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Three Types of Societies, Three Types of Governments – The Neo-Ciceronian Times
Having said all of this, I would then note that among the many other things which are influenced by both genes and surroundings are the broad types of governmental forms (specifically, the three “classical” types of monarchic, aristocratic, and democratic) which tend to be “inhering” traits of the peoples who exhibit them. Several months ago, I touched on this in a post which could be thought of as a “case study,” in this case the specific question of why medieval and renaissance republicanism seems to have been limited to high-IQ Germanic populations. Why do cultures – and I’m going to bring the focus specifically to European, European-derived, and near-kin Indo-European populations – exhibit preferences for one type over the others? Are there cultural reasons which may predispose a nation in a certain governmental direction?

Let me first note the three general types of societies which a culture may exhibit, in broad terms, within the larger unit of a civilisation (such as, e.g., Western civilisation or Indian civilisation, etc.).

First, you have what I call core groups. These are groups which, as the name suggests, inhabit central areas within their larger civilisational setting, often hailing from the urheimat of their clade, or from areas which were settled early on in cases of migration. They tend to be more centralised in their cultural and social organisation, and may tend toward the baroque, or even decadence.

Second, you have marcher groups. These cultures exist on the edges of their clade’s contiguous settled areas, facing outward toward alien groups. As a result, they are often more heavily militarised, exhibiting forms of organisation which tends towards enhancing military preparedness and effectiveness.

Third, you have pioneer groups. These cultures usually develop when a clade is undergoing an expansion phase into new lands, and involves a great degree of decentralisation and political experimentation. These groups tend towards greater levels of “rugged individualism” as they find themselves thrown upon their own resources for survival and expansion.

I believe that we can see some tendencies (keeping in mind that they’re just tendencies) that each type of society has toward the governmental forms they prefer. Core groups will tend towards monarchy, marcher groups toward aristocracy, and pioneer groups toward democracy. We should also note that groups can change their configuration over time as their environment changes. Likewise, within a political unit, we can also discern that subgroups of the dominant culture may begin to diverge because of varied roles.

...

The important thing to note is that even though we live in a world which is much smaller due to globalisation, the existence of marcher (and even pioneer) nations has not ended. Despite the high degree of world development, not every state and not every nation within the various states are necessarily core societies whose culture/genetic complex would tolerate absolutist authority systems. There are still fracture areas between civilisations and clades which will militate toward aristocratic systems entailing personal loyalty and distributed military power. It is always possible in the future that (depending on how bad any Great Reset event might end up being) situations involving rapid expansion and the formation of (relatively) more democratic pioneer-type societies may still occur. One of the goals for neoreaction is to seek to bring order to the chaos. This order will demand greater authority for rulers. Even in democratic-tending populations, the foolish errors of universal suffrage, egalitarianism, and mass society must avoid repetition. Yet, those who would desire absolute monarchy may have to suffer the existence of aristocratic republics and feudal organisations. Nevertheless, the goal should always be to keep the momentum moving away from the democratisation and egalitarianism we currently see and towards more orderly, stable, and hierarchical governing systems.
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4 weeks ago by nhaliday
Frontier: The Definitive Guide

Before there was the Open Scripting Architecture, before there was AppleScript, before there were Apple events, before there was System 7, way back in 1988, UserLand began development of Frontier. Its earliest incarnation, UserLand IAC Toolkit, appeared in 1989. IAC stands for inter-application communication; the program was dedicated to the proposition that if it was going to be too hard for the ordinary user to write an application, it should still be possible to tie existing applications together, acting in concert and communicating with one another.

frontier  mac  programming  history  apple  scripting  book 
7 weeks ago by jefframnani
tedchoward/Frontier
GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.
frontier 
8 weeks ago by axodys
John Dee - Wikipedia
John Dee (13 July 1527 – 1608 or 1609) was an English mathematician, astronomer, astrologer, occult philosopher,[5] and advisor to Queen Elizabeth I. He devoted much of his life to the study of alchemy, divination, and Hermetic philosophy. He was also an advocate of England's imperial expansion into a "British Empire", a term he is generally credited with coining.[6]

Dee straddled the worlds of modern science and magic just as the former was emerging. One of the most learned men of his age, he had been invited to lecture on the geometry of Euclid at the University of Paris while still in his early twenties. Dee was an ardent promoter of mathematics and a respected astronomer, as well as a leading expert in navigation, having trained many of those who would conduct England's voyages of discovery.

