Color is a new photo-sharing application for iPhone and Android phones. It allows you to share the photos you have taken through it with any other Color user near you. And you get to see also his or her pictures 
They defined a ‘proximity’ criteria, that creates local temporary networks. As soon as you leave the place, if you are no longer close to the other user, you loose access to his photos (and he to yours).
But if you hang around the same Color user for some time, photos will remain longer than with an occasional user. Color is using machine learning algorithms to create this ‘elasticity’. Great concept!
Much of last week’s buzz surrounding the launch of Color was justifiably skeptical. The startup, after all, raised $41 million to enter a crowded space without a business model or customers, and many wonder whether the world really needs another mobile photo-sharing app. But two components of Color’s vision — implicit networks (connections created without user effort) and place/time tagging — extend far beyond photo-sharing, and make the company worth watching as a potential indicator of social media and data-mining trends.
Read more of David Card’s article: Color: More Than Just Another Photo-Sharing App
[...] This is just one possibility, but the future of the interest graph is so much more than product recommendations. It has the power to create richer profiles of brand advocates, as Brian Solis found when analyzing @Starbuck’s twitter followers (hint: coffee is actually one of the weakest links between them). It can help us plan our careers by showing us the skills shared by those with the jobs we aspire to. It can inject a new layer of relevancy into the search experience by boosting results in which others like us found value, as expressed by onsite behavior and other factors. And because our interests are constantly in flux, it can also provide the “elasticity” that is the basis of some interesting apps like Color. [...]