10.5.2 Large Language Models (LLMs): Difference between revisions
Created page with "=== 10.5.2 Large Language Models (LLMs) === Imagine a super-smart robot that has read almost every book, article, and piece of text ever written on the internet. It knows how words fit together, how sentences are formed, and even facts about the world. This robot can then use all that knowledge to create new text, answer questions, or even write stories! That's a bit like what a '''Large Language Model (LLM)''' is. LLMs are a special and very powerful type of Artificial..." |
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* '''IBM - What are Large Language Models (LLMs)?''': https://www.ibm.com/topics/large-language-models | * '''IBM - What are Large Language Models (LLMs)?''': https://www.ibm.com/topics/large-language-models | ||
* '''NVIDIA - What Is a Large Language Model?''': https://www.nvidia.com/en-us/glossary/large-language-models/ | * '''NVIDIA - What Is a Large Language Model?''': https://www.nvidia.com/en-us/glossary/large-language-models/ | ||
* '''Wikipedia - Large language model''': | * '''Wikipedia - Large language model''': https://en.wikipedia.org/wiki/Large_language_model | ||
Latest revision as of 16:03, 8 July 2025
10.5.2 Large Language Models (LLMs)
Imagine a super-smart robot that has read almost every book, article, and piece of text ever written on the internet. It knows how words fit together, how sentences are formed, and even facts about the world. This robot can then use all that knowledge to create new text, answer questions, or even write stories!
That's a bit like what a Large Language Model (LLM) is. LLMs are a special and very powerful type of Artificial Intelligence, specifically designed to understand and generate human-like text. They are a big part of the Natural Language Processing (NLP) field.
Why are they "Large"? They are called "Large" because they are trained on an enormous amount of text data – often trillions of words from books, articles, websites, and more. This training requires huge amounts of computing power.
How do LLMs work (in a simple way)? Think of it like this:
- Reading and Learning: The LLM "reads" a massive amount of text. It doesn't understand it like a human, but it learns patterns, grammar rules, facts, and even different writing styles from all that text. It learns which words usually follow other words.
- Predicting the Next Word: When you give an LLM a starting phrase (a "prompt"), its main job is to predict the most likely next word, then the next, and the next, until it forms a complete and sensible response. It's like a super-advanced auto-complete!
- Complex Patterns: Because they've seen so much text, they can predict words in very complex and creative ways, making it seem like they understand and can even "think."
What can LLMs do? LLMs can perform many amazing tasks involving text:
- Answer Questions: From simple facts to complex explanations.
- Write Stories, Poems, Scripts: They can be very creative!
- Summarize Long Texts: They can read a long article and give you the main points.
- Translate Languages: Convert text from English to Spanish, or vice versa.
- Write Different Kinds of Content: Like emails, essays, or even code.
- Chat and Converse: They can hold conversations that feel very natural.
Examples of LLMs you might have heard of:
- ChatGPT (from OpenAI)
- Gemini (from Google)
- Bard (from Google)
- Llama (from Meta)
LLMs are changing how we interact with computers and access information, making AI tools more accessible and powerful than ever before.
Bibliography:
- IBM - What are Large Language Models (LLMs)?: https://www.ibm.com/topics/large-language-models
- NVIDIA - What Is a Large Language Model?: https://www.nvidia.com/en-us/glossary/large-language-models/
- Wikipedia - Large language model: https://en.wikipedia.org/wiki/Large_language_model