We introduce a new family of judgment aggregation rules, called the binomial rules, designed to account for hidden dependencies between some of the issues being judged. To place them within the landscape of judgment aggregation rules, we analyse both their axiomatic properties and their computational complexity, and we show that they contain both the well-known distance-based rule and the basic rule returning the most frequent overall judgment as special cases. To evaluate the performance of our rules empirically, we apply them to a dataset of crowdsourced judgments regarding the quality of hotels extracted from the travel website TripAdvisor. In our experiments we distinguish between the full dataset and a subset of highly polarised judgments, and we develop a new notion of polarisation for profiles of judgments for this purpose, which may also be of independent interest.

Over the course of the last month, two astounding videos surfaced showing the extent to which artificial intelligence and robotics have developed. If you've been keeping tabs on either of these projects, you would agree that both respective developments represent incredible breakthroughs. But perhaps the most interesting aspect of Atlas and DeepMind lies in the idea that such systems are now able to directly interact with people. Add to this the exponential rise of self-driving cars and the internet of things, and we begin to realise that the next decade will present legal challenges we never before thought possible. We've spoken at length here at Technolegem about the challenges facing the legal industry, tracking things such as the regulation of Uber, anti-piracy schemes and the saga that was Dallas Buyers Club.

Not surprisingly, the Guild isn't happy with the Supreme Court's choice -- it calls this a "colossal loss" and insists that the appeals court was "blinded" by Google's attempt to portray itself as rescuing lost books for the public good. The statements are a bit melodramatic (many of these titles are unlikely to return to print before they reach the public domain), but they do point out that the concerns over digitizing books aren't quite over. Although Google appears to have walked a fine line, the worry is that other outfits might not be quite so scrupulous.

The Authors Guild and several individual writers have argued that the project, known as Google Books, illegally deprives them of revenue. The high court left in place an October 2015 ruling by the 2nd U.S. Circuit Court of Appeals in New York in favor of Google. A unanimous three-judge appeals court panel said the case "tests the boundaries of fair use," but found Google's practices were ultimately allowed under the law. The individual plaintiffs who filed the proposed class action against Google included former New York Yankees pitcher Jim Bouton, who wrote the acclaimed memoir "Ball Four." Several prominent writers, including novelist and poet Margaret Atwood and lyricist and composer Stephen Sondheim, signed on to a friend-of-the-court brief backing the Authors Guild.

Fair use also allows for people to transform the original content into a new type of work, and that transformation of the printed books was part of Google's argument in this case. The group wanted the Supreme Court to "recognize Google's seizure of property as a serious threat to writers and their livelihoods, one which will affect the depth, resilience, and vitality of our intellectual culture," the Authors Guild said on a webpage detailing the case. The Supreme Court decision gave authors a "colossal loss," Authors Guild President Roxana Robinson said in a statement. Google Books project may lead to a short-term public benefit, but it will come at the expense of the future vitality of U.S. culture, Robinson added. "The denial of review is further proof that we're witnessing a vast redistribution of wealth from the creative sector to the tech sector, not only with books, but across the spectrum of the arts," she said.

Gaza City - Majd Oweida arrived at the Erez crossing on February 23, en route to the occupied West Bank, in the hope of fulfilling a lifelong dream to organise a programme that introduces talented Palestinians to the world. This was to be the first time that Majd, a 23-year-old electrical engineer, would set foot in a part of Palestine outside the electrified fence surrounding the besieged Gaza Strip. Excited, he posted a selfie to Facebook, in which he held up his Israeli-issued entry permit. But as soon as he entered the Israeli zone of the Erez crossing terminal, Majd's trip took an unexpected turn. His colleagues, including his brother Amjad, lost contact with him for hours. Suspecting he was being subjected to a routine interrogation, they continued to wait after they reached the Israeli side of the crossing.

Over the past week much has been made about the launch and (temporary) shutdown of Microsoft's chatbot Tay. For those of you who might not know, Tay is a machine learning project that was launched with the goal of conducting research and development in the field of conversational understanding. It's a bot that can chat with users online, and it has presence over several platforms, including Twitter, GroupMe and Kik. Tay is programmed to mimic the behavior of a young woman, tell jokes and offer comments on pictures, but she's also designed to repeat after users and learn from them in order to respond in personalized ways. Unfortunately, Tay was shut down shortly after her launch because she was found to make racist and offensive comments. Apparently, the quirks in the bot's behavior were capitalized by a subset of users to promote Nazism and attack other Twitter users.

Welcome to California Inc., the weekly newsletter of the L.A. Times Business Section. Expect financial markets to face headwinds today after the Federal Reserve reported Friday that U.S. industrial production fell more than expected in March. This is the latest sign that economic growth slowed significantly in the first quarter. On the plus side, though, many economists still forecast a rebound in growth as the year plods ahead. Tax deadline: Monday is the deadline for most Americans to submit their tax returns.

Gaussian process models are flexible, Bayesian non-parametric approaches to regression. Properties of multivariate Gaussians mean that they can be combined linearly in the manner of additive models and via a link function (like in generalized linear models) to handle non-Gaussian data. However, the link function formalism is restrictive, link functions are always invertible and must convert a parameter of interest to a linear combination of the underlying processes. There are many likelihoods and models where a non-linear combination is more appropriate. We term these more general models Chained Gaussian Processes: the transformation of the GPs to the likelihood parameters will not generally be invertible, and that implies that linearisation would only be possible with multiple (localized) links, i.e. a chain. We develop an approximate inference procedure for Chained GPs that is scalable and applicable to any factorized likelihood. We demonstrate the approximation on a range of likelihood functions.

I would like to propose that Watson could solve one of the biggest challenges facing anyone trying to innovate and product their innovation with a US patent - the USPTO first office action. While everyone is working hard and I know the patent office is overloaded, here how three problems I've seen over my years of working that perhaps Watson could address: 1) Speed - it can take 6-12 months to get a first office action 2) Almost any patent application is nowadays first rejected due to obviousness. But the patents cited to create this argument are often taken out of context. To me, these seem like challenges that Watson would be perfectly designed to addressed. And all the literature to be reviewed is, by definition, in the public domain.