I am passionate in various topics. At the moment i am stable economically and projecting my life, because i managed to create a start-up about my passion and it is going well, but its been pretty rough path.

Now that i have more time, i want to study.

Topics:

• artificial intelligence (already enrolled in MIT applied data science and machine learning program. Reason, to find solutions to the real world, that can be easy implementable)
• complex systems
• theory of strings, theory of relativity, theory of everything, but in terms of theoretical physics.
• psychedelics, altered states of consciousness (dunno)
• relate all this fractally to music and any passion

I myself have discovered a theory; but have no certificable background to have a voice in these topics. And being able to explain the theory is another topic.

And the other person receiving the theory 100%, another dimension of topic.

So i prefer to start walking this path the traditional way. I would like to head ways like Einstein / Stephen hawking followed, but are kind of outdated today because the fields have diverged through a convergence too much,

Which field converges most? I think complexity sciences.

But does it try to converge the divergent ones? Is there a more theoretical aspect or complexity sciences to be worked on, in order to be able to help it reconnect with its ancestors?

Converge all sciences, but being diverging at the same time, just as it is

hi I have a complex systems related essay to write and I was wondering if somebody could take a look at my plan and give me feedback im just really in my head here about it TT_____TT and also my essay when its done please and thank you

Hi everyone,

I'm a 30-year-old systems engineer keen on advancing my career by specializing in complex systems through a PhD. I'm currently looking at various programs worldwide and considering the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) in Spain. Does anyone here have insights into the reputation of IFISC or any other recommendations for top PhD programs in this field?

Appreciate all your insights and thank you in advance for helping me make this crucial decision!

I am writing a paper and in my results there are decent number of states giving jensen-shannon divergence value zero. I want to characterize and understand what it means for dynamical system. Chatgpt revealed following scenarios :

1. Model convergence: In machine learning or statistical modeling, it might suggest that two different iterations or versions of a model are producing very similar outputs or distributions.
2. Data consistency: If comparing empirical distributions derived from different datasets, a JSD of zero could indicate that the datasets are essentially measuring the same underlying phenomenon.
3. Steady state: In dynamic systems, it could indicate that the system has reached a steady state where the distribution of outcomes remains constant over time.

Please guide me to resources or directions to explore.

Hello everyone,

Having applied for the Complex Systems Modelling Masters at KCL, I would like to know if any of you have taken this course or have any information about its reputation. (And possibly more generally about the disordered systems research group).

For context, I also applied for the franco-italian Physics-Complex-Systems MSc (universities of Turin/Paris). I know a bit more about the proximity of this master's degree to the ISI or ICPT institutes, for example, but I have no idea about the opening of KCL's disordered systems group.

Thanks !

I studied Complex Adaptive Systems in my Master's but a lot of people aren't familiar enough to judge for themselves what that implies about my skillset. As a result I've been trying to describe my duties (ML for modeling manufacturing devices) and skillset (physics-informed ML methods, broad base of physics for rapid adaptation to problem domain).

I've been trying to wordsmith these descriptions into something parseable by people who are at many different levels of familiarity with tech, science, engineering, etc. but it's been difficult.

Do you have any perspectives or techniques you use to describe what it means to have studied complex systems in the rigorous sense?

The Nature of Technology is a book by complexity theorist, Brian Arthur.

In the book, Brian Arthur describes technology and how it evolves.

You might find the book interesting if;

a) You want to develop a few frameworks that will help you develop insights on how to come up with possible inventions or tech start-up ideas.

b) You are interested in how to come up with policies or strategies for corporate research departments, educational institutions, or government policies that will foster the creation of new technology.

c) You want to comprehensively understand if technological progress will slow down or speed up in the future.

In this blog post, I describe a few takeaways from the book that answer those questions and hopefully inspire you to pick it up.

