It is important to divide the overall understanding process into manageable pieces.

Venture Beat covered the closing ceremonies of the third summer session of the Singularity University. Matternet is the most technologically ambitious. In the first phase, it utilizes small-scale electric vehicles deployed with vertical take-off and landing capability, limited payload-bearing capacity and range. In the longer term, we will have a wide range of AAVs suitable for different payload capacity, flying range and weather conditions. Ground stations They create and use unmanned aerial vehicles (UAVs) that can be used to ferry medicine and other goods to remote places such as rural villages in Africa.

Projects that target aid toward villages and rural areas in the developing world often face time-consuming challenges, even at the most basic level of figuring out where the most appropriate sites are for pilot programs or deployment of new systems such as solar-power for regions that have no access to electricity. Often, even the sizes and locations of villages are poorly mapped, so time-consuming field studies are needed to locate suitable sites. Now, a team of graduate students at MIT and a social-service group of data scientists have come up with a way of automating parts of that evaluation process, by developing software that can identify houses and even types of houses from readily-available satellite imagery -- potentially saving considerable time that would otherwise be spent sending teams from village to village. Their findings have now been published in the journal Big Data. The multidisciplinary team came together in the course of discussions at MIT's Sidney Pacific graduate dormitory, explains team member Brian Spatocco: "We started talking about this problem, and we realized we all had skills that were relevant."

A team from MIT Lincoln Laboratory's Bioengineering Systems and Technologies Group was named a first-place subchallenge winner at the 2014 Audio/Visual Emotion Challenge and Workshop (AVEC 2014), the fourth annual competition that invites participants to use multimedia processing and machine learning to analyze subjects' emotional states or estimate subjects' level of depression. Held at the annual Association for Computing Machinery (ACM) International Conference on Multimedia, the challenge gauges the success of entrants' approaches to automated emotion detection on a set of common benchmarks. In 2014, two subchallenges were presented: continuously distinguishing emotions and estimating the level of subjects' depression from audio and visual data. Of the 14 groups competing in the 2014 depression assessment subchallenge, Lincoln Laboratory's team was the most successful in predicting a depression score. Participants in this subchallenge estimate the severity of subjects' depression from either vocal characteristics detected in audio or facial signs identified in video recordings, or both.

The annual MIT IDEAS Global Challenge awards ceremony awarded $79,500 on Monday night to 13 student-led teams to further develop inventions and ideas intended to solve pressing environmental and health challenges in developing countries. "Today marks an important opportunity for emerging entrepreneurs to take a big leap forward in their journey to improve the quality of life in communities around the world," Keely Swan, the Public Service Center's IDEAS Global Challenge program administrator, said in her welcoming remarks. Launched and run by MIT students, the winning ventures took home prizes of $10,000, $7,500, $5,000, and $1,500, to further support prototyping and field-testing, among other things. CleanData-CleanWater, a $10,000 winner last night, plans to use its earnings to manufacture 1,000 of its sensors, which gather previously unavailable data on water filter usage in developing countries. The sensors fit on a filter's tap and track how long the tap stays up or down, measuring the frequency and duration of use. The company plans to integrate the sensors into a new line of ceramic pot water filters being installed across Ghana by the company Pure Home Water, a previous IDEAS winner.

In 2008, Krishna Gupta '09 launched Romulus Capital, a venture capital seed firm, out of his MIT dorm room, scraping together $850,000 to invest in tech startups launched by his classmates. Today, Romulus controls $150 million in funds and other assets, having just raised a new fund of $75 million in June. Now Romulus plans to fund 20 new startups, adding to its existing portfolio of 30 startups, many of which are MIT spinouts. That's not bad for someone completely unfamiliar with the venture capital industry when he launched Romulus as an MIT junior studying materials science and management. "I knew nothing about venture capital, nothing of investing," Gupta says.

D. Fox Harrell, associate professor of digital media with appointments in the MIT Comparative Media Studies/Writing program and in the MIT Computer Science and Artificial intelligence Laboratory (CSAIL), has recently been awarded several grants to advance his research at the intersection of the social sciences and digital technology. These grants, funded by the National Science Foundation (NSF), the MIT CSAIL Qatar Computing Research Institute (QCRI) Alliance, and the MIT Center for Art, Science, and Technology (CAST), together amount to $1.35 million in support for Harrell's groundbreaking interdisciplinary research. Harrell's new set of complementary initiatives builds upon his NSF CAREER Grant research project, "Computing for Advanced Identity Representation," to delve more deeply into the dynamic relationship between virtual avatars and personal identities. He was able to push this work in innovative new directions while spending the 2014-15 year as a fellow at Stanford University in the Center for Advanced Study in the Behavioral Sciences (with the support of the Lenore Annenberg and Wallis Annenberg Fellowship in Communication). "For five years I have been researching this intersection between human experiences and our identities as implemented across digital technologies such as video games and social media," Harrell says.

That's exactly what HealthMap is trying to do. It was introduced in 2006 by two researchers at Boston Children's Hospital: John Brownstein, an epidemiologist and professor of pediatrics, and Clark Freifeld, a software developer who is now studying for his PhD in biomedical engineering at Boston University. The software tool they built collects data from the Internet in real time, looking at a wide variety of sources, including Twitter feeds, local newspaper articles, eyewitness reports as well as official data from governments and organizations like the WHO and then plots pertinent information on an interactive map. "We use natural language processing, machine learning, and cluster detection to represent a global view of epidemics," explains Brownstein. "As these sources build up, they bring together a picture of a serious situation for us. Our analysts work to synthesize and we disseminate the information via various channels."

Dogs have always had a role in combat but now they are helping engineers build better robots. Dogs are now in the field wearing high-tech bulletproof vests, parachutes and video cameras into combat. Rolling robots are getting stronger, smarter and smaller. Robots are being made to be more dog-like and dogs are being trained to be methodical, like robots. From infantry units to secret SEAL teams, the U.S. military is using increasing numbers of dogs and robots to assist in conflicts across the world.

Piracy off the shores of Africa continues to be a serious problem, costing the shipping industry billions of dollars. Could robots help in the battle against pirates? ReconRobotics has teamed up with Space and Naval Warfare Systems Center Pacific to develop a concept robot that would be able to climb hulls and perform reconnaissance missions on ships seized by pirates. The micro-robot would be based on Recon's Throwbot platform, a rolling surveillance robot that can be tossed through a window, down a staircase, or into hazardous situations. It's used by military and law enforcement and can survive throws of 120 feet. The 1-pound ship-boarding bot would launch from a "marsupial robot deployment system," in which a larger robot would carry it to its deployment location.