Simulating Real World: What's Needed?

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Discussion Overview

The discussion revolves around the computational requirements for simulating biological systems, particularly focusing on the brains of small organisms like ants and the complexities involved in simulating real-world interactions at a quantum level. Participants explore the feasibility of using supercomputers for such simulations and the challenges posed by the current understanding of neural structures and interactions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the computational power needed to simulate an ant's brain and a cubic millimeter of the real world, suggesting a standard measure for processing speed based on spatial simulation capabilities.
  • Another participant points out the difficulty of writing wave equations for complex systems, indicating that simulating electric field interactions in neurons may be beyond current capabilities, despite the relatively small number of neurons in an ant's brain.
  • A third participant references the PetaVision project, which simulates the human visual system, and discusses the potential of supercomputers like Roadrunner to model large numbers of neurons, proposing that existing computing power could theoretically allow for simulations of brains with greater complexity than humans.
  • One participant emphasizes the importance of understanding the structure of the systems being simulated, cautioning that random connections in neural models could lead to ineffective results (GIGO). They also note the disparity between the capabilities of small insects and current robotic technologies.

Areas of Agreement / Disagreement

Participants express differing views on the feasibility and current limitations of simulating biological systems. While some believe that the necessary computational power is nearly available, others highlight significant challenges in understanding and accurately modeling the systems involved. No consensus is reached on the specific requirements or methodologies for such simulations.

Contextual Notes

Limitations include the current understanding of neural structures, the complexity of interactions at the atomic level, and the dependency on accurate models for effective simulations. There are unresolved questions regarding the exact computational requirements for simulating various biological and physical processes.

aquaregia
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You've probably heard about the thing where scientists simulated 10 seconds of half of a mouses brain with a supercomputer. Does anyone know how fast of a computer it would take to simulate an ants brain?

On a related question, let's say you wanted to simulate 1 cubic milimeter of the real world. And you wanted to be able to simulate ANYTHING that can happen in that cubic milimeter (ants brain, chemical reactions, nuclear reaction) down to the lowest level describable by modern physics (quantum mechanics, or the standard model) in real time. How big of a supercomputer would you need to do that?

I think that there should be a way to convert all the different processing speed measures into some standard measure which was based on how large an area of space that that computer can simulate in real time. Or if you use FLOPS as the standard measure, how many FLOPS does say 1 atom have (looking at it from the point of view of how many FLOPS it would take to simulate that 1 atom)?
 
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You can't even write the wave equation for anything more complicated than a lone Hydrogen atom on it's own in space - so the electric field interactions in neurons at the atomic level is probably pushing it!

On the other hand ant's only have something like 50,000 neurons so you should be able to do a reasonable job of simulating it at that level.
 
"PetaVision models the human visual system—mimicking more than 1 billion visual neurons and trillions of synapses.

"On Saturday, Los Alamos researchers used PetaVision to model more than a billion visual neurons surpassing the scale of 1 quadrillion computations a second (a petaflop/s). On Monday scientists used PetaVision to reach a new computing performance record of 1.144 petaflop/s. The achievement throws open the door to eventually achieving human-like cognitive performance in electronic computers.

This was recently done with the Roadrunner supercomputer. The Roadrunner has something like 12,000 PS3 chips and 6,000 other chips in it. I think there are something like 10 million PS3s sold. There are at least 50 computers for every PS3, so just doing some quick math, it should be possible to hook up all those computers and PS3's to make something with 27,000 times the processing power of the Roadrunner.

If the Roadrunner can do 1 billion neurons, and the human brain has 100 billion neurons, that means it would be possilbe to make a computer simulation of a brain that had 270 times the complexity of a human brain, using just this small subset of the total computing power of the worlds computers.
 
That's all assuming you know structure of things simulated. At the moment we can throw in billion of randomly connected neurons - but that'll be GIGO (garbage in, garbage out).

Still, you are probably right that necessary power is almost there, we just have no idea how to properly use it.

The tiniest insects are able to feed, move and replicate, and they are quite effective at that. Their brain is so small that I would be not surprised if it can be simulated on my mobile. Yet automatic vacuum cleaners - with designated task much easier than that of insect - are still stupid enough to block themseves between chair legs. We just don't know how yet.
 

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