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Quote from: hamdani yusuf on 15/03/2021 21:46:05Your insistence to see morality from human individual's point of view makes you conclude that more inclusive moralities don't exist.Even if they do, if they are to be universal they must be applicable to humans, so the quickest test of universality is its applicability to humans. It might contain sulfur or chlorine, but if it doesn't turn litmus red, it isn't an acid!
Your insistence to see morality from human individual's point of view makes you conclude that more inclusive moralities don't exist.
Fleas are happyWhen they bite usWhy deny them our bloodWhen it makes fleas feel good
A moral value is a meme. It will compete with other moral values for their existence in the minds of conscious agents. There are at least 3 strategies they can adopt to survive. First by spontaneously generated into existence. It's only feasible for simple moral values, which usually come from more basic mechanisms, such as instinct. Another strategy is by helping their media, which are conscious agents, to survive and thrive. The other strategy is by infecting other conscious agents.
superorganism conscious system known to exist in the universe.
Quote from: hamdani yusuf on 16/03/2021 13:09:29superorganism conscious system known to exist in the universe. Evidence?If humans are an essential element, at what point in the evolution of homo sapiens did this superorganism suddenly appear? Us fleas are the key element of universal consciousness. Humans are merely an irritation that tries (unsuccessfully) to commit flea genocide. But if dogs were to suddenly disappear, we'd be in real trouble.Less vanity, more science, please.
From cells to dynamic models of biochemical pathways and information theory, and back.How to apply Shannon's information theory to biology.Cells, from bacteria to human cells, constantly take up, store, retrieve, communicate and make decisions based on information. How they realise all this computation using very unreliable components is still largely an open question. Instead of transistors they have to employ proteins, but proteins constantly degenerate and are re-built making their numbers fluctuate. If cellular signalling is impaired severe diseases can be the result, for instance cancer or epilepsy.As cellular communication is so pervasive and essential, researchers start to look into this information flow in biological systems in more detail. My research group at the BioQuant centre, Heidelberg University, is also active in this area, an area which I would call Information Biology — the study of how biological systems deal with information.I will show you how you can apply Shannon's information theory to biological systems. For this we need three ingredients, namely dynamic models of biological pathways, stochastic simulation algorithms (that take into account intrinsic fluctuations in molecular numbers), and, of course, Shannon's theory of information.I will give brief and user-friendly introductions to these three ingredients. After that I am going to talk about a number of use cases, such as:How much memory does a bacterium have? And how long can it remember things?How many bits per second can a liver cell process via its calcium signalling pathway?How must signalling pathways be constructed, structurally and dynamically, for certain stimuli to be decoded?and others…I will also give links to (open source) software that is being developed in my group, which you can use to simulate and play around with biochemical pathways, and also to estimate information flows and do information biology.FYI: The research I am talking about here is part of a research area which is called Computational Systems Biology. Systems Biology is a field which studies biological systems not by reducing them to their constituent parts, such as single receptors, genes, molecular complexes etc., but by viewing them in the cellular or organismal context and, importantly, as (dynamic) systems. And Computational Systems Biology is Systems Biology done with the help of mathematical models and simulation/analysis algorithms.
Atoms make molecules and molecules make proteins, like the keratin in your hair or hemoglobin in your blood. These proteins interact in complex ways to create movement, metabolism, consciousness, and everything we call life. But there is a vast divide in complexity between the simplest amoeba and a human being. How do those chemicals self-assemble to breathe and communicate? Information control is one of the key hallmarks of life, but we don’t know a lot about how information is organized in biology, or how information is held in chemistry. There is a fascinating complexity gap that is begging to be understood, and this is why Sara Imari Walker does science. I got the chance to chat with her about ways of thinking about this complexity gap to further our understanding on this question.When trying to understand how the interactions of life came to be, Sara and her lab start by looking at the networks of life. There are gene networks that control how and when our body makes proteins, protein networks that create tissues and organs, and organ networks that create individuals. Individuals interact to create populations, and social networks of those populations form communities, and those communities form ecosystems. There are also non-living networks, such as computer networks. The big question to ask here is, what are the key parallels between a living network and a non-living network? Are there common features among these networks that will give us a universal blueprint for life?
If biology is the study of self-replicating entities, and we want tounderstand the role of information, it makes sense to see how information theory is connected to the 'replicator equation' - a simple model of population dynamics for self-replicating entities. The relevant concept of information turns out to be the information of one probability distribution relative to another, also known as the Kullback-Liebler divergence. Using this we can get a new outlook on free energy, see evolution as a learning process, and give a clearer, more general formulation of Fisher's fundamental theorem of natural selection.
QuoteIf biology is the study of self-replicating entities, and we want tounderstand the role of information, it makes sense to see how information theory is connected to the 'replicator equation' - a simple model of population dynamics for self-replicating entities. The relevant concept of information turns out to be the information of one probability distribution relative to another, also known as the Kullback-Liebler divergence. Using this we can get a new outlook on free energy, see evolution as a learning process, and give a clearer, more general formulation of Fisher's fundamental theorem of natural selection.//www.youtube.com/watch?v=IKetDJof8pk
The big question to ask here is, what are the key parallels between a living network and a non-living network?
The non-living network is created for a purpose.
The difference is in intentional design versus the survival of random variants with no purpose. Evolution of living things is unbelievably wasteful compared with the design of nonliving things.If I want 36, I can write down 36 - purposive design. Or I can throw 6 dice 50,000 times and write down the answer each time - evolution.
If I want 36, I can write down 36 - purposive design. Or I can throw 6 dice 50,000 times and write down the answer each time - evolution.
Dr. Thomas Sowells book, A Conflict of Visions, discusses the ideological roots of modern day political battles. He argues that many of modern day political battles are merely a distant reflections on what we believe human nature is capable of.The Constrained Vision believes that human nature is unchanging, that we can try all we want to make humans inherently smarter or better, more moral people, but that is doomed.The Unconstrained Vision believes human nature is capable of continuous improvement. That if we simply put enough effort into ourselves, we’d be ables to make a perfect world.Its important to note that Constrained & Unconstrained are not the same as Conservative & Liberal.
There is a test that is more powerful than any IQ test, that measures you resilience against making simple investing mistakes. Technically the test is called the CRT (or Cognitive Reflection Task) & it measure the likelihood of tripping over common behavioral biases. I was inspired to make this video after rereading The Little book of Behavioral Investing by James Montier. There are a lot of books out there on Behavioral thinking, you’ve probably heard of Thinking Fast and Thinking Slow by Daniel Kahneman.
Could humans ever evolve to have wings? Why don’t fish have propellers? Why don’t tigers have wheels? Why don’t zebras have laser turrets? These might all seem like stupid questions (and maybe they are!) but they can teach us a lot about how evolution actually works, and how it doesn’t work.
Why would a zebra benefit from projecting coherent light?
The Constrained Vision believes that human nature is unchanging, that we can try all we want to make humans inherently smarter or better, more moral people, but that is doomed.The Unconstrained Vision believes human nature is capable of continuous improvement. That if we simply put enough effort into ourselves, we’d be ables to make a perfect world.
Quote from: alancalverd on 19/03/2021 10:00:58Why would a zebra benefit from projecting coherent light? In the video depiction, the laser turrets can ward off predators.
Human can improve through genetic or memetic changes.
But radical genetic change would produce a new species, so it wouldn't be human improvement but human replacement.