This new AI tool from Google could change the way we search online

What does the future of internet search look like? Google envisions it as looking more like a casual conversation with a friend.

While Google’s search engine has been online for over two decades, the technology that powers it has been constantly evolving. Recently, the company announced a new artificial-intelligence system called MUM, which stands for Multitask Unified Model. MUM is designed to pick up the subtleties and nuances of human language at a global scale, which could help users find information they search for more easily or allow them to ask more abstract questions.

Google already used MUM in an independent task to learn more about the different ways people refer to COVID vaccines, but says that the new tech is not yet part of their search system. While there’s currently no set timeline on when the feature will roll out in live search, the team is actively working on developing other one-off tasks for MUM to complete.

Here’s what to know about what MUM is, how it’s different from what’s come before, and more.

When vaccines became available earlier this year, Pandu Nayak, the VP of search at Google, and colleagues designed an “experience” that gave people information about the COVID vaccines–where to get them, how they work, and where they were available–when users searched for it. The experience patchworked all this essential and relevant information together and pinned it to the top of the first page of search results. But first, the team needed to program it so it only popped up when the queries were about COVID vaccines. That could become a problem because people around the world may refer to COVID vaccines in different ways, and by different names.

Last year, the team spent hundreds of hours combing through resources to identify all the different names for COVID itself. But this year, they had MUM. “We were able to set up a very simple experiment with MUM that within seconds was able to generate over 800 names for 17 different vaccines in 50 different languages,” Nayak says. “We have a lot of language tasks that need to be solved, whether it’s classification, ranking, information extraction, and a whole host of others. In the short term, we expect to use MUM to improve each of those. Not that it will lead into a new feature or a new experience, rather, existing features and existing experiences will just work that much better.”

We first heard about MUM back at the Google I/O developer’s conference in the spring, when  Prabhakar Raghavan, senior vice president at Google, unveiled it.

The new tech is the natural evolution of machine-learning based search that Google has been refining and modifying over the last decade. Google boasts that MUM is able to acquire deep knowledge of the world, understand language and generate it, and train across 75 languages at once. There’s also internal pilots testing if it can be multimodal—that is, able to simultaneously understand different forms of information like text, images, and video.

All this complexity can be illustrated by a simple example laid out at the conference and via a blog post. Suppose you ask Google, “I’ve hiked Mt. Adams and now want to hike Mt. Fuji next fall, what should I do differently to prepare?” This is the type of search query most people wouldn’t bother typing in today, because users understand that that’s generally not how you search for information online.

“This is a question you would casually ask a friend, but search engines today can’t answer it directly because it’s so conversational and nuanced,” Raghavan explained at I/O. But ideally, MUM would understand you’re looking to compare two mountains, and also understand that “prepare” could include things like fitness training for the terrain and hiking gear for fall weather. It would be able to dissect your question and break it down into a set of queries, learn about each aspect of your problem, then put it back together.