Social Search - The Future of Image Search

[Disclaimer: I'm CEO of Zooomr, we are building both a social based image search system as well as a stock photography platform]
Unfortunately, I'm going to have to disagree. While I like the fact that Microsoft claims an increase in speed on how fast their images load, the relevancy of their results still pale significantly in comparison to what can be done with social search. This is not the first time that I've blogged about this and it won't be the last. The future of image search very much belongs to social search.

What do I mean by this? Well, image search is one of the hardest types of search (audio and video aren't so easy either). With text search, Google, Yahoo and Microsoft all have their proprietary algorithms where they look for text on a page, see who links to a page, etc. etc. words are in contrast to images much easier to figure out. If Mike Arrington is mentioned 40 times in a post by a highly ranked internet site, then the article probably has some authority to be placed in the results for an article about Mike Arrington.

But photos of Mike Arrington are a different matter. It is very difficult for image search engines to get at what's inside a photo and how good a quality photo it is.

Accordingly, image search engines that rely solely on algorithms without any human filtering fall flat compared to results that are filtered through social networks.

To see what I mean lets look at some examples:

Mike Arrington, "new and improved" live.com
Summer, "new and improved" live.com
Brunette, "new and improved" live.com
Africa, "new and improved" live.com