19 MAR 2015 by ideonexus
Whole Brain Emulation
We consider a strategy of straightforward duplication of the activity, and look at the numbers of some of the components. The human brain has up to one hundred billion (10^11) neurons and between one hundred trillion (10^14) and one quadrillion (10^15) synapses. But we have reached a point where for purposes of data acquisition these objects are now considered fairly large (e.g. 200 nm to 2,000 nm for synaptic spines and 4,000 nm to 100,000 nm for the neural soma), at least by the standards o...
1 From Randal A. Koene's "Uploading to Substrate-Independent Minds"
06 FEB 2015 by ideonexus
A Worm's Mind in a Lego Robot Body
The nematode worm Caenorhabditis elegans (C. elegans) is tiny and only has 302 neurons. These have been completely mapped and the OpenWorm project is working to build a complete simulation of the worm in software. One of the founders of the OpenWorm project, Timothy Busbice, has taken the connectome and implemented an object oriented neuron program.
The model is accurate in its connections and makes use of UDP packets to fire neurons. If two neurons have three synaptic connections then when ... 1 
notes
notes09 AUG 2014 by ideonexus
Spherical Cows
Milk production at a dairy farm was low, so the farmer wrote to the local university, asking for help from academia. A multidisciplinary team of professors was assembled, headed by a theoretical physicist, and two weeks of intensive on-site investigation took place. The scholars then returned to the university, notebooks crammed with data, where the task of writing the report was left to the team leader. Shortly thereafter the physicist returned to the farm, saying to the farmer, "I have the ... 1 notes
notes09 AUG 2014 by ideonexus
Two Kinds of Societal Collapse
Running the model in dierent scenarios produces two kinds of collapses, either due to scarcity
of labor (following an inequality-induced famine) or due to scarcity of Nature (depletion of natural
resources). We categorize the former case as a Type-L (Disappearance of Labor) Collapse and
the latter as a Type-N collapse (Exhaustion of Nature). In a Type-L collapse, growth of the
Elite Population strains availability of resources for the Commoners. This causes decline of the
Commoner Population ... 1 notes
notes09 AUG 2014 by ideonexus
The HANDY Model is Based On Predator-Prey Cycles
As indicated above, Human And Nature DYnamics (HANDY) was originally built based on the
predator-prey model. We can think of the human population as the predator", while nature
(the natural resources of the surrounding environment) can be taken as the prey", depleted by
humans. In animal models, carrying capacity is an upper ceiling on long-term population. When
the population surpasses the carrying capacity, mechanisms such as starvation or migration bring
the population back down. However, ... 1 notes
notes07 FEB 2014 by ideonexus
Life Reduced to Bad Physics
Those reductionists who try to reduce life to physics usually try to reduce it to primitive physics—not to good physics. Good physics is broad enough to contain life, to encompass life in its description since good physics allows a vast field of possible descriptions. There is no reason why living beings should be compared to primitive machines which don't make use of feedback. 1 notes
notesGood physics is complex enough to account for life.
27 DEC 2013 by ideonexus
Why Economists Will Continue to be Wrong
Carter had initially used arbitrary parameters in his perfect model to generate perfect data, but now, in order to assess his model in a realistic way, he threw those parameters out and used standard calibration techniques to match his perfect model to his perfect data. It was supposed to be a formality--he assumed, reasonably, that the process would simply produce the same parameters that had been used to produce the data in the first place. But it didn't. It turned out that there were many ...They make models based on past data, and when they fail to predict the future, they adjust them to match the new past data. The problem is that so many models will match the past data, there could be no end to the number of models they throw out.
24 DEC 2013 by ideonexus
Causality as a Conceptual Tool
Causality itself is an evolved conceptual tool that simplifies, schematizes, and focuses our representation of situations. This cognitive machinery guides us to think in terms of the cause—of an outcome’s having a single cause. Yet for enlarged understanding, it is more accurate to represent outcomes as caused by an intersection, or nexus, of factors (including the absence of precluding conditions). In War and Peace, Tolstoy asks, “When an apple ripens and falls, why does it fall? Becau...John Tooby on how causation is a way we simplify the world to more easily understand it, but it can also over-simplify.
24 DEC 2013 by ideonexus
The Web of Causation
...complex systems, such as financial markets or the Earth’s biosphere, do not seem to obey causality. For every event that occurs, there are a multitude of possible causes, and the extent to which each contributes to the event is not clear, not even after the fact! One might say that there is a web of causation. For example, on a typical day, the stock market might go up or down by some fraction of a percentage point. The Wall Street Journal might blithely report that the stock market move...Nigel Goldenfeld explains why the simplistic explanations for market movements so popular in the news media are also so ridiculous.
24 DEC 2013 by ideonexus
You Can't Predict What You Are Going to Do
In the physical world, the only way to learn tomorrow’s weather in detail is to wait twenty-four hours and see, even if nothing is random at all. The universe is computing tomorrow’s weather as rapidly and as efficiently as possible; any smaller model is inaccurate, and the smallest error is amplified into large effects.
At a personal level, even if the world is as deterministic as a computer program, you still can’t predict what you’re going to do. This is because your prediction me...Folksonomies: predictability modeling
Folksonomies: predictability modeling
Rudy Rucker on why our brains are like the weather, so complex that only the actual system can run the computation.
