AI Models Are Flunking Intelligence Tests That Humans Can Solve

Testing AI Intelligence the Same Way We Test Ourselves

For decades, game developers and computer scientists have used puzzles and games to push AI forward — much like how you might do a crossword puzzle or play chess to test your own thinking skills. These tests help researchers understand how advanced an AI system really is. The tradition actually goes back to 1959, when IBM computer scientist Arthur Samuel wrote about "machine learning" — the idea that computers can learn and improve on their own, rather than just following pre-programmed instructions.

The Surprising Problem

Here's where it gets interesting: despite all the recent hype about how powerful AI has become, these systems are actually flunking many intelligence tests that regular people can solve without much trouble. Researchers created a kind of obstacle course of puzzles to see how well today's AI models perform. A "model" is essentially a trained AI system designed to solve problems or answer questions.

Why This Matters for Everyone

This reveals something important: AI might be good at specific tasks — like writing emails or finding information — but it doesn't necessarily think the way humans do. Just because a system can handle one job well doesn't mean it's truly intelligent across the board. Understanding these gaps helps developers build better, more reliable AI tools. For you as a user, it means AI has real limits that developers are still working to overcome.