At one time or another, we’ve all likely been there. Faced with a problem we don’t readily know the answer to, we turn to a search engine. And most of us likely start with Google. We feed it the question on our minds and wait for results. What we get is a skein of links to other sources, sometimes with brief blurbs below the link providing a hint of text culled from the actual link’s location. And whether or not this is helpful depends on our capacity to read between the lines, as well as a little sheer blind luck. But with Google’s latest improvement known as “semantic search”, we may have to count less on luck and more on the search results.

The difference between the original concept, called “literal search” and Google’s new search technology “semantic search” is pronounced. Literal search requires you to know exactly what it is you’re looking for, and once you’ve provided the terms in question, the search goes looking for pages that contain those words. If you’re wondering if there’s a Mother’s Day brunch special in your area, you’d input the terms “Mother’s Day brunch” and hope that someone spelled out on their website that they were offering a Mother’s Day brunch.

Some searches can be augmented, using what’s called stem-matching to also give you the results for a Mom’s Day brunch or a Mom’s Special Day brunch. But rather than getting dates and times, you might instead get an article about how businesses like to put on Mother’s Day brunches, or recipes for you to make one at home.

But semantic search tries to get closer to the truth by analyzing the terms of the search, and then returning answers accordingly. Semantic searches are geared to provide answers to a question, so instead of you searching for Mother’s Day brunches, you’d ask a semantic search engine: “What restaurants are offering Mother’s Day brunch?” and, optimally, it would return a list of locations, with hours and phone numbers and links to menus where available.

As it turns out, literal searches are the easiest for a computer to perform, and thus, we’re used to them. Literal searches do a great job when you know exactly what you want: a John Deere lawn mower, an omelet recipe, horseshoes. But when you want specific information, like who discovered Iceland or what restaurants offer Mother’s Day brunches, a semantic search engine does a better job.

Some have posited that this move on Google’s part is related to the release of Siri, which uses Wolfram Alpha to handle the bulk of its searches, and indeed, as long as you stay within the confines of Wolfram Alpha’s knowledge, you’ll get the results you need. Google, meanwhile, looks to expand upon that and make the results more accessible for users, almost trying to one-up Siri in a bid to stay relevant.

At any rate, moving to such a search style may make things much easier for search users when Google finally rolls it out over the next several months, and seeing just how it works should be a sight worth seeing.