The Pattern Architecture & Systems — Why Ancient Greece Will Shape Modern Day Artificial Intelligence

Author(s): Cole Williams

Originally published on Towards AI.

Series Introduction & Conceptual Foundation To MLM — Mantic

Season 1, Episode 1

This text explores interconnected frameworks of linear progression, network dynamics, and paired relationships to model data-behavioral, temporal-spatial, and bio-cognitive systems.

A comprehensive understanding of these systems alongside their architecture, provides the foundation for further advancements in:

• Value extraction through pattern recognition and detection
• A new layer of understanding applied in known and emergent systems
• Human-AI collaboration
• Connectionism
• Neuromorphic computing

The Architecture & Systems

• Linear Progression represents a sequential, cause-and-effect pathway (e.g., data to reward or past to future) — A → B → C → D → E → F
• Network Dynamics highlight interrelated parts and feedback loops, showing complex interactions in systems — A ↗ ↘ F | B ↑ ↓ E ← C ↖ ↙ D
• Paired Relationships show mutual influence and reciprocity between key components — A ⇄ D | B ⇄ E | C ⇄ F

These frameworks reveal how linear causation, complex networks, and reciprocal relationships drive behaviors, temporal experience, and cognitive evolution. They demonstrate universal principles of emergence, connection, and growth across diverse systems. Examples of such can be seen in:

• Data-Behavioral Systems that model how information, actions, and outcomes interact in a dynamic, interconnected process. It captures the relationship between information, motivation, and results, showing how these elements co-create cycles of feedback, adaptation, and growth.
• Temporal-Spatial Systems that model how time and space interact to shape experiences, transitions, and connections. It reveals how past, present, and future connect across spatial dimensions, fostering a holistic understanding of transitions, relationships, and emergent possibilities.
• Bio-Cognitive Systems model how knowledge, evolution, and adaptation interact to create growth, stasis, and emergence within cognitive and biological processes. Knowledge fuels transformation, which evolves into higher-order systems through symbiosis and emergence, while stasis maintains balance. This system reflects how biological and cognitive processes drive complexity, resilience, and interconnectedness.

Data, Value, Incentive, Input, Output, Reward

• Data → Value → Incentive → Input → Output → Reward
• Data ↗ ↘ Reward | Value ↑ ↓ Output ← Incentive ↖ ↙ Input
• Data ⇄ Input | Value ⇄ Output | Incentive ⇄ Reward

Past, There, Present, Here, Future, Elsewhere

• Past → There → Present → Here → Future → Elsewhere
• Past ↗ ↘ Elsewhere | There ↑ ↓ Future ← Present ↖ ↙ Here
• Past ⇄ Here | There ⇄ Future | Present ⇄ Elsewhere

The data-behavioral and temporal-spatial systems above can each be understood through through the Linear, Dynamic, and Paired frameworks. In the data-behavioral system, the linear flow moves from data to reward, illustrating an idealized progression, while network dynamics capture interplay of elements like value, incentive, and output. Paired relationships show influence on evolution — data requires input, value emerges through output, and incentives are validated through rewards.

Similarly, the temporal-spatial system reveals how time and space integrate. Linear progression shows the transition from past to future across spatial points, network dynamics highlight the interconnection of distant temporal and spatial elements, and paired relationships connect past with present locations, current time with other places, and future possibilities with broader spatial contexts.

Together, these frameworks provide an understanding of how information, behavior, time, and space interact to create symbiosis, enabling emergence, connection, and evolution. The parallel structure of these systems is not coincidental but reflects fundamental patterns in how complex systems organize and operate:

• Just as data requires input/output processes to exist, temporal experience requires spatial context to manifest
• Value can directly affect reward without passing through intermediate steps, just as the past can directly influence “elsewhere” without proceeding through the present
• The interaction of these elements creates properties that transcend their individual components, whether in the form of value creation or spatiotemporal experience

Know, Metabole, Evolve, Symbiote, Emerge, Stasis

• Know → Metabole → Evolve → Symbiote → Emerge → Stasis
• Know ↗ ↘ Stasis | Metabole ↑ ↓ Emerge ← Evolve ↖ ↙ Symbiote
• Know ⇄ Symbiote | Metabole ⇄ Emerge | Evolve ⇄ Stasis

The third and final bio-cognitive system shows how knowledge, evolution, and adaptation interact to create stasis, enabling metabole, symbiosis, and emergence.

