Advanced Chatbots with Deep Learning and Python - Generative Versus Retrieval Chatbots

The video tutorial discusses the differences between retrieval-based and generative chat bots. Retrieval-based chat bots use predefined responses and are limited in handling unseen cases, while generative chat bots leverage machine learning and deep learning to generate new insights and learn over time. Generative chat bots require extensive training and can handle grammatical errors. The tutorial highlights the advantages of deep learning in creating self-learning chat bots that can provide human-like responses.

What is a key characteristic of retrieval-based chat bots?

• They generate new insights.

• They use predefined responses.

• They are self-learning.

• They require extensive training.

How do generative chat bots differ from retrieval-based chat bots?

• They are unable to handle unseen cases.

• They use machine learning to create new insights.

• They do not generate new insights.

• They rely on predefined responses.

What advantage do generative chat bots have over time?

• They rely more on predefined responses.

• They become self-learning and improve.

• They require less data.

• They become less accurate.

What is a limitation of retrieval-based chat bots?

• They are easy to train.

• They cannot judge grammatical mistakes.

• They can handle unseen cases.

• They generate human-like responses.

What is required for training advanced generative chat bots?

• Minimal data and effort.

• Predefined responses.

• Extensive training and large datasets.

• Simple algorithms.