Google’s new MUM (multitask unified model) algorithm is a true AI milestone when it comes to understanding hoards of information. It also has the world of search engine optimisation experts buzzing with how it will change the field and search in the years to come.
As usual, Google has not elaborated on what the new MUM technology comprises, but we do know that it is a state of the art multi-task learning innovation.
Essentially, Google MUM is a group of technologies that work closely together to resolve particularly complicated search queries entered into search engines. These answers cannot be simply answered with the usual short snippet or the well known blue links.
The main aim of MUM is to be able to return information to the search user by using multiple forms of content, including both images and text, across many different languages. Pandu Nayak, who writes for Google’s blog, states that the main issue for MUM to solve is “having to type out many queries and perform many searches to get the answer you need”.
Google has also stated that MUM is a thousand times more powerful than the current BERT algorithm.
Most search users enter pretty long form questions, which in term require long form question answering. This type of search is complex, and usually cannot be answered with a simple blue link or rich snippet. Instead, paragraphs of information are needed.
Google gives a great example of how this looks and would be answered with the MUM algorithm:
‘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’.
Search Engine Journal also gives an insightful example of a Long Form Question:
“What are the differences between bodies of water like lakes, rivers, and oceans?”
The above question requires a more in depth approach to answering, and as mentioned before, cannot be done with a simple snippet. Although Google does not directly mention Long Form Questions as a target, MUM itself seems to solve this.
The true power of MUM can be seen across it’s skillset.
It has been trained across 75 different languages. Referring back to the Mt. Fiji example, you’d have to traverse info in Japanese to find the answers you are looking for. With MUM, you can type in your search query, and be served the necessary information, already translated for you.
MUM is a multi-tasking powerhouse. Being able to deal with multiple tasks effectively, MUM allows for a more comprehensive understanding of information.
MUM can both ‘understand’ and ‘generate’ language. One can say that it doesn’t really understand language, instead it is a real example of Searle’s Chinese room argument.
As SEO experts know all too well, the flurry of algorithm updates that Google releases, and how we mitigate these will be no different to the MUM update. Something to take into account, though, is that this model reads and understands text better, with a more human-like feel. How do you prepare for an all new language model?
Google requires more insight into your content. Structured data is a great way to do this. Further assisting Google at this stage will get you the gold stars you require to be successful. This content needs to be well written, and truly embody a natural language flow. Stuffing your content with the same keyword breaks this, instead write something your audience will truly want to read. Ideally something niche or new, with good structure.
You won’t be seeing the effects of this new AI in search just yet, as it is still very much in the experimental phase. Google is currently doing internal pilots, however, they do state that it may assist in powering some search features in the months to come.
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