It's no secret that agencies like the NSA, FBI, and CIA have been collecting unfathomable amounts of information for decades. For example, even well before the age of Big Data, J. Edgar Hoover collected and recorded information by hand beginning in the 1920s. After over half a century of amassing information, the next step will be to organize it, because what good is having all of that data unless you know how to use it? How will these agencies start to organize this information into actionable intel? According to Dawn Meyerriecks, the CIA's deputy director for science and technology, the Agency has 137 projects directly related to artificial intelligence (AI).

NEW YORK – The foreign ministers of Japan, the United States and India agreed Monday in New York to work together to develop strategically important ports and other infrastructure in the Indo-Pacific region, apparently seeking to balance China's bid to strengthen its regional influence. Foreign Minister Taro Kono said he, U.S. Secretary of State Rex Tillerson and Indian External Affairs Minister Sushma Swaraj "completely agreed to coordinate with each other toward the realization of a free and open Indo-Pacific." They agreed to work to spread and establish their shared basic values of the rule of law and the freedom of navigation and overflight in the region, Foreign Ministry officials said. The ministers affirmed that they will strengthen connectivity in the region through investment in infrastructure and work together to assist strategically important coastal nations in the region with maritime capacity-building, centering on key ports. According to the U.S. State Department, the ministers "discussed the importance of a free and open Indo-Pacific region underpinned by a resilient, rules-based architecture that enables every nation to prosper."

Learning distributed node representations in networks has been attracting increasing attention recently due to its effectiveness in a variety of applications. Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network. However, in reality there usually exists multiple types of proximities between nodes, yielding networks with multiple views. This paper studies learning node representations for networks with multiple views, which aims to infer robust node representations across different views. We propose a multi-view representation learning approach, which promotes the collaboration of different views and lets them vote for the robust representations. During the voting process, an attention mechanism is introduced, which enables each node to focus on the most informative views. Experimental results on real-world networks show that the proposed approach outperforms existing state-of-the-art approaches for network representation learning with a single view and other competitive approaches with multiple views.

As datasets capturing human choices grow in richness and scale--particularly in online domains--there is an increasing need for choice models that escape traditional choice-theoretic axioms such as regularity, stochastic transitivity, and Luce's choice axiom. In this work we introduce the Pairwise Choice Markov Chain (PCMC) model of discrete choice, an inferentially tractable model that does not assume any of the above axioms while still satisfying the foundational axiom of uniform expansion, a considerably weaker assumption than Luce's choice axiom. We show that the PCMC model significantly outperforms both the Multinomial Logit (MNL) model and a mixed MNL (MMNL) model in prediction tasks on both synthetic and empirical datasets known to exhibit violations of Luce's axiom. Our analysis also synthesizes several recent observations connecting the Multinomial Logit model and Markov chains; the PCMC model retains the Multinomial Logit model as a special case.

Immigration activists interrupted House Minority Leader Nancy Pelosi during a press conference in San Francisco, which she held with DREAMers to reaffirm her support for pro-DACA legislation. Drowned out by protestors, Pelosi responded, "Yes I have ... You don't know what you're talking about." The context: The activists said they protested Pelosi because she and other Democrats are negotiating with Trump and congressional Republicans about a legislative replacement for DACA, the Obama-era order that shielded about 800,000 illegal immigrants who came to the U.S. as children from deportation, and allowed them to apply for work permits. Worth noting: Pelosi and Chuck Schumer raised DACA with Trump at a White House meeting earlier this month, and have said replacing it will be a top priority in the coming weeks and months.

German Chancellor Angela Merkel is introduced to Pepper the Robot by DigitalSTROM employee Martin Vesper in Berlin, Germany. Deep learning, a popular form of machine learning, is being applied across across a number of the latest tech products and services. But for the most part, all that computing is still taking place in the cloud. San Francisco-based artificial intelligence startup Skymind is hoping to embed deep learning directly into robots. The startup is releasing a new toolkit, SKIL Somatic, that will enable robots to recognize the visual world around it using a popular type of deep learning, called a convolutional neural networks.

Xbox 360 controllers have long since been replaced by Microsoft, but an unlikely source is getting a second lifespan out of them: the U.S. Navy. The Navy is starting to use repurposed Xbox 360 controllers to control the periscopes on some of its submarines, according to The Virginian-Pilot. In the past, many Virginia-class submarines used mast-mounted cameras to see above the water and they required helicopter-like joysticks that required extensive training and were costly to use. According to Lockheed Martin, a standard control panel would usually be $38,000 per unit. For the Navy and partner Lockheed Martin, a major reason behind the change was familiarity.

Public speaking can be terrifying. Before every TechCrunch Disrupt, moderators are required to go through mandatory speaker training to ensure we're not flaming disasters on stage. Our bosses bring in a real-life human to train us and point out how often we use filler words or simply don't make any sense at all. It listens to you speak, compares your speeches to pros like President Barack Obama and then gives you immediate feedback. "Public speaking is one of the biggest challenges for engineers," Chirag Mahapatra, co-creator of the project and engineer at Airbnb, said.

Several leading figures in AI, including LeCun, have studied or taught at Canadian universities. Reinforcement learning builds on deep learning to let machines learn through experimentation. Michael Bowling, a U.S.-born computer scientist who leads a lab at the University of Alberta that has produced cutting-edge poker-playing machines, says the new Facebook lab simply shows that Canada already leads the rest of the world in AI. Indeed, after seeing AI researchers snapped up by big U.S. companies in recent years, Canada may well hope that the environment fostered by new labs, including the one in Montreal, will eventually produce companies that rival the likes of Facebook.

Craig Federighi, Apple's senior vice president of software engineering says there are two things you can do to stop nefarious actors from forcing you into FaceID. According to Federighi, "If you don't stare at the phone, it won't unlock," & "If you grip the buttons on both sides of the phone when you hand it over, it will temporarily disable Face ID." Clearly, iPhone X owners will have to practice their squeezing techniques. It would be painful and costly to be held up and discover that you were squeezing it all wrong. The ACLU & the EFF recently sued the DHS for searching the phones and laptops of 11 plaintiffs at the US border without a warrant. The group of plaintiffs includes 10 US citizens and one lawful permanent resident, several of whom are Muslims or people of color.