Microsoft's Cortana voice assistant is coming to IOS and Android. In a blog post published Tuesday, Joe Belfiore, head of Microsoft's Operating Systems Group, announced the upcoming launch of a Cortana app for Android phones and iPhones that will work as a companion to Cortana on your Windows 10 PC. The new Phone companion app will allow you to install and use Cortana for Android and iOS as part of Microsoft's goal to connect your Windows PC to whichever smartphone you own. Will Cortana for Android and iOS have the same capabilities as the version on your Windows Phone? You won't be able to use Cortana to open apps and change settings in the Android or iOS editions.

Much of the data being created on the web contains interactions between users and items. Stochastic blockmodels, and other methods for community detection and clustering of bipartite graphs, can infer latent user communities and latent item clusters from this interaction data. These methods, however, typically ignore the items' contents and the information they provide about item clusters, despite the tendency of items in the same latent cluster to share commonalities in content. We introduce content-augmented stochastic blockmodels (CASB), which use item content together with user-item interaction data to enhance the user communities and item clusters learned. Comparisons to several state-of-the-art benchmark methods, on datasets arising from scientists interacting with scientific articles, show that content-augmented stochastic blockmodels provide highly accurate clusters with respect to metrics representative of the underlying community structure.

Google's experimental "skunkworks" lab, Google X, has come up with a lot of weird, potentially useful ideas, including Internet-enabled weather balloons and special contact lenses to monitor the composition of users' tears. But a patent filed by Google X and published this week might be the lab's oddest project yet: a line of Internet-connected stuffed animals that can control appliances throughout your house and maintain eye contact with kids. Similar to Amazon's Echo home speaker/information hub, the Google toys would be activated by a spoken word or phrase which, the patent says, would cause the toy to "aim its gaze at the source of the social cue." The toys would be built with motors so they could physically open their eyes and turn their heads toward the person delivering the command. They would also have embedded speakers to let them verbally respond to the user, and the ability to mimic emotions the patent speculates that "to express surprise, [a toy] may make a sudden movement, sit or stand up straight, and/or dilate its pupils."

It's official, Microsoft has killed off Internet Explorer, its new browser will be Microsoft Edge although you'll be forgiven for thinking nothing has changed if you're looking at the logo. The browser, formally known as Project Spartan after the protagonist of Microsoft's Halo game series, is completely new according to the company. It announced the new name as part of its Windows 10 presentation at its Build developers conference in San Francisco. Edge is meant to give Microsoft a clean break from the negative connotations attached to the Internet Explorer brand by millions of people forced to use old, decrepit versions on work computers. It will live on for many of Microsoft's customers as the centrepiece of much software as a services packages, often required by administrative applications and point of sale.

Apple is refusing to explain how and why the Russian language version of its voice-controlled virtual assistant, Siri, provided homophobic answers to queries relating to gay or lesbian topics. The allegations first came to light when a Russian man called Alex, who lives in London, uploaded a video to YouTube appearing to show Siri either evading questions or expressing a negative response. Alex asked questions such as: "Are there any gay bars around me?", "tell me about gay marriage?" "I would have turned red if I could", "you are so rude!" and "I will pretend I haven't heard". These responses seem to suggest that the word gay () in Russian has been programmed as profanity. Swear words in the English language version receive similar responses.

A YouTube video sent to Apple blog 9to5Mac lets you hear the difference between the old Siri and the new one. In the video, a more lifelike Siri says certain words much more naturally, as if they were recorded by an actual person. The digital assistant's cadence has also improved, as the pitch of Siri's voice drops at the end of clauses just like a natural English speaker's would. Siri's voice has undergone periodic tweaks and fixes, but none so major as when Apple (AAPL, Tech30) released iOS 7 in 2013. In that update, Siri got an entirely new sound, switching from actress Susan Bennett's voice to two other unnamed actors (one male and one female).

We address the collective matrix completion problem of jointly recovering a collection of matrices with shared structure from partial (and potentially noisy) observations. To ensure well--posedness of the problem, we impose a joint low rank structure, wherein each component matrix is low rank and the latent space of the low rank factors corresponding to each entity is shared across the entire collection. We first develop a rigorous algebra for representing and manipulating collective--matrix structure, and identify sufficient conditions for consistent estimation of collective matrices. We then propose a tractable convex estimator for solving the collective matrix completion problem, and provide the first non--trivial theoretical guarantees for consistency of collective matrix completion. We show that under reasonable assumptions stated in Section 3.1, with high probability, the proposed estimator exactly recovers the true matrices whenever sample complexity requirements dictated by Theorem 1 are met. The sample complexity requirement derived in the paper are optimum up to logarithmic factors, and significantly improve upon the requirements obtained by trivial extensions of standard matrix completion. Finally, we propose a scalable approximate algorithm to solve the proposed convex program, and corroborate our results through simulated experiments.

We consider the classic problem of establishing a statistical ranking of a set of n items given a set of inconsistent and incomplete pairwise comparisons between such items. Instantiations of this problem occur in numerous applications in data analysis (e.g., ranking teams in sports data), computer vision, and machine learning. We formulate the above problem of ranking with incomplete noisy information as an instance of the group synchronization problem over the group SO(2) of planar rotations, whose usefulness has been demonstrated in numerous applications in recent years. Its least squares solution can be approximated by either a spectral or a semidefinite programming (SDP) relaxation, followed by a rounding procedure. We perform extensive numerical simulations on both synthetic and real-world data sets, showing that our proposed method compares favorably to other algorithms from the recent literature. Existing theoretical guarantees on the group synchronization problem imply lower bounds on the largest amount of noise permissible in the ranking data while still achieving exact recovery. We propose a similar synchronization-based algorithm for the rank-aggregation problem, which integrates in a globally consistent ranking pairwise comparisons given by different rating systems on the same set of items. We also discuss the problem of semi-supervised ranking when there is available information on the ground truth rank of a subset of players, and propose an algorithm based on SDP which recovers the ranks of the remaining players. Finally, synchronization-based ranking, combined with a spectral technique for the densest subgraph problem, allows one to extract locally-consistent partial rankings, in other words, to identify the rank of a small subset of players whose pairwise comparisons are less noisy than the rest of the data, which other methods are not able to identify.

Speech to personal assistants (e.g., reminders, calendar entries, messaging, voice search) is often uttered under cognitive load, causing nonfinal pausing that can result in premature recognition cut-offs. Prior research suggests that prepausal features can discriminate final from nonfinal pauses, but it does not reveal how speakers would behave if given longer to pause. To this end, we collected and compared two elicitation corpora differing in naturalness and task complexity. The Template Corpus (4409 nonfinal pauses) uses keyword-based prompts; the Freeform Corpus (8061 nonfinal pauses) elicits open-ended speech. While nonfinal pauses are longer and twice as frequent in the Freeform data, prepausal feature modelling is roughly equally effective in both corpora. At a response latency of 100 ms, prepausal features modelled by an SVM reduced cut-off rates from 100% to 20% for both corpora. Results have implications for enhancing turn-taking efficiency and naturalness in personal-assistant technology.

Microsoft is reportedly developing a version of its year-old digital assistant, named Cortana, for iOS and Android. The move seems to indicate Microsoft is trying new ways to get its products onto the two dominant mobile operating systems across the US. For mobile users, the question will be: how does Cortana stack up next to Siri? The Cortana project came out of a branch of Microsoft developing artificial intelligence, dubbed "Einstein." Cortana, which is named after a central character in the massively popular Microsoft-owned video game series Halo, has been installed on Microsoft phones for the past year.