March 23, 2017 --If some NASA researchers have their way, Mars exploration technology of the future may rely on an art form from the past. NASA's Jet Propulsion Laboratory (JPL) has developed a Pop-Up Flat Folding Explorer Robot (PUFFER) prototype that could change how we explore Mars. The rugged yet portable machine takes its inspiration from the art of origami, which, despite Americans' association with grade-school arts and crafts, is proving to be a cutting-edge design philosophy. Recent developments in the field have led to an explosion of uses ranging from solar panels to bulletproof barriers. What sets PUFFER apart from other rovers is that it folds flat, making its mini-profile even slimmer.

Artificial Intelligence could almost double the UK's economic growth rate and boost the country's labour productivity by up to 40 per cent by 2035, according to a research report from Accenture. The market report, 'Why Artificial Intelligence is the Future of Growth,' suggests AI is poised to fundamentally change the nature of work and create an entirely new level of interaction between man and machine, both in the UK, elsewhere in the EU and further afield. The net result could be a dramatically more productive economy in the UK, with the adoption of artificial intelligence technologies by the private and public sectors almost doubling the country's economic growth rate and thereby adding an extraordinary £650 billion to the UK economy by 2035. "AI is poised to transform business in ways we've not seen since the impact of computer technology in the late 20th century," explained Paul Daugherty, Chief Technology Officer at Accenture. "The combinatorial effect of AI, cloud, sophisticated analytics and other technologies is already starting to change how work is done by humans and computers, and how organisations interact with consumers in startling ways.

The great explorers Lewis and Clark knew the importance of team expeditions. Now, engineers at NASA's Jet Propulsion Laboratory in Pasadena, California are developing a small scout robot called the Pop-Up Flat Folding Explorer Robot (PUFFER) to accompany the next generation of Martian rovers in their outer space explorations. Inspired by origami, the Japanese art of paper folding, PUFFER is designed to change shape in order to squeeze into small crevasses that are too tight for rovers to reach. So far the two-wheeled scout has been successfully tested in hostile and diverse terrains including the Mojave Desert and Antartica. Though rovers themselves are built to last, they're expensive and NASA engineers take care not to send them on overtly dangerous missions.

Max More runs Alcor, an American company which, in exchange for $200,000, will store your corpse in liquid nitrogen until the science exists to revive you. Tim Cannon is a computer programmer who implanted a device the size of a pack of cards into his arm, without the aid of anaesthetics. Zoltan Istvan recently ran for US president and publicised his campaign by driving across the country in a huge vehicle modified to look like a coffin. These are among the unusual individuals Mark O'Connell interviews in his travelogue-style exploration of transhumanism, the movement that campaigns for the direct incorporation of technology into our bodies and minds, and strives to remove ageing as a cause of death. "What are my chances, would you say, of living to a thousand?" the author asks Aubrey de Grey, an established figure in this strange world: "I would say perhaps a little better than fifty-fifty," is the serious reply.

The FBI quietly developed a facial recognition network that allows law enforcement to identify people in the United States without their knowledge. Now lawmakers want to know why the agency didn't tell people about it. "Why did the FBI not fulfill the requirement of the law?" asked House Oversight Committee chairman Jason Chaffetz at a hearing on Wednesday. The FBI didn't let citizens know the agency was collecting photos from motor vehicle departments, according to a report from the Government Accountability Office. And a lot of people can be found on law enforcement facial recognition networks -- around half of American adults, according to a study from Georgetown University's Center on Privacy and Technology.

Like a child learning about its parents, artificial intelligence has begun to study the human condition. An A.I. system created by a Boulder, Colorado-based company CaliberMind can form analytical judgments about how people think and communicate, with a text input of only 100 words. CaliberMind's software can rank someone on a spectrum of emotional versus analytical decision-making, then draw conclusions about their character traits. Culling these details into a snapshot of someone's personality, the software then makes recommendations on how to best communicate with that person. It's nothing less than an artificially intelligent effort to peer into a person's heart and mind.

SpaceX fans are excited about what is likely the first clear image of a robot that could be used on the company's autonomous spaceport drone ships. SpaceX's Of Course I Still Love You Drone Ship is seen at Port Canaveral on Monday, March 20, 2017. In the lower-right is what is believed to be a Falcon 9 first stage securing vehicle. CAPE CANAVERAL -- Stephen Marr had his suspicions when he photographed a mysterious piece of equipment atop SpaceX's drone ship at Port Canaveral on Monday. "I knew there was something different there," Marr, 34, said. So he did what any lover of space and social media would do: He posted it online.

Algorithmic decision making systems are ubiquitous across a wide variety of online as well as offline services. These systems rely on complex learning methods and vast amounts of data to optimize the service functionality, satisfaction of the end user and profitability. However, there is a growing concern that these automated decisions can lead, even in the absence of intent, to a lack of fairness, i.e., their outcomes can disproportionately hurt (or, benefit) particular groups of people sharing one or more sensitive attributes (e.g., race, sex). In this paper, we introduce a flexible mechanism to design fair classifiers by leveraging a novel intuitive measure of decision boundary (un)fairness. We instantiate this mechanism with two well-known classifiers, logistic regression and support vector machines, and show on real-world data that our mechanism allows for a fine-grained control on the degree of fairness, often at a small cost in terms of accuracy.

Word embeddings are a powerful approach for unsupervised analysis of language. Recently, Rudolph et al. (2016) developed exponential family embeddings, which cast word embeddings in a probabilistic framework. Here, we develop dynamic embeddings, building on exponential family embeddings to capture how the meanings of words change over time. We use dynamic embeddings to analyze three large collections of historical texts: the U.S. Senate speeches from 1858 to 2009, the history of computer science ACM abstracts from 1951 to 2014, and machine learning papers on the Arxiv from 2007 to 2015. We find dynamic embeddings provide better fits than classical embeddings and capture interesting patterns about how language changes.

United States Representative Jason Chaffetz (R-UT) suggested in a Congressional hearing on the use of facial recognition technology by law enforcement officials Wednesday that facial recognition software should be used to identify "people that are here illegally," according to Gizmodo. The Representative who previously drew criticism for saying that Americans who can't afford healthcare should just give up their iPhones, is the chairman of the House Committee on Oversight and Government Reform. Chaffetz's comment on the facial recognition software was in reference to the FBI's use of databases that have more than 400 million American's faces. Representative Chaffetz argued Wednesday that the databases are a privacy concern that could spread to the limiting of certain citizen's rights. He also suggested that if the databases were smaller, or limited "to known criminals, wanted criminals, people that are here illegally, maybe those are the types of things that we should be focused on, as opposed to everybody," they would be more useful because it would be easier for the software to accurately identify people.