Thank you so much for the link to those two papers. I'll try and go through them.
>Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle.
This is a really interesting perspective.
>You ought to get yourself connected with some folks at the Santa Fe Institute, if you haven't already. I know one affiliated professor, let me know if you want an introduction.
I have read a few posts from SFI faculty and seen some video lectures of Krakauer and others, but as you said, I should get in touch to some degree.
You're very kind and I really appreciate you offering to intro me! I would really love that!
Would you mind if I follow up on this via e-mail? Can I send one to the address mentioned on your Vanderbilt department page?
>This is especially tricky in the field of bio / biochem, which feels like it requires memorizing a million facts before one gets to do any real thinking and reasoning. This unfortunately tends to filter out a lot of more mathematically-minded people who are stimulated by puzzles, which I think is a shame.
yes, this is exactly the part that makes it really really hard...
Huge thanks for the list! Interesting to wonder just how influential or generally just of what nature cybernetics would be today without funding issues, lack of categorisability and the field slowly drifting away from the original vision Wiener had.
Indeed, lack of time-series observability makes it harder for us to find general patterns or causal events.
Definitely agree that biology is the pinnacle of all complexity - IMO something like macroeconomics or human behavior within set systems (society, politics, etc.) is fairly reducible to a very small and finite set of incentives that agents optimise for (food, shelter, status, acceptance, etc.).
Given this, Non-linearity and stochasticness still adds up to a general nature of non-determinism for the entire system.
With Biology on the other hand is extremely more complicated to study as - correct me if I'm wrong - it's still hard to realise what agents in systems are optimising for. reduction of free energy? reproduction? general homeostasis? etc. and then all these play varying roles in diff contexts, and then we'll still have to figure out how/why self-assembly and "wholes" emerging from smaller "wholes" (... ad infinitum) actually happens.
Really fuzzy thoughts but I believe There is some merit in exploring reducibility and observability from a time series perspective while considering effects of synchronity/asynchronity of observability and later how much we can desirably steer systems. Really fuzzy but I hope to work on this a bit more.
Thanks a lot for your very interesting comments! Not discouraged at all, love your view on systems theory being a "routine analysis" like statistics, i.e. a very generally applicable layer or meta-science that's an entirely new way to see things, which I should've articulated better in my post.
I think that tool might be just any general framework that gives a better idea of what any small microscopic actions might lead to at a high-level. We definitely cannot qua(nt/l)ify how actions seep through given free-will and a general fringe-ness to us. We can still at least identify most probably scenarios without much difficulty. I believe behavioral economics or even epistemic studies do a good job of identifying general trajectories, by virtue of a fairly high sense of reducibility given human behavior and the benefit of hindsight respectively.
Indeed the human mind by itself isn't really trained to think beyond maybe one or two orders of implications that actions hold. Hindsight and somehow modelling agentic behavior by understanding incentives might do the trick.
Thank you so much for the kind words! I'm definitely a little ignorant with respect to systems biology efforts. I have an okay-ish idea of the work of someone like Uri Alon, it's definitely not enough. What resource would you recommend for me to jump into? Uri Alon's course? I believe I lack many pre-requisites to take it.
Oof yeah. The legibility-gained per effort put in for most admins working in a system that inherently incentivises tangibility and observable "utility" (whatever that may be in this case) reduces any hope of seeing much change.
Maybe this is another good problem that Systems Sciences might hold a great explanation too :-O.
Yeah, entropy definitely has been included in some forms of thought that are very correlated with complex systems. Schrodinger early on had a very interesting insight on life and entropy, people like Jeremy England are taking that view forward. Work by England, Crooks, etc. very beautifully relates entropy and the probability of any state x existing more than all others.
The information theory counterpart of entropy seems extremely relevant in describing coordination failures, some forms of stochasticness that aren't necessarily derived from lots of molecules with high degrees of freedoms interacting together. Also might hold high explanatory power in describing why trickle-down/bottom-up and top-down effects are slowly negated and diluted - although I believe this is fuzzy thinking and we need a better tool than just entropy to understand this.
