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Why Feedback Loops and Systems Are Hotter Than Kathryn Winnick
Any behavior or action made by anything or something will have a certain result, which is feedback. And any whole is a system, and any system will have a feedback effect, that is, A can lead to B, and similarly, B can also lead to A.
This creates a feedback system. The feedback system creates a snowball effect in the market, which can also be used to explain the Matthew effect, which the winner takes.
Feedback is also positive and negative. Every day, with different goals in different directions, we get involved in different feedback loops.
In real life, the feedback will be delayed and the feedback loop of the system will shake.
Complex systems can be found everywhere, such as what we often call: ecological chains, bee colonies, ant colonies, interpersonal networks, neural networks, human immune systems, computer networks, and global economic trade.
In all these systems, numerous independent bits of intelligence interact with each other in many ways.
How each person, as an individual, can better adapt to this society is a question we must think about. Sometimes it is not that you need to be strong, but that your opponents are strong and you must be strong or be eliminated.
Just like the Red Queen effect, you must run differently to maintain the original position, you want to go beyond, and you must come up with twice or even more times the speed to do so.
Each of us must constantly learn and evolve to adapt to this complex system in order to better gain a foothold in this society.
Although we often shout about fairness, equality, and freedom, we have to face the reality that human society is stratified, aggregated, diverse, labeled, and non-linearly developed, which means that we cannot achieve fairness in an absolute sense.
Each person possesses an internal model adapted to the world, and each one is different, and each one interacts with others.
The accumulation of only knowing is building blocks, gradually piled up through different simple parts, but each person has a different shape and height of the patchwork.
We can better adapt to complex systems only by learning important models of ideas from important disciplines through interdisciplinary learning.
“While it includes all the individuals as players, it robs them of any real agency, since they are caught in a perpetual action-reaction cycle.
As a result, we become sufferers of our own actions. The notion of complex adaptive systems thinking is also epistemically futile because it necessarily implies systemic closure, [because] every adaptation to pressure simultaneously injects more adaptive pressure into the system.
It is a continuously escalating, perpetual motion machine of antibiotics and bacteria, insects and pesticides, markets and trade, nuclear arms and weapons defense, viruses and vaccines.
7 Inside complex adaptive systems thinking, closure [is] predicated on the very properties of the model itself.”
Sorry to go on.. but there is just a lot of quotable writing in this article “In our highly complex and volatile world, most of our efforts to create new potential worlds hardly materialize on the global stage.
Is it possible, though, to reframe the big questions of climate change, existential risk, institutional crisis, and the breakdown of meaning from one of adaptive pressure on a global scale to a theory of complex potential states on a human scale?
In a world as diverse in people and rich in meanings as our big change might come from small acts by everyone operating everywhere in the contexts that already present themselves in their ordinary lives — even though these contexts seem disconnected.
These acts might be instances of what Connolly calls “the uncanny processes of creativity.” “The process is uncanny,” Connolly writes, “because creativity is neither the simple result of a profound intention nor the realization of a preordained principle waiting to be elaborated.”
This last part here, about the uncanny process of creativity, feels prescient and relevant to our work here in Concave.
The crypto space is undoubtedly a domain in which it often feels like “everyone is caught in a closed loop of escalating complexity and accelerating risk.” Thus, we contend with many of the pitfalls described by Roy, when we find ourselves as a collective guided, consciously or unconsciously, by the characteristics of complex adaptive systems (CAS) thinking.
Feedback control is widely used in modern electronic engineering. In the industrial production of factories and mines, the use of a feedback digging system can achieve production automation, in the amplifier circuit using feedback control can stabilize the static operating point and amplification, reduce nonlinear distortion, expand the frequency band and change the input resistance and output resistance, etc…
Where a certain way to the system of an output quantity (such as current, voltage, or other physical quantities) part or all back to the system’s input side, this back feeding process is called feedback control.
The closed loop formed by the output side of the system and the input side of the system is called the inverse control loop. In order to achieve feedback control of any physical quantity, should have two important links, which is:
(1) any control system, its output, and an input connected to form a closed anti-confusion control loop;
(2) the control of the output physical quantity under control, must be formed to control the physical quantity under control of the error signal.
If the above two important links, we can achieve feedback control for any physical quantity of the sinusoidal signal.
Interestingly, I discovered Concave thanks to a feedback loop. I read an article written by the amazing Concave researchers about what happened with Temple, and I was surprised at its great insights and accurate analysis.
In the end, the main problem that Temple had was the creation of a feedback loop that went in the opposite direction of what the designers of the protocol wanted.
One must be very careful with feedback loops, because positive ones reinforce themselves and get faster and faster, reaching an end state before we can even do something to stop them.
This is something that one must have always in mind when analyzing all the new protocols that are coming into space lately since almost all of them propose a feedback loop (but using the more trendy term “flywheel”) that could end up working differently as intended.
Feedback loops are dangerous and powerful at the same time. Even a negative feedback loop could turn into a positive one (the one that reinforces itself) if one is not careful.
But one has to love the emergent behaviors that they produce!