As network data become increasingly available, new opportunities arise to understand dynamic and multilayer network systems in many applied disciplines. Statistical modeling for multilayer networks is currently an active research area that aims to develop methods to carry out inference on such data. Recent contributions focus on latent space representation of the multilayer structure with underlying stochastic processes to account for network dynamics. Existing multilayer models are however typically limited to rather small networks. In this paper we introduce a dynamic multilayer block network model with a latent space represention for blocks rather than nodes. A block structure is natural for many real networks, such as social or transportation networks, where community structure naturally arises. A Gibbs sampler based on P\'olya-Gamma data augmentation is presented for the proposed model. Results from extensive simulations on synthetic data show that the inference algorithm scales well with the size of the network. We present a case study using real data from an airline system, a classic example of hub-and-spoke network.

One of the most pressing questions in climate science is that of the effect of anthropogenic aerosol on the Earth's energy balance. Aerosols provide the `seeds' on which cloud droplets form, and changes in the amount of aerosol available to a cloud can change its brightness and other physical properties such as optical thickness and spatial extent. Clouds play a critical role in moderating global temperatures and small perturbations can lead to significant amounts of cooling or warming. Uncertainty in this effect is so large it is not currently known if it is negligible, or provides a large enough cooling to largely negate present-day warming by CO2. This work uses deep convolutional neural networks to look for two particular perturbations in clouds due to anthropogenic aerosol and assess their properties and prevalence, providing valuable insights into their climatic effects.

Artificial intelligence is touching almost every industry in the ongoing era of digital transformation. But what does it mean? Put simply, AI and machine learning -- a closely related idea -- are computer programs that emulate and learn human behavior to then make autonomous decisions. AI can be especially transformative in retail, helping almost every aspect of a retailer's business -- from utilizing data to drive sales, to automating the supply chain, or to hyper-personalize the customer experience. While AI can sound like some far-off idea, it's closer than you may think.

Anyone standing in line at the Department of Motor Vehicles has probably wondered why the waits are so long. Why it's seemingly so difficult to complete basic tasks. Why, in this digital age, we can't apply a little modern technology to take the pain out of such agonizing experiences. We've also heard the buzz about artificial intelligence potentially coming along to save the day by automating overly bureaucratic processes to make our lives simpler. And many government officials probably think that's all it is--buzz--right?

The firm has also developed a drone able to fly around the underground corridors of coal mines to detect gas emissions and other potential threats. Marcin Dziekanski, coordinator of the drone project of the Silesian metropolis, an alliance of more than 40 cities in the coal-mining Katowice region, said they use drones to monitor the smoke produced by coal-heated individual houses. "They fly over Katowice, over the buildings, as well as over other cities, enabling us to intervene, in cooperation with the city police, showing that we are monitoring our space, our environment," he told AFP, adding that "we are creating a set of good practices that we are sharing with others." Spartaqs considers itself above all a research firm looking into new technologies, though it has already sold a dozen drones--at an average price of 50,000 euros ($55,000) a pop--in Poland and Georgia. But the company has realised that buyers like the Saudis and the Americans, who are very interested in certain models, want to see "the plant where they are produced." So they have begun looking for investors, including abroad, who would like to participate in the development of a serial production line.

In June, TechCrunch Ethicist in Residence Greg M. Epstein attended EmTech Next, a conference organized by the MIT Technology Review. The conference, which took place at MIT's famous Media Lab, examined how AI and robotics are changing the future of work. Greg's essay, Will the Future of Work Be Ethical? reflects on his experiences at the conference, which produced what he calls "a religious crisis, despite the fact that I am not just a confirmed atheist but a professional one as well." In it, Greg explores themes of inequality, inclusion and what it means to work in technology ethically, within a capitalist system and market economy. Accompanying the story for Extra Crunch are a series of in-depth interviews Greg conducted around the conference, with scholars, journalists, founders and attendees. Below he speaks to two key organizers: Gideon Lichfield, the editor in chief of the MIT Technology Review, and Karen Hao, its artificial intelligence reporter.

Artificial Intelligence (AI) and Machine Learning are used to power a variety of important modern software technologies. AI also powers the facial recognition software commonly used by law enforcement, landlords, and private citizens. Of all the uses for AI-powered software, facial recognition is a big deal. Security teams from large buildings that rely on video surveillance – like schools and airports – can benefit greatly from this technology. An AI algorithm has the potential to detect a known criminal or an unauthorized person on the property.

Artificial intelligence (AI) is proving to be one of the most influential and game-changing technology advancements in the business world. As more and more enterprises go digital, companies all over the globe are constantly engineering new ways to implement AI-based functions into practically every platform and software tool at their disposal. As a natural consequence, however, cybercriminals too are on the rise, and view the increasing digitization of business as wide open window of opportunity. It should come as no surprise, then, that AI is affecting cybersecurity – but it's affecting it in both positive and negative ways. Cybersecurity Ventures' Official 2019 Annual cybercrime Report predicts cybercrime will cost the world $6 trillion annually by 2021 – up from $3 trillion in 2015.

Meili Gupta is about to ask another question. A poised and eloquent rising senior at elite boarding school Phillips Exeter Academy, Gupta, 17, is anything but the introverted, soft-spoken techie stereotype. She does, however, know as much about computer science as any high school student you'd ever meet. She even grew up faithfully reading the MIT Technology Review, the university's flagship publication, which shows, because Meili is the most ubiquitous student attendee at EmTech Next, a conference the publication held on campus this past summer on AI, Machine Learning, and "the future of work." Ostensibly, the conference is an opportunity for executives and tech professionals to rub elbows while determining how next-generation technologies will shape our jobs and economy in the coming decades. For me, the gathering feels more like an opportunity to have an existential crisis; I could even say a religious crisis, though I'm not just a confirmed atheist but a professional one as well.

I will begin by saying, we are living in a time where the dangers of Military technology is now beyond our control. We live as guinea pigs in a world where those with the power, knowledge and technology keep us from our true freedom. To live with free will in this beautiful world. They manipulate us, direct us and destroy everything that was truly divine and sacred in our mind. In this timeline we must decide, will they take our spirit and destroy what god intended or will we stand and fight the evil and it's new designs.