By 2020, 30% of all website sessions will be conducted without a screen. Now, you may be asking yourself, how is that possible? It turns out that voice-only search allows users to browse the web the Internet and consumer information without actually having to scroll through sites on desktops and mobile devices. And this new technology may be the key to successful brands in the future. Voice search essentially allows users to speak into a device as opposed to typing keywords into a search query to generate results.
At the Sixth International Conference on Learning Representations, Jannis Bulian and Neil Houlsby, researchers at Google AI, presented a paper that shed light on new methods they're testing to improve search results. While publishing a paper certainly doesn't mean the methods are being used, or even will be, it likely increases the odds when the results are highly successful. And when those methods also combine with other actions Google is taking, one can be almost certain. I believe this is happening, and the changes are significant for search engine optimization specialists (SEOs) and content creators. Let's start with the basics and look topically at what's being discussed.
When is milk not milk? This is no trick question -- it's a distinction that artificial intelligence (AI) is going to have to learn to make in order for eMerchants to fully leverage the potential of machine learning. To one customer, "buy milk" means buy a gallon of whole milk; to another, a 1.4-liter jug of unsweetened vanilla almond milk. Digital shopping lists, apps and virtual assistants must understand this and not force the customer to spell it out each time before these platforms can successfully become the new normal. "We think about things in shorthand, not in terms of specifics," Dave Barrowman, Skava VP of Innovation, told PYMNTS' Karen Webster in a recent webinar.
Most people use Google's search-by-image feature to either look for copyright infringement, or for shopping. See some shoes you like on a frenemy's Instagram? Search will pull up all the matching images on the web, including from sites that will sell you the same pair. In order to do that, Google's computer vision algorithms had to be trained to extract identifying features like colors, textures, and shapes from a vast catalogue of images. Luis Ceze, a computer scientist at the University of Washington, wants to encode that same process directly in DNA, making the molecules themselves carry out that computer vision work. And he wants to do it using your photos.