Plus: Technology Predicts When You’ll Get Sick, Learning through Confusion and the Agile Robo-Plane.

Olympic Athletes vs. Nature’s Top Competitors

Michael Phelps is now the winningest Olympian ever, setting the bar high at 20 medals. He also holds or shares the world record in seven Olympic events. But his achievements have only come from competition with other human beings.

According to a report from Veterinary Record, if the Olympics were expanded to include all species, human beings would hardly stand a chance to win any medals. For instance, Usain Bolt, who completed the 100-meter dash in a world-record 9.58 seconds, would get left in the dust at an interspecies Olympics. Even at his fastest, Bolt would lose to a cheetah, a rabbit and even a monkey — and still be behind by at least three seconds.

In the long jump, humans shouldn’t even try. Mike Powell currently holds the long-jump record of 8.95 meters, or about five times his height. The jumping spider, however, can launch itself more than 30 times its own body length. As for the high jump, tiny insects called springtails can leap 30 times their own 1 millimeter body length – the equivalent of a human being jumping over the Eiffel Tower.

Although humans would lose in individual competitions, we do have several advantages over other species. “What we are good at is being really versatile; we can sprint, we can run long distances, we can jump, we can swim, we can lift weights,” Craig Sharp, the study’s author, told Agence France-Presse.

Not to mention our ability to handle firearms, hold rackets and understand the double-dribble rule – sports expertise that might give animals some trouble.

A.I. Knows When You’ll Get Sick

Computer scientist Adam Sadilek, from the University of Rochester, has developed a system that analyzes large amounts of social media data to accurately predict when a person will come down with the flu up to eight days before showing any symptoms.

“To see whether it was possible to bring such a service down to the level of the individual, Sadilek and his team analyzed 4.4 million tweets tagged with GPS location data from over 630,000 users in the New York City area over one month in 2010,” New Scientist explains. “They trained a machine-learning algorithm to tell the difference between tweets by healthy people — who might say something like ‘I am so sick of this traffic!’ – and someone who is actually sick and showing signs of the flu.”

Sadilek and his team achieved a 90 percent level of accuracy in predicting whether a healthy person is about to contract the flu. The technology may help in understanding and controlling the spread of infectious diseases across the world, particularly in dense urban areas.

“We apply machine learning and natural language understanding techniques to determine the health state of Twitter users at any given time,” Sadilek writes. “Since a large fraction of tweets is geo-tagged, we can plot them on a map, and observe how sick and healthy people interact. Our model then predicts if and when an individual will fall ill with high accuracy, thereby improving our understanding of the emergence of global epidemics from people’s day-to-day interactions.”

The disease-prediction system could someday be converted to a mobile device app that warns users when they’re at a higher risk of getting sick. Sadilek notes that it could also be used to determine public sentiment about a company or products, how information spreads throughout a population and to predict customer behavior.

The following video shows the spread of the flu across New York in a single day, based on Sadilek’s data:

Confused? Good, You’re Probably Learning

It’s time to embrace your confusion. While everyday situations — that recent meeting or presentation, for example — can leave you feeling bewildered, research shows that in the long-run, confusion leads to better learning.

A study published in the journal Learning and Instruction found that subjects who were intentionally confused in a series of experiments were able to become better learners and were effective in applying the information they retained during the study.

The researchers triggered confusion among subjects by providing them with incorrect and contradictory information. Confused subjects performed better in difficult post-study tests than those who hadn’t experienced confusion. Apparently, confused subjects were more in-tune with the information and therefore more successful in spotting flaws within the tests.

The researchers, who are studying “productive confusion,” claim that their methods can be applied to “high-level learners,” and, as Medical Daily reports, the process is most beneficial for people who can handle negativity and failure. Ultimately, those who struggle to understand a subject can achieve a more thorough knowledge of it, so that puzzled-looking person may actually be the smartest one in the room.

The Smart Plane Takes Off

Even the most advanced autonomous flying machines can’t match the precision and skill with which birds avoid obstacles and navigate through inclement conditions. But robotics engineers from MIT are working hard to change that, developing a self-flying aircraft that can maneuver as nimbly as a bird.

The team’s computer-controlled plane is capable of performing knife-edge turns and rolling 90 degrees to thread an opening narrower than its wingspan, all while flying at high speeds, according to MIT News. During flight, a remote computer analyzes the plane’s trajectory and sends the results wirelessly to the aircraft, where onboard computers transmit electrical signals to the motors and enable the wings to be adjusted.

The project’s goal is to “gain a better understanding for control theory, and how to operate machines under complex and varying conditions such as aerodynamic disturbances.”

Here’s a video showcasing some of the smart plane’s advanced maneuvering abilities:

Have a great weekend, folks.