The eye-watering $999 price tag doesn't seem to be keeping fans away as thousands waited in long lines outside of Apple stores around the country to get their hands on the much-anticipated iPhone X. And the high-end device is testing the patience of consumers and investors because the company did not make enough models to meet demand worldwide. So those who do manage to get through the door to buy one this morning will be pleased to know they are sitting on potential gold mines, with some devices already being auctioned off on eBay for up to $18,000. The X is Apple's next generation smartphone that uses facial recognition software for the first time and is on sale today in cities around the world - with queues building at Apple Stores amid rumors of limited stock. And sales had Wall Street booming as shares hit an all-time high on Friday morning as optimistic reviews poured in about how the X would make this quarter's earnings soar.

With an eye-watering price tag of £999, these customers will be hoping for some decent bang for their buck. But that didn't put off Apple fans as the much-anticipated iPhone X's with its lush screen and facial-recognition skills tests the patience of consumers and investors with demand outstripping supply around the world. And those who managed to get their hands on one this morning will be pleased to know they are sitting on potential gold mines, with devices already listed for sale on auction website eBay for up to £15,000. The X is Apple's next generation smartphone that uses facial recognition software for the first time and is going on sale in cities worldwide today - with queues building at Apple Stores amid rumours of limited stock. Among the first to get the new device in Britain was reality TV contestant Marco Pierre White Jr, 22, the son of the celebrity chef, who joined the queue last night to pick up a phone for his girlfriend Francesca Suter.

Hot Montreal artificial intelligence startup Element AI has scored its third high-profile hire in the past month, recruiting former IBM chief innovation officer Linda Bernardi to join as its chief product and strategy officer. The Seattle-based Ms. Bernardi follows Denis Therien, McGill University's former vice-principal of research and international relations, and Valérie Bécaert, former director of partnerships with Montreal's Institute of Data Valorization, who joined Element AI last month. The Element AI moves come after the hiring of top-ranked Canadian AI research scientists by giant U.S. tech companies, including Facebook, Google and Uber Technologies, and the sale of a handful of AI startups to the likes of Microsoft. In the face of growing concerns over the loss of talent to these foreign heavyweights, Ottawa and the provinces have committed hundreds of millions of dollars to new AI institutes in Montreal, Toronto and Edmonton. Element, co-founded by University of Montreal professor and deep-learning pioneer Yoshua Bengio, has quickly emerged as one of the most heavily financed Canadian AI startups.

Process mining is a research field focused on the analysis of event data with the aim of extracting insights related to dynamic behavior. Applying process mining techniques on data from smart home environments has the potential to provide valuable insights into (un)healthy habits and to contribute to ambient assisted living solutions. Finding the right event labels to enable the application of process mining techniques is however far from trivial, as simply using the triggering sensor as the label for sensor events results in uninformative models that allow for too much behavior (i.e., the models are overgeneralizing). Refinements of sensor level event labels suggested by domain experts have been shown to enable discovery of more precise and insightful process models. However, there exists no automated approach to generate refinements of event labels in the context of process mining. In this paper we propose a framework for the automated generation of label refinements based on the time attribute of events, allowing us to distinguish behaviourally different instances of the same event type based on their time attribute. We show on a case study with real-life smart home event data that using automatically generated refined labels in process discovery, we can find more specific, and therefore more insightful, process models. We observe that one label refinement could have an effect on the usefulness of other label refinements when used together. Therefore, we explore four strategies to generate useful combinations of multiple label refinements and evaluate those on three real-life smart home event logs.

A new material inspired by mussels is flexing its muscles. It can stretch without snapping and repair its own molecular bonds, so it could be useful in robot joints that lift heavy objects, or for packaging to protect delicate cargo from accidental falls. Mussels and some other molluscs hang onto solid surfaces using an adhesive protein and tough, plasticky fibres, which are extremely strong and can repair themselves when a few molecular bonds within them are broken. For a mussel, these stretchy yet strong fibres come in handy when a wave hits. Megan Valentine at the University of California, Santa Barbara, and her colleagues created a plastic with these same properties by mimicking the chemistry the mussels use.

Can coal make a comeback under President Trump? In her old life, it was not unusual for Annie Evans to find herself standing in the pouring rain outside of a coal mine at three in the morning, staring down a broken piece of equipment. A heavy maintenance superintendent for a surface coal mine in Elgin, Texas, Evans was responsible for figuring out how to patch or replace outdated parts of a field delivery system that ferried coal from the mine to a plant. Each minute of downtime could cost the company as much as $170. Now the third-generation coal miner gets her adrenaline rush sitting indoors on a soft swivel chair, fixing code on a computer screen.

The scene around the flooded Whitehill Yeo pit in Devon, UK, resembles a lunar landscape. Until it was abandoned just a few years ago, an endless stream of diesel trucks carried china clay out of the mine seven days a week. But don't be fooled by the silence: this is very much an active site. It's just that all the excavation is happening deep beneath the placid waters. This is a test bed, the first, for a new type of mining by underwater robots.

Samsung's revamped Bixby takes on Amazon Alexa - Samsung announced it is upgrading its Bixby digital assistant and making it available for a range of connected devices, setting up a clash with Amazon's Alexa and others competing for leadership in artificial intelligence. The South Korean electronics giant, which is the world's biggest smartphone maker, launched Bixby last year but only for its own flagship Galaxy handsets....

These pictures are unlikely to make it into the glossy tourist brochures that sell the Caribbean as a paradise destination. For they show the much grimmer reality of clear blue seas increasingly choked by a tide of discarded plastic. In one photograph taken near Roatan, an island off the coast of Honduras, a diver grimaces as he prepares to enter the water almost completely covered by waste. Another, taken from below the waterline, shows plastic bottles, bags and other rubbish on the surface blocking out sunlight. Waste: Disposable cutlery and other rubbish trapped in seaweed.

Machines won't become intelligent unless they incorporate certain features of the human brain. Europe's massive €1 billion project has shifted focus from simulation to informatics By Megan Scudellari Large-scale brainlike systems are possible with existing technology--if we're willing to spend the money By Jennifer Hasler Researchers in this specialized field have hitched their wagon to deep learning's star By Lee Gomes Running algorithms that mimic a rat's navigation neurons, heavy machines will soon plumb Australia's underground mines By Jean Kumagai Artificial intelligence might endow some computers with self-awareness.