Google's algorithm update, called MUM, is new SERP organizer AI technology

When I tell people I work on Google Search, I’m sometimes asked, "Is there any work left to be done?" The short answer is an emphatic “Yes!” There are countless challenges we're trying to solve so Google Search works better for you. Today, we’re sharing how we're addressing one many of us can identify with: having to type out many queries and perform many searches to get the answer you need. - Pandu Nayak, Google Fellow and Vice President, Google Search

What is Google MUM? or What is Google MUM AI?

MUM's full form is Multitask Unified Model. This is an artificial intelligence developed by Google. Its work and purpose is that all the pages in it are searched. Checking their quality and getting them ranking signals.

How it works?

Take this scenario: You’ve hiked Mt. Adams. Now you want to hike Mt. Fuji next fall, and you want to know what to do differently to prepare. Today, Google could help you with this, but it would take many thoughtfully considered searches — you’d have to search for the elevation of each mountain, the average temperature in the fall, difficulty of the hiking trails, the right gear to use, and more. After a number of searches, you’d eventually be able to get the answer you need.

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But if you were talking to a hiking expert; you could ask one question — “what should I do differently to prepare?” You’d get a thoughtful answer that takes into account the nuances of your task at hand and guides you through the many things to consider.  
This example is not unique — many of us tackle all sorts of tasks that require multiple steps with Google every day. In fact, we find that people issue eight queries on average for complex tasks like this one.

Now Google AI has built a new model based on BERT to manage complex searches–Multitask Unified Model (MUM). Google says MUM is a thousand times more powerful that BERT; that is, it contains a thousand times the number of nodes–the decision points in a neural network whose design is based on the nerve junctions in the human brain. Google says MUM is trained using data crawled from the open web, with low quality content removed.

Meanwhile, all the points covered by Google are as follows

• Helping you when there isn’t a simple answer

MUM is built on a Transformer architecture, but it’s 1,000 times more powerful. MUM not only understands language, but also generates it. It’s trained across 75 different languages and many different tasks at once, allowing it to develop a more comprehensive understanding of information and world knowledge than previous models.

• Removing language barriers

Language can be a significant barrier to accessing information. MUM has the potential to break down these boundaries by transferring knowledge across languages. It can learn from sources that aren’t written in the language you wrote your search in, and help bring that information to you.

• Understanding information across types

MUM is multimodal, which means it can understand information from different formats like webpages, pictures and more, simultaneously. Eventually, you might be able to take a photo of your hiking boots and ask, “can I use these to hike Mt. Fuji?” MUM would understand the image and connect it with your question to let you know your boots would work just fine. It could then point you to a blog with a list of recommended gear. 

• Applying advanced AI to Search, responsibly

Whenever we take a leap forward with AI to make the world’s information more accessible, we do so responsibly. Every improvement to Google Search undergoes a rigorous evaluation process to ensure we’re providing more relevant, helpful results. Human raters, who follow our Search Quality Rater Guidelines, help us understand how well our results help people find information. 

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Just as we’ve carefully tested the many applications of BERT launched since 2019, MUM will undergo the same process as we apply these models in Search. Specifically, we’ll look for patterns that may indicate bias in machine learning to avoid introducing bias into our systems. We’ll also apply learnings from our latest research on how to reduce the carbon footprint of training systems like MUM, to make sure Search keeps running as efficiently as possible.

How will MUM impact on SEO?

Whether or not Google MUM will have an impact on the SEO, you will tell that the impact will be affected as soon as you see the update, because the major update of Google MUM AI is only in the content quality and language difference. Apart from the impact in seo, it has done something better in it, whatever the quality content was. By copying, anyone could paste and rank it. Your copy of it will now be closed. However, the update is still in the experiment.

Source: Google Search Blog

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