IBM’s Blue Brain and Simulated Level of Detail
Henry Markham calls IBM’s cat scale brain simulation a hoax. Markham claims that the simulation doesn’t have the 10,000+ differential equations needed to simulate the synapses with fidelity. This argument is a version of the naturalistic fallacy – if Nature requires X to achieve a result, we will have to perform X when replicating the effect.
It is useful to think about the simulation’s level of detail (LOD) in terms of certain thresholds, from most detailed to least detailed:
- Noise level: at this level (call it LODn) the lack of precision is on the order of the noise present in a biological brain. It is not possible to distinguish the functioning of such a simulated brain from the functioning of a biological brain.
- Functional level: at this level (call it LODf) the lack of precision is greater, but the result is functionally similar. There may be some behavior changes, but the overall capabilities (e.g. “intelligence”) are similar.
- Equivalence level: at this level (call it LODe) the precision is even lower, but this is compensated with tweaks to the simulated physiology. The result is equivalent in capabilities, although some characteristics may be very different. For example, the retina can be replaced with a non-biological equivalent.
The computation power required for LODn > LODf > LODe. There are likely order of magnitude differences between the levels.
If we consider a non-biological example – a digital computer, what does it take to simulate it? It is obviously enough to simulate the logic function. The Markham’s line of reasoning would seem to argue that we have to simulate the voltage gradients and charge movements in each transistor!
In the transistor case, LODn would involve simulating each transistor’s logic function. LODf would involve an instruction set simulation (e.g. the QEMU emulator). LODe would involve using the most convenient instruction set (e.g. x86) and recompiling any software. Clearly, an LODe simulation is several orders of magnitude more efficient.
Markham fails to convince that his preferred level of simulation is required for LODn, never mind the other levels.
One way to find out what levels require is to actually run simulations and compare to physical neural matter. The Blue Brain project aims to do that, although the results are not conclusive yet. It would be good if more research was directed at comparing their simulation to a biological brain. This would make the project more grounded.
Just want to establish in my mind a point of inquiry: isn’t the purpose
to establish how the human neurological system operates such that we can de
develop pharmaceuticals that will assist the user? So why do I worry
whether or not we are committing a fallacy?
I think one of the major goals of the IBM effort is to develop AI algorithms by mimicking the brain. To do this, they don’t have to operate exactly like a human brain, they just have to operate on similar general principles.
For the goal of developing medical interventions, you would indeed need to have higher simulation fidelity (somewhere between LODf and LODn in my newly invented jargon).