If I have a picture of a dog, and I want to search the Internet for pictures that look like that dog, how can I do that?
I need to make an algorithm to build an index of all the pictures on the Internet. That index can define the different features of my images. I can find mathematical features in each image that describe that image. The mathematical features can be represented by a matrix of numbers. Then I can run the same algorithm on the picture of my dog, which will make another matrix of numbers. I can compare the matrix representing my dog picture to the matrices of all the pictures on the internet.
This is what Google and Facebook do–and we covered this topic in our episode about similarity search a few weeks ago. Today, we evaluate a similar problem: searching images within Squarespace. Squarespace is a platform where users can easily build their own website for blogging, e-commerce, or anything else.
Neel Vadoothker is a machine learning engineer at Squarespace, and he joins the show to talk about how and why he built a visual similarity search engine.
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