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Misha Denil and her colleagues from the University of California, Berkeley announced that they have trained an AI to learn the "physical properties" of objects by interacting with them virtually. This includes numerous aspects of the world, including questions such as "Can I sit on this?" or "Is it squishy?" In their paper, the AI systems were experimented in two environments. The first involved introducing five blocks arranged in a tower. Others were stuck together to make larger blocks, while others did not.

At the University Hospital of Giessen and Marburg 6,000 patients are waiting for a diagnosis of their rare conditions. Most patients have spent years bouncing from one doctor to another, building up huge dossiers of medical notes. Rare diseases typically take at least five years to correctly name, and sometimes up to 30, by which time it can be too late for effective treatment. "This is an inefficient, costly business," Dr Jurgen Schafer, who heads the German university's medical team, said at a media conference at IBM Zurich in October. "The computer is not going to replace the physician. But with this amount of data, it is completely clear that we don't need more physicians – we need more computer power."

In this industry, it's a tired old cliche to say that we're building the future. The proliferation of personal computers, laptops, and cell phones has changed our lives, but by replacing or augmenting systems that were already in place. Email supplanted the post office; online shopping replaced the local department store; digital cameras and photo sharing sites such as Flickr pushed out film and bulky, hard-to-share photo albums. AI presents the possibility of changes that are fundamentally more radical: changes in how we work, how we interact with each other, how we police and govern ourselves. Fear of a mythical "evil AI" derived from reading too much SciFi won't help.

Just in time for Halloween, researchers at Data61 and MIT Media lab have created a deep learning algorithm to generate disturbing imagery. There are two parts to the Nightmare Machine project – Haunted Places and Haunted Faces – which are each terrifying and impressive in equal measure. For Haunted Places the team used algorithms to learn what it called a'nightmarifying' process, learning a variety of spooky artistic styles that can then be applied to idyllic imagery. "We use deep learning algorithms to learn first how haunted houses, then ghost towns, and more recently toxic cities look," explains principal research scientist at Data61, Manuel Cebrian. "Then, we apply the learned style to famous landmarks. It's surprising how well the algorithm can extract the element from the "scary" templates and plant it into the landmarks."

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."