How to get people interested in art? How to expose permanent-collection works that sit in storage? These are questions art museums constantly ponder. Recently, Tate Britain asked another one: How can artificial intelligence help? It put the question to anyone who wanted to compete for the 2016 IK Prize, which promotes the use of digital technology in the exploration of art at Tate Britain or on the Tate website.

Before you ever see a package dropped onto your doorstep from the sky, drones are going to force us to wrestle with some thorny questions about privacy. New rules from the U.S. Federal Aviation Administration for the commercial use of unmanned aircraft lighter than 55 pounds have opened the door to what could be a massive industry. It's much bigger than delivery drones, which are not yet practical or legal in the U.S. First we'll see more drones doing things like surveying real estate and inspecting infrastructure such as roofs, high bridges, cell towers, power lines, and wind turbines. But our new drone reality has privacy advocates spooked: low-cost vehicles and sensors are likely to spur widespread adoption of a technology that can be used for persistent aerial surveillance, and bad actors could exploit gaps in existing privacy laws. It's also not clear which government entities, if any, are responsible for addressing drone-related privacy concerns.

Stripe, the startup that lets websites and mobile apps implement payment services through its API and a few lines of code, is today adding in another new feature as it continues to build out its platform with more tools. It is now going to help prevent fraud on Stripe transactions, through a new service called Radar. Radar is being rolled out globally as part of Stripe's primary payments service, meaning companies that use Stripe's API for payments do not need to pay extra or do anything in particular to turn it on. That may change down the line if and when Stripe -- which has now raised around $300 million and is valued at around $5 billion -- begins to add in more features and decides to monetise the service separately. "This is an area of active development and there is a long list of things we want to do," said John Collison, Stripe's co-founder and president, in an interview. "We haven't ruled out [launching it as a separate service] but want to see how people use it and what works and what doesn't first."

Slack's attempts at small talk are about to get a whole lot better - it's just been announced the cloud-based workplace messaging system will incorporate IBM Watson's smarts to its own bots, and those built by its ever-growing pool of outside developers. The coworking platform, which has just reached four million daily active users, was designed as a means for better collaboration and communication at work. However, it has opened up its software to outside businesses, leading to a directory of more than 400 Slack-related apps. These add-ons provide Slack tools like lists, or bots tailored for specific purposes. Slack's mission to'kill email': firm invests in 11 new startups in just seven months There is even an entire section dedicated to health, as WIRED writer Rowland Manthorpe discovered when he sought out a therapist from TalkLife Connect on the platform.

As if quantum computing wasn't mind-bending enough, one of D-Wave Systems' founders is now pursuing another futuristic idea: using artificial intelligence and high-tech exoskeleton suits to allow humans--and, at least according to one description of the technology, monkeys--to control and train an army of intelligent robots. Geordie Rose is a cofounder and chief technology officer of D-Wave, the Canadian company selling machines that it claims exploit quantum mechanical effects to solve certain problems hundreds of millions times faster than traditional computers. Now an IEEE Spectrum investigation has discovered that Rose is also CEO of Kindred Systems (aka Kindred AI), a stealthy startup he founded with others in 2014 dedicated to delivering advanced teleoperated and autonomous robots. The goal is making programming robots faster and less costly–and possibly revolutionize the world of work. Kindred has so far received well over US $10 million in funding, according to Data Collective, the venture capital firm that led one of the rounds.

THE RISE OF ARTIFICIAL intelligence has inspired both fascination and fear of the world to come. Some tech prophets envision a "singularity," in which advances in AI trigger drastic technological growth, while others imagine that autonomous machines will someday turn on their creators and destroy us. But when you're engaged in the science of machine intelligence, you understand that this is a false set of choices shaped by a misleading phrase. The term "artificial intelligence" was coined in 1955 to convey the concept of general intelligence: the notion that all human cognition stems from one or more underlying algorithms, and that by programming computers to think in the same way, we could create autonomous systems modeled on the human brain. At the same time, other researchers were taking a different approach.

MasterCard (MA) is taking payments, the last -- and sometimes, the most painful -- part of shopping into the future, replacing card swipes with robots, artificial intelligence and the ubiquitous selfie. The steps, including this week's introduction of a chatbot for banks called "MasterCard KAI" that uses artificial intelligence to respond to customer queries via texts or through apps like Facebook Messenger, are vital parts of CEO Ajay Banga's strategy of leverage technological development to expand the $113 billion company beyond traditional card-based transactions. To create the chatbot, MasterCard partnered with startup Kasisto, developing a "conversational artificial intelligence platform" that banks and merchants can use to let customers make transactions, monitor their spending habits, check account balances and ask questions, the company said at the Money 20/20 conference in Las Vegas. It will be released in the U.S. early next year. "This bot enables entirely new experiences, bringing Mastercard benefits and offers to consumers with human-like conversations that are personal and contextual," Zor Gorelov, Kasisto CEO and co-founder, said in a statement.

We have discussed some AI topics in the previous posts, and it should seem now obvious the extraordinary disruptive impact AI had over the past few years. However, what everyone is now thinking of is where AI will be in five years time. I find it useful then to describe a few emerging trends we start seeing today, as well as make few predictions around machine learning future developments. The following proposed list does not want to be either exhaustive or truth-in-stone, but it comes from a series of personal considerations that might be useful when thinking about the impact of AI on our world. Companies like Vicarious or Geometric Intelligence are working toward reducing the data burden needed to train neural networks.

A team of computer scientists and legal professionals has created artificial intelligence with the ability to accurately predict the outcome of 79 percent of cases decided upon by the European Court of Human Rights. The performance of the artificial intelligence was published Monday by PeerJ Computer Science. Text from European Court of Human Rights cases was used to train a machine learning algorithm to find patterns in case text. The predictive model is made possible by advancements in natural language processing and machine learning, the analysis said. "We don't see AI replacing judges or lawyers, but we think they'd find it useful for rapidly identifying patterns in cases that lead to certain outcomes. It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights," said lead scientist Nikolaos Aletras in a statement by University College London.

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