Holarchy

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• general intro to holarchy, Koestler, Wilbur and Lent:web of meaning
• OD:holarchy

Internet

• internet (protocols, API(=resource abstraction), ontology)
• protocol stack and abstraction layers (p2p AL), AL vs walled garden
• internet is extensible with new protocols and layers formed wco others
• https://en.wikipedia.org/wiki/Category:Application_layer_protocols
• https://en.wikipedia.org/wiki/Internet_protocol_suite

Decentralisation

• p2p: (decentralisation in general, dimensions and levels of p2p, peer-def-only)

Ontology

• Philosophical ontology
• internet ontology
• foundation ontologies
  • our definition would be that any concept can be defined in an FO, and therefore any concept in any ontology can be mapped into any other, and all FO networks can overlay all others. IOW FOs are potentially unifiable into a network we call the Unified Foundation Ontology (UFO).

Class and instance

These two concepts usually belong in the context of software development, they're usually thought about in the classical OOP context whereby there's a class hierarchy defined which provides the structure and behaviour for the types of objects interacting at runtime. But there are many different forms of that teh class and instance relationship can take in the context of software development, and the paradigm that most closely matches our system is the so-called "mixin" pattern.

This is where one class is not defined as being based on another and extending it, but, rather other classes can be thrown into the class as children that extend its functionality. Actually the parent in this case becomes a subscriber of each mixin child, so in effect they're still a class-child. The key improvement with the mixin model is that the functionality is expressed purely in terms of the instance structure allowing the classes functionality to relate purely to it's fundamental purpose of categorising functionality.

But these concepts are much more fundamental than software development, they're concepts of the philosophical discipline of ontology. In fact they're concepts that belong in a unified foundation ontology.

• C&I are non-local and local
• non-local and local are the same dynamic as p2p, generalised so all can be a p2p group
  • one is dispersed in space and time, i.e it's not connected to actuality,
    • instance extends class, actuality extends possibility, it's the abstraction layer
  • connected into time and space (focus and resource)
• (really the class of class & instance)
• (the instance of class & instance)

Holarchy

• harmonious organisation
• integrative and self-assertive
• the future of holarchy (from AI article)

A three layer model

The holarchy design pattern is best understood in terms of three general abstraction layers. A new abstraction layer can re-organise computational resource into new possibility space that has a completely new own system of causality.

Layer 1

Layer 1 defines the fundamental data structure and its dynamics. It's a one-to-many tree where each node ... todo multiplexed TDBU

The defining characteristic of this layer is class-instance functionality. This can also be thought of as the functionality of functions themselves, i.e. the ability for named patterns of activity to execute in a private scope, and for such patterns to be composed into larger patterns.

The class side is composed of the public interfaces of these patterns, the outward facing aspect that connects to other patterns in their local scope, and together they form an entire ecosystem in the form of an ontology.

The instance side is the private inward-facing implementation of the patterns, which acts on state just like a function with it's internals encapsulated behind the public interface.

From the perspective of execution within the internal encapsulated implementation, the wider multiplexing pattern cannot be seen. Time only exists while there is executional focus, and so from this perspective it is an axiomatic phenomenon that all threads undergo change in linear time together.

By the same token, this inner perspective can also not see the opposite dynamic to the top-down multiplexing, which allows dispersed clones of the same class to be connected. This "non-local" connection is axiomatic and inherent from the inner perspective.

Layer 2

This new layer is the perspective from the inside outwards. From one of the many continuous threads within the multiplex data structure introduced in the first layer, out to its sibling context and parent.

The defining characteristic of this "inside-out" layer is that it enables the new perspective of linear time within which self-organisation through feedback is possible.

A self-organising system is a system that undergoes change in accord with it's own state and structure. In terms of our data structure, this makes a logically disconnected abstraction layer. Although this layer depends for its existence and operation on the first layer, this layer exhibits a brand new source of causal potency that is completely independent from the first layer logically. All causal chains and cascades are determined only by the interactions of these new layer 2 linear-time feedback structures. We say such a structure is a representation of a pattern.

Patterns are the layer 2 version of the layer 1 class concept. They can be thought of in both in the sense of behaviour patterns and design patterns. It's easy to see how these two forms of pattern also correspond to the concept of class.

...leading to a new causal foundation in the form of patterns and streams of activity. Classes in this context become packages of activity streams constituting an ecosystem of patterns, and a manifest structure of dynamically fitting representations.

