li Digital Creation Critical ANalysis
Common nouns | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Index Berger's Works
Proper nouns A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z| MY IDEAS

Transhuman Beings

We tend to thing of the transhuman beings on only two modes:
- a new species, let us say Mankind2.0, tending to replace us, something like intelligent robots, as for example in I Robot by Asimov (the book)
- enhanced (and notably immortal) present humans, through grapht and prostheses.

We tend to think that the transition will happen on much more multiple ways, including enhancement of animals or humanization of autonomous immaterial (more exactly, not dependent on a definite location) agents, beings or characters.

A tentative panorama of node kinds

We tend to see the transhumanism as the emergence of super-humans, more or less organised as we are.

Some major types

Let us begin with some major types, more or less existing today.

1. Enhanced humans

Humans are indeed always "enchanced", starting from their genome through nurture, culture, vaccination and, for most of us now, some kind of grafting, from glasses and dental prostheses to cardiologic stents and more and more kinds of implants.

Very probably, high level nodes will be of many different kinds.

At present, ethics limits these enhancements >
- to basic upgradings (cosmetics, aesthetic chirurgy, and even clothing, somehow).
- to accidents, illness and handicaps compensation.

With more or less precautions and ethical suspicion, it will progress along many lines, some of them intruding deeper and deeper into our bodies, brain included.

That could (and indeed had begun to) start with the sexual

2. Advanced (humanoïd) robots

Là en rentre réellement dans le sujet.

2. Enhanced vehicles (large enough to take humans on board)

Cars, planes, ships, exoskeletons


3. Smaller mobiles

Drones, submarine robots

4. Non-localized agents


Major evolution laws or trends

Stronger identity Vs. Standardization.

Classification according to differents characteristics

According to their evolution from present beings.

- Material/mechanical. Robots of all kinds. Drones (including insect like swarms. Autonomous cars, planes, ships, submarines.
- Vegetals. See some works by Sommerer & Mignonneau.
- Animals. More and more connected, for feeding, milking.
- Humans. Cyborgs. 7 billions

- Texts and codes. Hypertext. (I could make some analysis on my own network, personal or website).

According to their materialization in space

Machine networks can be more extended in space than biological ones, since they transmit information at light speed, and not biological speed. E.g. in one seconds hundredth, 3000KKm instead of the 2 meters from foot to brain.

According to their position in time and duration

Temporary nodes Vs. "eternal"

According to their complexity
The logic gate.
The basic feed-back regulation.

According to energy acquiring
The mains socket. Batteries. Solar cells. Grass eating.


According to the technology used
- silicium
- carbon and "DNA"

Communication channels/technology : biology/neurons
but also light signals, sound, odor, other ones.


New beings are not constrained by the biological laws of present humans. They can be, from a spatial standpoint, distributed into several separated bodies. For instance swarms (an hypothesis described for instance in The Diamond Age).


We can try to think of them as networks of "nodes". Our access points into them will be nodes that are somehow connected to humans... and we can think of humans as nodes also.

Let's use the neuronal model to start with. Each neuron receives signals from one, some or many neurons, applies them a summation function and sends the result to other neurons. On the other way round, retropropagation translates the answers of the external word to the successive neurons, starting from the outputs.

Any object can be so described. Generally with very simple function: a purely material objects radiates its mass and transmits (reflection, diffraction) or light and sound it receives. There is properly no retroprogation.
On the other hands, very complex objects have complex summation and retropropagation functions.
And, somehow indefinitely, each node can be considered as a network of subnodes.

This general model can be seen as an extension of the classical systems theory, of which we have tried a synthesis in our Systemics (1973, in French, of little interest today). We use here "node" where we used "processor" at that time. Better to look for network theory on Wikipedia (which looks quite like graph theory).

Let's note that such a collective image of a transhuman being was yet proposed by Fred Hoyle in his Black Cloud novel (1957). He does not elaborate much on this Cloud's structure, but I tend to remember that there is some kind of democratic (and long) deliberative process. An aspect no seen by Asimov, we think).

Node ranking

We can use the kind or algorithm used by Google for website ranking: sum up the related nodes, weighing them according to their importance (the function is recursive, but works fine, as any Google user can see).

Tentatively, we could sum :
- the input related nodes x their weight in this node x their global rank
- the output related nodes x the weight they apply to this node x their global rank.

Hence we see that a node is powerful if if receives many important inputs and influences strongly many other important nodes.

A system could be said hierarchical if there is one node that outweithts all other inputs in the other nodes.

"Natural" evolution of networks

A natural trend of networks is the concentration. On the 2010's that's impressive as well for machines as for humans. Among two recent titles, you could nearly think that these two books deal with the same topic : The Uptstarts (by Brad Stone, Bantam, 2017) and $uperhubs (by Sandra Navidi, Brealey 2017). In fact, the first one tells the history of Uber and AirBnB, the second describes the super-power-people who typically meet at Davos. In both cases, the networks control tends to concentrate into few hands. And in Virtual Competition (Harvard University Press, 2016), Ariel Ezrachi and Maurice Stucke show how the computer cloud fosters concentration and makes difficult any anti-trust regulation.

Biological evolution. Crossover/fitness, death.

Then we can speculate that the same laws will apply in the transhuman worlds. And so more so since the frenetic move to Singularity is geared by Gafa and Cy.

The tripod coherenc.
Cloud needs Memory. Relation addresses. Local storage to limit data traffic.
Cloud needs Processing. Procotos use.

Mind demands connection : at least to be in relation, to see. Cooperation

Self protection.
Biological membranes.
Antiviruses. IBM Immune. Cyberwar.

Generation, cloning.



Network Theory
Dumbar's number : no more than 150 persons really known.

Elemntary negative feedback

Negative feedback




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