Recent developments in system identification have brought attention to regularized kernel-based methods, where, adopting the recently introduced stable spline kernel, prior information on the unknown process is enforced. This reduces the variance of the estimates and thus makes kernel-based methods particularly attractive when few input-output data samples are available. In such cases however, the influence of the system initial conditions may have a significant impact on the output dynamics. In this paper, we specifically address this point. We propose three methods that deal with the estimation of initial conditions using different types of information. The methods consist in various mixed maximum likelihood--a posteriori estimators which estimate the initial conditions and tune the hyperparameters characterizing the stable spline kernel. To solve the related optimization problems, we resort to the expectation-maximization method, showing that the solutions can be attained by iterating among simple update steps. Numerical experiments show the advantages, in terms of accuracy in reconstructing the system impulse response, of the proposed strategies, compared to other kernel-based schemes not accounting for the effect initial conditions.

We propose a new method for blind system identification. Resorting to a Gaussian regression framework, we model the impulse response of the unknown linear system as a realization of a Gaussian process. The structure of the covariance matrix (or kernel) of such a process is given by the stable spline kernel, which has been recently introduced for system identification purposes and depends on an unknown hyperparameter. We assume that the input can be linearly described by few parameters. We estimate these parameters, together with the kernel hyperparameter and the noise variance, using an empirical Bayes approach. The related optimization problem is efficiently solved with a novel iterative scheme based on the Expectation-Maximization method. In particular, we show that each iteration consists of a set of simple update rules. We show, through some numerical experiments, very promising performance of the proposed method.

Google is fighting harder than ever to get into your household. On Wednesday the company announced its entry into the voice-activated virtual assistant race with Google Home, its answer to the Amazon Echo. Google Home promises to live alongside you wherever you reside, answering your questions, playing your music and reading your news, much like its popular rival. It'll also have Google search built in, which means it'll know a lot about you as soon as you sign in. "We want users to have an ongoing two-way dialogue with Google," Google CEO Sundar Pichai said at the company's I/O developer conference on Wednesday. To be sure, the company already knows where you are, where you live and what you had for dinner this week (assuming you find your recipes through the search engine).

While Apple (AAPL) has Siri, its AI-based digital assistant for iPhones, it has yet to introduce a home hub device. Amazon, though, has sold an estimated 3 million Echo home hubs. "Credit to the team at Amazon for creating a lot of excitement in this space," Google CEO Sundar Pichai said in his I/O keynote speech Wednesday. Google Home, designed for music streaming and other entertainment, features built-in search capabilities. The "virtual agent" answers simple questions and carries out basic tasks.

Children who spend too much time watching television and playing video games may be damaging more than just their physical health. According to new research, it could also lead to lower grades in maths and English. A small study by a group of psychologists has found those who spent more time splitting their attention between various devices achieved lower test scores than those who did not. While constant switching attention between devices may be a growing trend, its affect on school performance and personality has not been well studied. Researchers at the University of Toronto looked at the effect of juggling multiple devices, such as watching television on while texting, on students' cognition, performance at school and personality.

Google on Wednesday became the latest major technology company to join a standoff with the FBI over encryption. At its developer conference, the company announced that its new messaging app, Allo, would feature an "incognito mode" that offered end-to-end encryption. Such technology can make it difficult for law enforcement to recover messages during investigations even if they have a warrant. In Washington DC, the FBI director, James Comey, has lobbied the administration to put restrictions on such technology. Google isn't the first Silicon Valley giant to offer a messaging app with strong encryption. Apple's iMessage system uses it by default, and Facebook's WhatsApp turned end-to-end encryption on by default this spring.

Google is turning to artificial intelligence to make sure people keep using its search engine, even if they're not spending as much time on the Web and personal computers. The Alphabet Inc. division unveiled a new mobile messaging application Wednesday called Allo containing a digital personal assistant, based on AI technology that powers other Google services like Inbox. At its I/O developer conference near its Silicon Valley headquarters, the company also showed off a voice-based search device called Google Home that uses the same assistant technology to answer questions when people are in their houses, a potentially potent rival to Amazon.com Google Chief Executive Officer Sundar Pichai said the goal is to develop an "on-going two-way dialog with Google" and build billions of people their own "individual Google." The CEO sees the Google digital assistant as an "ambient experience that extends across devices."

Panoramic Power, a leading provider of device-level energy management solutions, is pleased to announce the release of Device Analyzer, an innovative data-science approach to energy management that generates actionable energy and operational efficiency insights. Using advanced machine learning algorithms, Device Analyzer provides users with greater visibility into the operational state of each of their monitored devices. Device Analyzer learns usage patterns for any device such as lighting, HVAC and production lines and with pre-defined algorithms per device-type, allows users to see the device's operational state in real-time. It understands and monitors device sequencing, detects anomalies and automatically generates operational insights. Device Analyzer shifts the user interaction from a focus only on energy consumption, to an operational one - delivering significant value to improve operations, productivity and facility performance.

"[It's a] data token that boils you down to a data object," says Pete Kazanjy, founder of TalentBin, a service that uses social media to find job recruits (now part of Monster). That's especially true for hard numbers, said Google's SVP of "people operations" Laszlo Bock in a 2013 New York Times interview. "One of the things we've seen from all our data crunching is that GPAs are worthless as a criteria for hiring, and test scores are worthless," said Bock. A growing wave of hiring tech firms are ingesting far more information about candidates--surveys, work samples, social media posts, word choice, even facial expressions. Adding artificial intelligence (AI), they promise to assess work skills as well as personality traits like empathy, grit, and prejudice to provide a richer understanding of who the applicant is and whether they will fit.

On Google's recent Q3 earnings call, Google's CEO, Sundar Pichai said that one "transformative" technology is causing Google to rethink "how we're doing everything." There's a single technology that's causing Google to rethink they way it does everything. The same technology is in the process of transforming many of the biggest names in tech -- Facebook, Amazon, Netflix, UBER, Twitter -- not to mention smaller, up-and-coming startups. Entrepreneur and thought leader Peter Diamandis say that it will "do more to improve healthcare than all the biological sciences combined" and will generate large amounts of wealth and abundance. Billionaire venture capitalist Vinod Khosla agrees, saying that over the next 50 years, it will drive abundance, transform industries, and impact almost every part of society.