Understanding AI
Artificial intelligence can feel confusing, overwhelming, and sometimes even a little intimidating. Between the headlines, the hype, and the horror stories, it can be difficult to know what to believe.
This page is a companion to my newspaper series, Understanding AI. As each article is published, I'll add additional resources, explanations, links, and references here for readers who want to dig a little deeper.
You don't need to become an AI expert. A little understanding goes a long way.
Expanded Notes: Part 1 - What It Actually Is
If you haven't had a chance to read this week's newspaper column, you can read it here before continuing. The sections below expand on some of the concepts I introduced in the article and provide additional resources for readers who would like to learn more.
What Is a Large Language Model?
In this week's column, I mentioned that ChatGPT, and other generative AI systems like it, are powered by something called a Large Language Model, often shortened to LLM. That's a technical term that gets used a lot, but the basic idea is much simpler than it sounds. A Large Language Model is an AI system that has been trained on enormous amounts of written language so it can recognize patterns in how people communicate.
Rather than looking up an answer in a database, an LLM predicts what words are most likely to come next based on everything it learned during training. It repeats that process over and over, one word at a time, until it produces a complete response. Those predictions have become so accurate that the conversation often feels remarkably natural, even though the computer isn't thinking the way a person does.
How do generative AI predictions work?
If I write Peanut butter and _____, most people will predict jelly.
If I write Twinkle, twinkle, little _____, most people predict star.
If I write Roses are red, violets are _____, most people predict blue.
AI does something very similar. Instead of working from just a few familiar phrases, it has learned patterns from enormous amounts of written language.
The Major AI Assistants
ChatGPT (maker = OpenAI) is probably the AI assistant most people recognize because it received so much attention when it was released. It is far from the only one, however. Several companies now offer similar systems, each with its own strengths and features, which I will explore in more depth later in this series. Here are a few others, along with who makes them:
Claude (Anthropic)
Gemini (Google)
Copilot (Microsoft)
MetaAI (Meta)
Why AI Sounds Human
If you've interacted with generative AI, you may be wondering whether it is actually thinking. The answer is no, even though it often sounds like it is. Human conversation follows patterns, and after training on an enormous amount of written language, modern AI has become extremely good at recognizing those patterns and predicting what words should come next.
That prediction process is what makes AI seem so intelligent. It can produce thoughtful explanations, answer complicated questions, and even make jokes. At the same time, it can also make mistakes because predicting language is not the same thing as understanding the world. That's why AI can sometimes sound completely confident while still being completely wrong.
References and Further Reading
One statistic I mentioned in this week's column was that ChatGPT now has roughly 900 million weekly users worldwide. That figure comes from OpenAI's 2025 announcement. Here is where you can see more about this: https://techcrunch.com/2026/02/27/chatgpt-reaches-900m-weekly-active-users/
If you'd like to continue learning about artificial intelligence from the organizations building it and studying it, these are excellent places to start:
- OpenAI (Creator of ChatGPT)
https://openai.com - Anthropic (Creator of Claude)
https://www.anthropic.com - Google AI / Gemini
https://ai.google - Microsoft AI / Copilot
https://www.microsoft.com/ai - Stanford Human-Centered Artificial Intelligence (HAI)
https://hai.stanford.edu - MIT Technology Review – AI
https://www.technologyreview.com/topic/artificial-intelligence/