Recently, Talmor and Berant (2018) introduced ComplexWebQuestions - a dataset focused on answering complex questions by decomposing them into a sequence of simpler questions and extracting the answer from retrieved web snippets. In their work the authors used a pre-trained reading comprehension (RC) model (Salant and Berant, 2018) to extract the answer from the web snippets. In this short note we show that training a RC model directly on the training data of ComplexWebQuestions reveals a leakage from the training set to the test set that allows to obtain unreasonably high performance. As a solution, we construct a new partitioning of ComplexWebQuestions that does not suffer from this leakage and publicly release it. We also perform an empirical evaluation on these two datasets and show that training a RC model on the training data substantially improves state-of-the-art performance.

Modern consumers expect more from brands than ever. As a result of digital proliferation and advances in data science, consumers expect brands to deliver consistent, personalized, high-quality experiences across a growing set of relevant channels. Of course, this presents quite a challenge for brand marketers, who must develop enough on-brand content to address their various audiences -- doing so quickly and at scale, all while measuring the effectiveness of each channel, piece of content and customer interaction. This crunch is making it more difficult for brands to continuously create the content that consumers want to see to make their purchasing decisions. To beat that content crunch, many brands are producing a mix of user-, influencer- and brand-generated content. Of those three, user-generated content, or UGC, is the one that brands have the least control over -- both in terms of creation and curation, but delivers the highest impact.

On the heels of United States President Donald Trump's historic de-nuclearization summit with North Korean leader Kim Jong-un, non-proliferation is once again a timely topic. Since the dawn of the nuclear age, keeping tabs on who has military-grade nuclear capabilities and materials has been a vital – and difficult – task. Thankfully, it's also one that may be getting easier, thanks to leaps forward in fields like data analysis, machine learning and artificial intelligence. Last month, Thomson Reuters Labs was invited to present at a workshop called "Applications of Innovative Tools and Technologies for Nonproliferation and Disarmament" held in Krems, Austria, for diplomats representing their countries at the International Atomic Energy Agency (IAEA) and other international organizations. The diplomatic workshop was preceded by a day-long session for technical participants at the Vienna Center for Disarmament and Non-Proliferation.

There aren't many gadgets that I'm still using five years after I buy them, except for maybe a laptop. Even then, that's getting quite long in the tooth given how quickly upgrades arrive these days. Chromecast and Google Cast are still things that I use multiple times a day, every day. When Google first introduced the Chromecast in 2013, the company promised to make any TV with an HDMI port a smart display with the combination of a thumbdrive-like dongle and your home WiFi. That it did, but in the months that followed, Google expanded the tech undergirding its TV accessory well beyond that $35 device.

The use of natural wood, hand-knitted fabrics, and leather lend a rustic hand-made vibe to the Maverick.Cavalier Cavalier Audio is a New Jersey-based designer and manufacturer of voice-controlled speakers. The company's latest product is Maverick portable Bluetooth and Wi-Fi speaker with Amazon Alexa voice control. Maverick blends a hand-crafted finish and immersive sound to a market that's positively crowded out with'me-too' products produced from mass-produced plastics and so-so design. The Maverick has been designed to stand out from the crowd by using authentic materials, stylish design while incorporating the latest audio technology. Maverick was dreamed up by a team of musicians and engineers with the aim of offering world-class acoustics to life via a 20W stereo speaker system featuring two active drivers and dual passive radiators that the designers claim will produce true room-filling experience.

It's a well-known fact that humans are prone to be racist, but as artificial intelligence evolves, it has become evident that technology is racist too. Recent studies have found flaws in technological "advancements" that disadvantage people of a darker hue. For example, a ProPublica study found that software used to determine prison sentences for criminals (ostensibly to eradicate human bias) is biased against Black people. Similarly, an MIT Media Lab study revealed that certain facial recognition software can't seem to identify women of color. Technology like that and other artificial intelligence innovations rely on algorithms.

According to a Forrester report, robots will eliminate 6 percent of all jobs in the U.S. by 2021. McKinsey's assessment is even more expansive -- they believe that by 2030 one-third of American jobs could become automated. This, however, doesn't mean that life will soon be like "The Jetsons." As technological developments have done in the past, the next generation of robots utilizing artificial intelligence and automation to streamline processes currently handled with the assistance of human workers will significantly alter the job market. This idea represents a form of disruptive innovation, a term that refers to when an emerging technology can utilize fewer resources, thus competing better against those without it.

My name is Kris Coratti. Thank you for joining us on this very rainy morning. I'm glad you all made it out. We are going to have a fascinating series of discussion this morning on artificial intelligence. This is the latest in our ongoing event series that we call "Transformers." And our speakers this morning are going to explore the regulatory questions around this technology. They going to look at how AI is reshaping the way we live and work. And they're going to discuss how to make sure this technology is used responsibly in the future. Before we begin, I just want to quickly thank our presenting sponsor for this even, Software.org, And so now I'd like to go ahead and welcome to the stage The Washington Post's Tony Romm and Senators Maria Cantwell and Todd Young. And for those who don't know, Senator Cantwell is a Democrat from Washington State. Both are members of a Senate commerce committee which touches on artificial intelligence and many tech issues that we'll talk about today.

The Gucci-Dapper Dan lineup, which launched today, reimagines archival pieces of the designer -- especially tracksuits and jacket styles -- in Gucci's signature fabrics and decorative elements. Gucci leitmotifs, including embroidered dragons, bold letterings and the house's signature green and red stripes, stand out on bomber jackets, T-shirts and tanks, in addition to tracksuits, which are offered in GG-printed nylon and velour. A new yellow Gucci logo also makes its appearance, inspired by the original sign of Dan's Harlem store, reports @sandrasalibian.

IN DECEMBER 1989 Guido van Rossum, a Dutch computer scientist, set himself a Christmas project. Irked by shortcomings in other programming languages, he wanted to build his own. First, it should be easy to read. Rather than sprawling over line-endings and being broken up by a tangle of curly braces, each chunk would be surrounded with indented white space. Second, it should let users create their own packages of special-purpose coding modules, which could then be made available to others to form the basis of new programs.