Google MUM: The Multitask Unified Model Revolutionizing Search Understanding

Google has launched various algorithm updates over the years. Some of them have even made headlines and changed the way how SEO works. One such algorithm is Google MUM. If you haven’t heard about it, the announcement of this algorithm revolutionized the organic SEO. Short for Multitask Unified Model, this algorithm works with AI and answers complex search queries with multimodal data. 

Its purpose was to make search easier and find answers to queries by processing information from different media formats. In this blog, we’ll learn more about the Google MUM update and how it has drastically made an impact on the search we are familiar with today, let’s get started.

Uncovering what is Google MUM

Google MUM was introduced in May 2021, by Pandu Nayak, Vice President of Search at Google. Based on artificial intelligence technology, this update uses the T5 text-to-text framework and is said to be a thousand times more powerful than the search engine giant’s previously introduced algorithm in 2018, BERT. If you are wondering how the Google MUM algorithm works, it combines multiple technologies that make search more context-based to improve the user experience. Simply put, Google MUM is designed to help you when there isn’t a simple answer to your query.

So, what are the specialties of Google MUM update? For starters, the model is trained and has a deep understanding of not only 1 but 75 different languages, making it multilingual. The second one is its ability to handle and process multiple tasks at once, thereby making it effectively multitask and obtain a comprehensive understanding of knowledge and information. The third one is multimodal as it can understand information from text, images, audio, video, etc.

Functions of Google MUM Algorithm

Now that you understand what is google mum is, let’s explore the various features or functionalities this algorithm offers to the search.

Answering complex user queries

As explained above, this was the primary objective of the Google MUM update is to answer complex search queries with ease and provide a better user experience. This is made possible by artificial intelligence and analyzing various multimodal data, providing accurate results for the user. Let’s consider the following example.

Suppose you are planning to go to Mt. Fuji for hiking and want to know if your footwear will help you or not. Instead of typing to find out, you can just take a photo of your footwear and ask in a Google search whether it suits your trip. The multitask unified model would understand the image and connect it with your question to let you know whether your footwear would work or not.

Eliminating language hurdles

Whenever we travel abroad to a new country, one of the major issues we all face is language barriers. When it comes to search, there might be certain helpful results users are looking for that may not pop up due to language. However, this all ends with Google MUM as it provides complete results, regardless of the query. Since the algorithm is trained across 75 different languages, if you search for information about a topic in a language, the Google MUM model understands multiple languages and LLM models so it will transfer knowledge from sources in multiple languages thereby, eliminating language hurdles.

Simultaneous processing of various information types

The thing about Google MUM is that it can analyze information from multiple sources such as audio, video, text, etc. We are already familiar with Google Lens which allows us to take images and use them as search queries. However, the multitask unified model goes beyond that. The new algorithm allows users to search images along with adding a textual query. For eg, if you have a photo of a pair of shoes and add a search text for whether you can use them for hiking, the search engine understands the intent and will be able to provide an answer to the question effectively.

Google MUM & The SEO Changes

When Google releases a new algorithm, it results in various SEO strategy changes. Even though no major changes happened since MUM was introduced, it will certainly happen in the future. So, if you are wondering how to do SEO in Google MUM, it is important to understand certain things:

Decreased Click-through Rates

Since Google MUM algorithm provides well-detailed search results to users’ complex queries, the chances are that users will click the specific one offering relevant results. This results in a lower click rate for other search links. So when MUM becomes mainstream, those existing results which get better click rates become an important part of the algorithm.

Focusing on search intent rather than keywords

Unlike other algorithms, Google multitask unified model can understand information from whole page contents. This means that instead of relying solely on keywords which is the norm, it’s important to create content that focuses on the user search intent. Such contents are more likely to be picked up and shown to the user first.

Leverage multiple media

This is not the early 2000s, Google algorithms have become smarter and more sophisticated. Also, as Google MUM can analyse and understand information from various data types, adding images, videos, podcasts, etc to your content helps users get the exact and complete information they are looking for. Leveraging multiple media formats helps the search engine gain more valuable insights and helps improve your SEO strategies.

Google MUM vs BERT

Before the introduction of both these algorithms, Google used to process every word in a user search query. That all changed when Google MUM (multitask unified model) & BERT (Bidirectional Encoder Representation for Transformers) were introduced, BERT algorithm insights and the purpose were to understand the user intent by analyzing the context of the sentence, same with Google MUM. Since they have similar purposes, it’s obvious for people to do a comparison between the two. 

Well, as we know the latest algorithms are always more powerful than the previous ones and in this case, BERT was introduced before the Google MUM update. Also, The BERT update even though great, lacked various factors and resulted in issues such as language barriers, non-recognition of image and video-based content, etc. This is where Google MUM shines as it answers complex questions in fewer searches and also understands images, audio, and video files.

Winding up

Even though the multitask unified model was first announced in May 2021, its rollout has been gradual, and Google should have implemented it in its search. Suppose you are looking to be part of this major change. In that case, it is better to start improving the quality and scale of your webpage content by making it Google MUM algorithm-friendly, integrating SEO services and best strategies that focus on user search intent rather than only keywords, and ensuring the audience gets the answer they need without much effort.