Sometimes imitation is just a baffling form of flattery. Nowhere is that more often the case than with Android and iOS, dueling mobile operating systems that have been "borrowing" features from one another for years. Many of these moves have made sense: The iPhone slowly adopted popular Android phone elements such as wireless charging and edge-to-edge displays, while Google has learned from Apple's App Store and quick settings menu. But in the next version of its mobile operating system, Google plans to emulate one of the iPhone X's least favorable features: the notch at the top of the display. According to a report from Bloomberg, Google is working on an "overhaul" of its Android platform that will include the iPhone X's signature notch at the top of its displays.

Don't be rude to your home devices or there will be retribution. Google Home, Amazon Alexa, Apple Siri and Home Pod, Microsoft Cortana and any other voice operated smart device have something in common. It's not operating systems and it's certainly not the ecosystem in which each resides. What they...

The company's ethos -- as explained by CEO Tim Cook time and again -- is that Apple cares more about being the best than being first. The $349 HomePod is proof that's not always true. Apple put considerable time and effort into making its first smart speaker sound better than its rivals, and I'd argue they succeeded. After a few solid days of testing, I can honestly say the HomePod is the best smart speaker I've ever heard -- it's just not very smart in the ways I was hoping. It's no secret that the HomePod was designed to be a speaker first and an assistant second.

Amazon.com is developing a chip designed for artificial intelligence to work on the Echo and other hardware powered by Amazon's Alexa virtual assistant, says a person familiar with Amazon's plans. The chip should allow Alexa-powered devices to respond more quickly to commands, by allowing more data processing to be handled on the device than in the cloud. The effort makes Amazon the latest major tech company, after Google and Apple, to design its own AI chips, in hopes of differentiating their products from those of rivals. That strategy has major ramifications for chip companies like Intel and Nvidia, which are now competing with companies that previously have been their customers.

It's the speaker to beat in terms of audio but being locked in to Apple services is frustrating and its voice assistant is lacking Tue 13 Feb 2018 02.00 EST Last modified on Tue 13 Feb 2018 02.02 EST After much anticipation, and speculation that Apple has missed the boat and handed victory to Amazon's champion Echo, the HomePod smart speaker is finally here. But is it actually any good? And why exactly does it cost four times as much as an Echo? The HomePod is a voice-controlled speaker that listens out for its wakeword "Hey, Siri" and then starts streaming what you say to Apple to interpret your commands and play whatever it is you wish. The fabric-covered cylinder stands an iPhone X-and-a-bit tall (172mm) with a diameter of an iPhone X (142mm), weighing 2.5kg (14.4 times the iPhone X).

Japanese millennials are apathetic about romance, and everyone knows it. But according to Hirokazu Nakamura, chief product officer and chief marketing officer of Tokyo-based startup Eureka Inc., young people are not losing interest in love itself. It is just too much hassle for young people," Nakamura said at a business conference this month organized by Eureka, the developer of Japan's popular dating app Pairs. "They have been placed in a situation where finding love is too difficult. They just have too many things that they want to prioritize." While the surge in people remaining single may seem unstoppable, online dating apps have become increasingly popular among young Japanese, who are more inclined to pursue better kosupa (cost-performance) in finding love. Eureka's Pairs is just one of many dating apps aimed at making the process of finding a soulmate as easy as tapping and swiping on a smartphone screen. When you open Pairs, a list of photos and profiles of other registered members appears on the screen. A user who finds someone attractive can send that person a "like." If it is accepted, the pair become a "match" and start an online conversation. Registration is free but male participants must pay a monthly fee of ¥3,480 if they want to exchange unlimited messages. Between its launch in 2012 and this month, the app has been accessed by more than 7 million registered users, and some 4,000 every month enter a relationship, according to the company. About 80 percent of users are in their 20s to 30s. Taishi and Ayumi Kobayashi, both 29, are one such couple. They married after becoming a match in Pairs in July 2015. Although skeptical about online dating at first, Taishi, who works in the financial sector, said that meeting someone via software turned out to be easy and effective as it increases the chance of finding someone "attractive." "Even if you want to have a relationship with people around you, like in the same school or in the same circle, it's always difficult to find someone who shares the same values," he said. With the app, "I could meet someone who I had absolutely no chance of meeting before." Ayumi also said match-making apps fit well with young people's lifestyles, as it makes finding love "efficient." "I often used the app during my free time.

Amazon.com Inc paid about $90 million to acquire the maker of Blink home security cameras late last year, in a secret bet on the startup's energy-efficient chips, people familiar with the matter told Reuters. The deal's rationale and price tag, previously unreported, underscore how Amazon aims to do more than sell another popular camera, as analysts had thought. The online retailer is exploring chips exclusive to Blink that could lower production costs and lengthen the battery life of other gadgets, starting with Amazon's Cloud Cam and potentially extending to its family of Echo speakers, one of the people said. Amazon views its in-house devices as key to deepening its relationship with shoppers. The Blink security camera (pictured), which hit the market in 2016, did not require a power cable like many rival products, making it easier to place around users' properties.

Apple is rolling out a new version of its Maps app for iOS devices. The latest update adds transit directions and data for Tucson, Arizona. MacRumors reported Monday that the Cupertino giant has updated its Maps app to include transit directions in Tucson, Arizona. With the update, users in Tucson now have the ability to select public transportation routes when getting directions in the area. They can now view routes of SunTran bus lines.

There has been a fair amount of hype surrounding conversational interfaces or conversational UI lately and for good reason. Interfaces that allow users to interact with the machines using natural language processing either by talking or writing – akin to human-to-human conversations. With every passing day, we get closer to bridging the gap of natural communication between man and machine. These days, the process of filling out a form or sharing your information on most websites has become less tedious and more informal due to the wide adaptation of conversational UI. However, prior to the steady adaptation of conversational UI, one had to trudge through a barrage of web forms in order to access content or seek out information.

Predicting unobserved entries of a partially observed matrix has found wide applicability in several areas, such as recommender systems, computational biology, and computer vision. Many scalable methods with rigorous theoretical guarantees have been developed for algorithms where the matrix is factored into low-rank components, and embeddings are learned for the row and column entities. While there has been recent research on incorporating explicit side information in the low-rank matrix factorization setting, often implicit information can be gleaned from the data, via higher-order interactions among entities. Such implicit information is especially useful in cases where the data is very sparse, as is often the case in real-world datasets. In this paper, we design a method to learn embeddings in the context of recommendation systems, using the observation that higher powers of a graph transition probability matrix encode the probability that a random walker will hit that node in a given number of steps. We develop a coordinate descent algorithm to solve the resulting optimization, that makes explicit computation of the higher order powers of the matrix redundant, preserving sparsity and making computations efficient. Experiments on several datasets show that our method, that can use higher order information, outperforms methods that only use explicitly available side information, those that use only second-order implicit information and in some cases, methods based on deep neural networks as well.