I’ve been working on an experimental AGI-like logic simulator using nothing but *pen, paper, and a structured table system*.

*What it does*: - Simulates logical relationships between concepts using a grid-based structure - Works like a hand-written neural net or rule-based system - Learns from user feedback (like reinforcement learning) by adjusting weights - Automatically generates reasoning paths and simulates calculation flows

*Why it’s interesting*: - No API, no GPU, no software required - Every reasoning step is transparent and explainable - You can literally *see the logic flow on paper*, like tracing neurons

*Use cases*: - Engineering problem solving (like mechanics or materials) - Simulating how humans think in step-by-step logic - Could evolve into a domain-specific expert system or educational simulator

Here’s a photo of the current prototype:

-> https://i.postimg.cc/4y0hB5rc/image.png

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I’m curious if anyone here has tried similar “analog AGI” experiments — or sees potential use cases I’ve missed.

Happy to answer any questions or share more detail. Thanks!