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Updates books and research

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[[!meta title="Four Futures: Life After Capitalism"]]
* Author: Peter Frase
* Year: 2016
* Publisher: Verso / Jacobin
## Trechos
Fictional futures are, in my view, preferable to those works of
......
[[!meta title="You're not a Gadget"]]
## Concepts
* Technological lock-ins.
* Cybernetic totalists versus humanistic technologies.
* Circle of empaty.
* Computationalism.
* Value of personhood contrasted to "the hive".
* Neoteny and it's contradictory qualities in culture.
* Cephalopods + Childhood = Humans + Virtual Reality.
* There's an underlying discussion between individual versus collective. Does creativity is just individual? He seems to view the polarization as a obligation to choose sides.
## Information Doesn’t Deserve to Be Free
“Information wants to be free.” So goes the saying. Stewart Brand, the founder
......@@ -153,3 +164,237 @@
reverse-engineered or mucked with in any accessible way. Or it might even
involve the prospect, dreaded by some, of dualism, a reality for consciousness
as apart from mechanism.
## Wikified Biology
Dyson equates the beginnings of life on Earth with the Eden of Linux. Back when
life first took hold, genes flowed around freely; genetic sequences skipped
from organism to organism in much the way they may soon be able to on the
internet. In his article, Freeman derides the first organism that hoarded its
genes behind a protective membrane as “evil,” just like the nemesis of the
open-software movement, Bill Gates.
Once organisms became encapsulated, they isolated themselves into distinct
species, trading genes only with others of their kind. Freeman suggests that
the coming era of synthetic biology will be a return to Eden.
I suppose amateurs, robots, and an aggregation of amateurs and robots might
someday hack genes in the global garage and tweet DNA sequences around the
globe at light speed. Or there might be a slightly more sober process that
takes place between institutions like high schools and start-up companies.
However it happens, species boundaries will become defunct, and genes will fly
about, resulting in an orgy of creativity. Untraceable multitudes of new
biological organisms will appear as frequently as new videos do on YouTube
today.
One common response to suggestions that this might happen is fear. After all,
it might take only one doomsday virus produced in one garage to bring the
entire human story to a close. I will not focus directly on that concern, but,
instead, on whether the proposed style of openness would even bring about the
creation of innovative creatures.
The alternative to wide-open development is not necessarily evil. My guess is
that a poorly encapsulated communal gloop of organisms lost out to closely
guarded species on the primordial Earth for the same reason that the Linux
community didn’t come up with the iPhone: encapsulation serves a purpose.
[...]
Wikipedia has already been elevated into what might be a permanent niche. It
might become stuck as a fixture, like MIDI or the Google ad exchange services.
That makes it important to be aware of what you might be missing. Even in a
case in which there is an objective truth that is already known, such as a
mathematical proof, Wikipedia distracts the potential for learning how to bring
it into the conversation in new ways. Individual voice—the opposite of
wikiness—might not matter to mathematical truth, but it is the core of
mathematical communication.
## The Culture of Computationalism
For lack of a better word, I call it computationalism. This term is usually
used more narrowly to describe a philosophy of mind, but I’ll extend it to
include something like a culture. A first pass at a summary of the underlying
philosophy is that the world can be understood as a computational process, with
people as subprocesses.
[...]
In a scientific role, I don’t recoil from the idea that the brain is a kind of
computer, but there is more than one way to use computation as a source of
models for human beings. I’ll discuss three common flavors of computationalism
and then describe a fourth flavor, the one that I prefer. Each flavor can be
distinguished by a different idea about what would be needed to make software
as we generally know it become more like a person.
One flavor is based on the idea that a sufficiently voluminous computation will
take on the qualities we associate with people—such as, perhaps, consciousness.
One might claim Moore’s law is inexorably leading to superbrains, superbeings,
and, perhaps, ultimately, some kind of global or even cosmic consciousness. If
this language sounds extreme, be aware that this is the sort of rhetoric you
can find in the world of Singularity enthusiasts and extropians.
[...]
A second flavor of computationalism holds that a computer program with specific
design features—usually related to self-representation and circular
references—is similar to a person. Some of the figures associated with this
approach are Daniel Dennett and Douglas Hofstadter, though each has his own
ideas about what the special features should be.
