AI Basics: A Simple Introduction to Artificial Intelligence and LLMs

Introduction

AI is all around us, but what exactly is it, and how does it work? From recommending the next movie to watch to answering our questions in real-time, AI is becoming a normal part of our lives. But many people still aren’t quite sure what AI really is or how it can be useful in everyday life.

In this article, we’ll break down AI in simple terms, explaining what it is, what it can do, and how it works. Then, we’ll dive into one of the most popular types of AI—Large Language Models (LLMs)—and explore how they’re used in work, learning, and daily life. By the end, you’ll have a better understanding of AI basics and see how this technology can help you get things done.

What is Artificial Intelligence?

Let’s start with a simple definition. Artificial Intelligence (AI) is a type of technology that enables machines to perform tasks that usually require human intelligence, like learning, problem-solving, and making decisions. The goal of AI is to create systems that can “think” and “learn” from data to carry out tasks more effectively.

Examples of AI in Everyday Life: AI is more common than you might think! When you ask Alexa to play a song or get a Netflix recommendation based on what you’ve watched before, you’re using AI. Smart home devices, virtual assistants, and even spam filters in your email are all powered by AI, which means they’re learning from past actions to help you in the present.

How AI Works at a Basic Level: At its core, AI is about data and patterns. Imagine you have a machine that’s given thousands of photos of cats and dogs. By examining patterns in these images, AI can eventually “learn” to recognize whether a new picture is of a cat or a dog. It doesn’t “know” what cats or dogs are, but it knows how to identify them based on patterns in the data it’s seen.

Types of AI You May Encounter

AI comes in different forms, each designed for specific tasks. Here are some of the key types you might encounter:

• Machine Learning (ML): This is a type of AI that enables machines to learn from data without needing to be explicitly programmed for every task. Instead of following a set of strict rules, ML algorithms “learn” from examples.

  • Example: When Netflix suggests movies, it’s using ML to learn from your previous picks. The more you watch, the better it gets at guessing what you might like.

• Deep Learning: This is a more advanced type of ML that uses layers of algorithms called neural networks, which are loosely inspired by the human brain. Deep learning allows AI to recognize complex patterns.

  • Example: Facial recognition on smartphones uses deep learning to accurately identify people’s faces. It learns from millions of images to detect even small differences between individuals.

• Natural Language Processing (NLP): NLP is a branch of AI focused on understanding and interacting with human language. It powers systems that can interpret spoken or written language.

  • Example: Translation apps, voice assistants like Siri, and even spam filters use NLP to understand and respond to language.

These types of AI form the backbone of many tools we use today, but one of the most popular types right now is called Large Language Models (LLMs)—let’s explore those next.

Introducing Large Language Models (LLMs)

What Are LLMs? Large Language Models (LLMs) are a type of AI specifically trained on vast amounts of text data to understand and generate human-like language. Think of LLMs as AI with a special knack for understanding words, sentences, and conversations.

How They’re Trained: LLMs are trained on massive amounts of text—think books, articles, websites, and more. By learning from these texts, they develop an understanding of grammar, context, and language patterns. They’re not “reading” or “understanding” in a human way, but they do get very good at predicting which words or phrases are likely to come next in a sentence.

Why They’re Popular: LLMs are popular because they’re incredibly versatile. They can generate text, answer questions, help write essays, and even chat with users in a way that feels surprisingly human. Popular examples include ChatGPT and Google Gemini, which are used for everything from customer support to content creation.

How LLMs Work at a High Level

Pattern Recognition and Prediction: LLMs don’t think or understand like we do. Instead, they rely on patterns they’ve learned. When you type a question into ChatGPT, for instance, it processes the text and predicts what would make the most logical response based on patterns it has learned from its training data.

• Example: If you ask ChatGPT, “What’s a good recipe for pasta?” it generates a response based on patterns in cooking texts it has analyzed. It doesn’t “know” pasta but can use its training data to put together a coherent answer.

Limitations of LLMs: While impressive, LLMs have limitations. They don’t “understand” in the human sense; they only recognize patterns in data. This can lead to mistakes or strange answers, especially if they’re asked about something they weren’t trained on or if they lack context. This specific type of mistake is known as a hallucination and you should be careful as sometimes they can be hard to identify.

• Example: If asked a question that has many possible answers, an LLM might give a confident response that’s incorrect. This is because it’s pulling from patterns, not true knowledge or reasoning. Don’t confuse it’s confidence with the accuracy of its answers.

Everyday Uses of LLMs

LLMs are flexible tools that can help with various tasks, both at work and at home:

• At Work: LLMs can draft emails, summarize reports, generate ideas for content, or help with customer support. They’re great for saving time and reducing repetitive tasks.

  • Example: An employee might use an LLM to create a quick outline for a presentation, turning hours of planning into minutes.

• At Home: LLMs can answer questions, generate meal plans, provide study tips, or even tell stories.

  • Example: You could ask ChatGPT for help planning a week’s worth of meals based on dietary preferences or get it to help with homework explanations.

• In Education: Students can use LLMs to break down complex subjects, get writing help, or understand study materials more easily.

  • Example: A student struggling with history can ask an LLM to summarize a topic, making it easier to grasp difficult information.

By subscribing to my newsletter you’ll get real world examples and tutorials on how you can make use of LLMs to get more done with less time. I’ll stay on top of quickly evolving AI landscape and you can focus on how to use it in your own life.

Conclusion

AI may sound complex, but it’s simply a technology that learns from data to perform tasks in a human-like way. From smart recommendations to virtual assistants, it’s already helping us in countless ways. Among the many types of AI, Large Language Models (LLMs) are particularly popular right now, thanks to their ability to generate text and assist in communication.

As AI continues to evolve, understanding these basics can empower you to make the most of it in your daily life. Why not try out an LLM like ChatGPT today? You might be surprised at just how helpful this technology can be!

Don’t find it useful? Stay tuned for tips and tricks to get started.