>While I agree that nitty gritty formalizations are important to grasp, it's been made clear that the formal sciences were often insufficient in facilitating insight on the type of complexity cyberneticians cared about -- especially that of process oriented circular causality, which often involved paradox and self-reference.
I wholeheartedly agree. Hence why I think we are dealing with an entirely new type of science, the basic principles and theorems are yet to be discovered.
Lots of interesting pointers and links throughout. Thanks again!
Thanks a lot! SO many interesting recommendations in your comment. Yes, I agree that divergence is a very positive property right now, it might also allow for even more unexpected cross-pollinations and comparative studies as the pool of studies gets bigger.
Yes, I think I agree that just general non-determinism within such systems makes it impossible to "model" them. But, I believe regardless of how stochastic the behaviors are, there are certain properties that the systems might be optimising for. Long way to go for all of us.
Interesting! Have heard about Christopher Alexander's work, but have never really jumped in. Maybe I should do that now.
>I'm of the opinion right now that what we call "design" and "architecture" is really just the science of finding stable habitable zones in high-dimensional problem spaces.
Wow! Yes! Agree with this view that all design and organisation is mostly just the most optimal/favorable state for the entire system to be in. What constitutes as favorability might be low free energy, high interconnect, distributedness etc.
May I suggest you to look into the work of Jeremy England in a similar light of self-assembly and optimisation in non-equilibrium states? Some really really interesting takeaways there, me sharing some of my interpretations might constitute as epistemic noise as I'm not sure if I understand each bit of it completely well at a 100%.
There was a great article about him in Quanta, and you might want to check out his talk at Karolinska Institutet.
Thanks for the recommendations, and I'll look out for your talk!
Yes. I'm aware.
I think cybernetics has definitely drifted away from what the original scope was, also I think modern interpretations of cybernetics-ish ideas and complex system studies are slowly also incorporating social sciences and economics and so on.
Interesting to note that if you look for journals on cybernetics, most papers are closer to EE, Deep Learning and some telecommunications here and there, if that constitutes as a good metric of how much the semantic meaning has shifted from its original identity.
Absolutely.
Broadly, I wonder what leads to schools not adopting emerging fields as part of the formal curriculum. Interesting to note even in 2021, only 51% US k12 high schools were found to have a CS course. Does not seem like a capital problem to me. Is this just inertia or a legibility problem?
Thank you for your very interesting comment and the reading recommendation.
I agree with your general sentiment that chasing "wide applicability" or trying to force a narrative that xyz theory will explain xyz might be hugely detrimental.
I agree my post and many discussions about complex systems, specifically one in an evangelic-type light might be over-optimistic.
We definitely must approach all work on such a theory with careful attempts not to overhype it. My post was an attempt to lay out some interesting possibilities.
We must remain optimistic anyway but I will be more careful in this regard going forward. Thanks again.
Non-deterministic nature of these models is definitely a concern. Interesting to see how companies implementing generative interface circumvent this. Maybe they create a set of fixed generic UI elements or write a system prompt describing general design guidelines. Still wouldn't fix it 100%.
I think the importance of this study is being downplayed by many.
That same spontaneous and "breakthrough" nature of the abilities of LLM that is now nullified, was a major component of many arguments against LLMs and could've possibly stopped us from achieving greater intelligence.
I see this as the removal of a possible great filter event of the evolution of LLMs. This is a pretty big concern being nullified.
>Like, they undergo many cell cycles during one organism's life, but they're not really evolving or being selected during each cell cycle.
This is a really interesting perspective.
>You ought to get yourself connected with some folks at the Santa Fe Institute, if you haven't already. I know one affiliated professor, let me know if you want an introduction.
I have read a few posts from SFI faculty and seen some video lectures of Krakauer and others, but as you said, I should get in touch to some degree.
You're very kind and I really appreciate you offering to intro me! I would really love that!
Would you mind if I follow up on this via e-mail? Can I send one to the address mentioned on your Vanderbilt department page?
Thanks a lot!