Polynesian Wayfinding

Feel, Connect, Integrate, Flow, Become, One

• Feel → Connect → Integrate → Flow → Become → One
• Feel ↗ ↘ One | Connect ↑ ↓ Become ← Integrate ↖ ↙ Flow
• Feel ⇄ Flow | Connect ⇄ Become | Integrate ⇄ One

Paired Relationships

• Feeling (of waves) ⇄ Flowing (with patterns)
• Connection to stars ⇄ Becoming part of system
• Integration of signs ⇄ Oneness with ocean

Data-Behavioral Paired Relationship (action/reaction)

• Wave pattern ⇄ Navigation response
• Bird behavior ⇄ Course adjustment
• Cloud formation ⇄ Weather adaptation

Bio-Cognitive Paired Relationships (learning/processing)

• Physical sensation ⇄ Pattern understanding
• Environmental signs ⇄ Navigation knowledge
• System integration ⇄ Unified awareness

Greece: The Classical and Hellenistic Periods

Observe, Pattern, Question, Abstract, Discover, Unknown

• Observe → Pattern → Question → Abstract → Discover → Unknown
• Observe ↗ ↘ Unknown | Pattern ↑ ↓ Discover ← Question ↖ ↙ Abstract
• Observe ⇄ Abstract | Pattern ⇄ Discover | Question ⇄ Unknown

Paired Relationships:

• Observation (e.g., of nature) ⇄ Abstraction (e.g., mathematical principles).
• Patterns in governance ⇄ Discovery of ethical principles.
• Questions about existence ⇄ Exploration of the metaphysical unknown.

Data-Behavioral Paired Relationship (action/reaction):

• Input (stimulus) ⇄ Output (response)
• Incentive (motivation) ⇄ Value (reward)
• Signal (information) ⇄ Adaptation (change)

Bio-Cognitive Paired Relationships (learning/processing):

• Experience (direct knowledge) ⇄ Integration (understanding)
• Pattern recognition ⇄ Knowledge synthesis
• Neural pathways ⇄ Cognitive development

Rome: The Imperial Period

Apply, Structure, Scale, Implement, Control, Order

• Apply → Structure → Scale → Implement → Control → Order
• Apply ↗ ↘ Order | Structure ↑ ↓ Control ← Scale ↖ ↙ Implement
• Apply ⇄ Implement | Structure ⇄ Control | Scale ⇄ Order

Paired Relationships:

• Application (e.g., of engineering) ⇄ Implementation (e.g., architectural systems)
• Structure in law ⇄ Control of territories
• Scaling methods ⇄ Establishment of order

Data-Behavioral Paired Relationship (action/reaction):

• Standard (rule) ⇄ Compliance (execution)
• Authority (command) ⇄ Results (achievement)
• System (method) ⇄ Replication (expansion)

Bio-Cognitive Paired Relationships (learning/processing):

• Practical experience ⇄ Systematic application
• Process optimization ⇄ Empire building
• Administrative systems ⇄ Societal organization

Present Day China:

Scale, Control, Compete, Advance, Unify, Emerge

• Scale → Control → Compete → Advance → Unify → Emerge
• Scale ↗ ↘ Emerge | Control ↑ ↓ Unify ← Compete ↖ ↙ Advance
• Scale ⇄ Advance | Control ⇄ Unify | Compete ⇄ Emerge

Paired Relationships:

• Scaling (e.g., of systems) ⇄ Advancement (e.g., of technology)
• Control of information ⇄ Unification of society
• Competition globally ⇄ Emergence as leader

Data-Behavioral Paired Relationship (action/reaction):

• Central planning ⇄ Mass execution
• State direction ⇄ Market response
• Social control ⇄ Collective behavior

