![]() ![]() With MUM’s powerful capabilities, Mark Sullivan, Google’s Search Liaison, predicts that search might begin to look more like research, and Google may act more like a research assistant on the user end. It could then point you to a blog with a list of recommended gear,” Nayak wrote. Fuji?’ MUM would understand the image and connect it with your question to let you know your boots would work just fine. Nayak elaborates: “Eventually, you might be able to take a photo of your hiking boots and ask, ‘can I use these to hike Mt. Since MUM is multimodal, it understands information simultaneously across different media formats. Fuji, you might see results like where to enjoy the best views of the mountain, onsen in the area, and popular souvenir shops - all information more commonly found when searching in Japanese,” Nayak wrote. So in the future, when you’re searching for information about visiting Mt. But MUM could transfer knowledge from sources across languages, and use those insights to find the most relevant results in your preferred language. Fuji written in Japanese today, you probably won’t find it if you don’t search in Japanese. “Say there’s really helpful information about Mt. He provides a very helpful example of how MUM does this. According to Nayak, MUM can learn from sources that aren’t written in the language users wrote their search in and help bring that information to them. This new algorithm can transfer knowledge across languages. MUM could also surface helpful subtopics for deeper exploration - like the top-rated gear or best training exercises - with pointers to helpful articles, videos, and images from across the web,” Nayak wrote further.Īnother breakthrough advantage of using MUM to power Google Search is its capacity to remove language barriers. Fuji so you might need a waterproof jacket. “Since MUM can surface insights based on its deep knowledge of the world, it could highlight that while both mountains are roughly the same elevation, fall is the rainy season on Mt. MUM’s deep knowledge can provide more insights and return more detailed, relevant answers. It could also understand that, in the context of hiking, to “prepare” could include things like fitness training as well as finding the right gear,” Nayak explained. Fuji: MUM could understand you’re comparing two mountains, so elevation and trail information may be relevant. To better understand how MUM works, Nayak wrote an example scenario on how MUM interprets complex queries. “And MUM is multimodal, so it understands information across text and images and, in the future, can expand to more modalities like video and audio,” Nayak further shared. “It’s trained across 75 different languages and many different tasks at once, allowing it to develop a more comprehensive understanding of information and world knowledge than previous models,” Nayak wrote.Īnother factor that makes MUM very robust is that it has the potential to understand multimedia information. According to Pandu Nayak, Google’s Vice President for Search, MUM is trained across 75 languages. What makes MUM more robust than BERT, its predecessor, is that it understands language and generates it. ![]() This latest algorithm has the potential to transform how Google Search returns results from complex queries that need multiple answers. A thousand more powerful than BERT, Google’s upcoming search algorithm, MUM, is a new AI milestone for understanding information. MUM or Multitask Unified Model will power specific search features in the coming months. SEO Consultant Qamar Zaman provides an explanation of how Google’s MUM, which is powered by AI, will change the search landscape. ![]()
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