Whether you’re a creator, an IT professional, or a school teacher, search engines are undeniably an integral part of your everyday life. From settling an argument over a fact to finding the nearest restaurant, we call upon search engines to save the day.
The technology behind these search engines has evolved greatly. It is no longer simply matching keywords in the query to those in the content. Search engines now have a complex understanding of the user intent behind the query.
In this article, we will find out the growing role of AI in making search engines smarter than ever before.
The Keyword Era of Search Engines
Let’s go back to the beginning. The key to understanding the role of AI in today’s search engines lies in the reasons for the failure of its predecessors. The technology behind the early days of search engines was quite basic. Yahoo! and AltaVista would simply match the keywords typed in the search query.
There were some clear limitations to this approach. More often than not, the search results would have little to no relevance to the query. These engines could not understand natural language. That was a major reason for the poor relevance and failure to understand user intent.
Not only were they slow to adapt to the rapid changes in the online world, but they were also limited in terms of the number of sites they could index.
The Next Stage – Machine Learning & Semantics
The introduction of Google’s Hummingbird and RankBrain algorithm updates changed search engines forever. Understanding the meaning of the search query was the focus of this update. If you were to search ‘best pubs near me’, the search engine returns local pubs even if the website doesn’t include the keyword ‘pub’. Search engines had now moved on from matching keywords and, with the help of machine learning and semantic search, could deliver more accurate and relevant results.
The Hummingbird update in 2013 focused on intent and also incorporated Natural Language Processing. This was a big game-changer. Hummingbird can be thought of as the memory, and RankBrain being the thinking.
The Role of AI in Enhancing Search
As mentioned earlier, search engines have now incorporated NLP or natural language processing, to understand the queries better. Google does this with the help of BERT, a neural network-based language model.
One of the highlights of this model is contextual understanding. Not only can the search engine understand the meaning of each word in the query, but even the context of the whole query by taking into account the whole sentence.
With the help of AI, the search engine can now understand long-tail searches, conversational queries, and even complex questions. This not only enhances your search but also helps businesses create a better online presence.
Websites can now improve their search rankings without compromising on user experience. For example, new sweepstake casino sites can focus on offering a more engaging experience for their players instead of creating content for the search engines. They would appear in search results even for the keywords they haven’t used on their webpages.
The key to success for these casino sites is offering more engaging games and a lucrative model of sweepstakes coins. They have more important tasks to accomplish with their offerings than simply writing content for the search engines.
Personalized Search Results
With the help of AI, search results can be personalized using search history and other user data. Search engines can also predict the query more accurately based on your browsing history.
Personalization is preferred by the majority of users. It takes your search experience to a whole new level. If you’re someone who often visits a particular website, say, for example, an online casino, then the search engine would understand what results are more relevant to you when searching for a query related to casino sites.
What does the Future of AI in Search Look Like?
Search is no longer limited to just typing in the query. Google search supports voice as well as image search. Voice search, in particular, has become mainstream and is probably the future of search.
The next generation of search engines will be more intuitive. They will incorporate the natural human interactions, such as voice and gestures. AI chatbots are also changing how we interact with search engines. Google’s Gemini is a great example of AI-powered search making our everyday lives better.
