Google is one of the leading providers of artificial intelligence-assisted language translation, and the company now says a new technique for doing so is vastly improving the results. The company's AI team calls it the Google Neural Machine Translation system, or GNMT, and it initially provided a less resource-intensive way to ingest a sentence in one language and produce that same sentence in another language. Instead of digesting each word or phrase as a standalone unit, as prior methods do, GNMT takes in the entire sentence as a whole. "The advantage of this approach is that it requires fewer engineering design choices than previous Phrase-Based translation systems," writes Quoc V. Le and Mike Schuster, researchers on the Google Brain team. When the technique was first employed, it was able to match the accuracy of those existing translation systems.

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.

As companies like Google, Microsoft and Salesforce compete for enterprise business, they're increasingly offering customers a wide range of integrated productivity tools, rather than siloed applications. Google, however, seems to be missing one key piece: customer relations management (CRM). For that, it's turned to ProsperWorks, a cloud-based CRM platform built expressly for Google Apps for Work. Linking its future to Google's enterprise business, ProsperWorks has done well for itself so far, growing its revenue 504 percent year-over-year and attracting 63,000 businesses. On Tuesday, the company's announcing it's secured 24 million in Series B funding, enabling its plans to expand internationally and build a data science team that will transform its CRM from a database to effectively a virtual VP of sales.

Microsoft and Renault-Nissan say their in-car productivity tools will make it "easier for people to stay connected to work, entertainment, and social networks". Microsoft and carmaker Renault-Nissan are working on connected car services, including in-car productivity tools, powered by the cloud. The companies said the services will include navigation, predictive maintenance, and vehicle-centric services, remote monitoring of car features, and over-the-air updates using Microsoft's Azure. Driven to distraction: Why IBM's Watson is getting onboard with self-driving vehicles and impatient passengers IBM has teamed up with Local Motors for a new autonomous vehicle. Here's how it will handle difficult passengers - and why you won't be able to buy one.

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".