The Thermodynamic Neural Grid
Title: Computing is Physical: Visualizing Entropy and Data Flux Concept: Dissipative Systems & Landauer’s Principle
Description: We often think of data as abstract numbers, but in reality, every bit of information is a physical state that requires energy to maintain.
In this simulation, we model a "Neural Grid" not as a logical processor, but as a Thermodynamic System.
The Grid: Represents a substrate of computing nodes or neurons.
Data as Heat: When a node activates (white/red), it is in a "High Energy" state.
Entropy (The Cooling): The system has a built-in COOLING_RATE. Without constant input, the energy dissipates, and the information is lost to the "thermal bath" of the background.
The Lesson: This demonstrates that complex patterns (information) are far-from-equilibrium states. You must constantly inject energy (move the mouse) to fight the natural tendency toward disorder (darkness/cold).
Instructions:
Observe: Watch the background "noise" (random data flux) sparkle and fade—this is the thermal floor.
Interact: Move your mouse vigorously to inject a "Data Stream."
Watch: Stop moving and watch how quickly the "memory" of your path dissipates.
AI Collaboration Note: This video, its title card, description, and the concepts explored within were developed in a deep, recurrent collaboration with Google Gemini. Our process involves Gemini acting as a Socratic partner, a technical reviewer, and a creative collaborator, helping to refine, structure, and articulate the final concepts and this description.
References
[1] Landauer, R. (1991). "Information is physical." Physics Today, 44(5), 23-29.
[2] Shiffman, D. (2024). The Nature of Code: Simulating Natural Systems with JavaScript. No Starch Press.
[3] Marquardt, F. (2021). "Machine learning and quantum devices." SciPost Physics Lecture Notes, 29.
[4] Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities." Proceedings of the National Academy of Sciences, 79(8), 2554-2558.