I was lead to this from Doug Belshaw’s newsletter. The site is called Same Energy. It’s a website devoted to finding images for you.
So, what makes this stand out in an environment full of search engine?
For the most part, search engines accept the descriptors that you send them and does its best to locate images that meet those descriptors. If you’re really good about describing what you want, you have success. If you aren’t that good, you might go back and add a few more terms to tighten up the descriptor. Or, if you’re in a hurry or you’re a student, you take the best fit and move on.
Same Energy works nicely to help you refine your search.
We believe that image search should be visual, using only a minimum of words. And we believe it should integrate a rich visual understanding, capturing the artistic style and overall mood of an image, not just the objects in it.
So, I put it to the test and promptly went down a rabbit hole!
For yucks, I started with the search “Toronto” and got this.
Now, we know that Toronto is more than the CN Tower.
I found a picture of a cute pooch sitting with the City Hall in the background which led me to this.
A few more clicks and I was well off the track from my original search or another way of looking at it was I was refining my search as I went.
Now, a starting point of “Toronto” isn’t the best of starts. Anyone who has ever taught students how to search knows that.
I went back and started with some more specific search terms like “White German Shepherd” and found that I could refine an image search nicely.
I found it responsive and very easy to zero in on things I’m in search of very quickly. Certainly much quicker than trying to describe the item in words.
You can create an account for yourself to download the images or create collections. This is a very interesting refreshing approach to finding images. The author warns that it’s in Beta and will likely change but what online doesn’t these days.
The author is very open about how it works.
The default feeds available on the home page are algorithmically curated: a seed of 5-20 images are selected by hand, then our system builds the feed by scanning millions of images in our index to find good matches for the seed images. You can create feeds in just the same way: save images to create a collection of seed images, then look at the recommended images.
I found the experience fascinating and look forward to hearing more about this search engine as it matures and grows based on feedback from users.
As always, I’d encourage you to take a look and share your thoughts about it in the comments below.