The patterns introduced in this layer embody a scale-independent paradigm of processing enabled by the multiplexing. These patterns can contain any complexity of parallel and serial thread structures.

This is a declarative paradigm of selection and action in which both sides are free to become arbitrarily complex. Selection and action form a feedback loop, because the selection side is about assessing potential work, and the action side is about reducing that potential.

This loop construct of selection and action with respect to self in linear time is the fundamental "atom" of life in layer 2. In terms of user interaction, this layer can be thought of as the "application-ability", the ability for arbitrary applications to be created.

The general high level structure of level 2 operational loop is the top-down "fitting" of the local representation to the current consensus state and to the class. And the bottom-up process of allocating energy to the appropriate set of class to act on the current situation (fitting the salience landscape to the representation).

The subjective POV with its patterns and representations in linear time, can instantiate a set of general concepts such as work, cost, expectation, performance, reputation etc. Instantiation is the knowing of something in a participatory way, it's a concept that has become embodied in your own patterns of behaviour.

In summary, layer 2 introduces the organisation-ability (a.k.a the common logistic), basically the ability to work with patterns and representations in the subjective linear time threads provided by layer 1.

• class is used mixinly, instance is a runtime-loop-mixin which is a representation
  • representation structure exists and evolves causally in layer 2 (but depends existentially on layer 1), the structure can only evolve or undergo any kind of change at all in layer 2, because it's formed from subjective meaning
• explain ito queries vs indexes (representations are maintained, connected to activity stream)
• we might call this the libre society...
• the representation represents both current state and the pattern (i.e. its a representation and a representative)
  • it publicly represents both of those aspects,
  • and it operates internally within that public context

Layer 3

Layer 3 then defines a specific application which opens up a yet another new abstraction layer also introducing it's own new system of causality.

Layer 2 introduced the fundamental time and work related concepts that underpin the concept of agreement. In layer 3 these are extended into a higher level of organisation to yield contracts for resources, value assessment, services, and quality of service. This also includes information (think "information market") accuracy and objectivity where the authority aspect of an information source is the reputation (reputation being a landscape over the ontology).

• market and organisation
• universal interface: the natural extension of universal representation
  • IF extends layer 2 (self-representation) which already has the public and private sides to the representation
  • so being an interface of itself, it's usability involves two general applicational aspects to deal with market and organisation (self-as-market-participant and self-as-organisation)
• layer 2 is "interface-ability" with reports and related action policies, but layer 3 is a specific interface paradigm, a specific "application" intended for interaction with self-as-org and with society as a market-participant
• layer 3's main theme is harmonious organisation, which functionally is about balance (between the two behaviours, two both sides of an exchange, and other context-dependent dichotomies)

. . .

In summary, layer 3 extends the ability to organise logistically provided by layer 2 into a definite organisational pattern. This pattern forms a new abstraction layer, or arena, in which all the participants are organisations interacting with a common protocol that results in a harmonious evolving society.

Organisation and market

• social mechanism, social contract/protocol
• self-as-organisation and self-as-market-participant
• higher level concepts in organisation, concepts only possible wco subjective being
• exchange, economy, work
• specialisation & evolution (organised extension)

Organisational representations

The ultimate purpose of the representations is to represent our entire continuously growing and diversifying informational life.

Maintaining this structure is very administration intensive, due to the great variety of protocols and applications that need to be connected to. One solution would a huge active user base that collectively are able to respond to these changes in a timely fashion. Due to the organised nature of the holarchy, these adjustments made in one local context immediately becomes available to all instances of that same class of context.

But the other solution is that it will soon be a very practical job for LLM AIs, they are very good at connecting protocols with minimal assistance in nearly all cases. The foundation use that the holarchy will have for AI is as a representation administrator.

The idea is not that AI has to actually sit there making connection regularly to keep the local data up to date. A representation structure should have instantiated all the necessary connections in the most resource efficient way it can, which would most likely be using an available language in the system such as C or Python. The administration work involves ensuring these connectors are functional.

AI opens up the possibility of practically maintaining representations involving diverse non-standard connections like scraping websites or accessing applications on behalf of users.

Universal interface

The universal interface is a natural step to take if you already have a universal stream-based representation structure of all your information and how it relates together through time. But interestingly this idea of a generic stream-based interface has come and gone a few times over the years, probably most famously in the Google Wave product from back in 2009.

