Sparks of electricity emanating from a Tesla coil at the Mendeleyevskaya metro station in Moscow, Russia, January 24, 2016. Editor's Note: This is an excerpt from John Wasik's new book, "Lightning Strikes: Timeless Lessons in Creativity from the Life and Work of Nikola Tesla" (Sterling, 2016), slightly edited for this column. World-changing inventions made Nikola Tesla a celebrity in his own time, but something otherworldly makes him transcend his era and remain a perpetual beacon for our civilization 70 years after his death. He's now an immortal rock star, an icon for billionaires, cyberpunks, artists and "maker" inventors who are still fiddling with everyday machines in their basements and garages. Search engine designers, energy czars, musicians, artists and creators everywhere feel his influence.

Machines have long been great at quickly scanning and organizing immense pools of information. So where better to put them to use than in the hiring process, where both companies and employees depend on a good fit? Here's how artificial intelligence is changing the way companies hire and workers look for jobs. When workers used to search for and apply to jobs through their local newspapers, employers would end up with a manageable stack of candidates to review. All of that changed in 1999, when the online jobs board Monster.com was founded.

Mark Zuckerberg has a new housemate: Jarvis, an artificial intelligence assistant he created this year that can control appliances, play music, recognize faces and, perhaps most impressively, entertain his toddler. The Facebook founder spent 100 hours putting together the virtual assistant -- named after the artificial intelligence system in "Iron Man" -- which understands spoken commands as well as text messages, he wrote in a 3,000-word Facebook post Monday. The virtual assistant texts Zuckerberg images of visitors who stop by during the day and opens the front door for those it recognizes. It can also tell when Zuckerberg's 1-year-old daughter, Max, wakes up "so it can start playing music or a Mandarin lesson," he wrote. In a tongue-in-cheek video he posted Tuesday on Facebook, Zuckerberg offers an example of Jarvis at work: "Max woke up a few minutes ago. I'm entertaining her," the virtual assistant (voiced by Morgan Freeman) tells Zuckerberg, before turning his attention to the toddler.

India is home to the world's largest population of blind people and not nearly enough optometrists to provide the care the country needs. But recently, some doctors there have been receiving help in the fight against eye disease from an unexpected source. As Mashable reports, machine learning is being used to better understand the spread of blindness and predict the success rates of eye surgeries. The initiative is part of a collaboration between Microsoft and the Indian not-for-profit LV Prasad Eye Institute (LVPEI). At the center of the project are their Azure machine learning and Power BI services: After analyzing the anonymous records of 1.1 million people, the AI system can trace patterns of eye disease.

When Mark Zuckerberg wants an AI assistant, he recruits the "Voice of God." The Facebook (FB, Tech30) CEO and cofounder posted a video teasing an artificial intelligence application on Tuesday that he built for his home, voiced by none other than actor Morgan Freeman. In October, Zuckerberg asked his followers for suggestions to be the voice for Jarvis, his AI tool inspired by Iron Man. Freeman was a top pick. Zuckerberg personally called Freeman to ask him to do it.

Facebook chairman and CEO Mark Zuckerberg just achieved what most of us have only seen in the movie "Iron Man" and never dreamed would be possible in 2016: He has an artificial intelligence (AI) system running his home, which incidentally, just like you, hates Nickelback. Inspired by Stark's home in "Iron Man," Zuckerberg developed the project and named it "Jarvis," just like in the movie. And oh yeah, it's voiced by Morgan Freeman. So Zuck may have just one-upped "Iron Man" for real. It may be a little less high-tech than the one in the movie, but we're still impressed.

Machine learning algorithms are enabling organizations to supercharge workflow processes across their enterprises. They center around technology that has the ability to learn without being explicitly programmed: machines that can study their mistakes and reprogram themselves to improve their performance over time. Lots of big names are investing R&D dollars into machine learning. Here are some ways it can help improve business operations. A workflow process is the backbone of just about every common business activity, whether it centers around finance, inventory or another back-office task.

Retailers and technology firms are experimenting with chatbots, powered by a combination of machine learning, natural language processing, and live operators, to provide customer service, sales support, and other commerce-related functions. Chris Messina of Uber recently coined the term "conversational commerce" to describe this movement, which he defines as: The net result is that you and I will be talking to brands and companies over Facebook Messenger, WhatsApp, Telegram, Slack, and elsewhere before year's end, and will find it normal. While messaging and voice interfaces are central components, they fit into a larger picture of increasing infusion of technology into our daily lives, which in turn is unlocking new potential for brand-to-consumer interaction. The fact is, technology overall is becoming more deeply woven into our lives, and the entire ecosystem is enjoying tighter cohesion through the increasing availability and sophistication of APIs. Smart companies are finding new and innovative touch points with consumers that are contextual, relevant, highly personal, and, yes, conversational.

Ben Dickson is a software engineer and the founder of TechTalks. As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we've become somewhat expectant that robots can succeed where humans have failed -- namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society. While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make. At its core, machine learning uses algorithms to parse data, extract patterns, learn and make predictions and decisions based on the gleaned insights.

There was the voice recognition software that struggled to understand women, the crime prediction algorithm that targeted black neighbourhoods and the online ad platform which was more likely to show men highly paid executive jobs. Concerns have been growing about AI's so-called "white guy problem" and now scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making. Mortiz Hardt, a senior research scientist at Google and a co-author of the paper, said: "Decisions based on machine learning can be both incredibly useful and have a profound impact on our lives ... Despite the need, a vetted methodology in machine learning for preventing this kind of discrimination based on sensitive attributes has been lacking." A beauty contest was judged by AI and the robots didn't like dark skin The paper was one of several on detecting discrimination by algorithms to be presented at the Neural Information Processing Systems (NIPS) conference in Barcelona this month, indicating a growing recognition of the problem. Nathan Srebro, a computer scientist at the Toyota Technological Institute at Chicago and co-author, said: "We are trying to enforce that you will not have inappropriate bias in the statistical prediction."