Hyperconnected neural networks. Imitating biological neurons: OS, pruning, inhibition, and inter-batch connection

▤ Summary

This article describes a custom neural-network design inspired by biological neurons and focuses on hyperconnected layers, pruning, inhibition, and inter-batch connections. It explains how outputs are combined, normalized, pruned, and gated inside the model, with code snippets showing the forward pass and encoder logic. The piece also discusses how the Gardner component manages outputs, loss flow, and batch-aware behavior. Overall, it reads like a research-and-implementation note for building a new AI architecture rather than a business announcement.

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