What is BERT

BERT (Bidirectional Encoder Representations from Transformers) is a natural language processing (NLP) model developed by Google in 2018. Its design aims to better understand the contextual relationships of language, capturing the interactions between words in a text through a bidirectional approach.

The key feature of BERT is its bidirectionality, which allows it to consider the context of words from both left and right sides simultaneously. This holistic understanding enables BERT to grasp the nuanced meanings of sentences more effectively than traditional unidirectional models.

BERT has significantly influenced both academia and industry, enhancing applications in question answering, sentiment analysis, and text classification. Many search engines and chatbots have begun implementing BERT to improve their natural language comprehension capabilities.

However, BERT does have limitations, such as high computational resource requirements and potentially slower processing speeds. Additionally, it may require further fine-tuning to achieve optimal performance in specific domain language understanding.