Read the full blog post here.

arXiv: https://arxiv.org/abs/2402.05959

OpenReview: https://openreview.net/forum?id=uCMxeZCp2T

Abstract:

The spectacular results achieved in machine learning, including the recent advances in generative AI, rely on large data collections. On the opposite, intelligent processes in nature arises without the need for such collections, but simply by online processing of the environmental information. In particular, natural learning processes rely on mechanisms where data representation and learning are intertwined in such a way to respect spatiotemporal locality. This paper shows that such a feature arises from a pre-algorithmic view of learning that is inspired by related studies in Theoretical Physics. We show that the algorithmic interpretation of the derived "laws of learning", which takes the structure of Hamiltonian equations, reduces to Backpropagation when the speed of propagation goes to infinity. This opens the doors to machine learning studies based on full on-line information processing that are based the replacement of Backpropagation with the proposed spatiotemporal local algorithm.

https://complexityexplained.github.io/

Fundamental concepts explained, with interactives.

I am not sure if I came to the right subreddit; I’ve never been here before, but…

I feel deeply lonely and scared... :(( I feel like I am swimming in large clouds; I try to grip onto something so fiercely and desperately, but I can't catch nothing. I feel unattached or ungrounded in the reality of human society. I feel like I am far away from it and everyone within it, lost in a dark forest alone with no one to hug for comfort. I try to venture out and explore my surroundings in this scary forest, but I quickly return to a place of comfort as everything else seems so foreign and inconceivable.

I try to piece together a system for almost each thing that arises in my daily life — especially work life — but I fall short, every time. So much of what I want in life seems impossible to me. I have such a rich imagination and creativity about how I want the specifics of things, the way I want them, etc., but they're impossible to achieve, at least all of them together, in this lifetime. They’re not even fully reasonable pursuits in my own eyes despite the immense attachment to them.

I often wish my mind could just let go…. It it can’t.

If there is anyone out there that this resonates with and can relate, and also is secretly seeking a connection where they want to be there for one another in these vast, dark, scary and lonely forests and clouds, then message me.

https://www.theguardian.com/business/2022/jun/03/flash-crash-set-off-by-fat-fingered-citigroup-trader-could-cost-50m

Complex, integrated systems

Their chaos is beautiful.

Message me on chat if you’re interested. My project involves microscopic and how they emerge and the relationships between parts and wholes.

Hi I’m looking for some advice on a good statistical mechanics / complex systems MSc. Any ideas?

I’d really appreciate if some current students could share their experience. In particular is there somebody enrolled at Chalmers or at UniTo ?

Paper: https://arxiv.org/abs/2312.16815

Abstract:

Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed to the cause of individual properties. On the other hand, causality can exhibit emergence, meaning that new causal laws may arise as we increase the level of abstraction. Causal emergence theory aims to bridge these two concepts and even employs measures of causality to quantify emergence. This paper provides a comprehensive review of recent advancements in quantitative theories and applications of causal emergence. Two key problems are addressed: quantifying causal emergence and identifying it in data. Addressing the latter requires the use of machine learning techniques, thus establishing a connection between causal emergence and artificial intelligence. We highlighted that the architectures used for identifying causal emergence are shared by causal representation learning, causal model abstraction, and world model-based reinforcement learning. Consequently, progress in any of these areas can benefit the others. Potential applications and future perspectives are also discussed in the final section of the review.

I want to illustrate emergent patterns in a classroom of children, say 25 kids. I hope what occurs will be analogous to the flocking of starlings or schooling of fish - not similar, but analogous. I want to give them a small number of rules for movement or positioning, and I hope something with noticeable (hopefully dynamic) group structure will appear. Any suggestions?

I was at a the Santa Fe Institute years ago, and remember a speaker mentioning how he suggested rules something like, maybe, "try to remain positioned close to <random person A>, while remaining distant from <random person B>, or, maybe, "try to remain between <random person A, and random person B>. My memory is very fuzzy on the specifics. Can anyone help me out with insights or suggestions? What sorts of rules could I assign kids in a classroom to produce noticeable dynamic patterns?

https://complexity-science.blogspot.com/

New blog on complex systems and math that I enjoy.

Im new to network science and complex systems is there any softaware that I can tinker with?

I’m a prospective PhD student who recently got a lot of interest into complex systems methodologies. Of course I have very limited knowledge on the topic, but I found that there are not much works going on this area as much as I thought it would have. Well, at least that seems like the case in public health.

Is it because this is a relatively new approach, or are there some other reasons? Or do I just have poor research skills?

I work in mental health. I'd like to learn more about complex systems in a mental health context. Are there well known thinkers/authors in this area? Who should I check out? Thanks.

How will that look?

I want to know what comes to your mind when I make this statement :)