Apple has reported a decline in both revenue and profits in its latest quarterly financial results, as the company feels the pinch from slowing demand for its star product, the iPhone. The results showed a 15 per cent fall in sales of the iPhone in the three months ending to 29 December, diving from $61.1bn (£46.8bn) in 2017, down to £51.9bn dollars (£39.8bn) a year later. Mac, iPad and the Wearables, Home and Accessories category all experienced an increase in net sales, but the most notable growth came from Apple's services - which includes its Apple Music streaming platform, the App Store, iCloud storage and Apple Pay - jumping 19 per cent, from $9.1bn (£7bn) to $10.9bn (£8.3bn) year-on-year. However, combined, the hole left by weak iPhone sales resulted in a total drop to $84.3bn (£64.5bn), Profits also fell slightly to $19.9bn (£15.3bn),

The World's Most Watched TV Show Will Be Hosted By Artificial IntelligencesObEN An audience of over one billion people worldwide is expected to tune into the Chinese state broadcaster's Spring Festival Gala marking the Chinese lunar new year on February 5. The four well-known human hosts – Beining Sa, Xun Zhu, Bo Gao, and Yang Long – will each be joined by an "AI copy" of themselves – in effect, their very own digital twin. The "personal artificial intelligences," created by ObEN Inc., are being touted as the world's first AI hosts. Rather than simply being computer generated avatars, AI technologies including machine learning, computer vision, natural language processing, and speech synthesis have been used to "rebuild" the virtual copies of the celebrities from the ground up. I spoke to ObEN CEO Nikhil Jain, who told me that while the TV event will showcase his company's technology to the largest TV audience in the world, the potential of personal AIs – PAIs – goes further still, and could revolutionize many areas of society. In fact, the company is already working to create AI-powered doctors, nurses, and teacher, as well as its highly publicized virtual celebrities.

Lauren Maffeo is a research analyst who joined the global technology sector in 2012. She started her career as a freelance journalist covering tech news for The Next Web and The Guardian. She has also worked with CEOs of pre-seed to profitable SaaS startups on media strategy. Lauren joined GetApp, a Gartner company, as a content editor in 2016. She covers the impact of emerging tech like AI on small and midsize business owners.

Call it a "Forrest Gump moment;" an instance of being in the right place at the right time for no other reason than just plain luck. A "Forrest Gump moment" is based upon Tom Hanks' character in the movie "Forrest Gump," a guy who always seemed to be in the right place at the right time meeting Presidents Kennedy, Johnson and Nixon at critical points in American history. I too have had a Forrest Gump moment in meeting President Reagan, however, my deeper Forrest Gump moments have been my long association with the history of analytics. I was fortunate to be at the birth of the Business Intelligence and Data Warehouse era while working for Metaphor Computers to deploy Decision Support Systems across Procter & Gamble in the late 1980's. And was fortunate again in the late 2000's to be at the launch of the Data Science era while building Advertiser Analytics at Yahoo.

Episode 106 - Edward Hess discusses The New Smart Machine Age and where humans fit into the convergence of business, technology and automation. Will smart machines and robots start taking our jobs? What can we do...us humans...to prepare for the inevitable transformation? Ed is a Professor of Business Administration and Batten Executive-in-Residence at the Darden Graduate School of Business at the University of Virginia. You've seen and heard him in places like WSJ Radio, CNBC, NPR, and Investor's Business Daily, among many others.

Music and Machine Learning- sounds not so musical? Just like everywhere, Artificial Intelligence has also pervaded the world of music. Spotify, Grooveshark, Pandora, and others can today recommend music based on our listening habits and moods. What does this mean for the music industry? Will AI take away jobs in the industry?

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictional domains are archetypes of entity universes that are poorly covered by Wikipedia, such as also enterprise-specific knowledge bases or highly specialized verticals. Our fiction-targeted approach, called TiFi, consists of three phases: (i) category cleaning, by identifying candidate categories that truly represent classes in the domain of interest, (ii) edge cleaning, by selecting subcategory relationships that correspond to class subsumption, and (iii) top-level construction, by mapping classes onto a subset of high-level WordNet categories. A comprehensive evaluation shows that TiFi is able to construct taxonomies for a diverse range of fictional domains such as Lord of the Rings, The Simpsons or Greek Mythology with very high precision and that it outperforms state-of-the-art baselines for taxonomy induction by a substantial margin.

Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously. An increasing number of rumours daily flood the social networks. Determining their veracity in an autonomous way is a very active and challenging field of research, with a variety of methods proposed. However, most of the models rely on determining the constituent messages' stance towards the rumour, a feature known as the "wisdom of the crowd". Although several supervised machine-learning approaches have been proposed to tackle the message stance classification problem, these have numerous shortcomings. In this paper we argue that semi-supervised learning is more effective than supervised models and use two graph-based methods to demonstrate it. This is not only in terms of classification accuracy, but equally important, in terms of speed and scalability. We use the Label Propagation and Label Spreading algorithms and run experiments on a dataset of 72 rumours and hundreds of thousands messages collected from Twitter. We compare our results on two available datasets to the state-of-the-art to demonstrate our algorithms' performance regarding accuracy, speed and scalability for real-time applications.

This story forms part of a collaboration with Dazed Digital -- where pop culture meets the underground. The opinions expressed in this article belong to each individual author. Technology is advancing at such a fast rate right now that it can feel like we are well on our way to a robot apocalypse. But, if we closely observe how artists are harnessing artificial intelligence in ways that push humanity forward, we can see that our fears of a technological dystopia might never actualize. From using AI to create new and innovative genres in music, to new takes on classical nudes, and innovative ways to track anonymous warfare, art's relationship to AI right now is illuminating humanity's strength.