When most people think about artificial intelligence (AI), they envision high-tech robots and automated processes, or, in a more romantic sense, the promise of technology finally being realized. Hardly anyone thinks about the actual people behind the technology. However, for every game-changing technology and innovative product, there is a team of humans conceiving new ideas, powering them from behind the scenes, and collaborating alongside it. AI technologies have existed in some form for a few decades, but until recently, the possibilities were more science fiction than reality. It's only been in the past few years that the potential of AI has started to come to life, and it is growing at an incredibly fast rate.

Each year, the U.S. Census Bureau spends $1 billion surveying the population. These surveys are designed to tease apart the demographic makeup of the country by asking a representative group of people about their race, gender, education, occupation, and so on. This is an important exercise because it gives a crucial bird's-eye view of the population and how it is changing. For a start, the data is relatively large scale--the Census Bureau's main survey, the American Community Survey, gives results for all cities and counties with a population greater than 65,000. What's more, surveying the population is a time-consuming exercise; so much so that some data can be five years old by the time it is published.

I do think that machine learning altogether is probably going to be one of the biggest shifts in computing that we'll see in quite a few years. I'm reluctant to put a number on it like -- the biggest thing in 25 years or whatever,

Rick Delgado explores why it makes sense to add an AI layer to the IoT, possibly adding new possibilities and capabilities to both technologies.

NEXTracker, who makes devices that shift solar panels to soak in as much direct sunlight as possible, acquired a startup called BrightBox Technologies out of Berkeley (shocker) to add some intelligence to its hardware. NEXTracker will use software developed by BrightBox, originally made to monitor and control temperatures in large buildings, to increase energy production of solar farms, thereby enabling faster operations and easier maintenance. Can you say streamlining processes? AI is great for that.

Spurred by the rise of chatbots in consumer apps, companies are giving voice (literally) to virtual assistants in the workplace. Watch this video demo of HanaHaus, a caf; and community workspace in Silicon Valley, where people reserve tables via chatbots communicating in natural, everyday language.

Google researchers say they are using deep learning algorithms to enable computers to examine slide images of tissue samples and diagnose cancer relatively reliably.

The relationship between humans and machines has captivated people for years--from robots that can win Jeopardy to those that can sense human emotions, the list is endless. Today, however, machines are no longer simply a novelty. The rise of analytics and artificial intelligence (AI) has become a key component of a business' success. In the banking world, there are many examples to point to: self-service tellers, automated loan processing, payments, etc. But there's one in particular that is fascinating--the robo-advisor.

Worries that robots may end up replacing human workers have lately sparked debates over the role of artificial intelligence in corporate jobs. During a Fortune conference that tackled the subject and its various implications, voices from IBM and Google proceeded to dissipate concerns and state there's no need for alarm. Present at the Most Powerful Women International Summit in Hong Kong on March 2, women leaders of the two tech companies reassured the public that there's no need to worry about an A.I. takeover, as the technology is here to help and could significantly improve the activity of firms. According to Vanitha Narayanan, chairman of IBM India, the first corporate sector to gain the most from this technology would be that of service-oriented companies. Just like what her boss, IBM CEO Ginni Rometty, previously explained at the World Economic Forum, Narayanan reaffirmed the idea of a partnership between humans and machine.

I listened once to an old professor talking about working out factorial ANOVA and multiple regression on paper, back in the day. He described a whole room full of papers, all in a particular order, every sum contributing to the next sum and if you got one number wrong the whole thing would be wrong and you'd have to start over. Adding machines made it go quicker, and when punch-card mainframes came they were, well, frustrating at times -- lots of graphic and emotional stories there! By the end of the nineties everybody had a computer on their desktop, mostly with a connection to the brand-new Internet. SAS, SPSS, and other statistical and data-management packages became crucial office workhorses, and don't forget Excel.