What are Large Language Models?

What is it?

An **Artificial Intelligence (AI)** system refers to a machine’s ability to perform tasks that typically require human intelligence. A **Large Language Model (LLM)** is a specific type of AI trained to understand, generate, and manipulate human language. Unlike traditional software that follows rigid rules, an LLM operates on probability and patterns.

Think of an **LLM** as a highly sophisticated version of autocomplete. Imagine a librarian who has read every book, article, and piece of code ever written. When you ask this librarian a question, they do not look up a single answer in a specific book; instead, they calculate the most likely sequence of words that should follow your query based on everything they have ever read.

The big picture

In the modern technology stack, **LLMs** reside within the **Generative AI** layer. They are built using **Deep Learning** techniques and rely on the **Transformer Architecture**. Developers use these models to bridge the gap between structured computer data and unstructured human communication.

We use **LLMs** because they provide a reasoning engine for software. Instead of writing thousands of lines of code to handle every possible user input, a developer can send a prompt to a model like **GPT-4** or **Llama 3** to interpret the intent and provide a relevant response.

Core concepts

To understand how these models function, you must grasp several foundational components:

• **Tokens**: These are the basic units of text processing. A token can be a whole word, a part of a word, or even punctuation. The model converts text into numerical tokens to perform calculations.
• **Weights**: These represent the learned strengths of connections between neurons in the neural network. During training, the model adjusts billions of **Weights** to better predict the next token in a sequence.
• **Attention Mechanism**: This allows the model to focus on specific parts of the input text when generating an output. It helps the AI understand that in the sentence **The bank of the river**, the word **bank** refers to land, not a financial institution.
• **Temperature**: This is a configuration parameter used during inference. A low **Temperature** makes the model predictable and factual, while a high **Temperature** increases creativity and randomness.

Code snippet

Interacting with an **LLM** typically involves sending a request to an **API**. Below is a conceptual example using **Python** to generate a response from a model.

import openai

response = openai.ChatCompletion.create(
  model=**gpt-4**,
  messages=[
    {**role**: **system**, **content**: **You are a helpful assistant.**},
    {**role**: **user**, **content**: **Explain recursion.**}
  ],
  temperature=0.7
)

print(response.choices[0].message.content)

When to use it?

Choosing an **LLM** depends on the complexity of the task and the need for flexibility. They are ideal for:

• **Content Transformation**: Summarizing long documents, translating languages, or changing the tone of a piece of writing.
• **Code Generation**: Converting natural language requirements into functional code or debugging existing scripts.
• **Knowledge Retrieval**: Acting as an intelligent interface over large datasets when combined with **Retrieval-Augmented Generation (RAG)**.

However, **LLMs** are not always the best choice. For simple mathematical calculations or deterministic logic, traditional programming is more efficient and reliable. **LLMs** can suffer from **Hallucinations**, where they confidently state false information, making them risky for high-stakes factual lookups without verification layers.

Conclusion

Understanding **Artificial Intelligence** and **Large Language Models** is essential for navigating the current technological landscape. By leveraging **Tokens**, **Weights**, and **Attention**, these models simulate human-like understanding of text. While they offer immense power for automation and creativity, successful implementation requires a clear understanding of their probabilistic nature and the architectural components that drive them.