Summary
This proposal outlines a novel AI architecture that combines Predictive Coding with a 1-bit LLM design, aiming to eliminate backpropagation. It suggests using probabilistic neuron activation controlled by calculated chance, which could significantly boost efficiency and reduce memory usage, especially with specialized stochastic hardware. The approach envisions AI systems that iteratively refine outputs rather than expecting perfect results in a single attempt, making them suitable for non-deterministic tasks.
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