Whenever we talk to people about our work on Google Search, we are also often asked, “is there any particular task missed to finish?” Our answer is “Yes!” emphatically. There are endless challenges that we often try to fix on Google Search for better results. Today we are going to discuss how we address one many of us can identify with: the need to type out those multiple queries and act several searches to get a proper answer that you are looking for.
Google has launched the latest technology called MUM or Google Multitasks Unified Model for answering all different complex questions that have not any straight answers. This new Google MUM update is basically a comprised version of various innovations. In the HyperGrid Transformers; Google’s research paper it indicated- Towards A Single Model for Multiple Tasks. This describes that a new art state in multi-task learning which might become a part of MUM.
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Example to Understand:
You can take a scenario, where you have hiked Mt.Denali. Now if you are willing to Mt. Everest, and want to know what you need to do to get ready. Then we can say that today Google can give you support, but it might take multiple thoughtfully considered searches. You need to go for a search for the elevation of all mountains, the overall temperature on those spots, difficulties in hiking the trails, appropriate gear to use, and all. After doing this wide number of searches, you could have your exact answer to what you want to know.
On the other hand, if you go to a mountaineer, you just need to ask one question- “what should I do differently to prepare?” You will surely get an answer which takes into account the nuances of your task on one hand and will guide you through various considerable things.
However, today’s google search engines are not that much sophisticated to answer like an expert. But with the arrival of Multitasks Unified Model or Google MUM update, helps us to get closer to those tricky and open-ended questions. So shortly, you will require a little search to know your answers.
Importance of MUM:
MUM has the potential to transform how Google supports you with complicated tasks. What Google MUM uses is the T5 text-to-text framework and is almost 1,000 times better and effective than BERT. MUM not only understands the language but also can generate it. It offers 75 numerous languages and could perform many other works simultaneously. It permitting to build a more significant understanding of information and the entire world’s knowledge than the older one. Moreover, MUM is a multimodal engine, so it can easily identify information around images, text, and in the upcoming years, it could be enhanced to more modalities including audio and video.
You could ask the question about hiking Mt. Everest: MUM can easily know you are comparing two different mountains, so trail and elevation information might be relevant. It could also understand that, in the hiking context, to “prepare” might include various things like finding appropriate gear and fitness training.
As MUM could surface insights depends upon its deep knowledge about the world, it can highlight that when both these mountains have roughly 8,000 ft gaps, fall is the rainy season on Mt. Denali, so you might require a waterproof jacket to wear there. Google MUM update also surface helpful subtopics to give you a deeper exploration- like the best training exercises or like the top-rated gear.
Eliminating Language Barriers:
Language is so far a huge obstacle to get information properly. What Google MUM does is break down those interrupted barriers by transferring knowledge around different languages. It could just learn from various sources that are not written in the language that you wrote in your search and support you in bringing the required information to you.
Say there is really essential information about Mt. Everest in Japanese; today, you might not find it if you have not to search it in Japanese. However, MUM can shift knowledge from one source to another source across numerous languages, and utilize those vital insights to get the most relevant outcomes in your preferred language. So in the upcoming future, when you are looking for accumulating information about visiting Mt. Everest, you might observe a result like where to enjoy the best mountain views, famous souvenir shops, and onsen in the area- all information is commonly discovered while searching in Japanese.
Understanding Information Across Types:
MUM is multimodal, which indicates it could understand information from various formats including pictures, webpages, and simultaneously more. In due course, you could be able to take a photograph of your hiking shoes and can ask to Google MUM update, “can I use these to hike Mt. Everest?” MUM will easily understand the photo and connect it with your question to allow your shoes would work well. It could thereafter take you to a blog where you will have the knowledge list of recommended gear