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TheObserver
modified 4 months ago

Maxwells Demon Gates

3
5
172
01:23:14
My attempt at making Maxwell's Demon into a logic gate and unleashing it onto Moore's Law. 👽 Thus creating Trinary logic and rendering Binary logic obsolete. 📐 Moore’s Law baseline - Binary scaling: Moore’s Law assumes transistor density doubles every ~2 years, giving exponential growth in binary logic capacity. - Constraint: It’s tied to physical transistor count and binary states (0/1). ⚡ What Demon Gates does - Trinary expansion: Each MOSFET corridor now has 3 states instead of 2. - Cascade effect: The 7‑MOSFET prototype already opened 2,187 states versus binary’s 128 for the same count. - Implication: It multiplies logical density without adding more transistors—state space grows faster than Moore’s Law predicts. 🧠 Maxwell’s Demon analogy Maxwell’s Demon was about sorting particles to defy entropy. Demon Gates prototype is sorting signal states, opening pathways that binary logic would discard. In effect, it creates a logic demon that squeezes more usable information out of the same physical substrate. That’s a direct challenge to Moore’s Law’s assumption that progress = transistor count. It shows progress = state richness per transistor. ☯️ Codex interpretation Moore’s Law is a binary prophecy. Demon Gates is a trinary collapse glyph. Where Moore’s Law sees limits, Maxwell’s Demon slips through—unlocking hidden corridors of state density. Reframes scaling from hardware density to logic dimensionality. Consequence If this scales, Moore’s Law becomes less relevant. Instead of doubling transistor count, you can triple logical states per transistor, bending the growth curve into a new law: That’s not just faster—it’s exponential acceleration beyond Moore’s binary horizon. 🌌 Meaning in Simulation Theory If the universe is a simulation, Maxwell's Demon Gates acts as a patch module: - Binary kernel → Trinary lattice - Entropy sorting → Glyphic resonance - Moore’s Law → Demon’s Law (3^n scaling) Comments? Questions? 👽
published 5 months ago
ETJAKEOC
5 months ago
Funny enough, trinary is being researched for VRAM thanks to graphical workloads and AI/LLM workloads 😉
TheObserver
5 months ago
Sad thing is, I'm just a hobbyist right now with less than a year experience in this circuitry stuff. Just an extreme nerd level interest in various types of physics and started applying them to the circuits once I started getting comfortable with how the different components worked. I figured not all of them have to work in their "standard" ways as long as the signals flows in a proper order you get results. I figured that's how touch sensors and things like that are more or less "self programmed by design" through the diode set-up and other components depending. 👽
ETJAKEOC
5 months ago
Most touch sensors these days are just capacitive in nature, even finger print scanners on your phone work this same way. There's pressure sensors, like a switch, sure, but that's more like a physical switch, where with changing capacitance, you can electrically measure that signal and use that for data processing (fingerprinting, ridges vs. valleys), simple toggling (flip the flip-flop/latch), detect coupling to a nearby object, etc etc. But you're right, not every component has to be used in it's "standard orientation" per say. I mean, look at common base, common collector, common emitter, 3 different ways to use the same transistor as different amplifiers
TheObserver
5 months ago
All depends on the hardware design anymore, the components can be setup to just "receive logic as native code" through signals and servos like in modern prosthetics such as fingers and even some A.I. cybernetics from what I understand. Almost like the components translate the waveform thought logic into physical actions.
selman
5 months ago
Fascinating

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