With technologies constantly developing, people usually ask themselves if there’s anything else left to be done in the future. The answer is yes: Google has been creating new ways to enhance and optimize its search results and engines, leading to the creation of the Google Multitask Unified Model.
What is the Multitask Unified Model?
The Multitask Unified Model is a technology that has been developed in order to answer complex questions that cannot simply be answered by search engines. This algorithm focuses on complex and long-tail search queries that need to be resolved by the user’s request at high efficiency.
Since this method processes search engines in a different way because it works with new artificial intelligence, MUM uses text as well as images and lots of languages. Audio files and even videos are taken into consideration to answer searches.
How Does MUM Work?
Introduced by Google around May 2021, the Multitask Unified Model is a powerful evolution 1000 times better than any search engine. It’s based on natural language processing, but it can provide and work with many new features.
Combining several technologies to make searches more semantic and context-based, Google is able to answer what a snipper or a SERP could not. In order to do so, some characteristics and features had to be added, such as:
- Multitask Unified Model was developed and coded in order to provide deep knowledge and easy understanding of a certain search.
- This resource was trained to understand and use more than 75 languages simultaneously, in addition to the language model it was previously trained on.
- MUM was also trained to understand any type of media files, in order to make the search more simple.
At the same time, certain Google statements allow for the deduction of other statements and methods the Google Multitask Unified Model uses:
- Google is known for using MUM to expand its semantic databases, such as the Knowledge Graph. This works towards the goal of completing a knowledge database online.
- Google MUM can also make searches more international, bringing all indexes and search instances worldwide to a similar level. This would ensure that the user experience is equally efficient for every country and language .
- MUM also provides exciting resources for SEO development since it accesses all media formats to collect data and information. This is done to understand and process it in a way that the search intention is understood for improved user experience in Google searches.
- Since search engines like Google have access to more than a trillion pieces of information based on text content, this can increase the entity index. This results in the generation of even more information, such as text, videos, and audio.
All of these characteristics make MUM a very powerful tool for search engines which can provide businesses and individuals with more tools to search and learn.
How MUM Updates Are Vital for Performance and User Orientation
Google focussed on only one language model (English) for many years which made the semantic interpretation almost obsolete and quite unnclusive. Most of the algorithms were trained based on this language, which is a disadvantage worldwide.
The newest updates allow the mechanism used for the English language to be used for all other countries and languages, creating a significant advantage and a new point of view. Although English is much easier to interpret using natural language processing, the first translations have already begun.
Knowledge panels translated to more complex languages like German starting around 2019, and have been being developed non-stop up until today. This is a significant improvement that allows resources to be used more efficiently, boosting performance and summarizing data quickly.
Ways Multitask Unified Model Will Change SEO
Since MUM is the next piece of the Internet puzzle, many things will change, making content relevance shift toward new objectives. This will undoubtedly impact Search Engine Optimization practices, which will need to think more about entities and topics concerning E-A-T instead of keywords.
Technical SEO needs to ensure that the crawling and indexing remains search-relevant, even with all these changes. But this new technology doesn’t create authority or expertise, meaning that there are only a few small levers where SEO can intervene in order to alter the ranking.
While these new levers do not guarantee a top position, content and links remain two of the most important factors for influence, along with co-occurrences. With MUM, text, video, and images are part of the trust and authority signals, which are the most important data source of information.
Factors that MUM Will Modify for SEO and Industries
Besides the structural changes that it will bring, the Google Multitask Unified Model is known to focus on three other major factors that will change:
- Content quality: Google’s algorithm traditionally ranked sites based on certain factors like how many backlinks it has or if it’s well written. MUM focuses heavily on content quality, especially in terms of the content’s intent. Rushed work and unnecessary sentences won’t help at all.
- Better user experience: Google’s algorithms are always focused on trying to provide the best user experience. MUM takes this to the next level by looking at a site’s overall layout, navigational structure, and functionality.
- Local intent: the algorithm always tries to rank sites based on how they are generated. This means that if a company is generating local traffic, it will be located higher. Local doesn’t necessarily mean on a street or city level, but nationally.
This trend will continue for a while, the ranking of sites based on where the servers are located and where content is being generated. For example, when MUM detects that a site is hosted in China, it will assume that the content is more relevant to Chinese users rather than people in the United States.
How SEO Can Adapt to Other Media Formats with MUM
It is well-known that Search Engine Optimization heavily focuses on text content. The Multitask Unified Model makes SERPs more diverse in terms of media formats, meaning that Google will understand images, audio, and videos with more context.
The classification of new searches such as images can be noticed when looking for images, for example where some images are displayed at the top and tagged with other similar pictures.
For SEO, this means that content for audio and videos will be needed in the near future. Such designs will need to be semantically meaningful, similar to any other SEO text work. Google will also improve and develop new techniques to implement the spoken content and audio of videos to rank them on YouTube.
Other semantic databases, such as the Knowledge Graph, benefit from these additional resources about data mining. Such a combination of high-performance and natural processing, and the large number of additional sources can also speed up the development of knowledge.
Relations Between MUM and E-A-T
There are other major challenges that Google needs to face besides data mining. One of those is validating information, which has been a long-running project with E-A-T (Expertise, authoritativeness, and trustworthiness).
Nowadays, there’s a possibility that you will get information from a source via the “about this result” box, which is still in beta but can be quite useful and has potential for the future.
The “About this result” box includes a description of publishers, trusted resources, websites like Wikipedia, and other information on whether a connection is secure. It’s possible to find out what the publisher writes about it themselves or what others say about the topic.
What Has Changed Through the Years?
Buying Freebase in 2010 allowed Google to acquire a semantic database, which, two years later, would become known as Knowledge Graph. Changes in algorithms and improvements have been done non-stop since then, with the introduction of Hummingbird in 2013, the E-A-T principles in 2014, and Knowledge Vault.
Artificial intelligence has also seen great improvements, such as the introduction of Rankbrain in 2015 and the natural language processor called BERT in 2016. Since then, most of the focus up until 2021 was on the development of the Google Multitask Unified Model, which is still being tested and updated today.
MUM will provide a new natural language processor, meaning that it will be the successor to BERT, which was known only for interpreting search queries and documents based on text.
Search engings are always developing new methods to improve user experience and modify how people can search on the web. One of these new methods is the Multitask Unified Model by Google, also known as MUM.
MUM can open up a new era of information since its main goal is to gather knowledge not only from text but also from images, audio, and videos. All of this will greatly increase the data and information available across the Internet, as well as changing methods of ranking, such as SEO.
Kala Agency can help meet all needs for lead generation and SEO methods that can help identify what the audience is looking for, how to optimize the site properly, and more. Using all these tips will undoubtedly position your company at the top of the searches, generating more profit and clicks.