As the election results rolled in last night, it became increasingly clear that America -- and the world -- would never be the same. The American people overlooked all of Republican nominee Donald Trump's faults and elected him to office in the belief that he will fix the nation's deep-seated problems of inequity and injustice. And they rebelled against the business interests and corruption that they believed Hillary Clinton represented. Trump's victory was enabled by technology -- everything from his use of social media to Clinton's email scandals to Russian hacking. But advancements in technology and how they reshape our economy may also keep him from delivering on some of the major promises that made him so popular during the campaign season.

If you are a fan of Iron Man or the Avengers franchise, you know that when Tony Stark is talking to Jarvis, he is talking with Artificial Intelligence or AI. According to computer science, an'intelligent machine' is a rational agent who perceives its environment and takes those actions, which will maximize its chances of success for the specified goal. In simple terms, intelligence that is exhibited by the machines is termed as'Artificial Intelligence' or AI. Ever wondered how Google Now, Siri, and Cortana help you find information? They are all AI applications used on different platforms.

Technology is rapidly changing how people do everything; from taxis to food delivery, from dating to media consumption and everything in-between. There have been many visible ways in terms of technology impacting healthcare. From microscopes & stethoscopes invented hundreds of years ago, to MRI machines today, to the goal of creating a Tricorder in a Star Trek-like future, technology is making sweeping changes in healthcare and undoubtedly India will be a big beneficiary. The main drivers, today and in the future, are smartphones, always-on connectivity, big data and artificial intelligence (AI). In the way regular mobile phones became ubiquitous, soon most people in India will have powerful and connected supercomputers in their pocket as prices for smartphones and internet access continue to drop and become more accessible.

For more than a decade, neuroscientist Grégoire Courtine has been flying every few months from his lab at the Swiss Federal Institute of Technology in Lausanne to another lab in Beijing, China, where he conducts research on monkeys with the aim of treating spinal-cord injuries. The commute is exhausting -- on occasion he has even flown to Beijing, done experiments, and returned the same night. But it is worth it, says Courtine, because working with monkeys in China is less burdened by regulation than it is in Europe and the United States. And this week, he and his team report the results of experiments in Beijing, in which a wireless brain implant -- that stimulates electrodes in the leg by recreating signals recorded from the brain -- has enabled monkeys with spinal-cord injuries to walk. "They have demonstrated that the animals can regain not only coordinated but also weight-bearing function, which is important for locomotion. This is great work," says Gaurav Sharma, a neuroscientist who has worked on restoring arm movement in paralysed patients, at the non-profit research organization Battelle Memorial Institute in Columbus, Ohio.

But after decades of anticipating the advent of "adult" robots, artificial intelligence is finally growing up and starting to get real jobs. The implementation of AI has been a slow and, at times, clunky process. We had ELIZA by 1966, but it wasn't until three decades later -- in 1997 -- that Deep Blue was able to beat chess champion Garry Kasparov. Fast-forward almost two more decades: my laptop just underlined "Gary" in red, because it knew that, despite G-A-R-Y being the far more common spelling, Kasparov's first name has two Rs. And then there's our dear friend Siri, who can show us where to get sushi, find a picture of Batman, or even tell us a story.

In research conducted in China, a rhesus monkey whose spinal cord was partially severed quickly regained lost control over his paralyzed leg after researchers implanted a signal-emitting electronic array below the site of the spinal injury. That pulse generator sent out electrical signals to the monkey's leg to move, and the monkey's affected leg responded as early as six days after his spinal cord was deliberately injured. The signals to move were commands collected from the motor cortex of unharmed rhesus monkeys as they freely walked and used their legs. Together, the two devices leaped over the broken connection between brain and limb, allowing the partially paralyzed monkey to mimic key walking motions. The brain-spine interface offers new hope that patients who have lost function due to spinal cord injury might be able to restore movement and prevent the degeneration of the neural wiring that is needed for an eventual return to movement.

Just like nuclear physics, machine learning, AI, and data science can be used either for the better of for the worse. You can make either useful energy or terrible bombs using nuclear fission. The same applies to machine learning, and in my example below, it gets even worse than Hiroshima or Nagasaki. Here I am discussing a potential use of machine learning in military operations. The scenario below is entirely hypothetical.

When today's millennial generation has children of their own, they could live in a world filled with flying cars and robot workers while having the option to travel through space to distant planets. Science fiction buffs know the Star Trek universe takes place in the 23rd century when the Earth is at peace, humans have given up their desire for money, and mankind has developed colonies on other worlds. That's a mere 200 years from where we stand today, an insignificant time period in the history of the world. Looking at the technological achievements of humanity today, it's easy to see how such a world might become reality. While humans will always be a part of the Earth's labor pool, it's easy to see how smart robots will one day push large numbers of men and women out of the workforce.

Deep learning just may be the buzziest, most misunderstood term in the tech world. And October was a banner month for the enigmatic subject. The term "deep learning" is, essentially, a synonym for a type of neural network approach. And though voguish at the moment, the goal of the field has long been to create a system that can independently learn. Now, research into machine learning is rapidly accelerating, and those intellectual seeds are bearing widely applicable fruits.

Data Analytics is one of the most sought-after skill sets today, with students and professionals alike aspiring to be enabled with the necessary skills to derive data-driven business insights in their careers. It also helps organisations attain a competitive advantage over others. Data Analytics is not limited to mathematicians, statisticians or IT professionals with programming skills. The need to analyse data has become so elementary today that a professional in any business is expected to know the necessary skills. While professionals today are aware of the need to be trained, some are unaware of how to embark on a career in analytics.