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Google Bert
One of the major technological advances of recent years, Google Bert is a key player in improving the understanding, processing and indexing of natural language information.
In this article, we demystify this artificial intelligence developed by Google and explain how it works and what it is used for, to understand why it has revolutionised the way we interact with information technology.
In October 2019, Google announced a major update to its search algorithm called. Google Bert.
Behind this strange name lies a cutting-edge technology based on artificial intelligence, aimed at improving the understanding of natural language for computer systems, particularly search engines.
Bert stands for "Bidirectional Encoder Representations from Transformers".
One of the major problems in computer science is understanding human language. Computers still have difficulty analysing, processing and understanding all or part of texts written or spoken in natural language, i.e. the language we use every day.
However, with the advent of more advanced and powerful language models, machines can now better understand the context and nuances of human language.
The rise of algorithms using NLP (Natural Language Processing)or Traitement Automatisé du Langage Naturel in French, has enabled a major step forward in the understanding and analysis of natural language by computers.
These algorithms are designed to identify and appropriately represent the words, phrases and other expressions likely to be used by a person when speaking naturally.
In order to take advantage of the latest and most advanced NLP techniques, Google Bert uses the notion of a "Transformer", which is a special type of neural architecture that enables the exchange of information between different parts of a sentence.
This innovative approach encourages bidirectional learning of word relationships.
Google Bert works on the principle ofdeep learningDeep learning involves training a computer model by providing it with very large quantities of data.
In this case, Google Bert has been trained on more than 3 billion words from a variety of sources that are representative of everyday language. Once the model is confident enough in its predictions, it is able to understand complex sentences and extract the relevant information.
One of the key features of Google Bert is that it takes into account the context while being two-way.
Unlike other models that analyse a text word by word and sequentially, Google Bert examines words as a whole and in relation to the other words in the sentence. This provides a better understanding of the interactions and relationships between the different elements of a text.
Thanks to its ability to accurately analyse the natural language used in queries, Google Bert has made it possible to significantly improve the relevance of the results displayed during a Google search. This makes it easier for users to find answers to their questions.
Searches involving long, ambiguous sentences or specific terms are now better handled by Google thanks to the intelligence of Google Bert.
In fact, this model can even correctly interpret idiomatic or metaphorical expressions, making the search engine even more relevant for users.
For marketing professionals, the introduction of Google Bert has also changed certain practices in terms of natural search engine optimisation (SEO), in particular by making the overuse of keywords less and less relevant and by encouraging priority to be given to high-quality, well-structured content that can be understood by the human reader as much as by the computer. indexing robot.
In short, Google Bert is the result of a major technological advance in natural language processing that has enabled the famous Google search engine to considerably improve the relevance of the results it delivers to users.
This innovation continues to evolve and be refined in order to provide an even better service to Internet users around the world.
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