Introduction to LLM

This page provides an easy-to-understand guide on LLMs (Large Language Models) from basics to applications for AI enthusiasts.


Total of 5 articles available. | Currently on page 1 of 1.

1.3 Entropy and Information: Quantifying Uncertainty

A clear, intuitive exploration of entropy, information, and uncertainty in Large Language Models. Learn how information theory shapes next-token prediction, why entropy matters for creativity and coherence, and how cross-entropy connects probability to learning. This section concludes Chapter 1 and prepares readers for the conceptual foundations in Chapter 2.

2025-09-06

4.4 How LLMs Write Code: The Rise of AI-Powered Programming Assistants

Explore how large language models (LLMs) generate and complete code from natural-language prompts, and what it means for the future of software development.

2024-09-27

4.3 LLMs in Translation and Summarization: Enhancing Multilingual Communication

Learn how Large Language Models (LLMs) leverage Transformer architectures for accurate translation and summarization, improving efficiency in business, media, and education.

2024-09-18

2.3 Key LLM Models: BERT, GPT, and T5 Explained

Discover the main differences between BERT, GPT, and T5 in the realm of Large Language Models (LLMs). Learn about their unique features, applications, and how they contribute to various NLP tasks.

2024-09-10

1.1 Understanding Large Language Models (LLMs): Definition, Training, and Scalability Explained

Explore the fundamentals of Large Language Models (LLMs), including their structure, training techniques like pre-training and fine-tuning, and the importance of scalability. Discover how LLMs like GPT and BERT work to perform NLP tasks like text generation and translation.

2024-09-03