Is Google’s Search Engine Powered by Artificial Intelligence?
Have you ever wondered when you are searching for something, how did the search engine know what I am searching for this fast?
Google’s search engine isn’t just a line of logic and cookies, Google’s search algorithm incorporates machine learning, Artificial intelligence, and natural language processing to improve search every day. For search results to be accurate, Google uses an AI algorithm that can understand what the user is trying to say when they make the search query. This algorithm was launched by Google in October 2015, six years ago.
I will discuss in this article how AI got its start, the difference between AI, machine learning, and deep learning, how did AI affect Google’s search engine forever, and what google’s RankBrain and beyond is all about.
How did AI start?
The term AI cannot be defined in one way. Currently, AI is often used as a general term for artificial intelligence. in any case, AI is one of the most significant instruments that will usher us into a revolutionary era. Computers and the internet played the same key role a long time ago.
It all started in 1957, with a psychologist named Frank Rosenblatt. He created what was known as “Perceptron” at the time. Several brain neurons have been modeled by this digital neural network to simulate their functions. Frank Rosenblatt's goal was to have the network learn the differences between men and women over time or, at the very least, detect patterns that caused them to seem different over time. Almost a year later, media outlets hopped on the idea and there was a definite buzz. in the end, Frank Rosenblatt’s neural network technology failed miserably, and the concept was obsolete in 1969.
In the 1980s, Geoffrey Hinton, a computer scientist, proposed that the human brain was a network of neural connections and that it was extremely powerful. Since Frank Rosenblatt, this concept has become popular again. Geoffery Hinton and his team found that Frank Rosenblatt’s single-layer approach did not permit significant gains in capabilities because more layers were necessary for the network.
A neural network using multiple layers solved the problem that frank Rosenblatt had. nowadays, this type of network is referred to as a deep neural network. Deep neural networks were soon being used in other innovations, including self-driving cars, which will further reduce accidents by up to 90%. Artificial intelligence (AI) is transforming a wide range of industries, from identifying diabetes to space exploration to farming to predicting natural disasters, and much more.
AI, ML, and Deep Learning: what’s the difference?
Let’s talk about AI first. The goal of AI is to make machines smart enough to perform human tasks and make intelligent decisions for themselves. A machine learning algorithm, however, as a form of artificial intelligence, uses statistical methods to increase its accuracy with practice. And As neural networks imitate neurons in the brain, deep learning mimics the behavior of the human brain. But, there is a more important question, why do we need deep learning when there is machine learning? Because machine learning performance will be reduced due to its incapability to handle a larger amount of data. On the other hand, deep learning is more accurate than machine learning and it can handle a large amount of data without losing its performance. But machine learning also has an advantage over deep learning as it has a shorter training time than deep learning.
What is Google’s RankBrain algorithm?
A machine-learning system based on the Hummingbird search algorithm has brought Google to a new level. Google’s RankBrain algorithm was implemented in October 2015, marking the dawn of a new era for its search engine. The algorithm is used for unknown or unique words and predicts search results based on historical information, and optimizes search ranking. Furthermore, it can be used to better comprehend and handle search queries. The RankBrain algorithm takes into account a range of factors, such as user behavior on SERPs and time spent on the page.
A long-tail query is a reliable indicator of RankBrain’s effectiveness. In the past, Google ignored “without,” and long-tail queries were not considered. As an example, in the old days, a user who searched for “How to download Kali Linux without Windows” would see lots of results that allowed him to download Kali Linux with Windows, which the user did not want. When using RankBrain, the user receives a better response, such as knowing how to download Kali Linux on operating systems other than Windows.
At the time, Google’s senior research scientist, Greg Corrado, described RankBrain in a Bloomberg article:
“RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities — called vectors — that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.”
What is the effect of AI on Google’s search engine?
Before RankBrain, Google’s search algorithm was entirely hand-coded. However, now that RankBrain is in place, the algorithm is improving on its own. In one experiment, engineers from Google were assigned the task of picking the most relevant page for a specific search. RankBrain was also asked, but RankBrain came out on top by 10%.
As I mentioned earlier, RankBrain is likely to take into account various factors, such as the authority of backlinks, the freshness of the website’s content. Finally, it evaluates the effect that Google search results have on Google searches. Whenever the new algorithm is preferred by users, it remains. Otherwise, RankBrain reverts to the old algorithm.
RankBrain, one of several algorithms that enhance search results, identifies signals from relevant sources and assists the user in finding the most relevant results.
At the end of this article, artificial intelligence and the internet will have influenced our lives in many different ways. It’s important to remember that this will only be beneficial if it’s used correctly. The use of technology and artificial intelligence will likely rise in the near future. With the right use of them, we can be more efficient and productive. Most importantly, they can save lives, and that is what matters most.