MUM’s the Word… New Google Technology Set to Transform Search
June 8th 2021 | By Emma Grant
If we ever needed proof that the world of SEO is so fast paced it can change in a heartbeat, here it is. Only in December were we singing the praises of Google BERT and how it had evolved into the DeepRank algorithm, setting the pace of search to high with its machine learning and natural language processing capabilities.
Now, just a few months later, there’s something new on the landscape. Something that’s set to transform search. In a VERY big way.
Google Multitask Unified Model (MUM) is a pioneering artificial intelligence-powered technology designed to answer complex questions that don’t have straight answers.
Google MUM is a thousand times more powerful than BERT. And BERT is pretty clever. So what’s behind it?
Google itself has said that it is constantly innovating to make the search engine work better for its users. One issue it has identified is that sometimes, when we’re looking for answers, we have to enter multiple queries and carry out lots of searches to collate the information we need.
Here’s the scenario Google uses to explain the issue…
You’ve hiked Mt. Adams. Next, you fancy tackling Mt. Fuji. You have plenty of questions you need answered, namely what you need to do differently this time to prepare.
Google can of course help you with this. But you’d need to do a few searches. The elevation of each mountain. The average temperature when you’re going. The difficulty of the hiking trails. The right gear to use, and more. So, a fair amount of time and searches later, you get your answer.
But wouldn’t it be dandy if you could speed this process up, and get all the information you need in one search, just like you would if you asked a mountaineering expert the same question?
We have lots of these types of queries in everyday life that need multiple steps with Google. In fact, the search engine says that people use eight separate searches on average for more complex queries.
There’s nothing out there at the moment that’s sophisticated enough to deliver direct, rich answers at the same sort of level that an expert would. And that’s where Google MUM comes in. This is Google getting closer to helping users with more complex search needs. The overall aim is to help us get the information we need, in fewer searches. And we all love a bit of time saving.
Google MUM: The solution for when there’s no straight answer
MUM is built on a Transformer architecture, just like BERT. But as we’ve said, it’s a thousand times more powerful.
Google MUM is engineered not just to understand language, but also generate it. It is trained across an impressive 75 different languages, and has the ability to multitask. This means it can develop a more comprehensive understanding of world knowledge and rich information than BERT and other previous models.
MUM is also multimodal. This means it comprehends information not just across text, but also images, with video and audio to follow in future developments.
Going back to the Mt. Fuji query. MUM would be able to understand, just like a mountaineering expert would, that you are comparing two mountains. It would therefore know to return elevation and trail information. It would also understand, in the context of hiking, that the word ‘prepare’ could mean things such as sourcing the right gear, and fitness training.
Also, because Google MUM has an in-depth knowledge of the world, it could provide useful insights, such as whilst both Mt. Adams and Mt Fuji have similar elevations, if you’re heading to Fuji in autumn, you may need waterproofs because it’s the rainy season. It could even bring up helpful offshoot topics to help you with deeper research, such as top rated gear, best fitness training exercises and the like, presenting you with helpful content from across the web.
Bringing down language barriers
When you’re researching global topics, it could be that the best information is not in your native language. This has traditionally been a considerable barrier to accessing information. But with MUM, there is the potential to bring down these barriers, because it has the power to transfer knowledge across languages. MUM has the ability to learn from sources that are outside your native language, so widening the scope of information that’s available to you.
Say for example there was some hugely useful information about Mt. Fuji, but it was in Japanese. Today, that information probably wouldn’t surface if you carried out your search in English. But MUM could transfer this knowledge into a format you can understand, and it could be rich information you wouldn’t otherwise have had access to.
So much more than just text search
Imagine if you could snap a shot of your hiking books and ask Google, “can I use these to hike Mt. Fuji?” Now that’s clever. And MUM is eventually make that possible with its multimodal functionality.
MUM can understand information from different formats such as websites and images, all at the same time. It could understand your hiking boots image and link it to your question, giving you a helpful yes or no, so you know whether you need to invest in a new pair of boots or not.
A gradual introduction to your new research assistant
Google is set to introduce MUM-powered features and enhancements to its products over the coming months and years. The technology is in its early days, but it’s still a hugely significant milestone towards a future where Google can fathom its way through all the different processes people use to naturally communicate and decipher information.
It’s for sure not going to be an overnight revelation. However, if MUM is as transformative as Google suggests it might be, search is 100 per cent going to evolve into more of a research function, rather than simply an engine that returns search results. In the future, Google could turn into your handy research assistant. How cool!
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