Artificial intelligence has grown powerful, but still fragile.
One noisy dataset, one unstable gradient—and the system collapses.
Biology shows us a different path.
Human neurons stay reliable for decades through homeostasis and repair. They don’t just learn; they maintain themselves.
In our latest work, we explored how this principle can reshape AI.
The BioLogicalNeuron layer introduces health monitoring and self-repair into neural networks—bringing us closer to systems that can adapt, survive, and learn continuously.
This could be a step towards:
🔹 AI that doesn’t “forget” in continual learning
🔹 Models that remain stable in noisy, real-world environments
🔹 Self-maintaining intelligence for robotics and healthcare
Read the full article here:
https://doi.org/10.1038/s41598-025-09114-8