When Singapore decided that they needed a new smart water assessment network to track pollution in their reservoirs, they obviously went with a robot, because otherwise you wouldn't be reading about it here. They also decided that the robot had to be "aesthetically pleasing" in order to "promote urban livability."

There are a lot of things that chatbots have yet to master and high on the list is small talk. But researchers at Facebook think the best way to make software prattle away is to give it a personality. Workers were asked to chat in pairs and to give statements describing themselves, including their likes and dislikes. The crowdworkers' chatter was linked to these description statements and used to train the chatbots.

By default, both iOS and Android let you access their digital assistants--Siri and Google Assistant, respectively--right from the lock screen (unless the phone owner has disabled the feature).

Criminal recidivism is when a released criminal goes back to crime. From charging crimes through probation, the criminal justice system is constantly looking for ways to better predict which criminals are more likely to remain legal on release and who is a risk of recidivism. Bias can create inaccuracies through weighing variables incorrectly, and machine learning might provide a way of limiting bias and improving recidivism predictions.

One day after an American drone strike killed a leader of the militant Haqqani network in northwestern Pakistan, United States officials on Thursday rejected a claim by Pakistan that the strike had targeted an Afghan refugee camp. There were also conflicting accounts of the location of the drone strike and the number of people killed. A statement by Pakistan's Ministry of Foreign Affairs on Wednesday condemned the strike and maintained that it had "targeted an Afghan refugee camp in Kurram Agency" -- an assertion that the United States rejected on Thursday. "The claim in an M.F.A. statement yesterday that U.S. forces struck an Afghan refugee camp in Kurram Agency yesterday is false," said Richard W. Snelsire, the United States Embassy spokesman in Islamabad, Pakistan's capital. American officials said that there were no Afghan refugee camps in Kurram, a remote tribal region straddling the border with Afghanistan, where they said Wednesday's drone strike had taken place.

A dynamic network is a network that changes with time. Nature, society, and the modern communications landscape abound with examples. Molecular interactions, chemical reactions, social relationships and interactions in human and animal populations, transportation networks, mobile wireless devices, and robot collectives form only a small subset of the systems whose dynamics can be naturally modeled and analyzed by some sort of dynamic network. Though many of these systems have always existed, it was not until recently the need for a formal treatment that would consider time as an integral part of the network has been identified. Computer science is leading this major shift, mainly driven by the advent of low-cost wireless communication devices and the development of efficient wireless communication protocols. The early years of computing could be characterized as the era of staticity and of the relatively predictable; centralized algorithms for (combinatorial optimization) problems concerning static instances, as is that of finding a minimum cost traveling salesman tour in a complete weighted graph, computability questions in cellular automata, and protocols for distributed tasks in a static network. Even when changes were considered, as is the case in fault-tolerant distributed computing, the dynamics were usually sufficiently slow to be handled by conservative approaches, in principle too weak to be useful for highly dynamic systems. An exception is the area of online algorithms, where the input is not known in advance and is instead revealed to the algorithm during its course. Though the original motivation and context of online algorithms is not related to dynamic networks, the existing techniques and body of knowledge of the former may prove very useful in tackling the high unpredictability inherent in the latter. In contrast, we are rapidly approaching, if not already there, the era of dynamicity and of the highly unpredictable. According to some latest reports, the number of mobile-only Internet users has already exceeded the number of desktop-only Internet users and more than 75% of all digital consumers are now using both desktop and mobile platforms to access the Internet. The Internet of Things, envisioning a vast number of objects and devices equipped with a variety of sensors and being connected to the Internet, and smart cities37 are becoming a reality (an indicative example is the recent £40M investment of the U.K. government on these technologies).

Autopilot controls are not yet fully capable of functioning without human intervention – but they're good enough to lull us into a false sense of security

Ursula K. Le Guin, the immensely popular author who brought literary depth and a tough-minded feminist sensibility to science fiction and fantasy with books like "The Left Hand of Darkness" and the Earthsea series, died on Monday at her home in Portland, Ore. Her son, Theo Downes-Le Guin, confirmed the death. He did not specify a cause but said she had been in poor health for several months. Ms. Le Guin embraced the standard themes of her chosen genres: sorcery and dragons, spaceships and planetary conflict. But even when her protagonists are male, they avoid the macho posturing of so many science fiction and fantasy heroes.

Drone-maker DJI announced a new hobby aircraft today, one that weighs just a shade under a pound, fits in a jacket pocket, and is capable of flying itself. At that price, it hovers in DJI's lineup between the $499 DJI Spark, the gesture-controlled flyer released last year, and the more capable $999 Mavic Pro. The Mavic Air is tiny, half the size of a Mavic Pro, and about half the weight at just 15 ounces. When folded up, it's about the size of a paperback novel. At a press event in New York on Tuesday, DJI exec Michael Perry announced the Mavic Air by pulling it out of the pocket of his puffy Patagonia vest.

Google just made it a lot easier to build your very own custom AI system. A new service, called Cloud AutoML, uses several machine-learning tricks to automatically build and train a deep-learning algorithm that can recognize things in images. The technology is limited for now, but it could be the start of something big. Building and optimizing a deep neural network algorithm normally requires a detailed understanding of the underlying math and code, as well as extensive practice tweaking the parameters of algorithms to get things just right. The difficulty of developing AI systems has created a race to recruit talent, and it means that only big companies with deep pockets can usually afford to build their own bespoke AI algorithms.