Hofstadter suggests that software that includes a “strange loop” bears a
resemblance to consciousness. In a strange loop, things are nested within
things in such a way that an inner thing is the same as an outer thing.
[...]
A third flavor of computationalism is found in web 2.0 circles. In this case,
any information structure that can be perceived by some real human to also be a
person is a person. This idea is essentially a revival of the Turing test. If
you can perceive the hive mind to be recommending music to you, for instance,
then the hive is effectively a person.
[...]
The approach to thinking about people computationally that I prefer, on those
occasions when such thinking seems appropriate to me, is what I’ll call
“realism.” The idea is that humans, considered as information systems, weren’t
designed yesterday, and are not the abstract playthings of some higher being,
such as a web 2.0 programmer in the sky or a cosmic Spore player. Instead, I
believe humans are the result of billions of years of implicit, evolutionary
study in the school of hard knocks. The cybernetic structure of a person has
been refined by a very large, very long, and very deep encounter with physical
reality.
### From Images to Odors
For twenty years or so I gave a lecture introducing the fundamentals of virtual
reality. I’d review the basics of vision and hearing as well as of touch and
taste. At the end, the questions would begin, and one of the first ones was
usually about smell: Will we have smells in virtual reality machines anytime
soon?
Maybe, but probably just a few. Odors are fundamentally different from images
or sounds. The latter can be broken down into primary components that are
relatively straightforward for computers—and the brain—to process. The visible
colors are merely words for different wavelengths of light. Every sound wave is
actually composed of numerous sine waves, each of which can be easily described
mathematically.
[...]
Odors are completely different, as is the brain’s method of sensing them. Deep
in the nasal passage, shrouded by a mucous membrane, sits a patch of tissue—the
olfactory epithelium—studded with neurons that detect chemicals. Each of these
neurons has cup-shaped proteins called olfactory receptors. When a particular
molecule happens to fall into a matching receptor, a neural signal is triggered
that is transmitted to the brain as an odor. A molecule too large to fit into
one of the receptors has no odor. The number of distinct odors is limited only
by the number of olfactory receptors capable of interacting with them. Linda
Buck of the Fred Hutchinson Cancer Research Center and Richard Axel of Columbia
University, winners of the 2004 Nobel Prize in Physiology or Medicine, have
found that the human nose contains about one thousand different types of
olfactory neurons, each type able to detect a particular set of chemicals.
This adds up to a profound difference in the underlying structure of the
senses—a difference that gives rise to compelling questions about the way we
think, and perhaps even about the origins of language. There is no way to
interpolate between two smell molecules. True, odors can be mixed together to
form millions of scents. But the world’s smells can’t be broken down into just
a few numbers on a gradient; there is no “smell pixel.” Think of it this way:
colors and sounds can be measured with rulers, but odors must be looked up in a
dictionary.
[...]
To solve the problem of olfaction—that is, to make the complex world of smells
quickly identifiable—brains had to have evolved a specific type of neural
circuitry, Jim believes. That circuitry, he hypothesizes, formed the basis for
the cerebral cortex—the largest part of our brain, and perhaps the most
critical in shaping the way we think. For this reason, Jim has proposed that
the way we think is fundamentally based in the olfactory.
[...]
He often refers to the olfactory parts of the brain as the “Old Factory,” as
they are remarkably similar across species, which suggests that the structure
has ancient origins.
## Editing Is Sexy; Creativity Is Natural
These experiments in linguistic variety could also inspire a better
understanding of how language came about in the first place. One of Charles
Darwin’s most compelling evolutionary speculations was that music might have
preceded language. He was intrigued by the fact that many species use song for
sexual display and wondered if human vocalizations might have started out that
way too. It might follow, then, that vocalizations could have become varied and
complex only later, perhaps when song came to represent actions beyond mating
and such basics of survival.
[...]
Terry offered an unconventional solution to the mystery of Bengalese finch
musicality. What if there are certain traits, including song style, that
naturally tend to become less constrained from generation to generation but are
normally held in check by selection pressures? If the pressures go away,
variation should increase rapidly. Terry suggested that the finches developed a
wider song variety not because it provided an advantage but merely because in
captivity it became possible.
