In recent years, artificial intelligence algorithms have become very good at recommending content to users -- a bit too good, you might say. Tech companies use AI to optimize their recommendations based on how users react to content. This is good for the companies serving content, since it results in users spending more time on their applications and generating more revenue. But what's good for companies is not necessarily good for the users. Often, what we want to see is not necessarily what we should see.

Here's how John Brandon sees the future less than 15 years from now: augmented reality will be mainstream, digital assistants will guide our every move, everything will be translated on the fly, we'll be using digital scrolls, and some of our employees will not be human but robots. The list follows questions to futurists and smart thinkers about what business tech will be like in 2025. Future robots won't look like us but these smart machines will replace us on mundane tasks such as flipping hamburgers at a local eatery, diagnosing our illness at the doctor, and acting as our digital avatars at meetings. And like an advanced version of Siri, digital assistants will know our schedules, read our email, and store all of our photos and documents. More importantly, they'll know where we need to be and why.

Completing a data matrix X has become an ubiquitous problem in modern data science, with applications in recommender systems, computer vision, and networks inference, to name a few. One typical assumption is that X is low-rank. A more general model assumes that each column of X corresponds to one of several low-rank matrices. This paper generalizes these models to what we call mixture matrix completion (MMC): the case where each entry of X corresponds to one of several low-rank matrices. MMC is a more accurate model for recommender systems, and brings more flexibility to other completion and clustering problems. We make four fundamental contributions about this new model. First, we show that MMC is theoretically possible (well-posed). Second, we give its precise information-theoretic identifiability conditions. Third, we derive the sample complexity of MMC. Finally, we give a practical algorithm for MMC with performance comparable to the state-of-the-art for simpler related problems, both on synthetic and real data.

Google is working on some nifty new features for Google Maps, including a short list of your favorite places, the possibility of a'virtual positioning system' and more. Assistant is coming to Google Maps in a big way, with a ton of new shortcuts, as well as the ability for the digital assistant to text your friend when you're on your way. Google is rolling out a tool called'Your Match', which uses machine learning to determine your location and interests, serving up targeted suggestions for new businesses opening up in your area and more.

In January of 2018, Annette Zimmermann, vice president of research at Gartner, proclaimed: "By 2022, your personal device will know more about your emotional state than your own family." Just two months later, a landmark study from the University of Ohio claimed that their algorithm was now better at detecting emotions than people are. AI systems and devices will soon recognize, interpret, process, and simulate human emotions. With companies like Affectiva, BeyondVerbal and Sensay providing plug-and-play sentiment analysis software, the affective computing market is estimated to grow to $41 billion by 2022, as firms like Amazon, Google, Facebook, and Apple race to decode their users' emotions. Emotional inputs will create a shift from data-driven IQ-heavy interactions to deep EQ-guided experiences, giving brands the opportunity to connect to customers on a much deeper, more personal level.

Today, Google shows a list of hits for every search, from which the user can choose a suggestion. Voice assistants do not work the same way: They offer recommendations. In two years, half of consumers will no longer be searching the web manually, but with their voices. They will be using voice assistants like Alexa, Siri, and Cortana. The risks this new behavior poses for brands are enormous. Become conscious of what your brand stands for.

Since its announcement at WWDC, Apple has been teasing a range of iOS 12 improvements scheduled for release in the fall. The roster includes a streamlined Siri, speeding up elderly iPhones, and a FaceTime overhaul, with no mention of HomePod updates. However, it has emerged that the smart speaker could soon receive a much requested feature: phone call support. According to a HomePod prompt unearthed by 9to5Mac inside the latest iOS 12 developer beta release, HomePod will soon let you make calls directly on top of its standard skillset. Gone will be the necessity of dialing a number on your iPhone before switching over to HomePod for audio output.

Amazon, Apple, Google, and Microsoft are all working on artificial intelligence (AI) to enhance their virtual assistants. But a new report shows that Google's Assistant has come first in an IQ test that saw it compete with Amazon's Alexa, Apple's Siri, and Microsoft's Cortana. It appears that the recent developments by the search giant have improved the Assistant quite significantly and made it a strong contender against Siri, which has got the second position in the test. All four voice-based virtual assistants were asked 800 questions. In summary, the google assistant was able to answer 86% of questions then Siri answered 79% questions correctly and Cortana was found to be laggard in the race. Artificial intelligence is greatly relevant for this progress.

Alexa Cast is a new feature on Amazon products for the streaming and control of media content. It's similar to Google's Chromecast and Apple's AirPlay, and it allows users to transfer the playback of media from a smartphone or tablet to a compatible device. At launch it's available in the Amazon Music app, which you'll need to download and install if you haven't already. It can control Amazon's Echo smart speakers; third-party Alexa-compatible speakers, such as the highly rated Sonos One and Sonos Beam soundbar (or any other Sonos speaker if either of those is already on your network); and Apple AirPlay devices. To use it, look for the "casting" logo in the Amazon Music app.

In a remarkable new app, Google has addressed one of the most pervasive grievances of our impersonal times: voice mail jail, or its technical name IVR (Interactive Voice Response). Although IVR's multiple menu options, long waits, and tinny music are a bother, they pale by comparison with the annoyance of the technology's characterless robotic voices. This is where a new feature of Google Assistant, called Google Duplex, a technology for automating for "real world" telephone tasks, has come to the rescue. And it does so by going against the grain by including the bane of all speakers, the dreaded "um" and "ah" words, also called filler words. Listen to the audio clip in this Google AI Blog post marked "Duplex calling a restaurant," where an automated male voice calls to make a reservation with a live receptionist. You'll hear him say "um" four times in 50 seconds.