Every weekend we select a handful of in-depth articles we think are worth a bit of your valuable time, either because they peel back the layers on a compelling business story, or somehow make us look at business in a different light. AI may undermine big-company advantages. Machine learning – software that can improve itself without human intervention – may mean trouble for big companies that depend on their heft to outmaneuver smaller upstarts, writes Howard Yu for the Harvard Business Review. And for a sneak preview of where the world is headed, one need not look further than the success story of AlphaGo, an artificial intelligence that beat a champion of the ancient game of Go, something that was previously thought to be impossible. "It is easy to imagine a world where self-taught algorithms will play a much bigger role in coordinating economic transactions; AlphaGo simply shows us what is possible in the near future. With instantaneous adjustment, automatic optimization, and continuous improvement all quietly managed by unsupervised algorithms, the redundancy of production facilities and wastage in the supply chain should become headaches of the past."

Technology is the future of retail. Digital data, machine learning, cloud-powered analytics and the Internet of Things (IoT) will separate the wheat from the chaff in tomorrow's retail industry. A recent Sector Insights government report (PDF) said that retailers will need to embrace the latest technology trends, such as big data, and have the skills to work with digital systems if they are to be successful in the future. The retail industry is on the whole a voracious adopter of modern data-centric technology, aping the manufacturing world by using big data analytics to streamline supply chains, and using smartphone apps and wireless beacons to harvest customer data to deliver better service. However, Robert Hetu, retail research director at analyst house Gartner, noted that, despite having the technology to collect and access large amounts of digital data, retailers fail to put it to effective use.

Microsoft recently unveiled Tay, an artificial intelligent chat bot developed by Microsoft's Technology and Research and Bing teams to experiment with and conduct research on conversational understanding. The company stated that the more you chat with Tay, "the smarter it gets, learning to engage people through casual and playful conversation." Microsoft launched a verified Twitter account for "Tay" – billed as its "AI fam from the internet that's got zero chill". However, pretty soon after Tay launched, people starting tweeting the bot with all sorts of misogynistic, racist, and Donald Trumpist remarks. And as Tay was being essentially a robot parrot with an internet connection, started repeating these sentiments back to users.

Search on mobile can be a major pain. To start, the keyboard is small. Then there are the load times. Have you ever stared at your 4G smartphone screen and wondered in disbelief how only one bar of 3G was possible in San Francisco – in the country that put the first man on the Moon? How often have you longed for your laptop to be able to "search properly"?

Over July 4th weekend in 1981, several hundred game nerds gathered at a banquet hall in San Mateo, California. Personal computing was still in its infancy, and the tournament was decidedly low-tech. Each match played out on a rectangular table filled with paper game pieces, and a March Madness-style tournament bracket hung on the wall. The game was called Traveller Trillion Credit Squadron, a role-playing pastime of baroque complexity. Contestants did battle using vast fleets of imaginary warships, each player guided by an equally imaginary trillion-dollar budget and a set of rules that spanned several printed volumes. If they won, they advanced to the next round of war games--until only one fleet remained. Doug Lenat, then a 29-year-old computer science professor at nearby Stanford University, was among the players. But he didn't compete alone. He entered the tournament alongside Eurisko, the artificially intelligent system he built as part of his academic research. Eurisko ran on dozens of machines inside Xerox PARC--the computer research lab just down the road from Stanford that gave rise to the graphical user interface, the laser printer, and so many other technologies that would come to define the future of computing. That year, Lenat taught Eurisko to play Traveller. Doug Lenat says his common-sense engine is a new dawn for AI. The rest of the tech world doesn't really agree with him. Lenat fed the massive Traveller rulebook into the system and asked it to find the best way of winning.

A mesmerising simulation of the sun has provided the most accurate representation of its magnetic field to date. The hypnotic map shows the complex and turbulent forces that shapes the ball of plasma, causing violent solar flares and coronal mass ejections. Researchers hope the model could help solve a long-standing mystery about our star; if the magnetic lines on the surface are so chaotic, how is it that it has a unified magnetic field? A mesmerising simulation of the sun has provided the most accurate representation of its magnetic field to date. The hypnotic map shows the complex and turbulent forces that shapes the ball of plasma, causing violent solar flares and coronal mass ejections.

As many of you know by now, on Wednesday we launched a chatbot called Tay. We are deeply sorry for the unintended offensive and hurtful tweets from Tay, which do not represent who we are or what we stand for, nor how we designed Tay. Tay is now offline and we'll look to bring Tay back only when we are confident we can better anticipate malicious intent that conflicts with our principles and values. I want to share what we learned and how we're taking these lessons forward. For context, Tay was not the first artificial intelligence application we released into the online social world.

How far is too far when it comes to machine learning? We live in the digital age where companies like Google collect information which feeds and informs their algorithms, potentially advancing their technology into the realm of the uncomfortable. When it comes to digital AI and algorithmic predictions, when do we say enough is enough? Algorithms are digital codes that sort, predict and filter information in a fashion that is similar to the way the human brain works. They are in effect all over the internet, from Google's search predictions to Netflix's recommendation section.

This article was taken from The WIRED World in 2016 -- our fourth annual trends report, a standalone magazine in which our network of expert writers and influencers predicts what's coming next. Be the first to read WIRED's articles in print before they're posted online, and get your hands on loads of additional content by subscribing online. When assessing a patient, medics look at snapshots of physiological data that are manually taken by doctors or nurses, and make decisions against patient history, family background and test results, as well as their own knowledge and experience. But what if this data was constantly being taken, every second of every day? And what if a system was clever enough to compare these readings to thousands of patients worldwide with a similar history and disorder, as well as all the current clinical guidelines and studies, and make clinical suggestions to doctors?

The Henn-na Hotel in Japan just got more futuristic. Walking up to the front desk, customers are greeted with the familiar bow and the typical "Welcome" spiel from a typical Japanese woman. Henn-na means either "flower" or "it's weird," depending on your interpretation. Service bots and AI are used to help customers in retail stores like Lowe's. Why shouldn't they help guests check into a room?