Google has become so integral to our lives that we often chat with it directly.
As if speaking to a friend, users type in “how can I get to the supermarket” or “when will Spring begin?”. It is important to remember that Google is a collection of algorithms.
Google BERT is one of the algorithms that helps Google understand what users are searching for and provides the answers they need.
It’s true: bots aren’t people. But technology has advanced to the point that they understand our language. They can even recognize slang and other language expressions.
Google has created a new search algorithm to help it better understand the search intent of users and the content on web pages.
What is Google BERT?
Google BERT is a search engine algorithm that improves the understanding of human languages.
It is important to understand that people are spontaneous in their search terms, and they also express themselves in the content of the page. Google works hard to match the two.
The acronym BERT stands for bidirectional encoder representations from Transformers. Confusing? Confusing? Let’s clarify!
We’ll need to learn some technical terms to understand BERT.
BERT is an example of a neural network.
What is that?
Computer models based on the central nervous system of animals and neural networks can recognize and learn patterns. They are part and parcel of machine learning.
BERT is a neural network that can learn the different forms of human expression. The model is called a Transformer, and it uses Natural Language Processing (NLP), which understands relationships between words rather than viewing them one at a time.
BERT is an early training model for natural language processing. The model’s data is then trained on a text corpus, such as Wikipedia, and used to create various systems.
You can develop algorithms that analyze questions, answers, or sentiments, for instance.
Artificial intelligence is the key to all of this. Bots can do anything!
The algorithm, once programmed, continuously learns the human language as it processes the millions of data that it receives.
BERT is a powerful tool that can help you understand what users are searching for and how they intend to use the site.
When was BERT released?
In November 2018, Google released BERT, an open-source platform.
The pre-trained BERT codes and templates can be used to create a system quickly.
Google uses BERT as part of its search engine. Google’s biggest update since October 2019 was the adoption of BERT into its search algorithm.
Google already had models that could understand human language. But this new update is one of the biggest leaps in search history.
BERT was initially launched in the United States only in English. By December 2019, BERT had been extended to more than 70 languages. Search results around the globe have gained in quality.
What is NLP?
In our explanation of BERT, we mentioned that it is a model for natural language processing. Let me explain.
NLP is a branch of artificial intelligence that merges linguistics and human languages when examining the interactions between them. The goal is to bridge the gap between languages and help them communicate.
This type of system is not new. It has been around since Alan Turing‘s work in the 1950s.
In the 1980s, artificial intelligence adopted the NLP models. Since then, computers have been processing huge volumes of data. This has transformed the relationship between humans and machines.
Our verbal expressions are complex and varied, even if we don’t notice them.
Humans can sometimes barely understand one another because there are so many different languages, syntactic and semantic rules, slang and sayings, abbreviations, and everyday mistakes!
It is even harder for computers to understand because we use an unstructured language.
NLP uses a number of techniques to achieve this. These include removing irrelevant text, correcting typos, and reducing the words in their infinitive or radical form.
The content can then be segmented and categorized to understand the relationship between the different parts better. The system will then respond to the user in natural language.
The system works by having you say, “Alexa tell me the recipe of a chocolate cake.” and Amazon’s assistant will respond with the ingredients as well as the method of preparation.
The solution is currently used in several resources, such as interaction with chatbots, automatic translation of text, social media monitoring, and analysis of emotion.