A bot aided by artificial intelligence today will start drawing up wills for clients in the Northern Territory.

We investigate the use of alternative divergences to Kullback-Leibler (KL) in variational inference(VI), based on the Variational Dropout \cite{kingma2015}. Stochastic gradient variational Bayes (SGVB) \cite{aevb} is a general framework for estimating the evidence lower bound (ELBO) in Variational Bayes. In this work, we extend the SGVB estimator with using Alpha-Divergences, which are alternative to divergences to VI' KL objective. The Gaussian dropout can be seen as a local reparametrization trick of the SGVB objective. We extend the Variational Dropout to use alpha divergences for variational inference. Our results compare $\alpha$-divergence variational dropout with standard variational dropout with correlated and uncorrelated weight noise. We show that the $\alpha$-divergence with $\alpha \rightarrow 1$ (or KL divergence) is still a good measure for use in variational inference, in spite of the efficient use of Alpha-divergences for Dropout VI \cite{Li17}. $\alpha \rightarrow 1$ can yield the lowest training error, and optimizes a good lower bound for the evidence lower bound (ELBO) among all values of the parameter $\alpha \in [0,\infty)$.

The trucks that roam the highways of the Australian outback are a lot bigger than the average 18-wheeler. Instead of towing one container, these road trains, as Australians refer to them, pull at least three self-tracking semitrailers behind them, which follow each other like train carriages. The trailers are packed with heavy goods--cattle, gas, coal, cars--and sent roaring through the continent's interior to deliver supplies to coastal cities. Fully loaded, road trains weigh up to 120 tons, and materialize on the shimmering horizon of outback roads as great mechanical beasts. As they pass at 70 miles per hour, you can feel the air velocity generated by the machine trying to suck you under the rig. Road trains are as much a part of the outback as red dirt or Akubra hats, signifiers of a rugged, Mad Max mythology that has come to define Australia's interior in the global imagination.

A novel Python framework for Bayesian optimization known as GPflowOpt is introduced. The package is based on the popular GPflow library for Gaussian processes, leveraging the benefits of TensorFlow including automatic differentiation, parallelization and GPU computations for Bayesian optimization. Design goals focus on a framework that is easy to extend with custom acquisition functions and models. The framework is thoroughly tested and well documented, and provides scalability. The current released version of GPflowOpt includes some standard single-objective acquisition functions, the state-of-the-art max-value entropy search, as well as a Bayesian multi-objective approach. Finally, it permits easy use of custom modeling strategies implemented in GPflow.

There are many different types of sites that provide a wealth of free, freemium and paid data that can help audience developers and journalists with their reporting and storytelling efforts, The team at State of Digital Publishing would like to acknowledge these, as derived from manual searches and recognition from our existing audience. Kaggle's a site that allows users to discover machine learning while writing and sharing cloud-based code. Relying primarily on the enthusiasm of its sizable community, the site hosts dataset competitions for cash prizes and as a result it has massive amounts of data compiled into it. Whether you're looking for historical data from the New York Stock Exchange, an overview of candy production trends in the US, or cutting edge code, this site is chockful of information. It's impossible to be on the Internet for long without running into a Wikipedia article.

Space is a cold and barren place. Nothing can exist there, nothing!" Ludwig Von Drake, an obscure uncle of Donald Duck and a professor of astronomy, is sitting on a high stool in his observatory. When he sees that he is being filmed, he falls off and lands on the floor with a loud thump. "Now I can see stars I've never seen before!" he groans. He walks over to a table with a large pile of books on it. The thickest of them all is a guide to space travel that he wrote himself. In a 45 -minute- long monologue, he tells us in a thick German accent how mankind discovered the planets in our solar system and has fantasized about everything that might be crawling around on them. Every now and then, he picks up a book from the large pile and reads from it, and then throws it nonchalantly into a corner of the room. He tells us about Copernicus and Galileo, and about Kepler's dreams about Martians, Fontenelle's speculations about life on other planets, and even John Herschel's Great Moon Hoax. Science fiction comes to life in the colorful cartoon: Hairy space beings and flying saucers shoot across the screen. At the end, the professor has the last word. He finds all these fantasies poppycock; nothing can live in that empty, barren space! But, as he is speaking, Von Drake is kidnapped by a black Martian robot from one of his stories. The cartoon, Inside Outer Space, is part of Walt Disney's Wonderful World of Color, a television series from the 1960s. The absent minded duck professor hosts a number of episodes, each with their own topic: the history of flight, the color spectrum, space--all exciting stuff for American kids in the Space Age. Lou Allamandola spent his teenage years in the science- crazy 1960s. He grew up in a Catholic family in the state of New Jersey. His grandparents were immigrants from Italy, and he didn't learn to speak English until he went to school. He still clearly remembers the Disney cartoons with Ludwig Von Drake, which were broadcast on Saturday evenings. "Von Drake called the interstellar medium--the empty space between the stars and the planets--a barren place where nothing could exist," he tells me. "That was all we knew in the '60s.

According to a recent revelation by Elon Musk, a nation's Artificial Intelligence (AI) capabilities will determine its power. Economies and organizations globally are pursuing everything possible to utilize the benefits of AI in a bid to emerge as a superpower. In the wake of the growing awareness of AI's potential to propel business growth, Silverpond, an Australia-based firm, utilizes the technology to accelerate their customer's adoption of the technology. The company employs AI to engineer solutions for sectors like utilities, property, retail, healthcare, education, and research. "AI will transform the way services and products are delivered. Organizations need to re-think how they build, test, and deliver these solutions as AI makes previous approaches obsolete," states Jonathan Chang, Director, Silverpond.

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature.

In this paper we analyse the benefits of incorporating interval-valued fuzzy sets into the Bousi-Prolog system. A syntax, declarative semantics and im- plementation for this extension is presented and formalised. We show, by using potential applications, that fuzzy logic programming frameworks enhanced with them can correctly work together with lexical resources and ontologies in order to improve their capabilities for knowledge representation and reasoning.

Is the effort that AI/machine learning requires worthwhile? Usually when a new technology starts getting noticed, the subsequent hype in the industry is inevitable. The hype is partly created by the vendor and consulting community looking for new business, partly created by professionals in the industry wanting to keep up and comment on the latest trends, partly created by companies with the ambition to be seen moving with the times and becoming early adopters. Some hypes even have their lifecycle traced by Gartner, which coined the term "hype cycle". As all this energy and enthusiasm sometimes ignores "the gap from an academic paper to reality and the application to an engineered product."