Quora Questions are part of a partnership between Newsweek and Quora, through which we'll be posting relevant and interesting answers from Quora contributors throughout the week. Who is leading in AI research among big players like IBM, Google, Facebook, Apple and Microsoft? First, my response contains some bias, because I work at Google Brain, and I really like it there. My opinions are my own, and I do not speak for the rest of my colleagues or Alphabet as a whole. I rank "leaders in AI research" among IBM, Google, Facebook, Apple, Baidu, Microsoft as follows: I would say Deepmind is probably #1 right now, in terms of AI research.

After I was more comfortable with Facebook I joined Twitter. But I noticed the same behaviour – obsession. This intersection of people and technology was resonating with our tribal curiosity and creativity. Technology was becoming more human. Then the smart phone was added to the mix.

This article is courtesy of Techstars, the best global ecosystem for entrepreneurs to bring new technologies to market. From inspiration to IPO, Techstars empowers the world's most promising entrepreneurs throughout their lifelong journey by providing a global ecosystem made up of tens of thousands of community leaders, founders, mentors, investors, and corporate partners. More consumers are getting used to purchasing their items online, through voice activation or on their smartphone. But there are more solutions that need to happen in retail and startups are starting to respond. After walking the floors of CES and other events, talking with our corporate partners, and meetings with hundreds of startups, here are some trends I'm seeing for 2017 for retail technology for startups.

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.