MathWorks is putting social media and its MATLAB programming environment to the test. The company this week kicked off its 2010 Fall MATLAB online programming contest, which runs from Nov. 10 through 17, challenging contestants to leverage MATLAB to solve a navigation problem.
The contest, entitled “Sailing Home,” asks participants to plot a navigation course as captain of sailboat, leveraging the wind as much as possible and chartering the route from point A to point B with minimal reliance on a small motor. Like other MATLAB programming contests, the idea is to foster collaboration around engineering and science, encouraging participants to build on code written by fellow competitors and to foster an exchange of ideas.
As a result, MathWorks execs are pitching the contest as an exercise in “social learning,” citing Gartner Group research that details the knowledge exchange benefits of such an experience. According to a report by Gartner analyst Susan Landry, social learning gives participants the ability to create, discuss, share and capture learning content as learning objects; organize and find learning objects from varied sources; receive real-time, online coaching and support; and engage with peers beyond their social network to gain access to other trusted sources of information.
To promote the contest and foster the spirit of social learning, MathWorks is leveraging its MATLAB Central social network to allow participants in the contest to discuss their solutions and strategies with peers. MathWorks hosts such contests semiannually for its 1.3 million active MATLAB users.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.