Artificial Intelligence is poised to transform today's society as completely as the Internet did 20 years ago. The impact of both on all aspects of life, work, art, relationships, humanity, and consciousness, is as yet unknown-but not for long. In the past decade, Google introduced us to driverless cars and Apple launched Siri-a personal assistant we keep in our pockets. Robots have become an integral part of society on the battlefield and the road, in business, education, and health care. The ever-falling cost of sensors and powerful computers ensure that in the coming years, these robots will act on their own.

Google's billionaire executive chairman Eric Schmidt says he's seen the future of wealth creation from the IT industry, and its name is "machine learning." "This is the next transformation," Schmidt said during a keynote speech during Google's Cloud Computing Platform tech conference on Wednesday in San Francisco. "I'm a programmer who sort of got lucky at Google," he continued. "But the programming paradigm is changing. Instead of programming a computer, you teach a computer to learn something and it does what you want."

Since Homo Sapiens emerged until recently, our life with other humans among nature, plants, animals, man-made objects and machines may not have been as peaceful and harmonious as we might have desired. There have been devastating natural calamities, big technological accidents and human conflicts escalating into battles and wars tragic enough to make William James summarize: "History is a bloodbath". But during all that hundreds of thousands of years there have always been a certain peace of mind: because we knew fairly well all the players that were of some significance for the events influencing our life. Even if everything was changing all the time, through our evolution we grew up together with our natural environment, including plants, animals and climate. We know it is good to eat apples, and we know it is dangerous to swim among sharks. We know our fellow human beings – individuals, or groups of individuals – like villages, companies, political parties and countries.

In the October5, 2015 issue of the Wall Street Journal, there appeared a feature article titled: "Scientists Tap Dragonfly Vision to Build a Better Bionic Eye", with the subtitle: "Artificial-intelligence system could aid the blind and help create a better driverless car." The actual article was written by Rachel Pannett and starts as follows: "What can humans learn from dragonflies? Australian researchers have developed an artificial-intelligence system based on a dragonfly's vision that they say could help improve the eyesight of people who can see almost nothing. The system also is expected to find applications in automated technologies that rely on artificial sight, such as robots and driverless cars." In this article, the dragonfly's remarkable ability as a predator is mentioned.

It was hard to tell whether hope or fear was the predominant sentiment about the future of artificial intelligence, according to a panel discussing the state of the field at the World Economic Forum in Davos, Switzerland, Wednesday. A.I. systems are rapidly becoming more capable, the panel -- which included Ya-Qin Zhang, president of Chinese search engine company Baidu Inc., and Matthew Grob, the chief technology officer at Qualcomm Inc. -- agreed: they're able to learn from analyzing large data sets and they can increasingly discern human emotions by monitoring facial expressions and natural language. A.I. researchers Andrew Moore, the dean of the School of Computer Science at Carnegie Mellon University, and Stuart Russell, a professor of computer science at the University of California, Berkeley, were also on the panel and concurred that as a result, A.I. is likely to vastly improve human lives in the coming decade. But the researchers and executives voiced concern about possible downsides ranging from economic displacement to computers that escape the ability of humans to control them with potentially dire consequences. Using A.I. to improve search engine results has the potential to transform search from a 1 trillion industry today to a 10 trillion industry, Russell said.

You can stream your TV, swipe right for a date or tap an app to catch a ride. So why are designers still selecting typefaces like it's 1985? That's the question that inspired Hailin Jin, a principal scientist in Adobe Research, to create DeepFont -- a new technology that can automatically recognize typefaces from a photo as well as suggest similar type families. "My research background is in image recognition and artificial intelligence techniques like machine learning and deep learning," Hailin explains. "I wondered -- can we apply the power of machine learning with the font manual to make a useful tool for designers?"

Until recently, Robyn Ewing was a writer in Hollywood, developing TV scripts and pitching pilots to film studios. Now she's applying her creative talents toward building the personality of a different type of character -- a virtual assistant, animated by artifical intelligence, that interacts with sick patients. Ewing works with engineers on the software program, called Sophie, which can be downloaded to a smartphone. The virtual nurse gently reminds users to check their medication, asks them how they are feeling or if they are in pain, and then sends the data to a real doctor. As tech behemoths and a wave of start-ups double down on virtual assistants that can chat with human beings, writing for AI is becoming a hot job in Silicon Valley.

Netflix, Facebook, and Google can offer suggestions about TV shows, products, and companies that a user might be interested in based on trends. This is often done with machine learning, a computer science sub-field that uses pattern recognition and computational learning. In addition to providing suggestions for the next show you should binge-watch, researchers at the UW School of Medicine and the Yale University School of Medicine hope to use this technique to predict sepsis mortality in the emergency care setting. "I think we're surpassing our ability to account for these interactions [on our own]," said Dr. Kennedy Hall, acting instructor of emergency medicine at the UW. "This is where machine learning can come in as an adjunct to help us out."

Jen-Hsun Huang, CEO of the chipmaker Nvidia, is either very prescient or very lucky. His company was built around graphics processing units (GPUs) for video games. But those same chips are now widely used in artificial-intelligence projects such as efforts to build self-driving cars. Nvidia's chips turned out to be especially efficient for training the neural networks used in a technique called deep learning that has recently made software much smarter and caused tech giants and investors to pile money into machine-learning research. This week the company announced a new chip designed specifically for the task (see "A 2 Billion Chip to Accelerate Artificial Intelligence").

The annual Data Science Bowl hosted by Booz Allen Hamilton and Kaggle is based on the premise that crowdsourced solutions can be used to solve some of our world's most complex problems. This year, the focus was on heart health – an issue of critical importance worldwide. In the U.S. alone, one person is diagnosed with heart disease every 43 seconds. It typically takes 20 minutes to have an MRI analyzed and a diagnosis delivered. However, this year's Bowl managed to create an algorithm that allows your doctor to receive your results and prognosis in real-time.