Question 1

How are chatbots like ChatGPT different from typical neural networks?

Accepted Answer

They are based on large language models trained on a vast amount of information.

Answer

They are based on specific tasks like recognizing faces.

Answer

They are trained on only one type of information.

Answer

They are based on random probabilities.

Answer

They are trained on a small dataset.

Question 2

How does a large language model predict the text that a user wants it to produce?

Accepted Answer

Using probabilities based on previous text it has been trained on.

Answer

By randomly selecting words to produce text.

Answer

By analyzing the user's writing style.

Answer

By using a simple table of probabilities.

Answer

By memorizing specific text sequences.

Question 3

What is the downside of an AI only considering a single letter to predict the next one?

Accepted Answer

Not enough context is considered, leading to unhelpful output.

Answer

It limits the types of texts that can be generated.

Answer

It slows down the generation of new text.

Answer

It increases the accuracy of predictions.

Answer

It ensures the text is always correct.

Question 4

What additional information does a system like ChatGPT consider compared to just training on Shakespeare's plays?

Accepted Answer

All the information it can find on the Internet.

Answer

Information from social media platforms.

Answer

Information from a specific website.

Answer

Information from a single author.

Answer

Information from books only.

Question 5

What is one important addition to a system of large complexity like ChatGPT to ensure reasonable results?

Accepted Answer

Human tuning.

Answer

User feedback only.

Answer

Real-time monitoring.

Answer

Random selection of results.

Answer

Automatic adjustments.

Question 6

What technology is already using large language models to create apps, websites, movies, and video games?

Accepted Answer

AI.

Answer

Virtual Reality.

Answer

Augmented Reality.

Answer

Blockchain.

Answer

Quantum Computing.

Question 7

What does a neural network do in the context of large language models?

Accepted Answer

It learns patterns from sequences of text to predict the next letter.

Answer

It randomly generates text sequences.

Answer

It only focuses on the beginning of sentences.

Answer

It predicts full sentences without context.

Answer

It memorizes entire texts.

Related quizzes