From Data to Understanding: Why AI Needs to Learn Like Animals

Most artificial intelligence (AI) systems today are built on massive datasets and statistical pattern recognition. While this approach has enabled remarkable achievements, it reveals a fundamental limitation: AI does not understand, it only calculates. By contrast, both humans and animals are capable of learning from very few examples, thanks to their ability to analyze, generalize, and transfer knowledge. This article explores the gap between statistical learning in AI and analytical learning in biological systems, and argues that the future of AI lies in combining both approaches.