Introduction To Google BERT: Bridging the Gap in Language Understanding
In recent years, the field of natural language processing (NLP) has made significant strides, with Google BERT (Bidirectional Encoder Representations from Transformers) emerging as a groundbreaking innovation. Introduced in 2018, BERT represents a pivotal shift in how machines understand and process human language. Unlike traditional models that read text sequentially—either left-to-right or right-to-left—BERT employs a bidirectional approach. This means it considers the full context of a word by looking at the words that come before and after it.
This nuanced understanding allows BERT to grasp the intricacies and subtleties of human language far better than its predecessors. For example, in sentences where context is crucial for meaning—such as "He went to the bank to fish" versus "He went to the bank to deposit money"—BERT can discern which 'bank' is being referred to by analyzing surrounding words comprehensively.