> On Jun 16, 2015, at 3:26 PM, Dean Pomerleau <[email protected]> wrote: 
> In short, growing evidence supporting the importance of cortical oscillations 
> in neural processing suggests that this sort of analog/digital feedback loop 
> might be critical to how the brain works, and that such interactions might be 
> very hard (possible intractably hard) to model accurately (i.e. emulation vs. 
> merely crude simulation) on a digital computer, in a similar way to how 
> protein folding is intractable to model on a digital computer.   


The tractability challenges of computational dynamics for brain-like models is 
related to why we can’t analyze the dynamics of *any* non-trivial physical 
world system. It is not coincidence that all “big data” computation focuses 
solely on relationships in the electronic world and not the physical world.

Interestingly, computer scientists rarely notice that these software systems do 
not exist until you point it out. And when you do point it out they are at a 
loss to explain why. It is only “obvious” in hindsight.


Virtually all existing computer science is based on the manipulation of 
graph-like data models and primitives. The problem is that some systems, 
notably physical world systems, have relationships that are fundamentally 
topological in nature. Graphs are a special, strict subset of more general 
topological computing representations; it is not possible to construct a 
scalable topological computational model on top of graph primitives.

There is no computer science literature for computing on topological data 
models. To the extent algorithms and data structures exist to handle basic 
topological data models (e.g. R-trees), they exhibit pathological scalability 
because they are shoehorned into traditional graph models. If you want to 
compute on topological models at scale, you need to build a completely new 
computer science stack, from the most elementary primitives on up. And it needs 
to have an efficient implementation on conventional silicon.


If you can directly manipulate topologies as computational constructs, instead 
of graphs only, many types of computational dynamic suddenly become *much* more 
tractable. In practice, the use of inappropriate algorithms and data structures 
to represent topological relationships are responsible for most intractability 
related to expressions of physical world system dynamics on a computer. It just 
never crosses the mind of most computer scientists working on such things and 
it is never discussed in computer science curricula.





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AGI
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