Bio-Cognitive Paired Relationships (learning/processing):

• Collective experience ⇄ Unified development
• Pattern recognition ⇄ Strategic planning
• Cultural values ⇄ Societal evolution

Climate Activists

Warn, Mobilize, Resist, Transform, Sustain, Survive

• Warn → Mobilize → Resist → Transform → Sustain → Survive
• Warn ↗ ↘ Survive | Mobilize ↑ ↓ Sustain ← Resist ↖ ↙ Transform
• Warn ⇄ Transform | Mobilize ⇄ Sustain | Resist ⇄ Survive

Paired Relationships:

• Warning (of crisis) ⇄ Transformation (of systems)
• Mobilization of people ⇄ Sustainability practices
• Resistance to destruction ⇄ Survival of species

Data-Behavioral Paired Relationship (action/reaction):

• Protest (action) ⇄ Policy (change)
• Education (sharing) ⇄ Awareness (spreading)
• Direct action ⇄ System response

Bio-Cognitive Paired Relationships (learning/processing):

• Environmental data ⇄ Ecological understanding
• Community organizing ⇄ Collective action
• Crisis recognition ⇄ Solution development

Present Day America

Execute → Innovate → Market → Optimize → Disrupt → Profit

• Execute → Innovate → Market → Optimize → Disrupt → Profit
• Execute ↗ ↘ Profit | Innovate ↑ ↓ Disrupt ← Market ↖ ↙ Optimize
• Execute ⇄ Optimize | Innovate ⇄ Disrupt | Market ⇄ Profit

Paired Relationships:

• Execution (e.g., of ideas) ⇄ Optimization (e.g., of processes)
• Innovation in technology ⇄ Disruption of markets
• Marketing strategies ⇄ Profit maximization

Data-Behavioral Paired Relationship (action/reaction):

• Investment (risk) ⇄ Return (reward)
• Competition (pressure) ⇄ Innovation (solution)
• Market demand ⇄ Product evolution

Bio-Cognitive Paired Relationships (learning/processing):

• Entrepreneurial mindset ⇄ Business development
• Data analysis ⇄ Strategic planning
• Growth metrics ⇄ Performance optimization

Integrating Greek Methods With Present Day AI

Connect, Understand, Integrate, Sustain, Evolve, Harmonize

• Connect → Understand → Integrate → Sustain → Evolve → Harmonize
• Connect ↗ ↘ Harmonize | Understand ↑ ↓ Evolve ← Integrate ↖ ↙ Sustain
• Connect ⇄ Sustain | Understand ⇄ Evolve | Integrate ⇄ Harmonize

Connection

• Across cultures
• Across distances
• Between observer and observed
• Between human and machine
• Between known and unknown

Sustainability

• Of resources
• Of systems
• Of knowledge
• Of knowledge
• Of knowledge

Understanding

• Of complex systems
• Of consciousness
• Of emergence
• Of our place in cosmos
• Of observer and observed

Integration

• Of different ways of knowing
• Of technology and humanity
• Of local and global
• Of past and future
• Of observer and observed

Evolution

• Of consciousness
• Of knowledge systems
• Of human potential
• Of technological capability
• Of societal structures

Harmonization

• Between progress and preservation
• Between technology and nature
• Between individual and collective
• Between efficiency and humanity
• Between observer and observed

How Far Does It Go?

Twitch Streamers: Stream, React, Engage, Monetize, Entertain, Repeat

• Stream → React → Engage → Monetize → Entertain → Repeat
• Stream ↗ ↘ Repeat | React ↑ ↓ Entertain ← Engage ↖ ↙ Monetize
• Stream ⇄ Monetize | React ⇄ Entertain | Engage ⇄ Repeat

Gen Z Dating: Swipe, Vibe, Text, Ghost, Post, Repeat

• Swipe → Vibe → Text → Ghost → Post → Repeat
• Swipe ↗ ↘ Repeat | Vibe ↑ ↓ Post ← Text ↖ ↙ Ghost
• Swipe ⇄ Ghost | Vibe ⇄ Post | Text ⇄ Repeat

