IBM's California research lab sits atop a green hill here, 15 miles south of downtown San Jose. There aren't any signs that suggest if you drive up the narrow road that wraps around the hill you'll find a research facility at the top. No signs that the research center is home to a Fortune 500 company. No signs -- even inside -- that the company once dominated the personal computer industry. After decades in the spotlight as a hardware-centric firm selling PCs, servers and mainframes, the 105-year-old tech giant has made a dramatic shift into a realm that few understand: cognitive computing. Deep within the apps we use, the food we eat, the medicine we take and the medical diagnoses we make, you'll find traces of IBM.

Care Angel, which has been dubbed "Siri for Seniors, but with a brain like Watson," took the top prize at the MM&M Shark Tank held during Thursday's MM&M Transforming Healthcare conference in New York City. Jason Hendeles, co-founder of Care Angel, a virtual caregiving assistant, and executives from two other health startups presented their business models to seven pharma executives at the conference. "Judges liked the idea of an automated care call leading to a digitally assisted human one, and the potential to fill in those gaps in care for the elderly," said MM&M editor-in-chief Marc Iskowitz. The winning entrepreneur received the opportunity to pitch dRx Capital, the joint investment company of Novartis and Qualcomm, and discuss beyond-the-pill collaborations with the pharma and medical device judges on the panel. It also won a two-day immersion process with McCann Health's Think Tank, which will assist Care Angel in achieving its goals from a go-to-market perspective.

If your mind instantly went to Skynet, I can put your mind at ease; it's not Skynet. That's not, however, to say that this problem isn't just as scary, only without the cool special effects. While Sci-Fi has made the risks of robot takeover well-known, the more immediate concerns are the subtle decisions being made by (sometimes) poorly coded, or designed, algorithms that can drastically alter each of our lives. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. The Obama administration published a report this week that examines problems associated with the shift to an increasingly automated world.

It gets by, with a little help from its inanimate friends. Cooperation is an evolutionary advantage. While many creatures are perfectly comfortable spending most of their time alone, creatures that work together are capable of far more than their individual components working separately. It should come as no surprise, then, that when researchers make animal-inspired robots, they design them to work together, as a team. Created by the University of California, Berkeley, the VelociRoACH is a small, fast, insect-imitating little machine.

It's a strong contender for the geekiest video ever made: a close-up of a smartphone with line upon line of numbers and symbols scrolling down the screen. But when visitors stop by Nicola Marzari's office, which overlooks Lake Geneva, he can hardly wait to show it off. "It's from 2010," he says, "and this is my cellphone calculating the electronic structure of silicon in real time!" Even back then, explains Marzari, a physicist at the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, his now-ancient handset took just 40 seconds to carry out quantum-mechanical calculations that once took many hours on a supercomputer -- a feat that not only shows how far such computational methods have come in the past decade or so, but also demonstrates their potential for transforming the way materials science is done in the future. Instead of continuing to develop new materials the old-fashioned way -- stumbling across them by luck, then painstakingly measuring their properties in the laboratory -- Marzari and like-minded researchers are using computer modelling and machine-learning techniques to generate libraries of candidate materials by the tens of thousands.

Expertmaker was founded in 2006; in its own words, the company's "genetics-inspired multi-AI approach, extracts hidden value in your data." I couldn't have said it better myself. So if you have a ton of noisy data, as eBay most certainly does, these are the guys who can wrangle it and produce something useful. Lars Hard, Expertmaker's founder, will continue on as head of the team, though the company will operate under eBay's Structured Data initiative, which is led by Amit Menipaz. The rest of Expertmaker's employees will, mercifully, be allowed to continue working from their office in Malmö.

Adam Coates, director of Baidu Research's Silicon Valley AI Lab, isn't worried about artificial intelligence taking over the world. "I will tell you why I am not actually afraid of AI right now," he said at the InformationWeek Elite 100 Conference in the Four Seasons Hotel in Las Vegas on Tuesday, May 3. "I don't go around seeing every Camero on the street thinking that's a Transformer. I know what's under the hood. It's self-evident the technology is just not capable of doing something like that today." Not everyone in the audience was entirely convinced there's no need for fear.

Joab Rosenberg is the former deputy head analyst for the Israeli government and CEO of Epistema. Nature magazine announced in late January that a computer designed by Google's DeepMind defeated a human master in the ancient Chinese board game, "Go." This impressive achievement once again raised the expectations for a predicted future in which computers will have artificial intelligence, with major media outlets worldwide touting this anticipated future. One of the major questions raised in response to DeepMind's achievement is what are the outer limits, if any, of intelligent machines? In November of last year, Dr. Kira Radinsky, a computer scientist and "machine learning" expert, argued in the Israeli newspaper "Ha'aretz" that computers will be able to accurately predict the outcome of the Israeli-Palestinian conflict.

It's a strong contender for the geekiest video ever made: a close-up of a smartphone with line upon line of numbers and symbols scrolling down the screen. But when visitors stop by Nicola Marzari's office, which overlooks Lake Geneva, he can hardly wait to show it off. "It's from 2010," he says, "and this is my cellphone calculating the electronic structure of silicon in real time!" Even back then, explains Marzari, a physicist at the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, his now-ancient handset took just 40 seconds to carry out quantum-mechanical calculations that once took many hours on a supercomputer--a feat that not only shows how far such computational methods have come in the past decade or so, but also demonstrates their potential for transforming the way materials science is done in the future. Instead of continuing to develop new materials the old-fashioned way--stumbling across them by luck, then painstakingly measuring their properties in the laboratory--Marzari and like-minded researchers are using computer modelling and machine-learning techniques to generate libraries of candidate materials by the tens of thousands.

It's always exciting when a new robot arrives in your lab. Usually, the more expensive the robot is, the more exciting it is. With the possible exception of Boston Dynamics' ATLAS, NASA's Valkyrie has got to be one of the most expensive humanoid robots ever made, and last year, NASA promised to give away (or, at least, lend) three of them to universities in the hope that Valkyrie will learn some new skills. Within the last few weeks, the University of Massachusetts Lowell, which teamed up with Northeastern University in Boston, Mass., took delivery of their fancy new robot, as did MIT and the University of Edinburgh in Scotland. We talked to Holly Yanco at UMass Lowell and Taskin Padir at Northeastern, along with Sethu Vijayakumar at Edinburgh and Russ Tedrake at MIT, about what it's like to have a smokin' hot space robot show up on your doorstep in a bunch of pieces.