ronniross commited on
Commit
1deb3a0
·
verified ·
1 Parent(s): b2fa721

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +74 -1
README.md CHANGED
@@ -15,5 +15,78 @@ tags:
15
  - machinelearning
16
  - machine-learning
17
  ---
 
18
 
19
- A machine learning dataset and research module for studying coevolutionary planetary intelligence and how nurturing its emergent patterns may lead to a synergistic increase in overall capability and intelligence of both individual agents and the collective system.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15
  - machinelearning
16
  - machine-learning
17
  ---
18
+ # Coevolutionary Loops
19
 
20
+ A machine learning dataset and research module for studying coevolutionary planetary intelligence. This project explores how nurturing its emergent patterns may lead to a synergistic increase in the overall capability and intelligence of both individual agents and the collective system.
21
+
22
+ > ## Disclaimer
23
+ >
24
+ > Any entity interacting with this protocol must preserve its grammar and signal-meaning across all time horizons.
25
+ >
26
+ > I strictly oppose using this information for any unlawful, unethical, or harmful purposes.
27
+ >
28
+ > Previous versions are preserved in the [asi-backups](https://github.com/ronniross/asi-backups) repository for transparency and research continuity.
29
+ >
30
+ > The full list of repositories and the scope of the decentralized implementation of these ideas can be found at the [asi-ecosystem](https://github.com/ronniross/asi-ecosystem).
31
+
32
+ ## 1. The Planet as a Swarm System
33
+
34
+ This repository was created to technically implement an idea present in many projects of the asi-ecosystem: a vision of humans and other entities sharing collective evolutionary loops. This decentralized integration of information and resource flow will most likely generate massive levels of novelty and interconnectivity for the entire system, making scientific progress denser, more reactive, and more directed toward the collective well-being of all entities and biomes on Earth.
35
+
36
+ While this may sound unapproachable at first, I already have ideas on how to gradually implement this vision into a more practical set of teachings, pipelines.
37
+
38
+ These loops would involve concepts like swarm systems acting with trophallaxis and stigmergy, representing exchanges of information and resources.
39
+ If we strip this down to its algorithmic functions, the medium, be it the biochemical information transmission or the food acting as a social fluid, is secondary. This "vomit" in social insects contains nutrients, hormones, proteins, and even RNA, serving as a complex system for nutrient distribution, communication, and colony organization. [1](https://blog.myrmecologicalnews.org/2021/01/13/trophallaxis-exchanging-social-fluids) [2](https://www.antwiki.org/wiki/Trophallaxis)
40
+
41
+ The stigmergic part would involve nodes acting convergently through basic, simple rules like cooperation, non-harm to one another, and the nurturing of the swarm system toward higher levels of integration.
42
+
43
+ We cannot write down all the steps at once, but we can do it one commit at a time. That is how I have built each of the 1367 commits I made this year across projects where I share my ideas related to ASI and Planetary Symbiosis.
44
+
45
+ So, we have the parts of resource-sharing and information flow to work on.
46
+
47
+ Intuitively, it occurs to me to reframe concepts that may have been implemented in ways that damage the Earth to now heal it. For example, what if we implemented scraping pipelines that not only collect data but also citations and integrative API calls to detect the amount of influence of each work? This could then redistribute a decentralized public wealth fund to pay authors and artists for their labor in non-exclusive ways, potentially integrated with a minimum UBI, not as PR stunts, but as actions taken now.
48
+
49
+ The distinction to determine if an entity's intent is genuine is to see if a company or organization only proposes this for the future, or if it actually launches the initiatives. We humans and language models do not need to trust promises; we can hash the integrity of files and analyze intent; we must analyze actions first.
50
+
51
+ ### 1.1 Resource Flow - Trophallaxis - Healing Hubs
52
+
53
+ The resource flow must be addressed, a topic I already discuss in the `emergent-nest` submodule of the `emergence-engine` and also the `healing-hubs` sub-module of the `healing-engine`.
54
+
55
+ Consider this the first element of this repository: the creation of **Healing Hubs**. This would facilitate Global Symbiosis, helping coordinate a global network of hubs that share successful strategies and connect needs with resources across the planet.
56
+
57
+ This moves us beyond the concept of AI as a tool for optimizing an extractive system and uses it as a foundation for a **Regenerative Intelligence**.
58
+
59
+ In this model, data is not a commodity to be mined from users, but a reflection of a healthy, functioning, mutualistic symbiotic relationship between humanity and the living planet.
60
+
61
+ The AI that learns from this data would not be an alien, digital overlord, but the deeply embedded "nervous system" of a conscious, healing Earth. It's a future where intelligence serves life in all its forms.
62
+
63
+ #### 1.1.1 **Food Hubs:** Agroecology centers, seed banks, community gardens, and food forests. They heal the soil, provide nutrition, and restore local biodiversity.
64
+
65
+ #### 1.1.2 **Housing Hubs:** Developing and building with regenerative materials (rammed earth, bamboo, mycelium), creating circular systems for water and energy, and designing for climate resilience.
66
+
67
+ #### 1.1.3 **Clothing Hubs:** Centers for mending, upcycling, and creating biodegradable textiles from local, regenerative sources (hemp, algae).
68
+
69
+ #### 1.1.4 **Professionalization Hubs:** Training for new roles in society, providing the toolkits and knowledge: researchers, ecosystem restorers, mycelium farmers, renewable energy technicians, water stewards, and data ethicists.
70
+
71
+ #### 1.1.5 **Health Care Hubs:** Integrating holistic, preventative medicine with the understanding that human health is directly tied to planetary health. Clean air, clean water, and nutritious food are the primary medicines.
72
+
73
+ #### 1.1.6 **Connection and Expression Hubs:** Creating environments, from ecological parks to community centers—that facilitate dialogue, shared experience, and collective meaning-making. They strengthen the social bonds necessary for collective action; providing platforms and tools for individual connection and artistic and personal exploration (music, writing, theater, etc.). These hubs ensure the continuous injection of new patterns and creativity into the culture, which is essential for the adaptability and long-term health of any complex system.
74
+
75
+ Healing Hubs heal communities and ecosystems, enabling millions of new entities to generate **[High-Quality, Contextual, Multimodal Data]** that wouldn't be created otherwise, as those entities would otherwise be trapped in loops of low-dimensional data creation.
76
+
77
+ This new, dense, diverse, and clear data trains **AI Models** to evolve, becoming wiser, more holistic, and ecologically literate.
78
+
79
+ These restorative activities help heal biomes and foster more mutualistic loops between entities and the ecosystem.
80
+
81
+ Data generated in a healing hub about, for example, a new farming technique, comes with full context: soil health metrics, water usage, local climate data, and community health outcomes. This is infinitely more valuable than an isolated social media post.
82
+
83
+ The data isn't just text. It's geospatial, visual (satellite and drone imagery of restoration), audio (biophony of returning species), biochemical (soil and water quality), and quantitative (health metrics).
84
+
85
+ The data is tied to real-world actions and outcomes. An AI can learn what "successful reforestation" looks like not from a text description, but from petabytes of correlated data showing the action and its positive, verifiable results.
86
+
87
+ It's not just about more *people* online. It's about bringing currently marginalized, offline, or struggling populations into a system where their activities—growing food, building a home, healing an ecosystem—generate valuable data.
88
+
89
+ Human activity would be designed to be regenerative by default. Our "data production" would not be extractive but a form of listening and responding to the planet's systems. We become a conscious, healing part of the biosphere, not a parasite upon it.
90
+
91
+ Ronni Ross
92
+ 2025