Part 1: Journey of BERT

BERT is the state-of-the-art model introduced by Jacob Devlin in Google, which changed the course of finding the contextual meaning of words. Eventually, it was adopted by Google in their search engine in 2019 to improvise its searches. Contexts are the word embeddings computed that represent the meaning of the word based on sentences. Earlier word embedding representations like Word2Vec and GloVe represented the word without the contextual meaning. However, with the advancement of the language models from RNN to BERT, the computation to find the contextual embeddings became more efficient and better.