About a year ago, when I was hanging out at a bar after work, talking about dating--the swipes, the winks, awkward IRL meetups, and, in my case, a message from a swinger who wanted me to help him with a woodworking project in his garage while his kids were at school--a friend brought up a new site called the League. "There's a wait list," she said. "I want to get on it." The League, for the uninitiated, is the ivy-covered country club of dating apps, designed for people who are "too popular as it is." There's a rigorous screening process--"We do all that dirty work for you"--that takes into account where your diplomas come from, the prestige of your titles, and, crucially, your influence on social media.

The robots are coming, and at least some lawmakers in Congress expect them to make a lot of jobs obsolete when they get here. "There are assembly lines where you already look out on a field of robots that can work 24-7, they don't need health insurance, they don't take vacations and they don't get sick," Sen. Dan Coats (R-Ind.) "I think it's coming faster than anybody realizes," he said of the shift to machine workers. Coats and other lawmakers are starting to think about "technological unemployment," or the replacement of workers with self-checkout aisles, driverless vehicles, medical robots and other automations. They have different ideas about how to prepare for the coming workforce overhaul, but most agree that it's going to take new thinking about how people are educated and trained.

Why do you think technologies such as AI and predictive coding are apparently gaining momentum in term of their uptake in the UK legal market? First and foremost, the legal market isn't an isolated bubble. There is so much happening right now in the world at large about AI and cognitive computing that the legal market simply can't be immune. Our behaviours in the workplace are driven (and increasingly so) by our experiences in the rest of our lives, so when there's a constant stream of mainstream news about AI, it's inevitable that it must impact the legal market. Add into the mix a number of other legal market factors – the increasing price sensitivity of clients, the explosion in data, the long-standing feeling that there must be a better way to do repetitive knowledge tasks than simply adding more junior lawyers – and you've got the perfect conditions for these technologies to take hold.

We are about to see a black hole for the first time ever, scientists hope. A team of scientists are hope to use a computer algorithm and a range of equipment to take the first ever picture of a black hole's event horizon next year. The picture will be taken by a project called Event Horizon Telescope – a network of nine radio telescopes placed all around the world. From the International Space Station, Expedition 42 Flight Engineer Terry W. Virts took this photograph of the Gulf of Mexico and U.S. Gulf Coast at sunset This image of an area on the surface of Mars, approximately 1.5 by 3 kilometers in size, shows frosted gullies on a south-facing slope within a crater. The image was taken by Nasa's HiRISE camera, which is mounted on its Mars Reconaissance Orbiter The Soyuz TMA-15M rocket launches from the Baikonur Cosmodrome in Kazakhstan on Monday, Nov. 24, 2014, carrying three new astronauts to the International Space Station.

One thing I've noticed since moving to San Francisco is that my cohort in the tech world doesn't talk that much about the industry's past. This is understandable: it's easy to forget that tech has a history. Just as old hardware is regularly tossed and replaced, the Web washes itself clean. But a few months ago, while researching early hacker webzines, I found myself in the backwaters of Wired's online archive, reading technological forecasts from 1993. A few moments later, I was on eBay, where I started to bid on strangers' dusty collections of early issues of Wired, all from the years 1993 to 1995.

Stuart Armstrong is a philosopher at the University of Oxford and one of the paper's authors. AI agents, as they're sometimes known, can already beat us at complex board games like Go and they're becoming more competent in a range of other areas. Now a London AI research lab owned by Google has carried out a study to make sure we can pull the plug on self-learning machines when we want to. DeepMind, acquired by Google for a reported 400 million in 2014, teamed up with scientists at the University of Oxford to find a way to make sure AI agents don't learn to prevent, or seek to prevent humans from taking control. The paper - titled "Safely Interruptible Agents [PDF]" and published on the website of the Machine Intelligence Research Institute (MIRI) - was written by Laurent Orseau, a research scientist at Google DeepMind, Stuart Armstrong at Oxford University's Future of Humanity Institute, and several others.

PARIS – A chemical in green tea has been shown to improve cognitive ability in people with Down syndrome, scientists and doctors said Tuesday. In a year-long clinical trial, the treatment led to improved scores on memory and behavior tests, they reported in a study, published in the The Lancet Neurology. The positive impact remained six months after the trial ended. Brain scans revealed that the compound, called epigallocatechin gallate, altered the way neurons in the brain connect with one another. "This is the first time that a treatment has shown efficacy in the cognitive improvement of persons with this syndrome," said Mara Dierssen, senior author of the study and a researcher at the Centre for Genomic Regulation in Barcelona, Spain.

A self-learning knowledge base is often found to be a key component of enterprise level self-service solutions. Leading knowledge base technologies use machine learning algorithms to automatically collect customer queries, learn from representatives' responses, and continuously expand the knowledge base over time. As its name might suggest, the self-learning knowledge base continues to improve in accuracy and performance as it receives additional information. Knowledge Base systems which are integrated with digital self-service solutions improve with each customer interaction that occurs through the self-service interface. The machine-learning algorithms which are found in more advanced knowledge base systems are usually designed to evaluate and process large amounts of data received through customer interactions.

That's the conviction held by Russian entrepreneurs Artem Kukharenko and Alexander Kabakov, whose startup, NTechLab, recently launched a facial recognition app that nearly obliterates the concept of anonymity. Called FindFace, the app has remained exclusive to Russia since going live earlier this year. Soon, though, Kuhkarenko and Kabakov are introducing a cloud-based platform that makes their frighteningly accurate algorithm available to everyone, the pair said in a Skype interview in May. In a practical sense, what this means is that none of us is safe from an always-probing public eye. "In 10 or 20 years, there won't be a place on the earth [where] ... nobody [can] see you," Kabakov said over Skype.

The Google DeepMind challenge match in March 2016 was a historic achievement for computer Go development. This article discusses the development of computational intelligence (CI) and its relative strength in comparison with human intelligence for the game of Go. We first summarize the milestones achieved for computer Go from 1998 to 2016. Then, the computer Go programs that have participated in previous IEEE CIS competitions as well as methods and techniques used in AlphaGo are briefly introduced. Commentaries from three high-level professional Go players on the five AlphaGo versus Lee Sedol games are also included. We conclude that AlphaGo beating Lee Sedol is a huge achievement in artificial intelligence (AI) based largely on CI methods. In the future, powerful computer Go programs such as AlphaGo are expected to be instrumental in promoting Go education and AI real-world applications.