Amazon's Fire TV devices just became much more useful if you prefer to talk to your media hub. An update rolling out to the Fire TV and Fire TV Stick gives you dramatically improved search: you can now use voice to search over 75 apps and services, including Netflix and (soon) HBO Now. If the show you're looking for is available on multiple services, you'll see all your choices. You now have voice control of playback with Amazon's service, so you can skip to your favorite Transparent scene without using the fast forward button. Much like on Apple TV, you can get game scores and other sports updates with a voice command -- you'll have to specify your favorites, but you won't have to disrupt your show to get the scoop.

Machine learning is giving computers the ability to learn without explicit programming. This is primarily accomplished through various pattern recognition processes. For example, if you tell a computer to find the best candidates for a job by identifying patterns in data that produce the best results. In this way, a computer will find correlations and patterns that a human would overlook -- leading to increasingly higher quality candidates.Beyond that, the possibilities are infinite! Imagine that we're able to predict the crash of a certain market, and know that there will be a surplus of available candidates in that specific field, you can then focus your efforts as a recruiter to take advantage of that situation.

In the future imagined by science fiction, artificial intelligence will reign supreme and take over pretty much everything humans can do. Frankly this sci-fi vision isn't helpful when it comes to applying technology because it distracts us from thinking about what people do well and what advanced techniques such as deep learning do well. In the world of data science, great strides are being made in the area of deep learning. We've made so much progress that it is easy to think that instead of having to embrace data science as a discipline, we can somehow wait a little big longer and have a Watson-like box to perform all of these tasks for us. If you think this way, you are going to miss the boat.

Cognitive Computing in its essence is tremendously creative, it helps us to find complex correlations, and lets us see things that could not be seen with an average human eye. What once was science fiction, is now reality. And that's why I want to share a couple of practical examples, how life sciences companies have applied cognitive services and artificial intelligence to transform their businesses and ultimately provide better, innovative products, invent new business models, provide personalized, customer-centric services and optimized their operations. This first example with Dartmouth Hitchcock shows how to get closer to the vision of ever more individualized healthcare: ImagineCare is a highly coordinated, intensely personalized solution for chronic diseases. This cloud-based system enables nurses and health coaches track and respond to an individual's health status in real time.

This article was originally published by the World Economic Forum. The doomsday scenarios spun around this theme are so outlandish--like The Matrix, in which human-created artificial intelligence plugs humans into a simulated reality to harvest energy from their bodies--it's difficult to visualize them as serious threats. Meanwhile, artificially intelligent systems continue to develop apace. Self-driving cars are beginning to share our roads; pocket-sized devices respond to our queries and manage our schedules in real-time; algorithms beat us at Go; robots become better at getting up when they fall over. It's obvious how developing these technologies will benefit humanity. But, then, don't all the dystopian sci-fi stories start out this way?

Artificial intelligence (AI) is no longer the stuff of science fiction books and movies. It is a reality that is already permeating society and is affecting our daily lives. If you use facebook or google, artificial intelligence enables machines to virtually understand what you're looking for or to augment your network. In some countries and states in the US, self-driving cars have already taken to the streets. Elsewhere, companies are experimenting with bots that can act like lawyers, tellers, or doctors.

When IBM's Deep Blue beat chess Grandmaster Garry Kasparov in 1997 in a six-game chess match, Kasparov came to believe he was facing a machine that could experience human intuition. "The machine refused to move to a position that had a decisive short-term advantage," Kasparov wrote after the match. It was "showing a very human sense of danger."1 To Kasparov, Deep Blue seemed to be experiencing the game rather than just crunching numbers. Just a few years earlier, Kasparov had declared, "No computer will ever beat me."2

Chemotherapy kills cancer, but it also attacks healthy cells. This unfortunate phenomenon makes us sick and can cause permanent damage to our bodies. Of course the good (saving lives) still outweighs the bad, so we continue to use powerful drugs to kill cancer. But with the latest technology, we can do better. Delivering medicine directly where it's needed not only minimizes side effects but also makes the drugs more effective.

If your drone weighs more than 250 grams, airlines and pilots think you should get a drone pilots' license before you fly it in the European Union. They're worried about the number of near misses between drones and helicopters or fixed-wing aircraft, and they see greater regulation of drone use as the best way to improve safety. They also want more tests to be conducted to determine the damage that drones may cause to manned aircraft, much as is already done to reduce the threat of bird strikes. In a letter signed by 10 international associations for airlines, pilots, airports, and other organizations, they make little distinction between commercial and leisure uses of drones. All drones should be registered at the time of purchase or resale, they said, because knowing the devices can be traced is likely to make pilots behave more responsibly.

Around a year ago, a former embedded systems designer from the Japanese automobile industry named Makoto Koike, started helping out at his parents cucumber farm, and was amazed by the amount of work it takes to sort cucumbers by size, shape, colour and other attributes. In Japan, each farm has its own classification standard and there's no industry standard. There are some automatic sorters on the market, but they have limitations in terms of performance and cost, and small farms don't tend to use them. Makoto first got the idea to explore machine learning for sorting cucumbers from a wildly different source - Google AlphaGo - competing with the world's top professional Go player. "When I saw the Google's AlphaGo, I realized something really serious is happening here, said Makoto. That was the trigger for me to start developing the cucumber sorter with deep learning technology."