There are a lot of conspiracy theories about robots taking over our jobs or killing the humanity. In fact, famous physicist Professor Stephan Hawking agrees with researchers who claim AI robots will leave humanity ''Utterly Defenceless.'' Now, researchers at IOActive, a cyber security company has revealed that [Pdf] programs which "bring them (robots) to life" carry critical vulnerabilities which can be used by threat actors for negative purposes. The development of artificial intelligence (AI) robots is on the rise. Last year, IBM developed Ross – World's first AI lawyer and plans are to license it for being utilized in domains like bankruptcy, restructuring and creditors' rights team.

Artificial intelligence is already gaining steam as one of the most-talked-about tech trends of 2017. It's one of those umbrella terms that's easy to throw around. But away from the big conferences and debates about tech's role in society, the hard work to develop the predictive technology is happening. One of those spots is the Eastern Campus of the Emerging Technology Centers, where Insilico Medicine is working to develop algorithms that can help select and develop the right drugs. The company sees artificial intelligence as a path to reduce the use of animal testing in developing pharmaceuticals, and is even working on a virtual human to simulate how drugs affect the body.

Artificial intelligence has seen several breakthroughs in recent years, with games often serving as milestones. A common feature of these games is that players have perfect information. Poker is the quintessential game of imperfect information, and a longstanding challenge problem in artificial intelligence. We introduce DeepStack, an algorithm for imperfect information settings. It combines recursive reasoning to handle information asymmetry, decomposition to focus computation on the relevant decision, and a form of intuition that is automatically learned from self-play using deep learning.

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.

In science fiction, the promise or threat of artificial intelligence is tied to humans' relationship to conscious machines. Whether it's Terminators or Cylons or servants like the "Star Trek" computer or the Star Wars droids, machines warrant the name AI when they become sentient--or at least self-aware enough to act with expertise, not to mention volition and surprise. What to make, then, of the explosion of supposed-AI in media, industry, and technology? In some cases, the AI designation might be warranted, even if with some aspiration. Autonomous vehicles, for example, don't quite measure up to R2D2 (or Hal), but they do deploy a combination of sensors, data, and computation to perform the complex work of driving.

No longer is advanced computing only for the super rich or super intelligent. With thanks to companies like IBM, machine learning is becoming even more accessible. One of their next moves is to bring machine learning to a mainframe near you. Firstly they want to provide a simplified experience for data modeling and model deployment. Secondly, they are looking to support the deployment of machine learning tools on its z series mainframes.

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.