Simultaneously with these efforts, Dee immersed himself in the worlds of magic, astrology and Hermetic philosophy. He devoted much time and effort in the last thirty years or so of his life to attempting to commune with angels in order to learn the universal language of creation and bring about the pre-apocalyptic unity of mankind. However, Robert Hooke suggested in the chapter Of Dr. Dee's Book of Spirits, that John Dee made use of Trithemian steganography, to conceal his communication with Elizabeth I.[7] A student of the Renaissance Neo-Platonism of Marsilio Ficino, Dee did not draw distinctions between his mathematical research and his investigations into Hermetic magic, angel summoning and divination. Instead he considered all of his activities to constitute different facets of the same quest: the search for a transcendent understanding of the divine forms which underlie the visible world, which Dee called "pure verities".

In his lifetime, Dee amassed one of the largest libraries in England. His high status as a scholar also allowed him to play a role in Elizabethan politics. He served as an occasional advisor and tutor to Elizabeth I and nurtured relationships with her ministers Francis Walsingham and William Cecil. Dee also tutored and enjoyed patronage relationships with Sir Philip Sidney, his uncle Robert Dudley, 1st Earl of Leicester, and Edward Dyer. He also enjoyed patronage from Sir Christopher Hatton.

https://twitter.com/Logo_Daedalus/status/985203144044040192
https://archive.is/h7ibQ
mind meld

Leave Me Alone! Misanthropic Writings from the Anti-Social Edge
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9 weeks ago by nhaliday
Harnessing Evolution - with Bret Weinstein | Virtual Futures Salon - YouTube
- ways to get out of Malthusian conditions: expansion to new frontiers, new technology, redistribution/theft
- some discussion of existential risk
- wants to change humanity's "purpose" to one that would be safe in the long run; important thing is it has to be ESS (maybe he wants a singleton?)
- not too impressed by transhumanism (wouldn't identify with a brain emulation)
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10 weeks ago by nhaliday
The Hanson-Yudkowsky AI-Foom Debate - Machine Intelligence Research Institute
How Deviant Recent AI Progress Lumpiness?: http://www.overcomingbias.com/2018/03/how-deviant-recent-ai-progress-lumpiness.html
I seem to disagree with most people working on artificial intelligence (AI) risk. While with them I expect rapid change once AI is powerful enough to replace most all human workers, I expect this change to be spread across the world, not concentrated in one main localized AI system. The efforts of AI risk folks to design AI systems whose values won’t drift might stop global AI value drift if there is just one main AI system. But doing so in a world of many AI systems at similar abilities levels requires strong global governance of AI systems, which is a tall order anytime soon. Their continued focus on preventing single system drift suggests that they expect a single main AI system.

The main reason that I understand to expect relatively local AI progress is if AI progress is unusually lumpy, i.e., arriving in unusually fewer larger packages rather than in the usual many smaller packages. If one AI team finds a big lump, it might jump way ahead of the other teams.

However, we have a vast literature on the lumpiness of research and innovation more generally, which clearly says that usually most of the value in innovation is found in many small innovations. We have also so far seen this in computer science (CS) and AI. Even if there have been historical examples where much value was found in particular big innovations, such as nuclear weapons or the origin of humans.

Apparently many people associated with AI risk, including the star machine learning (ML) researchers that they often idolize, find it intuitively plausible that AI and ML progress is exceptionally lumpy. Such researchers often say, “My project is ‘huge’, and will soon do it all!” A decade ago my ex-co-blogger Eliezer Yudkowsky and I argued here on this blog about our differing estimates of AI progress lumpiness. He recently offered Alpha Go Zero as evidence of AI lumpiness:

...

In this post, let me give another example (beyond two big lumps in a row) of what could change my mind. I offer a clear observable indicator, for which data should have available now: deviant citation lumpiness in recent ML research. One standard measure of research impact is citations; bigger lumpier developments gain more citations that smaller ones. And it turns out that the lumpiness of citations is remarkably constant across research fields! See this March 3 paper in Science:

I Still Don’t Get Foom: http://www.overcomingbias.com/2014/07/30855.html
All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain.

