Microsoft envisions Cortana doing much more than reminding us to pick up toilet paper on the way home from work. Back in 2014, we Windows Phone fans could barely contain ourselves as we eagerly awaited Cortana's arrival on Windows Phone 8.1. At the time, like many writers, I had a vision of what Cortana would mean for Microsoft and mobile computing. So, well, I wrote about it. Alas, time has moved on, and that initial fervor that fueled the "Cortana conversations" of many Windows phone fans has transitioned through other topics. The Lumia 950 and 950 XL had their time in the limelight. HoloLens enters and re-enters the conversation. Windows 10 updates are a consistent topic, further fueled by Gabe Aul's passing of the torch to Dona Sarkar as the new face for the Insider Program.

Some of the behemoths giving a tough race to Google are Amazon, Apple Inc., Facebook, and Microsoft. A common platform on which they're all competing is a digital assistant to help with daily needs. Some of their AI-powered virtual assistants are Facebook's M, Apple's Siri, Microsoft's Cortana, Amazon's Echo and Allo's Google Assistant. While Amazon's Echo is a device solely serving as a virtual assistant, both Facebook's M and Allo's Google Assistant start at a disadvantage with the user first needing to install the app to exercise the luxuries of a digital assistant. One of the unique features of Allo is the Smart Reply built in, giving users the option of searching for restaurants, movie tickets, and information regarding flight delay without moving out of the chat.

It's all about trying to teach computers to make connections, similar to those humans make instinctively when growing up, in distinguishing objects. When it comes to video content, machine learning can help solve one of the growing issues in the industry. Barry Schwarz calls it'the paradox of choice' which he describes in his book and his excellent TED talk. Simply put, there has been an explosion of high quality video content production over the last decade. In 2014, Annalect reported that US consumers wanting to watch episodic TV had over 350 to choose from. Yet, consumers are less happy now than when they had fewer choices. It turns out that too many choices just make decisions harder. So, as an industry, we must come up with new ways of getting a better understanding of what each consumer wants to watch and create tools that will make discovery and recommendation more seamless and effective. In fact, machine learning could very well be the driver of a completely new set of content discovery and hyper-personalized services that will dramatically improve viewer satisfaction.

We're at the cusp of a sharp rise in devices that have no screen but do have conversational voice controls, such as the Amazon Echo. Smart home and Internet-of-things (IoT) objects that respond to users' voices will improve and become more intuitive with further iterations and wider adoption. Already they can, for example, dim the lights in a room and play a favorite song. With practice, and, by the virtues of machine learning, these user experiences will become ever more intuitive, capable, and innate. Beyond the IoT, brands are seeing bots as a new type of media – one that can be harnessed to expand a company's reach to new customers and networks.

Microsoft envisions Cortana doing much more than reminding us to pick up toilet paper on the way home from work. Back in 2014, we Windows Phone fans could barely contain ourselves as we eagerly awaited Cortana's arrival on Windows Phone 8.1. At the time, like many writers, I had a vision of what Cortana would mean for Microsoft and mobile computing. So, well, I wrote about it. Alas, time has moved on, and that initial fervor that fueled the "Cortana conversations" of many Windows phone fans has transitioned through other topics. The Lumia 950 and 950 XL had their time in the limelight. HoloLens enters and re-enters the conversation. Windows 10 updates are a consistent topic, further fueled by Gabe Aul's passing of the torch to Dona Sarkar as the new face for the Insider Program.

Microsoft envisions Cortana doing much more than reminding us to pick up toilet paper on the way home from work. Back in 2014, we Windows Phone fans could barely contain ourselves as we eagerly awaited Cortana's arrival on Windows Phone 8.1. At the time, like many writers, I had a vision of what Cortana would mean for Microsoft and mobile computing. So, well, I wrote about it. Alas, time has moved on, and that initial fervor that fueled the "Cortana conversations" of many Windows phone fans has transitioned through other topics. The Lumia 950 and 950 XL had their time in the limelight. HoloLens enters and re-enters the conversation. Windows 10 updates are a consistent topic, further fueled by Gabe Aul's passing of the torch to Dona Sarkar as the new face for the Insider Program.

Making Apple services even smarter and more personalized entails processing troves of information because intelligence is driven by big data. The fact that iOS 9's proactive features don't tap into the cloud has served Apple well thus far. But since Google Assistant came to light, people have been wondering if Apple can compete without resorting to raw data collection Google is infamous for. An en vogue statistical method, Differential Privacy helps Apple deliver smarter services without compromising privacy of their users. It's a relatively unproven technique with lots of potential which hasn't been used to boost Apple's services before iOS 10 and macOS Sierra.

Streaming service Sling TV is now available on Apple TV's fourth-generation set-top box. Apple is buffing up its Apple TV set-top box in hopes of making it a more popular choice for cord cutters. The purveyor of iPhones and iPads is playing catch-up in the Net video streaming device competition. But some Apple TV advances announced last week could give it a boost. Sling just added Comedy Central to that basic package.

Every time our customers visit the Zalando Fashion Store, we want to serve them personalised product recommendations, depending on their preferences. Others love ankle boots, while some prefer sneakers. Whilst some follow the latest trends and others prefer the classic style. In a nutshell, the task of a personalised recommender system involves building user profiles from their behavior and predicting which product recommendations will be most relevant to such profiles. Intuitively, the user profile specifies properties such as how much interest the customer has in sportswear, or whether flat heels are preferred over high heel shoes.

Facebook is well known for its early and increasing use of artificial intelligence. The social media site uses AI to pinpoint its billion-plus users' individual interests and tailor content accordingly by automatically scanning their newsfeeds, identifying people in photos and targeting them with precision ads. And now behind the scenes the social network's AI researchers are trying to take this technology to the next level--from pure data-crunching logic to a nuanced form of "common sense" rivaling that of humans. AI already lets machines do things like recognize faces and act as virtual assistants that can track down info on the Web for smartphone users. But to perform even these basic tasks the underlying learning algorithms rely on computer programs written by humans to feed them massive amounts of training data, a process known as machine learning.