LLMs Unlocked: Exploring Large Language Models Quiz

1. Understanding LLM Basics

   What does the term 'Large Language Model' (LLM) refer to in the context of artificial intelligence?

   1. A computer program for storing large files
   2. A deep learning model trained on vast amounts of text data
   3. A programming language for mathematical calculations
   4. A database system for managing images
   5. An operating system for mobile devices

2. Architecture Difference

   Which of the following best describes a key difference between transformers and earlier recurrent neural networks (RNNs)?

   1. Transformers process entire sequences in parallel, unlike RNNs that process sequentially
   2. RNNs can train on larger datasets than transformers
   3. Transformers use only one layer, while RNNs use multiple layers
   4. RNNs are faster than transformers on graphics processing units (GPUs)
   5. Transformers require handwritten grammar rules

3. Word Representation in LLMs

   In large language models, which technique replaced simple numerical tables to represent words and capture relationships such as similar meanings?

   1. Word embeddings using multi-dimensional vectors
   2. Shuffle arrays
   3. One-hot decoing
   4. Random tokenization
   5. Numbered word lists

4. Applications of LLMs

   Which of the following is a practical application of large language models, as mentioned in the context?

   1. Sorting digital photos by color
   2. Generating original copy and answering questions from knowledge bases
   3. Compressing video files
   4. Monitoring hardware temperature
   5. Designing circuit boards

5. Key Importance of LLMs

   Why are large language models considered important in modern AI, based on the context provided?

   1. They can only be used for translating languages
   2. They allow one model to perform a variety of tasks using human language
   3. They require less electricity than other models
   4. They are primarily used to play music
   5. They need no input data to work