Artificial Intelligence and Google: AI applications in Search
It was 2015 when Google announced the introduction of the first artificial intelligence system applied to Search, namely RankBrain, and in recent years the technological work has continued, mainly to improve the understanding of the language and, Consequently, provide in SERP search results closer to the real needs of people, as we told a few days ago presenting the latest developments of LaMDA. Now it is Google that takes stock of the state of this evolution and share information on how AI applied to Research “translates into relevant results”, and therefore where and how such systems are really used.
Artificial Intelligence in Google Search
It is directly Pandu Nayak, Google Fellow and Vice President of Search, to describe in an in-depth article on The Keyword “how AI provides excellent search results”helping Google understand what the user is looking for by improving their understanding of the language.
Before 2015 and before having advanced artificial intelligence, Google’s systems “simply looked for the corresponding words”, recalls Nayak, who in particular mentions the case of misspelling: looking for pziza “unless there was a page with that particular spelling error, we probably would have to repeat the search with the correct spelling to find the information we were interested in”. Over time, however, Google has learned to encode algorithms to find classes of models, such as popular spelling errors or potential typing errors from nearby keys and now, with advanced machine learning, its systems can recognize in a more intuitive way if a word does not seem correct and suggest a possible correction.
These AI enhancements to research systems allow you to constantly refine the understanding of what the user is looking for, a determining factor in light of the fact that “the world and people’s curiosities are constantly evolving”, with “15% of the searches we see every day that are completely new”.
The real applications of the AI systems
During the same days an article by Barry Schwartz dedicated to this topic also appeared, reporting the information provided by the public liaison Danny Sullivan, which reveals that – in summary – there are four technologies currently in operation in the Research system.
To be precise, RankBrain, neural matching, and BERT are used in Google’s ranking system in many, if not most, queries and try to understand the language of the query and the content it is classifying. And then there is MUM, which for now is not used for class