Some scientists devote themselves to curing diseases. Others are researching an end to famine or global climate change. And some spend their time making nightmare machines, deep learning algorithms that utilize Artificial Intelligence to tap into humans' deepest and darkest fears. Like Google's Deep Dream, only with way more dangling, bloodied flesh. MIT teamed up with Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO) to create the "nightmare machine" in an attempt to study what terrifies us as a species, utilizing a pair of deep learning algorithms for maximum terrorizing impact and applying them to otherwise benign images like the Taj Mahal, an Ikea catalog and, naturally, Kermit the Frog.

IBM's Watson IoT is aimed at bringing together artificial intelligence (AI) tools such as machine learning, deep learning, machine reasoning, natural language processing (NLP), and computer vision and applying them to industrial Internet of Things (IoT) applications. The platform collects data, analyzes it, and puts the data into a business context to solve specific problems that include asset performance, facility management, operations, product development, health and safety, and predictive maintenance, among others. One of the big differentiators for Watson IoT is the use of IBM's Blockchain platform for specific IoT applications, where IoT devices can send data to private blockchain ledgers that can be used for shared transactions with tamper-proof security. Rather than collecting, storing, and managing all of your IoT data centrally, the blockchain's distributed replication allows businesses to access and supply IoT data in a decentralized fashion. Centralized silos can be expensive and difficult to manage, especially when applied to a data-hungry and data-sensitive area like IoT. Therefore, a decentralized, blockchain-based approach is beneficial for IoT.

Google Play Music is getting a much-needed overhaul starting this week, both inside and out. Its Android, iOS and Web apps are getting a new interface that's powered by machine learning to recommend music based on what you're doing and where you are. TNW NYC is our New York technology event for anyone interested in helping their company grow. You've probably seen Google Now deliver contextual cards with information relevant to your location and activities like flying, visiting the gym and commuting. The company's music service will now use those smarts to bring you suitable playlists for every activity it can reliably detect.

Leaders should always be asking themselves What's new?, What's next? and What's better?; that's where the future is. What technologies will drive the biggest changes in industries over the next 10 to 20 years and create the next economy? There are many that in combination will drive massive change across enterprises and all size of business. Specifically, I think 10 are essential, and shaping the industries of the future: drones, blockchain, big data, augmented reality, virtual reality, 3D printing, artificial intelligence, robots, internet of things, genetics. We will see them both in the consumer and enterprise domain; specifically in how we get stuff done, how we hire and how we collaborate.

According to a survey of 122 founders, executives and investors in health-tech companies released today by Silicon Valley Bank, big data and artificial intelligence will have the greatest impact on the industry in the year ahead. Healthcare delivery and healthcare IT also promise the most growth in 2017. "Big data has been integral to our work at Celmatix. It has empowered physicians to be able to counsel women about their chances of having a baby, based on their relevant personal metrics, and not just their age," said Dr. Piraye Yurttas Beim, CEO at Celmatix. "It's an exciting time to be in a field where the pace of innovation continues to increase as both physicians and patients realize the potential of big data and personalized medicine."

The common, and recurring, view of the latest breakthroughs in artificial intelligence research is that sentient and intelligent machines are just on the horizon. Machines understand verbal commands, distinguish pictures, drive cars and play games better than we do. How much longer can it be before they walk among us? The new White House report on artificial intelligence takes an appropriately skeptical view of that dream. It says the next 20 years likely won't see machines "exhibit broadly-applicable intelligence comparable to or exceeding that of humans," though it does go on to say that in the coming years, "machines will reach and exceed human performance on more and more tasks."

Peter Drucker was prescient about most things, but the computer wasn't one of them. "The computer ... is a moron," the management guru asserted in a McKinsey Quarterly article in 1967, calling the devices that now power our economy and our daily lives "the dumbest tool we have ever had." Drucker was hardly alone in underestimating the unfathomable pace of change in digital technologies and artificial intelligence (AI). AI builds on the computational power of vast neural networks sifting through massive digital data sets or "big data" to achieve outcomes analogous, often superior, to those produced by human learning and decision-making. Careers as varied as advertising, financial services, medicine, journalism, agriculture, national defense, environmental sciences, and the creative arts are being transformed by AI.

It's Monday lunchtime and gym-goers at Virgin Active in Moorgate, London, are grabbing a bike for their group cycle class. But this isn't any ordinary spin class, where the teacher enthusiastically shouts instructions like "sprint" and "climb" and the backdrop is an uninspiring grey wall. This is the "Pack", a class divided into three teams that compete in a series of interactive challenges while each rider's bike data is tracked in real-time and projected on to a screen. "We created the Pack in response to the growing demand for cycle-based classes and technology that tracks workout progress," says Virgin Active group chief information officer Andy Caddy. "It creates a wholly differentiated group cycle offering."

It's no secret that technology is revolutionising consumer and brand interaction. In most cases, consumers are changing their behaviour faster than most retailers can adapt their marketing strategies. Marketers must engage savvy shoppers across a plethora of channels, the competition is intense, and customer satisfaction and retention have become top priorities for most brands. In our modern era, it is imperative to know and UNDERSTAND who our customers are, what they like/dislike, what will motivate them to buy or buy again, and why they leave. It is vital to have a forward-looking approach and to predict answers to questions such as: "What will my customer be interested in next week? In which city is my customer likely to shop? What is the most effective channel to connect with customers when they are ready to buy? Which products are my prospects waiting for?"

Machine Learning is making its presence felt on the worldwide stage as a major driver of digital business success. A good proof of that was our recently completed second edition of the Valencian Summer School in Machine Learning celebrated last September 2016 in Spain. Over 140 attendees representing 53 companies and 21 academic organizations from 19 countries travelled to Valencia for a crash course in Machine Learning and it was a great success! What are the next steps? Encouraged by the level of interest and motivated by our mission to democratize Machine Learning, we continue spreading Machine Learning concepts with this series of courses.