In recent years, how we search for information on Google has undergone major changes. It’s not just about keywords anymore; now, we try to understand what we mean, even when we search in different languages. The latest technology that Google relies on is MUM (Multitask Unified Model), an intelligent system that can understand questions more deeply and across languages.
For those unfamiliar with the term MUM, take it easy because this article will discuss how MUM changes how search engines work, especially in multilingual content. If you have a website targeting a global audience or want to know how to keep your content relevant across languages, let’s look!
What is Google MUM?
Google MUM, or Multitask Unified Model, is a powerful Google-made algorithm designed to understand information more deeply and thoroughly. Unlike previous algorithms that only process one type of input or one language at a time, MUM is able to analyze multiple types of data-text, images, etc.-simultaneously.
In addition, MUM is also trained multilingually, so it can understand the search intent in one language and find the best answer, even if the answer is written in another language. This makes MUM particularly relevant in a world where cross-language search is becoming an increasingly common requirement in every line of business.
The evolution from BERT to MUM
Before MUM, Google used the revolutionary BERT (Bidirectional Encoder Representations from Transformers) algorithm. BERT could understand the context of words based on the position and meaning of sentences in a bidirectional manner. This means that Google no longer matches keywords but starts understanding the search intent.
However, BERT still has limitations. For example, it can only work with one language at a time and only process text. Well, this is where MUM comes in with a big improvement. MUM can simultaneously understand text in 75+ languages to localize the writing format (for example, Hebrew writing using RTL format).
It can also handle multimodal input (text, images, even voice and video in the future). This allows Google to provide richer, deeper and more relevant search results, even if the questions and answers come from different languages or media.
Core capabilities of MUM
MUM is built on an advanced architecture called T5 (Text-To-Text Transfer Transformer) to understand deeper and more relevant searches. T5 revolutionizes how natural language processing (NLP) works by transforming all tasks-whether translating, answering questions, or summarizing text into a text-to-text format.
MUM brings at least 3 main strengths in improving search capabilities on Google, including the following.
- Multimodal understanding – MUM can simultaneously process different input types, such as text and images. For example, you can upload a photo of hiking shoes and ask, “Are these shoes suitable for hiking in rainy weather?” MUM will understand the image and the context of the question at once to provide the right answer.
- Multilingual training and transfer learning – MUM is trained using data from multiple languages, so it is not limited to a single language. More interestingly, it uses transfer learning techniques, which allow understanding from one language to be applied to another. So, high-quality information in Japanese, for example, can be used to answer questions in Indonesian if relevant.
- Multitasking capabilities – Unlike previous models that only completed one task at a time, MUM can do many things simultaneously. It can understand the question, evaluate content from various sources, compare information, and present the answer in a format that is most helpful to the user. This is done in a single process, making search results more efficient and informative.
How does MUM change the search experience?
With the arrival of MUM, the experience of searching for information on Google has become much smarter and more natural. Previously, we had to type questions with specific keywords to get relevant results. Now, Google can understand the intent behind our questions, even if the sentences are long, complicated, or do not directly address the main point.
MUM helps Google understand the context of a search, not just matching words, so that the results appear richer, deeper, and according to user needs.
One of the most noticeable changes is that Google can present search results that do not only come from one format or one language. For example, you can ask for something in a complex sentence or even upload an image. Google will show you answers that may come from relevant articles, videos, discussion forums, or even other language sources. This is called multimodal input, which refers to Google’s ability to understand different types of information, such as text and images, in a single search.
The result? Users don’t have to do many separate searches for a single topic, as everything is answered more completely simultaneously.
The affects of Google MUM on multilingual search rankings
Today’s users no longer just search for information in one language. They can type a question in Indonesian, but the best answer is available in English, Japanese, or other languages. This is where the advantages of Google MUM are felt. MUM allows Google to present relevant search results not limited to the input language.
So, how exactly does Google MUM affect multilingual search rankings? Let’s break it down.
Cross-language understanding
MUM understands that a person’s search intent isn’t always limited to the exact words they use—especially in a cross-language context. With its cross-language understanding capabilities, MUM can connect a question asked in one language with relevant information written in another. For example, suppose you search for “natural remedies for a cold” in English. In that case, MUM can surface a high-quality article written in Japanese discussing similar treatments—provided the content is relevant and trustworthy.
This allows users to get the best results across the web, not just from content written in their language. It’s more than just translation—it’s about understanding the search intent and matching it with information from multiple languages. For this reason, having high-quality automatic translation is crucial—it helps ensure your content stays accurate, natural, and competitive in various language markets, not just English.
Ranking improvements across languages
Before MUM, search results often depended on the strength of content in a single language or region. This meant that websites with high authority in one language could struggle to compete with others. MUM changes this by understanding and evaluating multilingual content more equally.
