NAT.IO SERIES

Understanding Large Language Models

A comprehensive guide to large language models, from the fundamentals to advanced concepts. Explore how LLMs work, their capabilities, limitations, and practical applications.

Understanding Large Language Models

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Articles in this Series

Part 1 • 5 min read February 20, 2024

A Beginner's Guide to Understanding LLMs

Navigate the complex world of language models with this comprehensive guide. Learn the fundamentals of LLMs, how they work, and why they've become so important in modern AI applications.

Part 2 • 5 min read January 18, 2025

Understanding Tokens in Large Language Models

A detailed guide on what tokens are, how they work in LLMs, and why they matter for anyone using AI language models.

Part 3 • 28 min read January 17, 2025

Beyond Next-Word Prediction: How Modern LLMs Really Work

Modern LLMs go far beyond simple next-word prediction. Discover how transformers, multimodal inputs, and in-context learning redefine what AI can understand and generate.

Part 4 • 24 min read January 15, 2025

How LLMs Understand Context

Unravel the mystery of how language models track and maintain context in conversations. Learn about contextual embeddings, reference resolution, and other techniques that enable coherent and relevant responses.

Part 5 • 7 min read January 25, 2025

What Is Training in the Context of LLMs?

Discover the fascinating process behind how large language models learn from data, the challenges involved in training them, and why high-quality training data is becoming increasingly scarce.

Part 6 • 5 min read January 17, 2025

Sparse Attention: Teaching AI to Focus on What Matters

Explore how sparse attention techniques allow large language models to process longer inputs more efficiently by focusing only on the most relevant relationships between tokens.

Part 7 • 12 min read March 14, 2024

Scaling Laws in AI: Bigger Might Not Be Better

Exploring the principles behind AI scaling laws and why the future of AI might not just be about building bigger models, but smarter and more efficient ones.

Part 8 • 4 min read December 20, 2024

The AI Memory Problem: Why Bigger Inputs Aren't Always Better

Explore the challenges of working with limited context windows in large language models, and learn effective strategies for optimizing your inputs when facing memory constraints.

Part 9 • 5 min read January 17, 2024

LLM Hallucinations: What They Are, Why They Happen, and How to Address Them

A comprehensive guide to understanding hallucinations in large language models, including their causes, examples, and practical strategies to mitigate them.

Part 10 • 5 min read January 17, 2025

What Is LLM Bias and What Can We Do About It?

Explore the origins and impacts of bias in large language models, and learn about the strategies researchers use to create more fair and inclusive AI systems.

Part 11 • 38 min read January 16, 2025

How LLMs Process Long Texts

Explore the fascinating mechanisms that enable large language models to understand and process lengthy documents, from attention mechanisms to chunking strategies.

Part 12 • 6 min read January 17, 2025

Understanding Overfitting in LLMs: What It Is and How to Address It

Explore how overfitting affects large language models, why it happens, and the techniques used to prevent models from memorizing rather than generalizing from training data.

Part 13 • 7 min read January 11, 2025

Quadratic Complexity Explained: Why LLMs Slow Down

Understand the computational challenge that makes large language models struggle with longer inputs, and learn about the innovative solutions being developed to overcome this limitation.

Part 14 • 5 min read March 30, 2024

Multimodality in LLMs: Bridging Text, Images, and Beyond

Explore how multimodal LLMs integrate text, images, audio, and video, revolutionizing AI's ability to understand and interact with different types of data.

Part 15 • 5 min read April 2, 2024

Fine-Tuning LLMs: A Comprehensive Guide

Discover how fine-tuning transforms generic language models into specialized tools for specific domains, and learn the practical approaches to implement this powerful technique.

Part 16 • 8 min read April 5, 2024

Experts-Based vs. Dense LLM Models: Understanding the Differences

Explore the fundamental architectural differences between dense models like GPT-4 and experts-based models like Switch Transformer, and learn where each approach excels.

Part 17 • 7 min read January 19, 2025

Real-Time vs. Latency in LLMs: Striking the Balance

Explore the challenges of balancing real-time responsiveness and latency in large language models, and discover the techniques used to optimize LLM performance for time-sensitive applications.

Part 18 • 21 min read January 17, 2025

Learning Paradigms in LLMs: From Examples to Feedback

Explore the different approaches that define how large language models learn, from supervised learning to reinforcement learning from human feedback (RLHF), and understand how each method shapes AI behavior.

Part 19 • 7 min read April 10, 2024

Transformers Architecture Explained: The Engine Behind Modern LLMs

Dive into the revolutionary architecture that powers today's large language models, understanding how transformers process information and why they've become the foundation of modern AI.

Part 20 • 5 min read April 12, 2024

Memory-Enhanced Transformers: Giving AI a Notebook

Discover how memory-enhanced transformers are revolutionizing AI by giving language models a persistent 'notebook' to retain information over time, enabling more coherent long-form interactions.

Part 21 • 8 min read December 30, 2024

Reasoning Capabilities in LLMs: Promise, Limitations, and Future Directions

Explore how large language models attempt to reason, the surprising capabilities they've demonstrated, and the fundamental limitations that still separate them from human-like thinking.

Part 22 • 5 min read January 18, 2025

Big Questions for Dumb LLMs: Understanding Model Limitations

Explore why large language models struggle with complex questions, and learn practical strategies to help you achieve better results when asking sophisticated queries.

Part 23 • 26 min read March 20, 2025

The Illusion of Thinking in Large Language Models

Explore how large language models create a compelling illusion of thought through pattern matching and statistical prediction, despite lacking true understanding or consciousness.

Part 24 • 9 min read January 12, 2025

Open Source vs. Proprietary LLMs: What's the Difference?

Compare the advantages and limitations of open-source and proprietary LLMs, examining real-world examples like Llama, Mistral, and GPT-4 to understand which approach best fits different use cases.

Part 25 • 6 min read January 18, 2025

Reference Resolution in LLMs: How AI Connects the Dots

Discover how large language models track and resolve references in text, a crucial capability that enables more coherent conversations and a deeper understanding of complex documents.

Part 26 • 5 min read February 25, 2024

Understanding Attention Mechanisms in LLMs

Dive into how attention mechanisms enable LLMs to focus on relevant information in text. Learn about self-attention, multi-head attention, and how they contribute to the remarkable capabilities of modern language models.