Overnight after release, a wide amount of speculation and unverified claims about the release of Google’s BERT update and what it meant for Google search was huge – as expected. It also currently only affects search results, but undoubtedly will move to AI-assisted voice search such as Google Assistant at some point in the future. How BERT affects Google search results in 2020īERT took effect in late October of 2019 and whilst only affecting 10% of searches, looks to shift the way prepositional searches are made for the future.Īlthough BERT only currently affects every 1 in 10 search results, this figure is staggering given there are over 3.5 billion Google searches made per day. This update is somewhat reminiscent of an old algorithm change made back in 2013, called Hummingbird which sought to improve conversational and human search, improving local search results as well as becoming the foundation of voice search. Sounds extremely complicated, but in practice, Google’s algorithm now utilizes pattern recognition to better understand how humans communicate so that it can return more relevant results for users. In conjunction, natural language processing (NLP) is the study of artificial intelligence for linguistics, where AI is being trained and accustomed to understanding the way humans communicate naturally. User behavior forms a huge moving part in the way Google enhances search engine results and provide relevance to the user’s search intent.Īfter all, users are the driving force for change and Google will always prioritize the needs of users rather than content writers and SEO’s. Neural networks have long existed before search engine implementation but were never considered a key part of improving the way search engines work. “With the latest advancements from our research team in the science of language understanding – made possible by machine learning – we’re making a significant improvement to how we understand queries”. Pandu Nayak, Google Search Vice President, had this to say about the advancement of human language processing and the way Google uses this to provide better search results. This network is designed for pattern recognition, being able to forecast and understand the occurrence of real-world applications such as recognising handwriting or the categorisation of images. The easier it is for Google to understand users, makes life easier for content writers to formulate more relevant content for user’s search queries.īERT is a neural network-based technique for natural language processing (NLP). In layman’s terms, it allows Google to understand the context and intent behind the user’s search query in a more efficient way. Understanding what BERT isīERT, standing for Bidirectional Encoder Representations from Transformers, is aimed at better understanding conversational and prepositional queries like ‘for’ and ‘to’ which have the ability to change the contextual meaning of a phrase. Introducing BERT, touted as ‘one of the biggest leaps forward in the history of Search’ and revolutionizing the way the world’s largest search engine understands linguistic interpretation. This means that SEO’s and blog writers need to consistently ensure they’re providing quality, user-focused content in order to show up for the most relevant results that users are actually searching for.
One thing is for certain, every time a major algorithm change occurs, it’s always in the interest of the user and Google being able to accurately provide the most relevant answers to a user’s search term. With BERT being Google’s largest algorithmic change for over five years, there was plenty of speculation and polarizing opinions on the update, but nine months on, the picture is much clearer.
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