It works the same way the chemical periodic table does. Instead of organizing elements by atomic number, the AI version groups models and techniques by what they do—language, vision, decision-making, content creation. The goal is to show how everything connects, so you can see the forest instead of just thousands of trees.
The big categories are pretty intuitive once you see them laid out. Natural language processing covers anything that works with text—translation, summarization, chatbots, that kind of thing. Computer vision handles images and video. Reinforcement learning is about systems that learn by trial and error, which is how AI mastered chess and Go. Generative AI is the flashy category everyone talks about now—models that create new images, text, or even music instead of just analyzing stuff that’s already there.
What’s useful about the table is seeing how these pieces fit together. You can look at a specific model and immediately understand where it sits in the bigger picture. It also shows what’s missing. If you’re building something and realize there’s a gap in what you’re using, the table makes that obvious.
Different people use it differently. Students usually start with one category and work their way through. Developers treat it like a reference when they’re picking tools for a project. Researchers look for the gaps—areas nobody’s working on yet. Teachers love it because it makes a blurry subject suddenly click for students.
The table changes constantly, which is probably the most honest thing about it. New categories keep appearing. A few years ago, nobody was talking about multimodal AI—systems that handle text and images together. Now it’s one of the hottest areas. The framework has to evolve with the field, or it becomes useless.
Honestly, the whole concept might need to shift eventually. Right now it organizes by what type of AI it is. But as models get more flexible and can do lots of different things at once, that neat categorization might start falling apart. The table works great for now, but the field it’s trying to capture doesn’t sit still.
If you’re trying to learn about AI or just want a way to explain what all these terms mean to someone who keeps seeing them in the news, the periodic table is genuinely helpful. It’s not perfect—nothing in a field this fast-moving can be—but it’s one of the better tools we’ve got for making sense of what’s becoming the most important technology of our time.
