Guidance mechanism dramatically improves performance of neural network architectures previously considered untrainable or ineffective

https://techxplore.com/news/2025-12-previously-untrainable-neural-networks-effectively.html

"network encouraged to match internal representations of guide network during brief training... transfers structural knowledge, aligning way 2 networks organize information within each layer, even when guide network untrained, as already encode valuable architectural biases steering other networks toward effective learning... even few alignment steps before full training sufficient to confer lasting benefits... stabilizes training, eliminates failure modes, prevents overfitting... success less dependent on task-specific data"

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For visual AI systems, selecting the right blueprint may accelerate learning
https://www.eurekalert.org/news-releases/1108079

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https://techxplore.com/news/2025-12-chaos-neural-networks-biologically-plausible.html