What are the applications of BERT in natural language processing?

What are the applications of BERT in natural language processing?

BERT, or Bidirectional Encoder Representations from Transformers, is widely used for tasks like sentiment analysis, question answering, and language translation.

Can you explain how BERT improves sentiment analysis?

BERT improves sentiment analysis by understanding the context of words in a sentence, allowing it to capture nuances in sentiment more effectively.

What makes BERT different from previous models?

BERT's bidirectional training allows it to consider the context from both sides of a word, unlike previous models that read text sequentially.

Are there any limitations to using BERT?

Yes, BERT can be resource-intensive and may require significant computational power, which can be a limitation for some applications.

What are some real-world examples of BERT in use?

Real-world examples include Google Search enhancements, chatbots for customer service, and tools for automated content moderation.