It's a weird feeling, cruising around Silicon Valley in a car driven by no one. I am in the back seat of one of Google's self-driving cars – a converted Lexus SUV with lasers, radar and low-res cameras strapped to the roof and fenders – as it maneuvers the streets of Mountain View, California, not far from Google's headquarters. I grew up about five miles from here and remember riding around on these same streets on a Schwinn Sting-Ray. Now, I am riding an algorithm, you might say – a mathematical equation, which, written as computer code, controls the Lexus. The car does not feel dangerous, nor does it feel like it is being driven by a human. It rolls to a full stop at stop signs (something no Californian ever does), veers too far away from a delivery van, taps the brakes for no apparent reason as we pass a line of parked cars. I wonder if the flaw is in me, not the car: Is it reacting to something I can't see? The car is capable of detecting the motion of a cat, or a car crossing the street hundreds of yards away in any direction, day or night (snow and fog can be another matter). "It sees much better than a human being," Dmitri Dolgov, the lead software engineer for Google's self-driving-car project, says proudly. He is sitting behind the wheel, his hands on his lap. As we stop at the intersection, waiting for a left turn, I glance over at a laptop in the passenger seat that provides a real-time look at how the car interprets its surroundings. On it, I see a gridlike world of colorful objects – cars, trucks, bicyclists, pedestrians – drifting by in a video-game-like tableau. Each sensor offers a different view – the lasers provide three-dimensional depth, the cameras identify road signs, turn signals, colors and lights. The computer in the back processes all this information in real time, gauging the speed of oncoming traffic, making a judgment about when it is OK to make a left turn.

In INHUMAN KIND, Motherboard gains exclusive access to a small fleet of US Army bomb disposal robots--the same platforms the military has weaponized--and to a pair of DARPA's six-foot-tall bipedal humanoid robots. We also meet Nobel Peace Prize winner Jody Williams, renowned physicist Max Tegmark, and others who grapple with the specter of artificial intelligence, killer robots, and a technological precedent forged in the atomic age. It's a story about the evolving relationship between humans and robots, and what AI in machines bodes for the future of war and the human race.

What do you think of when someone says "AI" or "Artificial Intelligence"? For most of us, it conjures up an image of the future. It doesn't much evoke the here and now. Artificial intelligence is already out of the box. And while it might not be as slick as the movies, it has vast applications in almost every field, from business to medicine, traffic jams to Facebook photos. Most of us use or benefit from artificial intelligence every day.

It might not happen anytime soon, but then again, it might. In Japan, a short novel co-written by an artificial intelligence program (its co-author is human) made it past the first stage of a literary contest, the Japan News reports. The Nikkei Hoshi Shinichi Literary Award is named after Hoshi Shinichi, a Japanese science fiction author whose books include "The Whimsical Robot" and "Greetings from Outer Space." Judges for the prize weren't told which novels were written by humans and which were penned by human-computer teams. The award is unique in that it accepts entries from "applicants who are not human beings (AI programs and others)."

Why did I bother writing this? Well, here is one of the most trivial yet life-changing insights and worldly wisdoms from my former professor that has become my mantra ever since: "If you have to do this task more than 3 times just write a script and automate it." By now, you may have already started wondering about this blog. I haven't written anything for more than half a year! Okay, musings on social network platforms aside, that's not true: I have written something – about 400 pages to be precise. This has really been quite a journey for me lately. And regarding the frequently asked question "Why did you choose Python for Machine Learning?" I guess it is about time to write my script. In the following paragraphs, I really don't mean to tell you why you or anyone else should use Python. To be honest, I really hate those types of questions: "Which * is the best?" (* insert "programming language, text editor, IDE, operating system, computer manufacturer" here).

Andy Grove, the refu gee from Hungary who became one of the pillars of Silicon Valley and, as both scientist and executive, was a principal figure in the rise of the Intel Corp. and a symbol of the world-wide computer revolution, died Monday. The death was announced on the company's website. It did not give a cause or a location. He had been diagnosed with prostate cancer and Parkinson's disease. In a statement, Intel chief executive Brian Krzanich said that Mr. Grove "made the impossible happen, time and again, and inspired generations of technologists, entrepreneurs, and business leaders."

Until now, medicine has been a prestigious and often extremely lucrative career choice. But with intelligent machines now used to diagnose diseases, in the near future, will we need as many doctors as we have now? Are we going to see significant medical unemployment in the coming decade? Dr Saxon Smith, president of the Australian Medical Association NSW branch, said in a report late last year that the most common concerns he hears from doctors-in-training and medical students are, "what is the future of medicine?" The answers, he said, continue to elude him.

SAN FRANCISCO, March 21 (Reuters) - Andy Grove, the Silicon Valley elder statesman who made Intel into the world's top chipmaker and helped usher in the personal computer age, died on Tuesday at age 79, Intel said. The company did not describe the circumstances of his death but Grove, who endured the Nazi occupation of Hungary during World War Two, living under a fake name, and came to the United States to escape the chaos of Soviet rule, had suffered from Parkinson's. Grove was Intel's first hire after it was founded in 1968 and became the practical-minded member of a triumvirate that eventually led "Intel Inside" processors to be used in more than 80 percent of the world's personal computers. With his motto "only the paranoid survive," which became the title of his best-selling management book, Grove championed an innovative environment within Intel that became a blueprint for successful California startups. Grove, who was named man of the year by Time magazine in 1997, encouraged disagreement and insisted employees be vigilant of disruptions in industry and technology that could be major dangers - or opportunities - for Intel.

In the first part of our interview with Sean Owen, Cloudera's Director of Data Science, we discussed the relationship between machine learning and Hadoop, the future of Apache Mahout and why machine learning has become such hot property. In this part of our discussion, we delved into the future of deep learning and neural networks, and how Owen foresees the relationship between machine learning and enterprise evolving. What do you think are some of the main trends in machine learning right now? To be honest, I think machine learning is still an advanced topic for enterprises. The infrastrcutres of most enterprises are built around reporting and retroactive analytics, and predictive analytics is still considered difficult and expensive.

This was the title of a very popular book published in 2012, featuring several job interview questions (brain teasers) asked by Google's hiring managers to candidates. They apparently dropped all these questions, as they found out that they were not good indicators of career success. Do you think you are smart enough to work for Google? I had one phone interview with Google long ago, and was rejected right away. The interviewer was just focused on very technical details, and spent all her time arguing about Lasso regression, and was clearly looking for a specialist, dismissing people with a broad range of skills and non-standard approach to solving tech problems.