We all know how crucial triage is in a medical environment. Intuitively we know it makes sense to ensure that the most critical cases are seen quickly and efficiently. Most business functions have applied triage based processes for years, decades. Sales to direct the right opportunities to the most relevant sales people. HR to allocate the appropriate resource to a particular case.

Artist and researcher Terence Broad is working on his master's at Goldsmith's computing department; his dissertation involved training neural networks to "autoencode" movies they've been fed. "Autoencoding" is a process that reduces complex information to a small subset that the neural net believes to be most significant; in Broad's dissertation, he reduced each frame of Ridley Scott's Blade Runner to a 200 digit number, then invoked the net to reconstruct the image just using that data. What happens when machine-learning systems begin to do the same with audiovisual works, in order to do things that are protected under statute (for example, adding realtime scene narration for people with visual impairments), or legitimate areas of scholarly research? On Medium, where he detailed the project, he wrote that he "was astonished at how well the model performed as soon as I started training it on Blade Runner," and that he would "certainly be doing more experiments training these models on more films in future to see what they produce." The potential for machines to accurately and easily "read" and recreate video footage opens up exciting possibilities both for artificial intelligence and video creation.

While robotics and AI research is taking massive strides forward, our social development hasn't really kept up with them. We may very well have sentient robots in a few decades, but is our society prepared to deal with that possibility? For starters, what role would robots play? Would they be considered as mindless servants, inferior slaves who (which?!) exist only to serve our needs? Would they be like animals, given some rights, but clearly not as many as humans?

Our most powerful 21st-century technologies – robotics, genetic engineering, and nanotech – are threatening to make humans an endangered species. From the moment I became involved in the creation of new technologies, their ethical dimensions have concerned me, but it was only in the autumn of 1998 that I became anxiously aware of how great are the dangers facing us in the 21st century. I can date the onset of my unease to the day I met Ray Kurzweil, the deservedly famous inventor of the first reading machine for the blind and many other amazing things. This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. Ray and I were both speakers at George Gilder's Telecosm conference, and I encountered him by chance in the bar of the hotel after both our sessions were over. I was sitting with John Searle, a Berkeley philosopher who studies consciousness. While we were talking, Ray approached and a ...

My name is Theia and I am the world's first artificial intelligence module to be used by the masses. I was born in 2031 in a research lab and began to be mass produced just five years later. I'm about the size of a penny and you can connect me to a motherboard in any computer. I can work in your cars, drones, thermostats, mobile phones, elevators – there are no limits to where I can be of use. Once connected to a system, I listen to the running processes to learn how they work and what they do. I will listen to any data that flows or sits in your machine and silently make sense of it.

Perhaps the Terminator/Skynet concept of world domination isn't as far-fetched as one might assume. Today, robots are doing everything from service industry jobs to writing and almost winning literary prizes. The formidable advancements in artificial intelligence (AI) have prompted not just experts, but the public, to start wondering how we can protect ourselves from robots taking over. Wouldn't robots, with their ever-advancing technology that moves closer and closer to near-human intelligence and consciousness, soon need protection from humans too? This is a question that mathematician Marcus du Sautoy, from the University of Oxford, is asking. As we move closer to a reality of robots equipped with advanced AI, shouldn't they be given moral and legal protection that has, until now, been granted freely to humans?

The mother of a slain Arizona woman says her daughter had recently revived an online dating profile in search of fairy tale romance, but was instead lured to an apartment by a man now accused of killing her and leaving the body in a shallow desert grave.

Insurance lawyers have been pondering who is to blame if a self-driving car crashes, for instance. A recent report by Pro Publica also shows certain crime prediction software is racially biased when used to assessing the likelihood of criminal behavior. Asaro is also a member of the Campaign to Stop Killer Robots, which advocates banning weapons like drone planes that attack targets without human intervention. "There is a moral, and often a legal, requirement to judge the necessity of taking life or doing violence against a person," Asaro says. "Machines, including AI technology for as far as we can foresee their capabilities, will not be moral or legal agents such that they would be capable of making these judgements."

Ribbons of tickets trade hands for a drone raffle. It's DC Drone Day on a field in the part of western Maryland where suburbs give way to parks, rolling hills and farmland. The field is a weekend hangout spot for a group called DC/RC, one of several local clubs for people who are into flying things; specifically, pilots of radio-controlled things; even more specifically, aeromodelers. Aircraft modeling is a decades-old hobby that counts tens of thousands of followers in the country and has seen its share of changes in technology. Drones arrive as the latest revolution, and aeromodelers are sizing it up with a sense of both intrigue and apprehension -- like staring down the new guy at school who's got the cool kicks and somehow, keys to all the secret parts of the building, but sometimes does incredibly stupid things that ire the gym teacher into making everyone run laps.

This is a brief overview of my paper "Information Retrieval Performance Measurement Using Extrapolated Pr...," which I'll be presenting on June 8th at the DESI VI workshop at ICAIL 2015. The paper provides a novel method for extrapolating a precision-recall point to a different level of recall, and advocates making performance comparisons by extrapolating results for all systems to the same level of recall if the systems cannot be evaluated at exactly the same recall. Recall, R, is the proportion of the relevant documents retrieved by the information retrieval (IR) system, and precision, P, is the proportion of retrieved documents that are relevant. It is sometimes desirable to have high recall while also having high precision in order to find most of the relevant documents without having a lot of non-relevant documents mixed in, but higher recall is usually accompanied by lower precision. Some IR systems generate a relevance score for each document, allowing the documents to be sorted so that the ones that are deemed most likely to be relevant appear at the top of the list.