Guided learning lets “untrainable” neural networks realize their potential

MIT researchers developed a "guidance" method that enables previously "untrainable" neural networks to learn effectively by briefly aligning their internal representations with a guide network during early training. This approach, which transfers structural knowledge rather than just copying outputs, can revive failed network architectures and suggests that many ineffective networks simply suffer from poor starting positions rather than fundamental design flaws.