Tokens, Context and Attention - Quiz

Question 1

What is a token in a language model?

A unit of text processed by the language model A physical processor inside the computer A complete database table A type of neural network hardware

Question 2

Why is text converted into numerical representations?

Because neural networks operate on numerical values Because computers cannot store text Because tokens are always numbers Because numerical representations eliminate context

Question 3

What does context provide to a language model?

It provides surrounding information that helps determine meaning It permanently changes every model parameter It removes the need for training It guarantees that every answer is correct

Question 4

What is a context window?

The amount of information that can be processed together for an interaction The physical memory installed in a computer The number of neurons in the model The number of users using the AI system

Question 5

What is the basic idea behind attention?

It allows the model to represent relationships between different tokens It removes all tokens from the input It permanently stores every conversation It prevents the model from using context

Question 6

What is self-attention?

It allows tokens within the same sequence to interact with one another It means that the model only processes one token It permanently stores tokens in a database It removes the need for neural networks

Question 7

Why is attention important in Transformer architectures?

Attention helps Transformers process relationships between tokens Transformers do not use neural networks Attention is only used for storing files Attention guarantees perfect reasoning

Question 8

Does attention guarantee that an AI model will understand everything correctly?

No. Attention helps process relationships but does not guarantee perfect understanding or accuracy Yes. Attention guarantees that every answer is correct Yes. Attention prevents all model errors Yes. Attention replaces the training process