The search to improve and eventually perfect artificial intelligence is driving the research labs of some of the most advanced and best-known American corporations. They are investing billions of dollars and many of their best scientific minds in pursuit of that goal. All that money and manpower has begun to pay off.In the past few years, artificial intelligence -- or A.I. -- has taken a big leap -- making important strides in areas like medicine and military technology. What was once in the realm of science fiction has become day-to-day reality. You'll find A.I. routinely in your smart phone, in your car, in your household appliances and it is on the verge of changing everything. It was, for decades, primitive technology. But it now has abilities we never expected. It can learn through experience -- much the way humans do -- and it won't be long before machines, like their human creators, begin thinking for themselves, creatively. Independently with judgment -- sometimes better judgment than humans have. As we first reported last fall, the technology is so promising that IBM has staked its 106-year-old reputation on its version of artificial intelligence called Watson -- one of the most sophisticated computing systems ever built. John Kelly, is the head of research at IBM and the godfather of Watson.

Listen in to this special episode of Charged Up!, taken from a live Facebook broadcast with Jason Schenker, who Bloomberg ranks as the world's foremost financial futurist. In this episode, we talk about Schenker's predictions, laid out in his 2017 book "Jobs for Robots: Between Robocalypse and Robotopia," and how the robot revolution will affect our jobs, our pay and our career prospects. Schenker talks about three industry sectors that are safest from being taken over by technology, what students should study if they're entering school now and what kind of skills will protect you from losing out to robots. So, get Charged Up! about learning how to survive the robot revolution! Jason Schenker: Thank you very much, Jenny. It's a real pleasure to be here. Hoff: So, we're going to talk today about your book, "Jobs for Robots" and this is a live broadcast on Facebook so we're also going to be taking questions from our listeners which I will then later translate for the podcast so we make sure that everybody can hear the questions. But first I want to talk a little bit about how did you get into being a futurist and then where did the interest in robots come from? Schenker: Sure, the most important thing is as a futurist there's three components to it: You're part historian because you need the historical perspective of where we've been.

Dr Crystal Valentine, the company's vice-president of technology strategy, told iTWire in an interview that it was still the very early days of seeing machine learning and deep learning being put to work by enterprises outside academia. Dr Valentine has a background in big data research and practice and before joining MapR, she was a professor of computer science at Amherst College. She has authored various academic publications in the areas of algorithms, high-performance computing, and computational biology and holds a patent for Extreme Virtual Memory. As a former consultant at Ab Initio Software, working with Fortune 500 companies to design and implement high-throughput, mission-critical applications and as a tech expert consulting for equity investors focused on technology, Dr Valentine has developed significant business experience in the enterprise computing industry. Dr Crystal Valentine: Machine learning encompasses a number of different algorithms for training computers to solve specific tasks, including tasks that are part of larger artificial intelligence systems.

At least since Isaac Asimov posited the Three Law of Robotics, many have wondered whether robots would ultimately help or harm humanity. Or maybe do a little of both. Humanity still has time to shape the answer to that question, and we're pleased to announce three speakers who have distinctive, grounded perspectives on how to secure a world made better (not worse) by robots. These speakers join our agenda for TechCrunch Sessions: Robotics, our first one-day event dedicated to discussing the core topics facing the robotics industry. General admission tickets are currently available for purchase though seating is very limited.

His impact on artificial intelligence research has been so deep that some people in the field talk about the "six degrees of Geoffrey Hinton" the way college students once referred to Kevin Bacon's uncanny connections to so many Hollywood movies. Dr. Hinton's students and associates are now leading lights of artificial intelligence research at Apple, Facebook, Google and Uber, and run artificial intelligence programs at the University of Montreal and OpenAI, a nonprofit research company. "Geoff, at a time when A.I. was in the wilderness, toiled away at building the field and because of his personality, attracted people who then dispersed," said Ilse Treurnicht, chief executive of Toronto's MaRS Discovery District, an innovation center that will soon house the Vector Institute, Toronto's new public-private artificial intelligence research institute, where Dr. Hinton will be chief scientific adviser. Dr. Hinton also recently set up a Toronto branch of Google Brain, the company's artificial intelligence research project. His tiny office there is not the grand space filled with gadgets and awards that one might expect for a man at the leading edge of the most transformative field of science today.

Notes from Reality is a series of posts on AI and its impact on humans, what can be done today, and what may happen tomorrow. No one has all the answers, but we are trying to arrive at the right questions.

AI was very popular 30 years ago, then disappeared, and is now making a big come back because of new robotic technologies: driver-less cars, automated diagnostic, IoT (including vacuum cleaning and other household robots), automated companies with zero employee, soldier robots, and much more. Will AI replace data scientists? I think so, though data scientists will be initially replaced by "low intelligence" yet extremely stable and robust systems. There has been a lot of discussions about the automated statistician. I am myself developing data science techniques such as Jackknife regression that are simple, robust, suitable for black-box, machine-to-machine communications or other automated use, and easy to understand and pilot by the layman, just like a Google driver-less car can be "driven" by an 8 years old kid.

Santiago Ramón y Cajal, a Spanish histologist and anatomist known today as the father of modern neuroscience, was also a committed psychologist who believed psychoanalysis and Freudian dream theory were "collective lies." When Freud published The Interpretation of Dreams in 1900, the science world swooned over his theory of the unconscious. Dreams quickly became synonymous with repressed desire. Puzzling dream images could unlock buried conflicts, the psychoanalyst said, given the correct interpretation. Cajal, who won the 1906 Nobel Prize for discovering neurons and, more remarkably, intuiting the form and function of synapses, set out to prove Freud wrong. To disprove the theory that every dream is the result of a repressed desire, Cajal began keeping a dream journal and collecting the dreams of others, analyzing them with logic and rigor. Translated here into English for the first time, the dreams of Santiago Ramón y Cajal offer insight into the mind of a great scientist. Cajal eventually deemed the project unpublishable.

A leading economist has inadvertently caused a storm by saying he preferred the voice on the iPhone Siri virtual assistant to be male because he felt that made it more trustworthy. Nobel prize laureate Sir Christopher Pissarides's comments at a conference in Norway attracted fierce criticism. He told the BBC he apologised for upsetting people and his comment was meant to be "light-hearted". "It's a mistake and I'm sorry, but the audience was laughing." Sir Christopher was part of an all-male panel taking part in a Q&A audience discussion at the Starmus Festival in Trondheim about the future of humanity.

Editor's note: The following is an interview with University of Illinois professor and text analytics guru Bing Liu, conducted by marketing scientist Kevin Gray, in which Liu concisely outlines the current state of the field. Kevin Gray: I see "text analytics" and "text mining" used in various ways by marketing researchers and often used interchangeably. What do these terms mean to you? Bing Liu: My understanding is that the two terms mean the same thing. People from academia use the term text mining, especially data mining researchers, while text analytics is mainly used in industry. I seldom see academics use the term text analytics.