Crypto Bros: HODL, Shill, Moon, Cope, Dump, FOMO

• HODL → Shill → Moon → Cope → Dump → FOMO
• HODL ↗ ↘ FOMO | Shill ↑ ↓ Dump ← Moon ↖ ↙ Cope
• HODL ⇄ Cope | Shill ⇄ Dump | Moon ⇄ FOMO

AI Doomer: Warn, Predict, Fear, Extrapolate, Catastrophize, Repeat

• Warn → Predict → Fear → Extrapolate → Catastrophize → Repeat
• Warn ↗ ↘ Repeat | Predict ↑ ↓ Catastrophize ← Fear ↖ ↙ Extrapolate
• Warn ⇄ Extrapolate | Predict ⇄ Catastrophize | Fear ⇄ Repeat

Fast Food Drive-Through: Order, Wait, Review, Regret, Eat, Nap

• Order → Wait → Review → Regret → Eat → Nap
• Order ↗ ↘ Nap | Wait ↑ ↓ Eat ← Review ↖ ↙ Regret
• Order ⇄ Regret | Wait ⇄ Eat | Review ⇄ Nap

Netflix Binge: Browse, Start, Binge, Zone, Sleep, Repeat

• Browse → Start → Binge → Zone → Sleep → Repeat
• Browse ↗ ↘ Repeat | Start ↑ ↓ Sleep ← Binge ↖ ↙ Zone
• Browse ⇄ Zone | Start ⇄ Sleep | Binge ⇄ Repeat

EDM Festival Hippy: Arrive, Vibe, Flow, Peak, Crash, Transform

• Arrive → Vibe → Flow → Peak → Crash → Transform
• Arrive ↗ ↘ Transform | Vibe ↑ ↓ Crash ← Flow ↖ ↙ Peak
• Arrive ⇄ Peak | Vibe ⇄ Crash | Flow ⇄ Transform

Tech Support Experience: Call, Wait, Explain, Restart, Escalate, Surrender

• Call → Wait → Explain → Restart → Escalate → Surrender
• Call ↗ ↘ Surrender | Wait ↑ ↓ Escalate ← Explain ↖ ↙ Restart
• Call ⇄ Restart | Wait ⇄ Escalate | Explain ⇄ Surrender

Instagram Influencer: Post, Filter, Hashtag, Monitor, Engage, Validate

• Post → Filter → Hashtag → Monitor → Engage → Validate
• Post ↗ ↘ Validate | Filter ↑ ↓ Engage ← Hashtag ↖ ↙ Monitor
• Post ⇄ Monitor | Filter ⇄ Engage | Hashtag ⇄ Validate

The Pattern Economy isn’t just about bridging Ancient Greece and modern AI — it reveals something more fundamental about human understanding itself. While the Greeks gave us powerful tools to comprehend the physical world through mathematics, our modern challenges require frameworks that can capture what their system couldn’t: the dynamic interplay of complex patterns, the integration of observer and observed, and the emergence of properties that can’t be reduced to their parts.

We can create new frameworks that:

• Preserve the precision of Greek mathematics while transcending its limitations
• Integrate multiple ways of knowing, from indigenous wisdom to quantum mechanics
• Create living systems of knowledge that grow through use
• Bridge the gap between mathematical truth and experiential reality
• Handle both what we can measure and what we can only experience

This isn’t just an idea, it’s crucial for addressing modern challenges from climate change to consciousness, from quantum computing to complex social systems. The frameworks we’ve explored suggest a new way forward: not replacing mathematics, but evolving it into something that can handle the full complexity of our modern world.

The Greeks used mathematics to explore the unknown. Now, using AI and our expanded understanding of patterns in systems, we can create new ways of exploring what even the Greeks couldn’t imagine. In doing so, we may finally bridge the gap between what we can calculate and what we can know.

The future lies not in choosing between ancient wisdom and modern technology, but in creating frameworks that unite them both in service of understanding the patterns that shape our world.

Episode 2 coming soon

Cole

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