Original Reddit post

I’ve been building a cognitive architecture called Pibody that takes a fundamentally different approach from neural networks and LLMs. No training data, no gradient descent, no cloud inference. It runs entirely on a Raspberry Pi 5 and learns through embodied experience. The core idea: A thermal manifold; a hypersphere of nodes where knowledge is encoded as heat. Nodes compete for existence through an entropy-driven tax. Concepts that prove useful accumulate heat and survive. Useless ones go dormant. The system has three psychology nodes modeled on Freudian structure:

  • Identity — sustained by perception (vision frames feed it heat). It sees the world.
  • Ego — pays the cost of action. Every decision spends heat. It does.
  • Conscience — earns heat from successful outcomes, penalized by negative ones. It judges. Decisions emerge from a 7-step chain: Map → Plot → Weigh → Simulate → Decide → Execute → Evaluate. The exploration/exploitation balance is driven by the ratio of Identity heat to Ego heat — not a hyperparameter, but a consequence of the system’s lived experience. It runs on Bedrock Edition. If you know Minecraft botting, you know that’s unusual — virtually every bot framework targets Java Edition because it has open protocols and a massive community ecosystem. Bedrock is almost built to prevent botting. There’s no Mineflayer, no protocol injection, no public API. Pibody sidesteps all of that because it’s not a protocol bot — a custom CUDA vision transformer on a Windows PC captures the screen and sends thermal features to the Pi over WebSocket. The Pi never sees pixels, it sees heat patterns. It plays the game the same way a human does: by looking at the screen and pressing keys. It doesn’t even know it’s playing Bedrock. https://youtu.be/3Zntj75uHjc In the video you can see it playing Minecraft (navigating, mining, running from hostile mobs, dying and respawning), while simultaneously playing blackjack and running mazes in separate environments. It chooses which environment to engage based on accumulated success rates and heat efficiency. No model weights. No epochs. Just thermodynamics, math, and a Raspberry Pi. Thanks for checking the project out! submitted by /u/Exciting-Log-8170

Originally posted by u/Exciting-Log-8170 on r/ArtificialInteligence