Artificial intelligence (A.I.) is making the "rise of machines" -- once the stuff of science fiction -- a reality. As 60 Minutes reported on October 9, "It might not be long before machines begin thinking for themselves -- creatively, independently, and sometimes with better judgment than a human." On February 28, 2018, you're invited to "Meet the Future" at DePauw University as the Ubben Lecture Series presents the world's first artificial intelligence-fueled android, Sophia, and her creator, David Hanson. In a 7:30 p.m. program in Kresge Auditorium, Dr. Hanson -- founder, CEO and chief designer of Hong Kong-based Hanson Robotics -- will be joined by his one-of-a-kind robot character. At the free event, which is open to all, the two will deliver a speech, take questions from the audience, and offer insights into the world of tomorrow that we're already entering today.

The changes in user preferences can originate from substantial reasons, like personality shift, or transient and circumstantial ones, like seasonal changes in item popularities. Disregarding these temporal drifts in modelling user preferences can result in unhelpful recommendations. Moreover, different temporal patterns can be associated with various preference domains, and preference components and their combinations. These components comprise preferences over features, preferences over feature values, conditional dependencies between features, socially-influenced preferences, and bias. For example, in the movies domain, the user can change his rating behaviour (bias shift), her preference for genre over language (feature preference shift), or start favouring drama over comedy (feature value preference shift). In this paper, we first propose a novel latent factor model to capture the domain-dependent component-specific temporal patterns in preferences. The component-based approach followed in modelling the aspects of preferences and their temporal effects enables us to arbitrarily switch components on and off. We evaluate the proposed method on three popular recommendation datasets and show that it significantly outperforms the most accurate state-of-the-art static models. The experiments also demonstrate the greater robustness and stability of the proposed dynamic model in comparison with the most successful models to date. We also analyse the temporal behaviour of different preference components and their combinations and show that the dynamic behaviour of preference components is highly dependent on the preference dataset and domain. Therefore, the results also highlight the importance of modelling temporal effects but also underline the advantages of a component-based architecture that is better suited to capture domain-specific balances in the contributions of the aspects.

So is the Apple HomePod really worth the extra cost? MailOnline gave the smart speaker a test run to find out. Apple's HomePod stands at nearly 7 inches tall, which is slightly larger than the average smart speaker. It also feels heavier weighing in at 5.5lbs (2.5kg). But despite its size, it appears to blend into its surroundings.

I think it is a good program but I'm just not interested in web development anymore. I was originally positioning myself to become a UX Designer/Researcher, which I'm still interested in, but not particularly as it relates to web. Recently I've been getting much more interested in AI, since it touches on so many subjects I'm interested in, and obviously because it is such an important topic for the future. I definitely want to start positioning myself more towards this field as I continue my undegraduate field. But I don't really know where to go from here.

Back at IBC2017 there were three workflow demos of the DPP News Exchange project promoting the sharing of metadata, and this vital work has now arrived at prototype mode, with the prospect of publication in early April along with implementation guidance. The drivers of this project are the BBC, ITV, ITN, Sky, C5, Thomson Reuters, Sony, Avid, Telestream, Scisys, IPTC, and SAM (now Grass Valley). Confirming that a compliance program will also follow publication, Andy Wilson, DPP Head of Business Development and Delivery says: "News Exchange will enable the efficient movement of story metadata from the newsroom out to the reporter and cameraman in the field. "They record their video clips, and with that video file it will then send the metadata from the newsroom, now augmented with data from the camera and in an XML file, to be imported back into the newsroom. "This means the metadata with the story will pass with the video throughout the chain. There are immediate benefits to journalists like less tagging," he adds.

BEIJING, CHINA - Media OutReach - 2 February 2018 - Fung Retailing Limited, with a network of over 3,000 stores, and JD.com (Nasdaq: JD, JD.com or JD.COM), China's largest retailer, today announced a partnership to develop AI-driven retail solutions. According to the agreement signed today, the two companies will cooperate in using AI to transform the retail landscape, and to collaborate in areas including AI platform development and the application of AI to smart retail. The agreement calls for the establishment of an AI Boundaryless Retail Center that will oversee and manage cooperative research and development projects, and facilitate the sharing of information and expertise relating to AI technology. Leveraging AI, and combining JD.com's extensive online expertise and Fung Retailing's offline expertise, the two companies aim to develop a new retail format for China and Asia. This includes creating an AI-driven retail system that seamlessly integrates online and offline retail platforms; developing an end-to-end system that enables the management of products, pricing, storage, order and payment; and enhancing consumer experience through solutions such as AI-driven virtual fitting, unmanned stores and smart shopping assistants.

I understand where the article is coming from, but it sounds to me like a classic case of projecting their biases (i.e. the author has very strong feelings about a topic which is pretty marginal to the research papers themselves, and interprets the claims made in the papers through the lens of a worldview in which that topic is very important) For example, AlphaGo Zero makes claims about not using any human (Go) knowledge, which is, by human standards, pretty close to true. It mostly only uses general assumptions which would apply to most turn-based, perfect information board games. While that is certainly "knowledge about Go" in the strictest sense, such a distinction is pretty irrelevant in practice. The paper never claimed it had spawned an AGI that could solve any general problem without human intervention -- the context makes it pretty clear that the research applies to a narrow domain, and I don't believe any claims are made about not making any assumptions which rely on the properties of that narrow domain (indeed, such assumptions existing is pretty much a given -- whether they were implemented on purpose or by pure chance, the fact that it works in a domain and not in another is proof that this is the case)

Self-driving cars and robots that can zoom on their own around warehouses are just some of what's possible because of artificial intelligence. But expect unforeseen consequences if researchers ignore the inherent ethical dilemmas in the emerging technology. That's one of the takeaways from a panel about AI ethics and education in San Francisco that was hosted by the Future of Life Institute, a research group focused on preventing societal problems created by the technology. Although humans typically program AI-powered robots to accomplish a particular goal, these robots will typically make decisions on their own to reach the goal, explained Benjamin Kuipers, a computer science professor and AI researcher at the University of Michigan. Get Data Sheet, Fortune's technology newsletter.

First, the futurist Amy Webb told the audience of journalists, librarians and foundation managers that they could easily be duped by the ever-growing purveyors of artificial intelligence. Images of their faces could be affixed to others' bodies, their voices to impostors. Media people have acknowledged to pollsters that they are so focused on the present that they don't pay close attention to what might be in store for them in five, 10 or 20 years. Later in her talk Wednesday before the Knight Media Forum in Miami, Webb told people of color that they weren't thought about when the creators of self-driving cars, GPS navigators, robotics and other such technologies were being developed. "My question is, what does all this mean for communities of color?" (video) asked Sara Lomax-Reese, president and CEO of black talk-formatted WURD radio in Philadelphia. She was one of about 500 at the sold-out conference sponsored by the John S. and James L. Knight Foundation. "It's not good," replied Webb. "Any person of color who's ever felt invisible, you're totally invisible to the networks. Right?" said the author of the 2016 book "The Signals Are Talking: Why Today's Fringe Is Tomorrow's Mainstream: Forecast and Take Action on Tomorrow's Trends, Today."

This week we'll be looking at some of the papers from WSDM'18. To kick things off I've chosen a paper tackling the problem of detecting fake news on social media. One of the challenges here is that fake news messages (the better ones anyway), are crafted to look just like real news. So classifying messages based on their content can be difficult. The big idea in'Tracking fake news footprints' is that the way a message spreads through a network gives a strong indication of the kind of information it contains.