DifferenceLearningMachineVsHuman

For artificial intelligence, learning usually means adjusting weights inside a neural network model for a better fit to a data set. For humans, learning means building a flexible internal model of the world, a graph of interconnected concepts, rules, facts, and experiences. These are not the same thing, and the differences explain why today's AI is powerful but still far from human intelligence.

• Source: 2025-09-16 Machine Learning vs Human Learning： They’re Not the Same

Machine learning systems depend on truly massive amounts of data while humans can learn from just a few examples.

• Source: 2025-09-16 Machine Learning vs Human Learning： They’re Not the Same

Machine learning systems don't understand what they're doing. They can't explain their reasoning, they fail when presented with data outside their training distribution, and they lack the abstraction and common sense that come naturally to people. They don't learn efficiently, requiring far more examples than any child would, and they don't learn continuously. Once trained, a machine learning model is frozen until retrained from scratch or fine-tuned.

• Source: 2025-09-16 Machine Learning vs Human Learning： They’re Not the Same