Google announced its first attempt to combat the circulation of "fake news" on its search engine with new tools allowing users to report misleading or offensive content, and a pledge to improve results generated by its algorithm. The technology company said it would allow people to complain about misleading, inaccurate or hateful content in its autocomplete function, which pops up to suggest searches based on the first few characters typed. It also said it would refine its search engine to "surface more authoritative pages and demote low-quality content" – and acknowledged for the first time that it had taken the measures to combat the threat of fake news. Ben Gomes, vice-president of engineering, Google Search, said in a blogpost: "In a world where tens of thousands of pages are coming online every minute of every day, there are new ways that people try to game the system,. The most high-profile of these issues is the phenomenon of'fake news', where content on the web has contributed to the spread of blatantly misleading, low quality, offensive, or downright false information."

Vizio may have been knocked by LeEco after its $2 billion buyout deal was cancelled, but the company's not going to fall into a grief-stricken funk. The home theater business has announced a new raft of soundbars that work with Google Assistant and come with Chromecast built in. Leading the pack is the SmartCast 36", which packs 5.1 wireless sound, the promise of crystal-clear dialog and a wireless subwoofer. It's on sale right now, setting you back $250, while smaller options in the same range will cost less, obviously. The company has also wheeled out an addition to its Sonos-troubling Crave speakers in the form of the Crave Go.

LONDON Jimmy Wales, the founder of online encyclopedia Wikipedia, has launched a website aimed at countering the spread of fake news by bringing together professional journalists and a community of volunteers and supporters to produce news articles.

As a designer, you will be facing more demands and opportunities to work with digital systems that embody machine learning. To have your say about how best to use it, you need a good understanding about its applications and related design patterns. This article illustrates the power of machine learning through the applications of detection, prediction and generation. It gives six reasons why machine learning makes products and services better and introduces four design patterns relevant to such applications. To help you get started, I have included two non-technical questions that will help with assessing whether your task is ready to be learned by a machine. We are expecting a great many things to happen once the big data deluge has been funnelled into a nurturing stream of bits. Data can be used in many ways. One is to build smart products, and another is to make better design and business decisions. The latter also, ultimately, trickle into products. Machine learning is a very promising approach radically shaping future product and service development. Machine learning is a branch of artificial intelligence. It employs many methods: Deep learning and neural networks are two well-known instances.

Many people are unsure about exactly what machine learning is. But the reality is that it is already part of everyday life. A form of artificial intelligence, it allows computers to learn from examples rather than having to follow step-by-step instructions. The Royal Society believes it will have an increasing impact on people's lives and is calling for more research, to ensure the UK makes the most of opportunities. Machine learning is already powering systems from the seemingly mundane to the life-changing.

Spotify is on platforms ranging to your desktop to your speakers, but could it head to your wristwatch next? According to three recent job postings spotted by technologist Dave Zatz, Spotify may be looking into making its own wearable that would prominently feature Spotify functionality. In a since taken down listing for a senior hardware product manager (read the cached version here), Spotify wanted candidates who'd be able to develop products that could "become new Spotify business lines," comparable to the "Pebble Watch, Amazon Echo and Snap Spectacles." Other notable listings that Zatz cites include two advanced postings for a natural language understanding engineer and voice product manager -- both heavily emphasize voice recognition and the second product manager listing also cites wearables. For Spotify, the potential move seemingly comes out of left field.

Disney is taking scary clown makeup to the next level. It's using a new projection system to transform the appearance of actors during live performances, tracking facial expressions and "painting" them with light, rather than physical makeup. Called Makeup Lamps, the system was developed by a team at Disney Research, and it could potentially change the way stage makeup is used in future theater productions. Makeup Lamps tracks an actor's movements without using the facial markers common in motion capture, then it displays any color or texture the actor wants by adjusting the lighting. It can make someone appear older by creating "wrinkles" on their face, for example, or it can paint their face in creepy clown makeup, à la Heath Ledger in The Dark Knight.

The digital media industry has long faced a unique data challenge. Radio, television and film productions generate massive unstructured data sets, which can measure up to hundreds of terabytes total for a single large-scale film project. The amount of data generated by these digital media productions is growing rapidly. In fact, IDC has projected that the world's total amount of data will grow to 44 zettabytes (or a billion terabytes) by 2020, and a whopping eighty percent of that growth will be from unstructured content much of it created by the digital media industry. Managing and storing all this digital content can be both complicated and costly.

Recently I watched a 15-second Burger King commercial, which was designed to trigger my voice-activated Google devices. In the ad, a Burger King employee, standing behind a counter at the restaurant, stared into my screen and told me that he didn't have enough time to explain all the "fresh ingredients in the Whopper sandwich." He glanced to the side, suggesting that he was about to let me in on a little secret. Then the camera zoomed in, and in a clear, crisp voice he said, "O.K. Google. What is the Whopper burger?" The video cut to black just as my phone, watch, and Google Home responded to the trigger, reading the first few lines of a Wikipedia entry about the Whopper in an unsynchronized mess of sound.

We may not give it a lot of thought, but artificial intelligence is already part of our daily lives in a number of ways. When it works well, it makes our life slightly easier – from trying to anticipate our needs (e.g. Amazon's suggested products or Netflix's recommended shows) to preventing us from being victims of fraud (e.g. As a result, our experiences as consumers and humans becomes more seamless and pleasant. It doesn't take long to get used to this, to the point that some of us are now starting to expect a certain level of personalisation prompted by artificial intelligence systems in our interactions with brands in the B2C space.