If we count by economic value, humans now do most of the mental tasks worth doing. Evolution has given us a brain chock-full of useful well-honed modules. And the fact that most mental tasks require the use of many modules is enough to explain why some of us are smarter than others. (There’d be a common “g” factor in task performance even with independent module variation.) Our modules aren’t that different from those of other primates, but because ours are different enough to allow lots of cultural transmission of innovation, we’ve out-competed other primates handily.

We’ve had computers for over seventy years, and have slowly build up libraries of software modules for them. Like brains, computers do mental tasks by combining modules. An important mental task is software innovation: improving these modules, adding new ones, and finding new ways to combine them. Ideas for new modules are sometimes inspired by the modules we see in our brains. When an innovation team finds an improvement, they usually sell access to it, which gives them resources for new projects, and lets others take advantage of their innovation.

...

In Bostrom’s graph above the line for an initially small project and system has a much higher slope, which means that it becomes in a short time vastly better at software innovation. Better than the entire rest of the world put together. And my key question is: how could it plausibly do that? Since the rest of the world is already trying the best it can to usefully innovate, and to abstract to promote such innovation, what exactly gives one small project such a huge advantage to let it innovate so much faster?

...

In fact, most software innovation seems to be driven by hardware advances, instead of innovator creativity. Apparently, good ideas are available but must usually wait until hardware is cheap enough to support them.

Yes, sometimes architectural choices have wider impacts. But I was an artificial intelligence researcher for nine years, ending twenty years ago, and I never saw an architecture choice make a huge difference, relative to other reasonable architecture choices. For most big systems, overall architecture matters a lot less than getting lots of detail right. Researchers have long wandered the space of architectures, mostly rediscovering variations on what others found before.

Some hope that a small project could be much better at innovation because it specializes in that topic, and much better understands new theoretical insights into the basic nature of innovation or intelligence. But I don’t think those are actually topics where one can usefully specialize much, or where we’ll find much useful new theory. To be much better at learning, the project would instead have to be much better at hundreds of specific kinds of learning. Which is very hard to do in a small project.

What does Bostrom say? Alas, not much. He distinguishes several advantages of digital over human minds, but all software shares those advantages. Bostrom also distinguishes five paths: better software, brain emulation (i.e., ems), biological enhancement of humans, brain-computer interfaces, and better human organizations. He doesn’t think interfaces would work, and sees organizations and better biology as only playing supporting roles.

...

Similarly, while you might imagine someday standing in awe in front of a super intelligence that embodies all the power of a new age, superintelligence just isn’t the sort of thing that one project could invent. As “intelligence” is just the name we give to being better at many mental tasks by using many good mental modules, there’s no one place to improve it. So I can’t see a plausible way one project could increase its intelligence vastly faster than could the rest of the world.

Takeoff speeds: https://sideways-view.com/2018/02/24/takeoff-speeds/
Futurists have argued for years about whether the development of AGI will look more like a breakthrough within a small group (“fast takeoff”), or a continuous acceleration distributed across the broader economy or a large firm (“slow takeoff”).

I currently think a slow takeoff is significantly more likely. This post explains some of my reasoning and why I think it matters. Mostly the post lists arguments I often hear for a fast takeoff and explains why I don’t find them compelling.

(Note: this is not a post about whether an intelligence explosion will occur. That seems very likely to me. Quantitatively I expect it to go along these lines. So e.g. while I disagree with many of the claims and assumptions in Intelligence Explosion Microeconomics, I don’t disagree with the central thesis or with most of the arguments.)
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11 weeks ago by nhaliday
Eternity in six hours: intergalactic spreading of intelligent life and sharpening the Fermi paradox
We do this by demonstrating that traveling between galaxies – indeed even launching a colonisation project for the entire reachable universe – is a relatively simple task for a star-spanning civilization, requiring modest amounts of energy and resources. We start by demonstrating that humanity itself could likely accomplish such a colonisation project in the foreseeable future, should we want to, and then demonstrate that there are millions of galaxies that could have reached us by now, using similar methods. This results in a considerable sharpening of the Fermi paradox.
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12 weeks ago by nhaliday

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