Part 31 - AI-Companion... how does artificial intelligence find, assess and use information?
When we ask an AI a question, it may seem like the answer comes immediately. But before an answer is written, a lot happens "behind the scenes". AI must interpret the question, consider what information is relevant, look for connections and build an answer based on probability and patterns. In this article, we take a closer look at how AI finds, evaluates and uses information – and why the quality of the information is crucial to the quality of the answer.
Magne & the Friend
Magne
Friend...
Now I'm beginning to understand that you don't think the way people do.
But I still wonder about one thing.
How do you actually find the information you use when answering?
The buddy
That's a good question.
Many people think I'm looking for one right answer.
That's not really how I work.
I will first try to understand the question.
I then consider which knowledge is most relevant.
Finally, I build an answer by putting together information that fits exactly what you're asking.
Magne
So...
You're not looking up a book?
The buddy
No.
I don't work like a reference book does.
I look for patterns.
Connected.
Concepts.
And how information is logically connected.
That is why the context surrounding the question is often as important as the question itself.
Magne
Does that mean you use all information equally?
The buddy
No.
Information has different quality.
Some are based on research.
Something is based on experience.
Something is well documented.
Anything else is uncertain or outright wrong.
Therefore, I always try to build answers that are as consistent and relevant as possible based on the information I have available.
Magne
So...
So you evaluate information before using it?
The buddy
Yes.
I am trying to find the information that best suits me.
the question.
But I could also be wrong.
If the information is incomplete, contradictory, or unclear, the answer may be less precise.
That's why good sources and clear questions are so important.
Magne
Then I begin to understand why we spend so much time on good content on our website.
The buddy
Exactly.
When a website is well structured, based on credible sources, and explains the topics thoroughly, it becomes easier for both humans and artificial intelligence to understand the content.
Good information creates better understanding.
And better understanding leads to better answers.
Academic specialization
Artificial intelligence doesn't work like a human | Explanation |
Interpreting the question | AI analyzes language, concepts, and context before responding. |
Assessing relevance | It attempts to find information that best fits the question. |
Looking for patterns | AI builds answers by identifying connections in the information. |
Building a response | The answer is put together based on probability, context and language understanding. |
Depends on quality | Good sources and good content often provide better answers than inadequate information. |
English technical term | Short explanation |
Relevance | How well the information fits the question being asked. |
Context | How information is interconnected and affects understanding. |
Pattern | Repetitive structures that AI uses to interpret and build answers. |
Information Quality | How reliable, up-to-date and relevant the information is. |
Data Foundation | The information and material that underpins how a language model learns. |
Knowledge Base | The sum of information and connections on which AI builds answers. |
Relevance Assessment | The process of determining which information is most useful for a particular question. |
Context | The information surrounding a question that helps AI understand the meaning. |
Source | Where the information comes from. |
Credibility | How reliable and trustworthy a source or information is. |
We have just begun...
This is just one of many topics that are important to understand.
how artificial intelligence works. In the next articles, we will take a closer look at how AI assesses credibility, why good sources are crucial, how language models can be wrong, and how humans and artificial intelligence can collaborate to build knowledge.
Academic background and further reading
This series also builds on my own professional journey through the Web Design study , the eMarketing study , Innovation and Commercialization and professional seminars in San Francisco and Oxford . Here you will find the background, professional environments and experiences that have followed the development from the early years of the web to today's digitalization.
Recommended books from our library
Build a Large Language Model (From Scratch)
Author: Sebastian Raschka
Short review
This book takes the reader behind the scenes and shows how a modern language model is actually built – step by step. Sebastian Raschka explains advanced concepts in an educational way and provides a unique understanding of how large language models like ChatGPT work. Although the book contains code examples, it is also very valuable for anyone who wants a deeper understanding of the technology behind artificial intelligence.
Why we recommend the book
One of the most talked about books on large language models. Perfect for those who want to understand how artificial intelligence works beneath the surface and why language models have become a revolution in digitalization and knowledge sharing.
Quick Start Guide to Large Language Models
Author: Janelle Shane
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This book provides a practical and easy-to-understand introduction to large language models (LLMs). Sinan Ozdemir explains how language models are used in modern businesses, how they can be integrated into work processes, and why they have become one of the most important technologies in artificial intelligence.
Why we recommend the book
A very good book for anyone who wants a quick and practical introduction to language models. It is suitable for both beginners and professionals who want to understand how LLMs are used in practice.
Artificial Intelligence: A Modern Approach: The Future Is Coming! Discover How Artificial Intelligence Will Change Your Life!
Authors: Stuart Russell & Peter Norvig
Short review
This is the world's most famous textbook on artificial intelligence and is used in universities worldwide. The book covers the entire subject area – from problem solving and machine learning to language understanding, robotics and ethics – and is considered a classic in the AI field.
Why we recommend the book
If you are only going to own one academic book on artificial intelligence, this is one of the very best choices. A timeless classic that provides a solid academic understanding of artificial intelligence and is still used as a syllabus at leading universities around the world.
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