In the wild, songs probably had to be rigid in order for mates to find each
other. Birds born with a genetic predilection for musical innovation most
likely would have had trouble mating. Once finches experienced the luxury of
assured mating (provided they were visually attractive), their song variety
exploded.
Brian Ritchie and Simon Kirby of the University of Edinburgh worked with Terry
to simulate bird evolution in a computer model, and the idea worked well, at
least in a virtual world. Here is yet another example of how science becomes
more like storytelling as engineering becomes able to represent some of the
machinery of formerly subjective human activities.
## Metaphors
One reason the metaphor of the sun fascinates me is that it bears on a conflict
that has been at the heart of information science since its inception: Can
meaning be described compactly and precisely, or is it something that can
emerge only in approximate form based on statistical associations between large
numbers of components?
Mathematical expressions are compact and precise, and most early computer
scientists assumed that at least part of language ought to display those
qualities too.
## Future Humors
Unfortunately, we don’t have access at this time to a single philosophy that
makes sense for all purposes, and we might never find one. Treating people as
nothing other than parts of nature is an uninspired basis for designing
technologies that embody human aspirations. The inverse error is just as
misguided: it’s a mistake to treat nature as a person. That is the error that
yields confusions like intelligent design.
[...]
Those who enter into the theater of computationalism are given all the mental
solace that is usually associated with traditional religions. These include
consolations for metaphysical yearnings, in the form of the race to climb to
ever more “meta” or higher-level states of digital representation, and even a
colorful eschatology, in the form of the Singularity. And, indeed, through the
Singularity a hope of an afterlife is available to the most fervent believers.
## My Brush with Bachelardian Neoteny in the Most Interesting Room in the World
But actually, because of homuncular flexibility, any part of reality might just
as well be a part of your body if you happen to hook up the software elements
so that your brain can control it easily. Maybe if you wiggle your toes, the
clouds in the sky will wiggle too. Then the clouds would start to feel like
part of your body. All the items of experience become more fungible than in the
physical world. And this leads to the revelatory experience.
## Final Words
For me, the prospect of an entirely different notion of communication is more
thrilling than a construction like the Singularity. Any gadget, even a big one
like the Singularity, gets boring after a while. But a deepening of meaning is
the most intense potential kind of adventure available to us.
......@@ -33,6 +33,7 @@
* Livro do knuppi e do lorenzi
* Instituto plantarum
* [Como diferenciar serralha e dente-de-leão](http://www.matosdecomer.com.br/2016/08/como-diferenciar-serralha-e-dente-de.html).
* [Cartilha Guia Prático de PANC Plantas Alimenticias Nao Convencionais](http://institutokairos.net/wp content/uploads/2017/08/Cartilha Guia Pr%C3%A1tico de PANC Plantas Alimenticias Nao Convencionais.pdf).
## Pesquisas futuras:
......
......@@ -44,6 +44,36 @@ Python encourages polymorphism:
floating points sometimes can, in different ways—by using rational
representation and by limiting precision
### Types
More formally, there are three major type (and operation) categories in Python
that have this generic nature:
Numbers (integer, floating-point, decimal, fraction, others)
Support addition, multiplication, etc.
Sequences (strings, lists, tuples)
Support indexing, slicing, concatenation, etc.
Mappings (dictionaries)
Support indexing by key, etc.
[...]
The major core types in Python break down as follows:
Immutables (numbers, strings, tuples, frozensets)
None of the object types in the immutable category support in-place changes,
though we can always run expressions to make new objects and assign their
results to variables as needed.
Mutables (lists, dictionaries, sets, bytearray)
Conversely, the mutable types can always be changed in place with operations
that do not create new objects. Although such objects can be copied, in-place
changes support direct modification.
## Libraries
* [SciPy.org — SciPy.org](https://www.scipy.org/) ([package](https://packages.debian.org/stable/python-scipy)).
## Test projects
* [Arduino Blog » How close are we to doomsday? A clock is calculating it in real time](https://blog.arduino.cc/2013/03/27/how-close-are-we-to-doomsday-clock/) ([python code](https://github.com/tomschofield/Neurotic-Armageddon-Indicator/blob/master/NAI_SERVER/nai_scraper.py) to parse [Timeline from the Bulletin of the Atomic Scientists](http://thebulletin.org/timeline)).
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