Disregarding all the other environments it has grown into, Google’s cornerstone is still search. The company has become the go-to option for millions of users a day. It’s estimated that over 40,000 Google searches are conducted every second, which adds up to 3.5 billion per day, and 1.2 trillion per year. The company’s very name has become synonymous with Internet searches. Think about it: When is the last time someone told you to Bing it?
So how does one company handle a search volume equivalent to approximately half the population of the planet every day? Enter RankBrain: Google’s Machine Learning system that comprehends information, not by being given instructions through programming or being directed by a human, but by teaching itself how to complete a task.
What is Machine Learning?
A more complex version of what we traditionally define as Artificial Intelligence, Machine Learning is comprised of three major pieces:
- Model: This is defined as the system that is able to identify markers, make distinctions, and even predict results when not enough relevant information is provided. In one test, when a prediction was required to generate results, human engineers had a 70% success rate, while RankBrain was closer to 80%.
- Parameters: These are the various factors that the model uses in order to form decisions. With the parameters established, RankBrain is then able to take text and convert it into a mathematical algorithm to provide the ideal results for a search query. However, it’s what happens next that sets RankBrain apart from the rest.
- Learning: This part of the system is what allows RankBrain to compare predictions to outcome and actually make small changes to both the parameters and model it order to generate a more refined algorithm. It can then take the new model and parameters and conduct the search again, making changes every time until it’s able to not only provide the best results, but target similar verbiage and make more educated predictions.
Where Does RankBrain Fit in the Google Ecosystem?
Google implemented a new algorithm called Hummingbird in 2013. It’s comprised of a number of systems that all work in tandem with each other to provide the best results for any type of query put into a Google search bar. These systems include RankBrain, along with others designed to refine results in other ways, such as Panda, which targets “low-quality sites,” Penguin, which targets sites that violate Google’s Webmaster Guidelines, and Pigeon, which increases local search results.
Algorithmic approaches have become the new standard by which most major informational systems are now judged. Not only are search engines implementing them, but social media sites such as Facebook, Twitter and Instagram have also applied this new standard in order to better serve users. By better understanding what users want, companies are then better able to provide those results for them, thus making their product and services more desirable. Traditionally met with user backlash, algorithms are merely the new territory in which technology is headed, and over time, become the new normal for most users.
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Just like how Machine Learning is able to modify its approach, the professionals at Utah SEO Pros are able to develop a specific marketing and SEO plan that works the best for you and your company. Contact us here, or call 801-413-7734 today to find out more about how our team can help.
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