So, if your content in English is highly relevant and of good quality, it may still appear in searches made in other languages—as long as it meets the user’s needs. This opens up huge opportunities for website owners to reach a global audience without translating every piece of content.
Contextual relevance over exact match
One of MUM’s major shifts is its focus on meaning and context rather than exact keyword matches. This means Google is more concerned with whether content satisfies the overall search intent, not just whether it contains specific phrases or terms.
This is especially helpful in multilingual searches. For instance, someone searching for “natural ways to remove scars” might not use the same phrase in every language. However, MUM can still return relevant results because it understands the meaning behind the question, no matter how it’s phrased.
That’s why localizing each piece of content is important according to each region’s cultural and language context. This is where translation services with localization editing features are essential. For example, with the Linguise front-end live editor, you can adapt terminology tone and even collaborate with local translators directly.
Equal visibility for regional content
Previously, content from certain countries or regions may have been less visible in global search results—even if it was highly relevant. MUM helps solve this by giving more balanced visibility to quality local content, especially when it effectively answers global search queries.
For example, a blog post from a local health site in Indonesia discussing herbal plants could appear in search results for users in Germany or India—provided MUM evaluates it as a good match for the query. This gives regional content a greater opportunity to compete on an international stage.
Preparing your website for MUM
In the era of MUM, relying solely on conventional SEO strategies is no longer enough. That’s why preparing your website to stay competitive and relevant in multilingual search results is important. Here are a few key steps to take.
Focus on user intent, not just keywords
Previously, targeting keywords was the go-to trick for appearing in search results. However, with MUM, understanding user intent takes center stage. Instead of focusing on broad keywords like “tourist spots in Bali,” creating content that addresses specific user needs is more effective, such as “budget-friendly family vacations in Bali during the rainy season.”
Start by identifying users’ problems or questions and answering them naturally in your content. This approach increases your content’s relevance to Google and creates a more meaningful experience for readers.
Address topics from multiple perspectives
MUM values content that explores a topic from various angles. That means an article covering pros and cons, comparisons, and usage tips will outperform one focusing only on a single aspect.
For example, don’t just discuss technical specs if you’re writing about laptops for graphic design. Include user experiences, budget-based recommendations, and tips for beginners versus professionals. The more complete the perspective, the more valuable the article becomes in MUM’s eyes.
Use multimodal formats where possible
Since MUM can understand different input types, such as text and images, adding visual elements can boost your content’s effectiveness. Photos, infographics, or even short videos can help explain information more clearly and digestibly.
Include step-by-step images or a quick tutorial video if creating a DIY guide. Multimodal content like this is popular with users and helps search engines better understand your content’s context and relevance.
Create content with depth and completeness
Google now favours content that answers not only the “what” but also the “why” and “how.” Comprehensive content signals that your article could be the main answer to a user’s query.
To achieve this, cover the topic from start to finish. Include supporting data, real examples, expert quotes, and even FAQs if needed. Avoid shallow content that repeats general knowledge without offering real value.
Pay attention to the technical aspects of the website
Technical SEO still matters. Use hreflang tags to direct Google to the correct language version of your content. Ensure your site’s navigation is user-friendly and logically structured so search engines can crawl it easily. Use clear URL structures like yourwebsite.com/id/ for Indonesian content so that search engines know which content is targeted to which audience.
To support this, choose a translation service that ensures accurate language and supports the technical implementation required for multilingual SEO. For instance, Linguise automatic translation supports hreflang tag setup, subfolder-based URL structures, and overall multilingual SEO optimization.
Prioritize localization, not just literal translation
If you aim to reach a global audience, literal word-for-word translation won’t cut it. You need website localization—the process of adapting content to fit the target market’s culture, habits, and language style.
For example, humor, local references, or measurement units may need to be adjusted. Content that feels local earns more trust, resonates better with users, and is more effective for SEO because it meets the target market’s needs.
Ensure that multilingual content maintains its quality
Avoid having your foreign-language content come off as a confusing, quick translation. Even using an automatic translation tool, ensure the final result is high-quality—grammatically correct, stylistically consistent, and complete information.
Maintaining consistent quality across all languages is essential for building user trust and preserving SEO performance. Ideally, native speakers or professional editors should be involved in reviewing multilingual content before publication.
Conclusion
Google MUM has revolutionized how search engines work by deeply understanding search intent across languages and formats. This means relevant, comprehensive, and contextual multilingual content now has a greater chance of appearing in global search results—regardless of its original language.
A translation service that supports localization is essential to fully leverage MUM’s power. Linguise stands out as a top solution—with features like a live editor that lets you adjust language style directly on your website and support from professional translators to ensure natural and contextual translations. So, if you want your content to compete globally and stay relevant in multilingual search, don’t hesitate to start using Linguise.
