Guidance makes untrainable networks trainable via representational similarity. Credit: arXiv (2024). DOI: 10.48550/arxiv.2410.20035 Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of archi