AI Basics in 10 Minutes: Easy Guide for Beginners

Artificial Intelligence (AI) might sound scary, but anyone can learn the basics. This short guide explains the main ideas in simple words, so you can understand tools like ChatGPT and Google Bard.

What Is AI?

AI is a big field of study. Inside AI there are smaller parts:

• Machine Learning (ML) – a part of AI that teaches computers to learn from data.
• Deep Learning – a part of Machine Learning (ML) that uses artificial neural networks.
• Large Language Models (LLMs) – a type of deep learning model used for language, like ChatGPT.

Machine Learning: Teaching Computers with Data

Machine learning means teaching a computer to learn from data so it can make predictions about new data it has not seen before.

Example: If you give a computer Nike sales data, it can learn from it and then predict how well a new Adidas shoe might sell.

Two Main Types of Machine Learning

1. Supervised learning: Uses labeled data (data with tags). Example: Predicting tips using bill amount and delivery type.
2. Unsupervised learning: Uses unlabeled data (data without tags). Example: Grouping employees by salary and years worked to find patterns.

Deep Learning: Inspired by the Brain

Deep learning uses artificial neural networks, which are layers of connected nodes inspired by the human brain. More layers often mean a more powerful model.

Deep learning allows semi-supervised learning: a small set of labeled data plus a large set of unlabeled data.

Example: A bank labels 5% of transactions as fraud or not fraud. The model learns from that 5% and applies the lessons to the other 95%.

Discriminative vs Generative Models

• Discriminative models: Learn to classify or label data (for example, cat or dog).
• Generative models (Generative AI): Learn patterns and create new data (for example, generate a new dog image).

Popular Generative AI Tools

• Text-to-Text: ChatGPT, Google Bard.
• Text-to-Image: MidJourney, DALL·E, Stable Diffusion.
• Text-to-Video: Imagen Video, CogVideo, Make-A-Video.
• Text-to-3D: Shap-E (for making 3D objects for games).
• Text-to-Task: Tools that perform tasks like summarizing your unread emails.

Large Language Models (LLMs)

Large Language Models (LLMs) are deep learning models trained on huge amounts of text.

• Pre-training: The model learns general language skills, like a dog learning basic commands.
• Fine-tuning: The model is trained further on specific data for a special job, like a guide dog.

Example: A hospital can fine-tune a general Large Language Model (LLM) with its own medical data to improve diagnoses.

Easy Tips for Learning AI

• Save this post for easy access to lesson.
• Try Google’s free beginner AI course and earn badges for each module.
• Practice with free AI tools to see how the ideas work in real life.

Why Learn AI Basics?

• You will use AI tools better and faster.
• You can avoid common myths and hype about AI.
• You will be ready for jobs and tasks that use AI.

Final Thoughts

AI is not only for experts. Remember the simple path:

AI → Machine Learning → Deep Learning → Generative AI and Large Language Models (LLMs).

If you want to learn more, try Google’s free beginner AI course and practice writing better prompts for tools like ChatGPT.