, who led the project. "In the China market, this is the first of its kind." Unveiled last week, the tool grew out of Baidu's newly launched Institute of Deep Learning, the company's Beijing- and Silicon Valley-based research arm focused on deep learning, a field of computer science that seeks to mimic how the human brain works. The company has already deployed deep-learning algorithms for optical character, face, and voice recognition, online advertising and web search.

There's a theory that human intelligence stems from a single algorithm. The idea arises from experiments suggesting that the portion of your brain dedicated to processing sound from your ears could also handle sight for your eyes. This is possible only while your brain is in the earliest stages of development, but it implies that the brain is -- at its core -- a general-purpose machine that can be tuned to specific tasks. About seven years ago, Stanford computer science professor Andrew Ng stumbled across this theory, and it changed the course of his career, reigniting a passion for artificial intelligence, or AI. "For the first time in my life," Ng says, "it made me feel like it might be possible to make some progress on a small part of the AI dream within our lifetime."

The brick office building sits next to a strip mall in Cupertino, California, about an hour south of San Francisco, and if you walk inside, you'll find a California state flag and a cardboard cutout of R2-D2 and plenty of Christmas decorations -- even though we're well into April. But there are big plans for this building. It's where Baidu -- "the Google of China" -- hopes to create the future. In late January, word arrived that the Chinese search giant was setting up a research lab dedicated to "deep learning" -- an emerging computer science field that seeks to mimic the human brain with hardware and software -- and as it turns out, this lab includes an operation here in Silicon Valley, not far from Apple headquarters, in addition to a facility back in China. The company just hired its first researcher in Cupertino, with plans to bring in several more by the end of the year.

The robots arrived years ago. They help build stuff in factories. But Ilker Yildirim envisions a robot that can operate with a bit more subtlety, a bot that needn't operate according to pre-programmed movements. This machine could respond to changes in its environment, much like humans do, and predict what will happen when one action is chosen over another. He envisions a robot that can do your dishes.

Last week, Ben Goertzel and his company, Aidyia, turned on a hedge fund that makes all stock trades using artificial intelligence--no human intervention required. "If we all die," says Goertzel, a longtime AI guru and the company's chief scientist, "it would keep trading." Goertzel and other humans built the system, of course, and they'll continue to modify it as needed. But their creation identifies and executes trades entirely on its own, drawing on multiple forms of AI, including one inspired by genetic evolution and another based on probabilistic logic. Each day, after analyzing everything from market prices and volumes to macroeconomic data and corporate accounting documents, these AI engines make their own market predictions and then "vote" on the best course of action. If we all die, it would keep trading.

Andrew Ng hands me a tiny device that wraps around my ear and connects to a smartphone via a small cable. It looks like a throwback--a smartphone earpiece without a Bluetooth connection. In a way, this tiny device allows the blind to see. Ng is the chief scientist at Chinese tech giant Baidu, and this is one of the company's latest prototypes. The device contains a tiny camera that captures whatever is in front of you--a person's face, a street sign, a package of food--and sends the images to an app on your smartphone.