While CRISPR, nanobots and head transplants are making headlines as medical breakthroughs, a number of new technologies are also making progress tackling some of the toughest age-old diseases still plaguing millions of people in the poorest parts of the world. In low income countries, over 75% of the population dies before the age of 70 due to infectious diseases including HIV/AIDS, lung infections, tuberculosis, diarrheal diseases, malaria, and increasingly, cardiovascular diseases. Over a third of deaths in low income countries are among children under age 14 primarily due to pneumonia, diarrheal diseases, malaria and neonatal complications. In the developed world, those living in extreme poverty, such as homeless populations, also die on average at age 48. Over the last year, artificial intelligence, robotics and biotechnology have all generated a number of new solutions that have the potential to dramatically reduce these problems.

At 100million a pop, you might expect F-35 fighter jets to take-off at the first time of asking. But the life of a test pilot is not that simple, with dozens of computer systems to calibrate and reset before the Air Force's most sophisticated plane can even taxi to the runway. Defense News got a glimpse of how testing F-35s works during a visit to Edwards Air Force Base in southern California. Major Raven LeClair, of the 461st flight test squadron, begins his day at around 10am by checking the plane for any issues. It immediately became clear that the day's testing would not pass without a hitch, with an alarm sounding as soon as he got to the aircraft.

Let's suppose you've agreed to a rather odd travel program, where you're going to be suddenly transported to a randomly selected country, and your job is to figure out where you end up. So, here you are in some new country, and all countries are equally likely. You make a list of places and probabilities that you're in those places (all equally likely at about 1/200 for 200 countries). You look around and appear to be in a restaurant. Some countries have more restaurants (per capita/per land area) than others, so you decrease the odds that you're in Algeria or Sudan and increase the odds that you're in Singapore or other high-restaurant-density places. That is, you just multiply the probability that you were in a country with the probability of finding oneself in a restaurant in that country, given that one were already in the country, to obtain the new probability. After a few moments, the waitress brings you sushi, so you decrease the odds for Tajikistan and Paraguay and correspondingly increase the odds on Japan, Taiwan, and such places where sushi restaurants are relatively common. You pick up the chopsticks and try the sushi, discovering that it's excellent. Japan is now by far the most likely place, and though it's still possible that you're in the United States, it's not nearly as likely (sadly for the US). Those "probabilities" are getting really hard to read with all those zeros in front. All that matters is the relatively likelihood, so perhaps you scale that last column by the sum of the whole column. Now it's a probability again, and it looks something like this: Now that you're pretty sure it's Japan, you make a new list of places inside Japan to see if you can continue to narrow it down. You write out Fukuoka, Osaka, Nagoya, Hamamatsu, Tokyo, Sendai, Sapporo, etc., all equally likely (and maybe keep Taiwan too, just in case). Now the waitress brings unagi. You can get unagi anywhere, but it's much more common in Hamamatsu, so you increase the odds on Hamamatsu and slightly decrease the odds everywhere else. By continuing in this manner, you may eventually be able to find that you're eating at a delicious restaurant in Hamamatsu Station -- a rather lucky random draw.

Artificial intelligence (AI) is an emotionally loaded term that strikes fascination into some and fear into others. But if we strip it of fantasy and ignore cyborgs and apocalypse, there is a near-term, practical side of AI that is already unfolding. Most humans can recognise a chair because they have learnt what a chair is – they can identify thousands of examples of chairs even if they have never seen that chair before. Instead of memorising every image of what a chair could be, humans learn what a chair is and then apply that to new images and examples of chairs. But how does a computer learn what a chair is?

Researchers from Stanford University have created a humanoid robot or robot mermaid to explore sunken treasures and relics. Tagged as OceanOne, the robo-mermaid uses artificial intelligence and virtual reality technology to allow human beings to operate it remotely, as per Stanford News. The robot mermaid looks like a human with hands that are installed with sensors to enable OceanOne to discern if an item is fragile or not. It also has two cameras as its eyes and an artificial human brain for navigating the deep sea and analyzing data. According to CNN, OceanOne's first journey to the deep water was to retrieve a vase from the ruins of Louis XIV's ship La Lune.

Over the past few years, IBM has been devoting a great deal of corporate energy into developing Watson, the company's Jeopardy-beating supercomputing platform. Watson represents a larger focus at IBM that integrates machine learning and data analytics technologies to bring cognitive computing capabilities to its customers. To find out about how the company perceives its own invention, we asked IBM Fellow Dr. Alessandro Curioni to characterize Watson and how it has evolved into new application domains. Curioni, will be speaking on the subject at the upcoming ISC High Performance conference. He is an IBM Fellow, Vice President Europe and Director IBM Research – Zurich Research Laboratory, Switzerland.

That represents a strategic error. The U.S. can and should sell more drones as a way of complementing its foreign policy objectives. After all, some of the top threats to U.S. national security are the very nonstate actors that countries in the Middle East and Africa are buying drones in order to fight. The question is a quasi-legal one. In accordance with the Missile Technology Control Regime, a voluntary arrangement established in the late 1980s and now followed by 34 countries, the United States subjects the sale of military drones and other Category 1 items to "a strong presumption of denial" when determining whether to export to a particular country.

Last week, the White House released a report chronicling the Obama administration's concerns over Big Data and artificial intelligence. Many prominent thinkers and scientists have come out recently with warnings about the dangers of unchecked artificial intelligence. However, the A.I. the White House report refers to is not of the Terminator ilk -- rather, Obama has concerns over algorithmic artificial intelligence operating without human oversight. The report, "Big Data: A Report on Algorithmic Systems, Opportunity, and Civil Rights," catalogs the growing sphere of influence represented by Big Data in society, including employment, higher education, and criminal justice. "As data-driven services become increasingly ubiquitous, and as we come to depend on them more and more, we must address concerns about intentional or implicit biases that may emerge from both the data and the algorithms used as well as the impact they may have on the user and society. Questions of transparency arise when companies, institutions, and organizations use algorithmic systems and automated processes to inform decisions that affect our lives, such as whether or not we qualify for credit or employment opportunities, or which financial, employment and housing advertisements we see." "If feedback loops are not thoughtfully constructed, a predictive algorithmic system built in this manner could perpetuate policing practices that are not sufficiently attuned to community needs and potentially impede efforts to improve community trust and safety. For example, machine learning systems that take into account past arrests could indicate that certain communities require more policing and oversight, when in fact the communities may be changing for the better over time."

The company is continuing its review of the potential to use drones someday in its global package delivery system, teaming with two partners to deliver blood supplies later this year in Rwanda. The company, through its UPS Foundation, has committed 800,000 toward the project with Zipline, a California robotics company; and Gavi, a Swiss-based group that works to bring vaccines to children in poor countries. UPS said that starting later this year, the Rwandan government intends to begin using Zipline drones to delivery blood to 21 transfusing facilities in the western half of the country. The goal is to step up the battle against the deaths of women who hemorrhage after giving birth. The additional blood can allow for life-saving transfusions on a continent known for the world's high rates of maternal death, according to the World Health Organization.

In October 2011, Apple added the emoji keyboard to iOS as an international keyboard. Since then, digital language has evolved such that nearly half of comments and captions on Instagram contain emoji characters. And earlier this week, Instagram also added support for emoji characters in hashtags, which allows people to tag and search content with their favorite emoji # . In Part 1 of this blog post series, we will take a deep dive into emoji usage on Instagram. By applying machine learning and natural language processing techniques, we'll discover the hidden semantics of emoji.