Queries that are simple for a human mind to comprehend may find themselves at a completely different level of machine comprehension. For example, if one types a question into Google on where to buy and sell fruits online, it would probably direct you to websites with different fruits and vegetables for seasons. Many times, Google AI missed the subtlety of the queries by humans.
What Google AI Is
Google AI is a tool that allows anyone, including data geeks, researchers, scientists, and data journalists to find information stored in datasets across millions of repositories on the web. The speech recognition AI of Google Assistant uses the deep neural network to understand better the written textual questions and spoken commands. It could do and learn everything – about users’ preferences and habits and continuously working on keeping them hooked to the internet.
Coming back to the accuracy of Google AI, Google is banking on MUM, which is its new AI language model. Google is hoping to improve its search results. However, some deviations in answers by Google were solved in 2019 when Google integrated an ML model BERT into its search features.
Search engines were not sophisticated enough to answer in a way a human expert could do. The new Google technology MUM or Multitask Unified Model is getting closer to solving complex needs.
The AI language systems, known as large language models, BERT helped it resolve the nuances of questions put to Google by breaking down the components and understanding their syntactic roles. In 2021 Google has updated its search tool using MUM as a successor to BERT.
How does the new AI help when there is no simple answer?
The new AI, MUM, is 1000 times more powerful than BERT, and it has the potential to solve complex tasks. It uses a framework that is text to text and also understands languages but generates it too. Language can be a major barrier to access information. MUM is trained in 75 languages and has the ability to multitask simultaneously. This allows them to break down the boundaries and transfer knowledge between languages, thus developing a better and complete understanding of information and global knowledge.
Because of its Multimodal nature, it can understand images and texts and, in the future, expand to audios and videos as well. For example, if one were to use an image of hiking boots and ask whether it can be used to hike Mount Fuji, MUM would understand the image and then connect it with the query. It would then be in a position to answer if the boots would work fine when hiking. It will also direct to other content that recommends different kinds of boots and hiking gear.
Final thoughts
The new advanced Google help is leaping forward to make information more accurate and accessible with responsibility. Its advanced AI makes sure that every improvement to its search engine is evaluated rigorously, so that information provided to users is relevant and helpful.
