With hosts and guests around the globe, Airbnb aspires to provide a frictionless payments experience where our guests can pay in their local currency via a familiar payment method, and our hosts can receive money via convenient means in their preferred currency. For example, in Brazil the currency is Brazilian Real, and people are familiar with Boleto as a payment method. These are quite different than what we use in the US, and imagine this problem spread across the 190 countries Airbnb serves. In order to achieve this, our Payments team has built a world-class payments platform that is secure and easy to use. The team's responsibilities include support of guest payments and host payouts, new payment experiences like gift cards, and assisting in financial reconciliation, to name a few.

CAMBRIDGE – How can we improve the state of the world? How can we make countries more competitive, growth more sustainable and inclusive, and genders more equal? One way is to have a correct theory of the relationship between actions and outcomes and then to implement actions that achieve our goals. But, in most of the situations we face, we lack such a theory, or if we have one, we are not sure that it is correct. Should we postpone action until we learn about what works? But how will we learn if we do not act?

Change detection (CD) in time series data is a critical problem as it reveal changes in the underlying generative processes driving the time series. Despite having received significant attention, one important unexplored aspect is how to efficiently utilize additional correlated information to improve the detection and the understanding of changepoints. We propose hierarchical quickest change detection (HQCD), a framework that formalizes the process of incorporating additional correlated sources for early changepoint detection. The core ideas behind HQCD are rooted in the theory of quickest detection and HQCD can be regarded as its novel generalization to a hierarchical setting. The sources are classified into targets and surrogates, and HQCD leverages this structure to systematically assimilate observed data to update changepoint statistics across layers. The decision on actual changepoints are provided by minimizing the delay while still maintaining reliability bounds. In addition, HQCD also uncovers interesting relations between changes at targets from changes across surrogates. We validate HQCD for reliability and performance against several state-of-the-art methods for both synthetic dataset (known changepoints) and several real-life examples (unknown changepoints). Our experiments indicate that we gain significant robustness without loss of detection delay through HQCD. Our real-life experiments also showcase the usefulness of the hierarchical setting by connecting the surrogate sources (such as Twitter chatter) to target sources (such as Employment related protests that ultimately lead to major uprisings).

The Times has assembled a panel of distinguished and diverse writers who will regularly contribute to the Books section. The 10 authors who make up the Los Angeles Times Cultural Critics At Large have published works of fiction, nonfiction and poetry. They have won dozens of prizes. A majority have deep connections to Southern California, even though they hail from four different nations. They will help expand the literary conversation, challenging ideas and broadening readers' understanding of literature and culture within the contemporary moment.

Some metaphors end up forgotten by all but the most dedicated historians, while others lead long, productive lives. It's only a select few, though, that become so entwined with how we understand the world that we barely even recognize them as metaphors, seeing them instead as something real. Of course, why some fizzle and others flourish can be tricky to account for, but their career in science provides some clues. Metaphors, as we all by now know, aren't just ornamental linguistic flourishes--they're basic building blocks of everyday reasoning. And they're at their most potent when they recast a difficult-to-understand phenomenon as something familiar: The brain becomes a computer; the atom, a tiny solar system; space-time, a fabric. Metaphors that tap into something familiar are the ones that generally gain traction.

"Our research shows that a growing number of customers actually prefer self-service channels to answer questions, resolve issues or complete transactions. Yet, automated handling often hits limitations when it comes to handling complex queries or'remembering' information previously mentioned in a conversation," says Dan Miller, Opus Research lead analyst. "As intelligent assistant technology evolves; we anticipate the emergence of highly specialized'intelligent advisors' that know when and how to involve a live agent. Inbenta's Hybrid Chat is the beginning of this progress." "As a transactional e-commerce-based company, having a superior digital customer support program is essential. You wouldn't make your brick and mortar customers search your store without helping them, so why not give them a personalized experience virtually," says Andreia Ferreira, Live Chat Manager, Ticketbis.

Chat apps are very popular and arguably, most people would prefer engaging in a chat conversation rather than make a phone call. Going by recent buzz, it's apparent that tech giants are planning to bring chat conversations to advertisers and marketers. But there are many startups out there already using chat conversations to simplify user queries. Yellow Messenger is one such Bangalore-based startup. Instead of a team of people answering your queries however, it has put in place an Artificial Intelligence-powered interface that converses with users and responds to their queries related to shopping, real estate, recharge, etc.

And the artificial intelligence chatbot that didn't survive a day on the Internet. Plus: Reviewing Santiago Calatrava's latest, how to be unprofessional and the "Grand Theft Auto" modification that may have you watching for hours on end. Time has Russian drone footage that provides an overview of what remains of the old Silk Road crossroads, as well as the contemporary human settlement of Tadmur that sits nearby. About 80% of the artifacts appear to be largely intact. The country's antiquities chief says repairs will take five years.

They died out more than 40,000 years ago but the legacy left by two prehistoric species of early humans is far more widespread than had been previously believed. Scientists have discovered a surprising number of bloodlines around the world carry fragments of DNA from Neanderthals or their sister species, the mysterious Denisovans. Their analysis suggests that our modern human ancestors appear to have interbred with the Denisovans just 100 generations after their trysts with Neanderthals. Scientists have produced new maps showing the levels of Neanderthal and Denisovan ancestry around the world. And the study has unearthed some surprising new benefits these illicit encounters have gifted to modern humans living today.

An important step in data analysis is data exploration and representation. In this tutorial we will see how by combining a technique called Principal Component Analysis (PCA) together with Cluster Analysis we can represent in a two-dimensional space data defined in a higher dimensional one while, at the same time, being able to group this data in similar groups or clusters and find hidden relationships in our data. More concretely, PCA reduces data dimensionality by finding principal components. These are the directions of maximum variation in a dataset. By reducing a dataset original features or variables to a reduced set of new ones based on the principal components, we end up with the minimum number of variables that keep the maximum amount of variation or information about how the data is distributed. If we end up with just two of these new variables, we will be able to represent each sample in our data in a two-dimensional chart (e.g. a scatterplot). As an unsupervised data analysis technique, clustering organises data samples by proximity based on its variables.