Hilton Nunez felt more like an air traffic controller than the commander of six Hunter unmanned aerial vehicles. A division commander wanted a UAV to check for surface-to-air threats. A corps commander sought one to fly far ahead of advancing troops to gather intelligence for the next day's war planning. There were never enough UAVs to go around. "There was a constant battle over who would control the UAVs," Nunez says.

JUST below a half-opened garage door a tiny device can be seen at the feet of someone lurking in the shadows. It looks like a blue dragonfly. Then its miniature wings begin to flap as it slips under the door and darts along the street. After rising through the air it stops to hover outside the window of a building several storeys high. There is an opening on the roof, and it slips inside.

To that end, the Department of Defense wants to seed the oceans with robotic vehicles, leaving them on the seafloor until they're needed. In a time of crisis, a military commander would transmit a signal to the underwater vehicles, which would then float to the surface and either monitor the area, or launch a separate unmanned vehicle into the air to gather intelligence. At the end of the mission the vehicle could be picked up by a submarine or support ship. The system of robotic vehicles and their UAVs would be called Upward Falling Payload. The Defense Advanced Research Projects Agency is asking private companies to come up with designs for the communications systems, the "risers" that will float the UAVs to the surface, the UAVs themselves and the equipment they would carry.

The dawn of the 21st century has been called the decade of the drone. Unmanned aerial vehicles, remotely operated by pilots in the United States, rain Hellfire missiles on suspected insurgents in South Asia and the Middle East. Now a small group of scholars is grappling with what some believe could be the next generation of weaponry: lethal autonomous robots. At the center of the debate is Ronald C. Arkin, a Georgia Tech professor who has hypothesized lethal weapons systems that are ethically superior to human soldiers on the battlefield. A professor of robotics and ethics, he has devised algorithms for an "ethical governor" that he says could one day guide an aerial drone or ground robot to either shoot or hold its fire in accordance with internationally agreed-upon rules of war. But some scholars have dismissed Mr. Arkin's ethical governor as "vaporware," arguing that current technology is nowhere near the level of complexity that would be needed for a military robotic system to make life-and-death ethical judgments.

Discrete-time hidden Markov models are a broadly useful class of latent-variable models with applications in areas such as speech recognition, bioinformatics, and climate data analysis. It is common in practice to introduce temporal non-homogeneity into such models by making the transition probabilities dependent on time-varying exogenous input variables via a multinomial logistic parametrization. We extend such models to introduce additional non-homogeneity into the emission distribution using a generalized linear model (GLM), with data augmentation for sampling-based inference. However, the presence of the logistic function in the state transition model significantly complicates parameter inference for the overall model, particularly in a Bayesian context. To address this we extend the recently-proposed Polya-Gamma data augmentation approach to handle non-homogeneous hidden Markov models (NHMMs), allowing the development of an efficient Markov chain Monte Carlo (MCMC) sampling scheme. We apply our model and inference scheme to 30 years of daily rainfall in India, leading to a number of insights into rainfall-related phenomena in the region. Our proposed approach allows for fully Bayesian analysis of relatively complex NHMMs on a scale that was not possible with previous methods. Software implementing the methods described in the paper is available via the R package NHMM.

On the west coast of Australia, Amanda Hodgson is launching drones out towards the Indian Ocean so that they can photograph the water from above. The photos are a way of locating dugongs, or sea cows, in the bay near Perth--part of an effort to prevent the extinction of these endangered marine mammals. The trouble is that Hodgson and her team don't have the time needed to examine all those aerial photos. There are too many of them--about 45,000--and spotting the dugongs is far too difficult for the untrained eye. Deep learning is remaking Google, Facebook, Microsoft, and Amazon.

On the west coast of Australia, Amanda Hodgson is launching drones out towards the Indian Ocean so that they can photograph the water from above. The photos are a way of locating dugongs, or sea cows, in the bay near Perth--part of an effort to prevent the extinction of these endangered marine mammals. The trouble is that Hodgson and her team don't have the time needed to examine all those aerial photos. There are too many of them--about 45,000--and spotting the dugongs is far too difficult for the untrained eye. Deep learning is remaking Google, Facebook, Microsoft, and Amazon.

The underwater search for Malaysia Airlines Flight MH370 found an oil barrel and cable debris but no sign of the missing jet, the Australian Transport Safety Bureau (ATSB) said Wednesday. The agency, which is leading the search for the Boeing 777-200, released sonar images of the man-made objects that are currently being examined by a Remotely Operated Vehicle (ROV). "The underwater search continues with an AUV searching areas of challenging terrain and an ROV examining a range of sonar contacts which have been previously identified. Over the past week, ROV missions have revealed those contacts to be geological or man-made objects," ATSB said. "Dive 17 identified a contact cluster as geological comprising basaltic rock outcrops on a slope."

Weather conditions this week will impact the progress of the search for missing Malaysia Airlines Flight MH370, Australian Transport Safety Bureau (ATSB), said Wednesday. The underwater operation to locate the missing plane had already been pushed to end in January 2017 in accordance with the weather forecast. ATSB, which is leading the search for the Boeing 777-200, said in its operational update that weather conditions are unsuitable for both Autonomous Underwater Vehicle (AUV) and Remotely Operated Vehicle (ROV) operations periodically during the week. This week, search vessel Fugro Equator continued underwater search operations in the north of the search area, which is in a remote part of the southern Indian Ocean, using AUV. During the past week, Fugro Equator has undertaken five missions, each one taking an average of 21 hours.

The Dong Hai Jiu 101 is back in action. The vessel, which is one of two searching for missing Malaysia Airlines Flight 370 in the Indian Ocean, ended its months-long break from the hunt this week. It also returned with some new equipment, according to an operational update released Wednesday by the Australian Transport Safety Bureau. The Dong Hai Jiu 101 finally left port on Oct. 20 after being delayed for months by bad weather. By Monday, it was back in the search area with a remotely operated vehicle on board.