That the modern world is a complex place will not have escaped your notice. We are all dimly, unsettlingly aware that our lives are enmeshed in systems we can't fully comprehend. The last meal you ate probably contained produce grown in another country that was harvested, processed, packaged, shipped, then sold to you. The phone in your hand is the end-product of an even more convoluted chain; one that relies on human labor from mines in Africa, assembly lines in China, and standing desks in San Francisco. Explaining how these systems connect and the effect they have on the world is not an easy task.

A world renowned pioneer in social robotics, Cynthia Breazeal splits her time as an Associate Professor at MIT, where she received her PhD and founded the Personal Robots Group, and Founder and Chief Scientist of Jibo, a personal robotics company with over $85 million in funding. While Breazeal's work has won numerous academic awards, industry accolades, and media attention, she had to fight early skepticism in the 1990s from other experts in robotics and AI. At the time, robots were seen as physical and industrial tools, not social or emotional companions. Her first social robot, Kismet, was unfairly called out in popular press as "useless". Breazeal bucked the trend with a very different vision: "I wanted to create robots with social and emotional intelligence that could work in collaborative partnership with people. In 2-5 years, I see social robots helping families with things that really matter, like education, health, eldercare, entertainment, and companionship." She hopes her work and influence will inspire others to create robots "not only with smarts, but with heart, too."

There used to be only three ways off of a kidney transplant waiting list. The first was to find a healthy person from within one's own pool of friends and family, who perfectly matched both the recipient's blood and tissue types, and possessed a spare kidney he or she was willing to part with. The second was to wait for the unexpected death of a stranger who was a suitable physical match and happened to have the organ-donor box checked on their driver's license. The third was to die. But then it occurred to doctors: given enough kidney patients, and enough healthy, willing donors, they could form a pool big enough to facilitate far more matches than the one-to-one system of the past. As long as patients could procure a donor--any donor, even one that wasn't a fit with the patient themselves--they could get a matching kidney. At first, this required doctors to spend brain-searing hours poring over the details of blood types and tissue variations in patients' and potential donors' charts. Then computer scientists and economists got involved. They built algorithms that performed these complicated matches more elegantly than human brains ever could.

Abstract--Meta-graph is currently the most powerful tool for similarity search on heterogeneous information networks, where a meta-graph is a composition of meta-paths that captures the complex structural information. However, current relevance computing based on meta-graph only considers the complex structural information, but ignores its embedded meta-paths information. To address this problem, we propose MEta-GrAph-based network embedding models, called MEGA and MEGA, respectively. The MEGA model uses normalized relevance or similarity measures that are derived from a meta-graph and its embedded meta-paths between nodes simultaneously, and then leverages tensor decomposition method to perform node embedding. The MEGA further facilitates the use of coupled tensor-matrix decomposition method to obtain a joint embedding for nodes, which simultaneously considers the hidden relations of all meta information of a meta-graph. Extensive experiments on two real datasets demonstrate that MEGA and MEGA are more effective than state-of-the-art approaches.

In a business where shaving off a mile per day per driver can result in savings of up to $50 million per year, UPS has plenty of incentive to incorporate technology to drive efficiencies in every area of its operations. Here are just a few of the ways UPS uses big data and artificial intelligence (AI) to prepare for the 4th Industrial Revolution. UPS was founded in 1907 and has a history of embracing change and evolving as new technologies arise. It's the use of big data and artificial intelligence that allows the company to operate its global logistics network in more than 220 countries and territories. On an average day, there are typically 96,000 UPS vehicles on the road handling 19 million packages.

Stretchable plant wearables and smart tags dropped by drones aim to help give farming a big data makeover. The relatively cheap technologies for mass monitoring of individual plants across large greenhouses or crop fields could get field tests in three countries starting in 2019. The idea came from researchers at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia with expertise in flexible electronics. After talking with colleagues who were cultivating genetically engineered plants in greenhouses, they recognized the need for inexpensive sensors that could be deployed en masse and report on individual plant conditions. Their early offerings include a stretchable sensor for measuring micrometer-level changes in plant growth and a "PlantCopter" temperature and humidity sensor designed to be dropped from a drone and corkscrew its way through the air for a gradual descent.

The CIA is reportedly expanding its armed drone programme in Africa and will start using a military base in the Nigerien desert to carry out raids on areas where ISIL and al-Qaeda are believed to operate. The New York Times reported on Monday that a secret military base in Dirkou, about 250km south of the Libyan border, will soon begin deploying armed drones in an apparent loosening of Obama-era limits on US raids outside conventional warzones. According to the Times, the Pentagon has already carried out five drone raids in Libya this year, including one two weeks ago. While the drones are currently being flown out of bases in Sicily and Niamey, Niger's capital, armed drones "would almost certainly" be deployed from Dirkou "in the near future". The Times added that one of its journalists said he saw "gray aircraft - about the size of Predator drones, which are 27 feet long - flying at least three times over six days in early August".

A key opponent of high-tech, automated weapons known as'killer robots' is blaming countries like the U.S. and Russia for blocking consensus at a U.N.-backed conference, where most countries wanted to ensure that humans stay at the controls of lethal machines. Coordinator Mary Wareham of the Campaign to Stop Killer Robots spoke Monday after experts from dozens of countries agreed before dawn Saturday at the U.N. in Geneva on 10 'possible guiding principles' about such'Lethal Automated Weapons Systems.' Point 2 said: 'Human responsibility for decisions on the use of weapons systems must be retained since accountability cannot be transferred to machines.' Killer robots must be banned to prevent unlawful killings, injuries and other violations of human rights'before it's too late', according to Amnesty International. Wareham said such language wasn't binding, adding that'it's time to start laying down some rules now.' Members of the LAWS conference will meet again in November. Last week Amnesty International said killer robots must be banned to prevent unlawful killings, injuries and other violations of human rights'before it's too late', as the talks kicked off.

Robots could teach themselves to treat other forms of life – including humans – as less valuable than themselves, new research claims. Experts say prejudice towards others does not require a high level of cognitive ability and could easily be exhibited by artificially intelligent machines. These machines could teach each other the value of excluding others from outside their immediate group. The latest findings are based on computer simulations of how AIs, or virtual agents, form a group and interact with each other. Robot could teach themselves to be treat other forms of life - including humans - as less valuable than themselves, new research suggests.

Before he died, eccentric philosopher Jeremy Bentham asked that his body be stuffed and wheeled out at parties to help his friends with their grief. But the social reformer didn't stop there, bequeathing 26 memorial rings to those he knew and admired, featuring his bust in silhouette and strands of his hair. Now scientists are on the hunt for Bentham's rings, of which just six have been found since his death in 1832. The philosopher commissioned the rings a decade before he passed, leaving them in his will and testament to a list that included famous politicians, journalists, fellow philosophers and several of his servants. Researchers say the missing artefacts could be spread across the globe, after one was found in a jewellery shop in New Orleans.