The vision of robots taking over the world might sound like something out of a dystopian science fiction novel. But robots will outnumber humans by 2048, an expert has predicted today. According to'leading futurologist' Dr Ian Pearson, earth's robot population will grow from around 57 million to 9.4billion over the next 30 years. Dr Pearson, a British novelist, engineer and inventor, said robots could also become'emotionally intelligent' by 2028. He said his predictions are based on the'modest' assumption that the number of robots will grow by a fifth each year.

The company on Monday demonstrated robots that can pick up a pile of boards and take them to an elevator. It says the Robo-Welder and Robo-Buddy, with twisting mechanical arms, will be deployed at construction sites later this year, though because of safety concerns they will be used during night shifts when most human workers are not around.

Seems like the term Machine Learning is popping up in mainstream media as the next big thing. The fact is, however, that Machine Learning went mainstream a long time ago. You don't think so? Check your mobile phone. Chances are you've been using and benefiting from Machine Learning algorithms all this time without even knowing it. In this blog post, I go through some of the many apps on your mobile phone that use Machine Learning algorithms to make recommendations, get you to your destination quickly and safely, improve your photos, tell you what song you're listening to and more.

We present a learning-based system for rapid mass-scale material synthesis that is useful for novice and expert users alike. The user preferences are learned via Gaussian Process Regression and can be easily sampled for new recommendations. Typically, each recommendation takes 40-60 seconds to render with global illumination, which makes this process impracticable for real-world workflows. Our neural network eliminates this bottleneck by providing high-quality image predictions in real time, after which it is possible to pick the desired materials from a gallery and assign them to a scene in an intuitive manner. Workflow timings against Disney's "principled" shader reveal that our system scales well with the number of sought materials, thus empowering even novice users to generate hundreds of high-quality material models without any expertise in material modeling. Similarly, expert users experience a significant decrease in the total modeling time when populating a scene with materials. Furthermore, our proposed solution also offers controllable recommendations and a novel latent space variant generation step to enable the real-time fine-tuning of materials without requiring any domain expertise.

Finance is today, metamorphosing into a strategically focused, value-driven function. Within organizations, finance teams are becoming important catalysts for business growth. CFOs are investing rapidly in various technologies to maximize the potential of the finance function through streamlining and automation. Historical and real-time big data; and predictive analytics are connecting operations, functions and teams, providing visibility and access to insights. Blockchain and IoT is enabling sophisticated data collection and analysis, resulting in actionable insights that help build the competitive advantage.

The Artificial Intelligence Products Market report explores and analyses the essential factors of market depending on present industry situations, market needs, business strategies and the growth condition.This report isolates the Artificial Intelligence Products market capacity, production, market share, …

How developers are humanizing their virtual personal assistants. The virtual personal assistant is romanticized in utopian portrayals of the future from The Jetsons to Star Trek. It's the cultured, disembodied voice at humanity's beck and call, eager and willing to do any number of menial tasks. In its early real-world implementations, a virtual receptionist directed customers ('To hear more menu options, press 9′). It wasn't until 2011 that Apple released Siri and the public had its first interactions with a commercially viable, dynamic personal assistant. Since Siri's debut with the release of the iPhone 4S, Apple's massive customer base has only gotten larger; the company estimates that more than 700 million iPhones are currently in use worldwide. Amazon's Alexa and Microsoft's Cortana debuted in 2014; Google Assistant followed in 2016.

I'm not what you would call a fan of Westworld. As an AI reporter, telling this to people often triggers an audible gasp, followed by a look of disbelief and disappointment. Despite my lack of enthusiasm for the show, I plan to watch every episode of season two, which starts Sunday on HBO, and developers should too. Earlier this week, I attended a showing of episode one in San Francisco and had an opportunity to chat with members of the cast. I took the interviews because I wanted to know how people playing parts in a show that shapes the world's perception of AI felt about the impact of AI.

"We're entering an era in which our enemies can make it look like anyone is saying anything at any point in time -- even if they would never say those things," says "Obama," his lips moving in perfect sync with his words as they become increasingly bizarre. "So, for instance, they could have me say things like, I don't know, [Black Panther's] Killmonger was right! Or Ben Carson is in the sunken place! Or, how'bout this: Simply, President Trump is a total and complete dipshit." As the video soon reveals, the man speaking is not the former commander-in-chief, but rather Oscar-winning filmmaker Jordan Peele with a warning for viewers about trusting material they encounter online.

"YOUR CALL IS important to us," a recorded voice tells resigned customers as they wait endlessly to speak to a human agent. AI is starting to help companies improve the quality and consistency of their service in order to persuade customers that they do in fact care about them. Ocado, a British online grocer, receives around 10,000 e-mails from customers every day and uses AI to detect the prevailing sentiment in them. It now replies to the most urgent ones first, and is planning to route complaints to agents with expertise in the relevant field. "Like other applications of AI, it's about trying to make humans more efficient, not take them out of the process entirely," says Paul Clarke, Ocado's chief technology officer.