How do BERT and GPT differ in their approaches to natural language processing?

What are the main differences between BERT and GPT?

BERT is designed for understanding context in text, while GPT is focused on generating coherent text.

Can you explain how BERT processes language?

BERT uses a bidirectional approach, analyzing text from both directions to grasp context better.

What about GPT's architecture?

GPT uses a unidirectional transformer architecture, predicting the next word based on previous words.

Which model is better for chatbots?

It depends on the use case; BERT excels in understanding queries, while GPT is better for generating responses.

Are there any hybrid models that use both?

Yes, some models combine BERT's understanding with GPT's generation capabilities for improved performance.