Last March, a computer built by a team of Google engineers beat one of the world's top players at the ancient game of Go. The match between AlphaGo and Korean grandmaster Lee Sedol was so exhilarating, so upsetting, and so unexpectedly powerful, we turned it into a cover story for the magazine. On a Friday in late April, we were about an hour away from sending this story to the printer when I got an email. According to the email, Lee had won all five matches--and all against top competition--since his loss to AlphaGo. Even as it surpasses human talents, AI can also pull humans to new heights--a theme that ran through our magazine story.

IT decision makers in the legal sector are much more inclined to using artificial intelligence and machine learning than their counterparts in other industries. This is according to a new report by CenturyLink, based on a poll of 200 ITDMs across a wide array of industries. In non-legal sectors, just 30 per cent, and 38 per cent of CIOs are doing the same thing, respectively. "IT staff in legal industries have a forward-thinking and well-reasoned attitude to artificial intelligence and automation technologies," says Jamie Tyler, Head of Digital Transformation, CenturyLink. "They understand the impact and benefits that this technology can have, as well as its limitations, well ahead of their peers."

Yesterday, AWS announced Amazon Machine Learning, which is set to vastly expand the number of companies that will perform machine learning on their data. The benefits of using Amazon Machine Learning is that we can use AWS's internal algorithms at low cost. With this service, data scientists should be able to save time by not writing complex algorithms on their own. The service detects useful prediction models based on your data, so as long as you have basic skills in statistical methods and to read charts, you can benefit from these algorithms. AWS mentions that they have based Amazon Machine Learning on ML technology they have been using internally, so we can imagine that it will scale quite well depending on the amount of data involved.

Increasing calls for changes in policing have departments across the country searching for new ways to build trust and protect citizens and officers alike. Led by the Center for Data Science and Public Policy at the Computation Institute and Harris School of Public Policy, the initiative applies machine-learning methods to police department data to identify officers and police calls at a higher risk of producing adverse events, such as the use of excessive force or a sustained citizen complaint. The predictive models can be used to guide personalized interventions for at-risk officers or adjust dispatch procedures to reduce high-stress situations. "The goal is to take historical data about these police officers--their behaviors, citations, arrests, dispatches--and use that data to assign each officer a risk score," said Rayid Ghani, the center's director. "That risk score is then used to predict which officers are at risk of one of these adverse incidents, and provide the police departments with this information so they can then work on interventions to prevent these incidents."

Innovation continues, life goes on. Old jobs are made obsolete, new jobs are created. When the greatest minds of the world decide to create something new, their engineers set out to find a way to do it. Concepts are created, wireframes are built, prototypes are designed, algorithms are written. In essence: these ideas start to take shape.

Who has not dreamed of being an artist? This dream is now within everyone's reach thanks to the Prisma application and the artificial intelligence. First released back in June in the Apple App Store, the Prisma app (developed by Russia-based company Prisma Labs) uses neural networks and AI technology to turn normal photos into instant famous painters' art styles (abstract, impressionist, Gothic and several others). It is almost like carrying Picasso in your pocket and ask him to paint for you. The art filters and photo effects create such a mind-blowing result that the app broke the Apple download records in Russia.

The Sony Computer Science Laboratory (CSL) has made a further advance in the application of artificial intelligence by using it to create a bizarre pop track called'Daddy's Car'. Created by AI software Flow Machines, the software analysed "a huge database of songs" and then derived the styling and combinations to produce a record in the style of The Beatles. A total of 13,000 songs were entered into the machine from which a melody and harmony were created. From there, French composer Benoît Carré arranged and produced the songs, and wrote the lyrics. Sony CSL said that its music research "leads to new modes of access to music, interaction with sound, and human interaction".

Apple recently purchased Turi, a Seattle-based machine learning company. "Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans." The tech giant's standard response to questions about recent acquisitions is frustratingly static and uninformative. But the company's latest purchase, machine learning startup Turi, is at least its fourth acquisition in the artificial intelligence space over the last several months – suggesting that whatever its "purpose or plans," Apple is certainly looking to make its devices smarter. The tech giant purchased the Seattle-based startup for around 200 million, according to GeekWire.

Networking among virtual machines in Microsoft Azure is going to get a whole lot faster thanks to some new hardware that Microsoft has rolled out across its fleet of data centers. The company announced Monday that it has deployed hundreds of thousands of FPGAs (Field-Programmable Gate Arrays) across servers in 15 countries and five different continents. The chips have been put to use in a variety of first-party Microsoft services, and they're now starting to accelerate networking on the company's Azure cloud platform. In addition to improving networking speeds, the FPGAs (which sit on custom, Microsoft-designed boards connected to Azure servers) can also be used to improve the speed of machine-learning tasks and other key cloud functionality. Microsoft hasn't said exactly what the contents of the boards include, other than revealing that they hold an FPGA, static RAM chips and hardened digital signal processors.

Learning to code isn't as easy as snapping a photo, but Alex Klein is betting that the two are more closely connected than you might think. Klein is the co-founder of Kano (the British company that developed the cleverly designed DIY computer kit that teaches kids to code), and on a recent fall day he's sitting in front of me with a transparent camera in his hand, showing me how to build my own photo filter. On his laptop, Klein drags and drops a block of code using the Kano operating system, chooses a color, and presses the camera's shutter button. He does it again, this time choosing a line of code that turns the frames into a kaleidoscopic image. "This generation is so used to communicating with photography, Klein says. "They're snapping a picture and they're using a pre-packaged alteration made by some genius at Instagram and Snapchat.