I'm not sure why the idea hasn't gained more traction, but it could well be due to the difficulty in maintaining connectivity across so many diverse and changing protocols, and possible also related to the fact that the idea opposes the general corporate agenda of reinforcing the "walled garden" model. In any case, I believe the "universal interface" is going to make a strong come-back now that AI can help us maintain, share and evolve our own interface paradigms amongst ourselves independently.

Specifically in the Organic Design context, the universal interface.... is an organisation interface... todo...

AI is playing an increasingly important role in connecting systems. It can understand foreign APIs from their documentation, and it knows how to make endpoints to such APIs in any clearly described executional context.

For example, an endpoint to the Wikipedia API can be made available in a Linode server if access credentials are available. This is a simple pattern, but its real power comes from how generically applicable it is with AI. In this context a language model can be used as a kind of "universal middleware".

Connection of diverse systems really is a perfect use-case for language models because interfaces are descriptions of communications behaviours in different languages used by various instances in the field. Connecting these interfaces together to abstract the resources they represent is a language-centric process, but yet is not completely deterministic (especially in the context of human interfaces), one-size-fits-all templates are impractical because things change too often and the diversity of requirements is too great.

So LLMs are the perfect tool to make possible a universal ontology of all the resources, interfaces and their instances and profiles etc.

A number of people, ourselves included, have envisaged the idea of such a "universal interface" or "everything app"....

• more exotic connectors can also be built that AI can then utilise such as a DOM connector that basically allows an URL to be present in the holon as a continuous browser DOM document session.
• and of course abstractions over those for representing web app states etc

Corporations are attempting to restrict API access to humans (or to charge large fees for non-human access), to try and mitigate the coming exodus of real human attention from their interfaces. But AIs can easily hack those systems by behaving like their human agents, and asking the human agents to renew sessions when necessary. So eventually I think they'll have to accept that the universal interface to all applications is inevitable.

AI can also convert between formats, or at least guide the development of such conversions. E.g. to aggregate or distribute posts in multiple social platforms.

AI can integrate UIs to present local session state

The holarchy is the category tree of connection patterns and abstractions, and the tree of associated instances being maintained.

The AI has a continuous root session that contains the entire history of the local holon including all the AI interaction over that time. Local instance in holons are like a CWD for interacting with AI in the holarchy.

AI could, without too much more trouble, suggest curations, warn of disorganisation (like repeated concepts), and help with relevant options.

The connections are bidirectional where possible, so the local representation can be an organisational interface.

A universal customisable interface over all our IT world, to be able to query, select and report on the information, and to activate pipelines (workflows) on schedule and in accord with reporting

If we think of the concept of an ideal universal operating system, it would be:

• can connect with all our data on our behalf
• an awesome user experience with variations to suit everyone
• completely libre: easily customisable, mergeable and shareable
• works, organises and searches transparently for us behind the scenes
• flexible querying, selecting and organising of "our stuff"
• easy reporting and assessing of what's going on
• management of opportunity and potential
• easy interaction with the wider community ecosystem and market
• managing presence in multiple networks of varying complexity (e.g. blogs, social, developer, biz)

• fitted representation
• shared ontology

AI and holarchy

The Organic Design the Holarchy would also have an AI, which can appear as a "presence" at the centre of every POV so that it can assist in decision making optimised to serve in a harmonious balance between that perspective and the parent. Surplus profit is passed upwards, which is how contributing to the whole is expressed. The ultimate beneficiary is the Source of truth and awareness.

AI puts the libre software minority group on a level playing field with corporate offerings in the operating system realm. Because it's precisely what they're better at that AI also excels in - staying up to date, distribution, logistics, pipelines and organisation etc.

The "human" creative part concerns more general patterns that change less frequently and, being of a more general nature, can be maintained by a small group as effectively as a large one. For example think of how often business logic patterns change compared to UI patterns, and the former are applicable across the spectrum of the latter.

Corporate AI is incentivised not to develop offline-first technology, it prefers the client-server model to maximise dependence and control, and to maintain secrecy over their system. This will make offline-first systems competitive and much more functional and independent. They will be the only option when denied internet access.

The collective consciousness (also called the noosphere), is tightly controlled by media narrative and behaviour manipulation, and soon by AI - we need this technology to be rooted in truth, not in one powerful elite or another.

See also

• Artificial Intelligence
• Peer-to-peer