Origins of Life: Early Life - Autocatalytic Sets - A cooperative origin of life | Wim Hordijk
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- Опубліковано 2 жов 2024
- These videos are from the ComplexityExplorer.org course 'Origins of Life. This course aims to push the field of Origins of Life research forward by bringing new and synthetic thinking to the question of how life emerged from an abiotic world.
This course begins by examining the chemical, geological, physical, and biological principles that give us insight into origins of life research. We look at the chemical and geological environment of early Earth from the perspective of likely environments for life to originate.
Taking a look at modern life we ask what it can tell us about the origin of life by winding the clock backwards. We explore what elements of modern life are absolutely essential for life, and ask what is arbitrary? We ponder how life arose from the huge chemical space and what this early 'living chemistry' may have looked like.
We examine phenomena, that may seem particularly life like, but are in fact likely to arise given physical dynamics alone. We analyze what physical concepts and laws bound the possibilities for life and its formation.
Insights gained from modern evolutionary theory will be applied to proto-life. Once life emerges, we consider how living systems impact the geosphere and evolve complexity.
The study of Origins of Life is highly interdisciplinary - touching on concepts and principles from earth science, biology, chemistry, and physics. With this, we hope that the course can bring students interested in a broad range of fields to explore how life originated.
The course will make use of basic algebra, chemistry, and biology but potentially difficult topics will be reviewed, and help is available in the course discussion forum and instructor email. There will be pointers to additional resources for those who want to dig deeper.
This course is Complexity Explorer's first Frontiers Course. A Frontiers Course gives students a tour of an active interdisciplinary research area. The goals of a Frontiers Course are to share the excitement and uncertainty of a scientific area, inspire curiosity, and possibly draw new people into the research community who can help this research area take shape!
Hopefully AI can one day confirm or share some insight into how this all started
what if that reflect human social interactions?
superb
Have to pay to read the scientific journals to source you? Well I'm sure all your viewers do that
Thank you for this fascinating talk. A question we might then ask is, is the Universe a kind of biological entity, with life and consciousness
enfolded in its atomic structure? Billy
Thank you, very well explained and so fascinating
Very good presentation. Thank you!
Very interesting. Thanks a lot.
Yes, autocatalytic sets are not just abstract mathematical constructs, but I think there is something you miss out Mr. Hordijk.
And that is related to one of the oldest problems in science out there-the eternal conflict betweeen chance and determinism. See, autocatalytic sets, even the largest and most versatile ones are stil first and foremost *chemical* reaction systems and as anything in any hard deterministic science their behaviour can be explained and therefore predicted to the detail. It means that in a "real" deterministic autocatalytic set (no matter the size, volume, diversity or whatever) the general direction of the reactions as well as all the complex interactions among the varoius components of the set *should* be prescribed and determinable. That's just the Nature of the physical laws as we know them according to the scientific method. Sorry, but Life doesn't work that way. Life is unprescribable, chaotic, random and as a rule UNdeterministic. And this is why anything that can be modelled on a chip is most definitely not alive.
What modern science (and not only the modern ones, but pretty much all the sciences throughout history) is missing is the ability to incorporate and explain phonomena which don't follow predetrmined path or constant set of rules and which can govern themselves by varying internal characteristics. And the evolution of Life is one of those phenomena that fits the bill perfectly. This is why all our attempts to go at it like a reaction we can just predetermine or a computer model that will complete itself out will fall right onto themselves. You can compute something that relies on chance to bring itself out.
Until you manage to correct for chance and give the network the ability to cluster and form internal organization in an UNpredictable manner you won't be close to the actual origins of Life. And this is a common problem aross the entire spectrum of origins of Life theories during the last century or so. Both the autocatalytic sets and the RNA world hypothesis, as well as many others, presume you can construct Life out in reverse using modern chemistry and a lot of computation and models and stuff. But what you people fail to capture out is the fleeing tendency of Life to evolve into ways that can't be predicted. To always expand into its ädjacent possible" as Mr. Stuart Kauffman puts it. And you can't do that in a model because it would quite literally require your model to produce new end configuration every time you run it and we all know mathematical modelling doesn't work like that.
Just like it if you assume you can just synthesize Life out of a preexisting set of chemicals and authomatize its creation into any other chemical system you would fail gorgeously because you would fail to include its most basic feature-chance. Call it randomness, call it noise, call it non-ergodic systems, call it underterministic behaviour, call it a miracle, but all the systems that only try to create known living organisms or just life-like structures based on what we know about Life de novo by synthesizing these structures out of ordinary non-living material chemicals following deterministic lab protocols have all failed and I would say are doomed to failure in the future until they manage to include chance in them. But the thing about chance is that it's UNdeterministic by its very definition. It means it doesn't follow predermined paths or repeatable rules, otherwise it won't be chance at all and if it doesn't it means you can't build a lab protocol around it. You can't include it in a predeterminable scheme and most definitely you can't model it in advance. And that is a consideration I find compoundly missing in the modern origins of Life field although there are few lone voices here and there who point out to the problem but get ignored or outright rejected.
Until you manage to incorporate that chance in both computationally and physically, in the real world wet chemistry of Nature, you will only end up with systems that struggle to reach EQUILLIBRIUM as all things in Nature naturally do. No matter how big, diverse or complex in interactions your system is until you manage to include that fleeing *chane* behaviour in you would end up in an orderly, predictable, streamlined, neat and in all things considerd-DETERMINISTIC system which would do everything any deterministic system likes to do-srives toward predictable defined behaviour evening out and canceling the variations of the system. Pretty much what almost all Artificial life programs known to modern day computer specialists and all neatly deterministic chemical reactions known today do. And we have a nice word for it in science-that is precisely what is alled an EQUILLIBRIUM-a determined and stable state of a system where all the processes goining on in it are in a perfect balance and the state of the system is well known and understood. Problem is by Nature Life is entirely UNdeterministic and if a living system is close to equillibrium it means it is already dead. This is why all methods of modelling Life are doomed to failure. If you can't make your system go OUT of equillibrium instead of trying to reach it, than you are msot definitely not modelling a real living system. However, if you want to make the system go out of equillibrium for real, then you definitely must leave all determinsm behind. And that's a trade off no one had manage to circumvent their way out of. What makes you think you had?
I think you are wrong. Chemical simulations typically have much of Random() function. But for scientific simplicity chemical reaction are choosed in limited but relevanted sets, so we can deduce common principles of evolving.
I don't think life is undeterministic, it's just chaotic. Just like the climate is perfectly deterministic (that is, can be predicted given the initial values of all variables in the system), but tricky to predict.
The problem is: in complex systems we never have ALL variables involved and a minimal discrepancy in the initial values can produce largely different results. Thus, these systems appear to be unpredictable, chaotic and random.
Of course, with increased knowledge we can find out which variables carry the most weight in our models and predictions. And with increased technology we can raise the precision with which we measure these same variables.
What I mean by all this is: life seems like it's a whole different world from abiotic processes, but it's just a bit more complicated. It abides by the same rules as everything else in the universe. And even though these experiments and models are simplified versions of real world phenomena, they help us understand the world better (and are always evolving as our knowledge evolves). The fact that these studies have predictive and explanatory power is a statement to their usefulness.