Kelly Fisher started using a robo-advisor a year and a half ago because she thought it would be more convenient and easier than investing through a human advisor. What she didn't anticipate, though, was just how much more truthful she would be with an automaton rather than a living, breathing person sitting across the desk. When someone starts asking me about my net worth, I get uncomfortable. The San Francisco-based retail executive has about 8,000 invested in accounts with robo-advisors. These are sites that ask a series of questions and then they match a fund with that investor's risk tolerance and lifestyle.

Everyone is talking about chatbots these days. Telegram has them, Facebook got them recently, Slack has them and many more want them (for a good reason). It was time to figure out what these chatbots are and how they can help and make life easier. We are at a point where artificial intelligence is a big thing again. Recent movies like "Ex Machina" and "Her" pictured super smart and dangerous AI-driven bots that could easily become a threat to humanity.

Google became one of the most powerful companies on the planet by addressing a once-in-a-generation problem: Make it easy for people to search for stuff online. Alphabet, Google's parent company, is hard at work tinkering with a sweep of projects, from Wi-Fi-connected thermostats to nanoparticles for detecting cancer. Sales from those projects, which Alphabet calls "Other Bets," brought in 166 million last quarter, up from 80 million a year earlier. But losses from those experiments widened to 802 million last quarter from 633 million this time last year. Normally that wouldn't matter much, but pressure is sure to mount after the company's disappointing earnings report on Thursday.

News flash: Artificial intelligence (AI) and other cognitive technologies are eliminating jobs left and right. The short answer is no…don't lose sleep over it. First off, cognitive technologies (even super cool advanced ones) are best with structured tasks and finding patterns. You know, auditing grunt work. I assume most sane people would prefer to not be subjected to the mundane, mind-numbing work anyway and say, "Go ahead, automate the cross-footing and put me out of my misery!"

Used to be you knew which city you were in from the food, the sports team, the historic sites, even the local brew. Now a team of microbiologists discovered they can tell cities apart by their unique bacterial fingerprints. The surprising finding was made after an intense study led by John Chase of Northern Arizona University's Department of Biological Sciences and Center for Microbial Genetics and Genomics. He and his colleagues spent a year swabbing for samples at nine offices in San Diego, Flagstaff, and Toronto. They wanted to find out what kind of impact factors like geography, location in a room, seasons, and human interaction have on the microbial communities we spread around, called microbiomes.

Taking a vehicle to the race track to improve it has been a thing for almost as long as we've had cars. Henry Ford built his brand's name on his early racing exploits, and so have countless others. So it's natural that some of the people interested in self-driving cars have been thinking about how the track can benefit this new technology. Joshua Schachter is one such person, and he's organizing the first autonomous track day, to be held on May 28th-29th at Thunderhill Raceway in Willow, California. Self-driving cars and racing are two of my favorite things, so I spoke to Schachter to find out more.

The stakes are large in the Natural Language Processing (NLP) market: It's the high ground in the battle for control of the data economy and the key to turning silicon into gold, according to a report issued this quarter from market intelligence firm Tractica. Report authors Bruce Daley, the Principal Analyst, and Clint Wheelock, the Managing Director, cite as an example the upcoming Facebook virtual digital assistant Moneypenny. Noting that Facebook already turns an average daily revenue of 11.96 per active user, they surmise that if the same number of active daily users adopt Moneypenny and generate just an additional 1 in additional ad revenue, the program would add 1 billion to the company's annual top line and almost as much to its bottom line. With these and other tantalizing economic prospects at hand, is it any wonder that big names from Amazon to Apple and from Google to Microsoft – not to mention IBM, Nuance, AT&T, and others – are driving further research into NLP and acquiring companies specializing in the space? This month saw another Natural Language Processing acquisition take place, as well-known CRM vendor SugarCRM purchased Contastic's NLP technology.

Here we are, part four of our Practicing Deep Learning Series. Alas, we are at the point where we will start to examine multilayer neural networks! We've spent a decent amount of time building up to this point, but with good reason. It can be easy to gloss over the details of the individual neurons and we feel the risk of being too verbose outweighed the risk of being uninformative. The real power of neural networks become increasingly apparent when we start making multi-layer networks. In this post, we're going to describe the basic multi-layer network and look at examples of some of simple tasks it can solve. We're going to dive into two specific examples, but we provide code for those two – plus a few others. We'll point you to that code as we go.

Ugh, that is not art, it is not even good design! Paradoxically, claiming that non-art is art is an artistic act, but the act of doing so is the art, not the subject.

I was a slow runner as a boy (jokes to a minimum please). I hated playing those backyard games where I had to chase people around. I found myself looking for ways to outthink the other kids I was chasing. Eventually, I became proficient at cutting around bushes, hopping fences and avoiding backyard obstacles (like garden hoses and trash cans) so that I could easily catch other kids. That's where we are with cognitive computing.