Types of AI Models in Simple Terms
Under the hood, AI systems are built from different types of models. You don't need the math, but it helps to know the basic categories:
Traditional Machine Learning
Models trained to make predictions from data (for example, whether a payment is likely to be late). These are still widely used in finance, risk scoring, and forecasting.
Deep Learning
More complex models (often with many layers) that can recognize patterns in images, audio, and large datasets.
Large Language Models (LLMs)
Models trained on enormous amounts of text that can read, summarize, translate, and generate text. These are behind most of the AI chat tools you see today.
Vision and Multimodal Models
Models that can work with images and sometimes text together—useful for understanding screenshots, documents, and visual content.
Generative Models for Images and Media
Models that create images, design ideas, or help plan and support video and audio content.
These Models Are Constantly Improving
- More accurate and coherent
- Better at following instructions
- More capable in multiple languages
- Safer and more consistent for professional use
Key Takeaway
You don't need to understand how these models work technically. What matters is knowing they exist and that they're getting better every month—which means more opportunities for you.