AI and the World's Hard Problems · Life sciences · MIT · 2026-10-13
How artificial neural networks build their own learning machinery
A group of randomly connected units can reorganize into an effective information-processing network when given simple rules for when and how connections should change. The MIT team argues that an artificial network's ability to organize itself, without a developer's guidance, is a key test of biological plausibility. The researchers caution that such networks may not offer much insight into biological learning.