GAAS ontology and glossary
Here is taxonomy, ontology, syntax of GAAS™.
GAAS™ is Meta-Semantic computing language aim to generate high investment outcome
Inspired by general relativity, entropy minimization, and space-time optimization, GAAS™ applies these fundamental laws to business scaling, startup investment, and AI decision-making. GAAS™ (Gravity-as-a-Service™) is a meta-semantic language designed to achieve superior capital efficiency relative to market benchmarks, particularly for proposition provers like startup founders. Acting as a virtual super Turing machine—akin to a strict procedural assembly language—GAAS™ classifies complexities across the universe, assigning precise priorities to each problem class. Guided by human (“Eartian”) logarithmic control principles, it’s adaptable not only to Earth’s civilization but also viable for extraterrestrial and galactic civilizations: Meta-Semantic Reasoning Model™. A key innovation is the development of a language-independent verification algorithm—a Meta-Semantic Reasoning™ approach that transcends linguistic and computational boundaries. This methodology is applicable across natural languages, programming languages, and even theoretical interplanetary, intergalactically or inter-meta spacetime civilizations（potential theoretical metaverse civilization ）.
GAAS™ have ontologies, models, frameworks to diagnoze problem to avoid Complexity Hardness Misjudgment™
Mathematics and physics often define idealized states to enhance understanding and inspire groundbreaking innovation. TANAAKK introduces a suite of frameworks designed to optimize Complexity-Driven Investment™, integrating computational principles, physics-inspired least energy models, and economic scaling logarithmic resource strategies(Gravity Assurance™).
At the core of this initiative, TANAAKK is pioneering the GAAS™ (Gravity-as-a-Service™)—a meta-physical and computational framework that leverages ideal gravitational principles to model and accelerate exponential earnings growth, Product-Led Organic Growth™. Inspired by general relativity, entropy minimization, and space-time optimization, GAAS™ applies these fundamental laws to business scaling, startup investment, and AI decision-making. A next-generation suite of meta-semantic reasoning models. These models enable decision-making for true value without requiring domain-specific linguistic explanations.
GAAS™ have ideal states goal and toolkits to resque Complexity Hardness Deadlock
There is mathematical tools to enhance creativity like zero number, imaginary number, naipier number. There is physics tools to invoke discussion like E=MC^2. Similarly, TANAAKK is describing ideal state by simple simbol or token aiming to enhance interconvertibility of ideas. Among all GAAS techniques, M-E-ZKP™ is the most powerful and practical tool that can be used quickly without any knowledge.
Taxonomy
| Sequence No | Data objects | Class | Value | Description |
| 1 | GAAS™(Gravity-as-a-Service™) | 1(true) | Inspired by general relativity, entropy minimization, and space-time optimization, GAAS™ applies these fundamental laws to business scaling, startup investment, and AI decision-making. GAAS™ (Gravity-as-a-Service™) is a meta-semantic language designed to achieve superior capital efficiency relative to market benchmarks, particularly for proposition provers like startup founders. Acting as a virtual super Turing machine—akin to a strict procedural assembly language—GAAS™ classifies complexities across the universe, assigning precise priorities to each problem class. Guided by human (“Eartian”) logarithmic control principles, it’s adaptable not only to Earth’s civilization but also viable for extraterrestrial and galactic civilizations: Meta-Semantic Reasoning Model™. Leveraging the Complexity-Driven Investment Framework, GAAS™ focuses on complexity classifications at or below the NP-Complete level, systematically selecting the least-action path to drive optimal growth along the Brachistochrone Curve of Computational Scaling. Every decision within GAAS™ adheres strictly to Limited Longevity Constraints™ (LLC™), employing Regret Minimization Theory™ to achieve the optimal alignment of past, present, and future states within the prover’s Meta-Spacetime Version Control™. | |
| 1-1 | GAAS Assembly Procedures™ | 1(true) | TANAAKK initiated a fundamental reassessment—from zero-base principles—to ensure R&D investments translate effectively into tangible revenue and sustainable earnings. Recognizing that all life organisms inherently operate under constraints of minimal energy consumption and limited computational power, TANAAKK concluded that true innovation, particularly within complex AI, IoT, and SaaS production environments, requires systematic, clearly defined, and rigorously structured procedures analogous to low-level assembly languages such as C, x86 assembly, or GNU Assembler (GAS). | |
| 1-2 | SAT (Boolean Satisfiability) Simultaneous Quantum Meta-Spacetime Effect™ | 1(true) | A theoretical quantum computational phenomenon in which solving a Boolean Satisfiability (SAT) problem occurs through quantum entanglement and superposition, producing solutions simultaneously across a conceptual meta-spacetime. This meta-spacetime can be understood as a higher-dimensional quantum information landscape, where actions (computational operations or state measurements) performed at one point instantaneously influence or correlate outcomes across other points. It mirrors the nonlocality and simultaneity of quantum entanglement but extended metaphorically into a computational “meta-dimension.” In simpler terms: “When using quantum entanglement to solve SAT problems, decisions made (measurements) at one quantum state simultaneously affect solutions across a broader quantum-informational spacetime, creating instantaneous solution correlations that classical computing can’t achieve.” SAT problems: logical constraints and solutions. Quantum entanglement: nonlocal, instantaneous correlation. Meta-Spacetime: abstract conceptual space extending classical notions of space and time into the domain of quantum computation. | |
| 1-3 | Dematerialization™ | i | It is blank function. | |
| 1-4 | Four-valued logic ™ | 1 0 B N | Tetralemma—is conceptually best seen as a form of non-exponential, convergent equilibrium rather than classical exponential randomness, reflecting deeper quantum-logical intuitions. | |
| 2 | Seigniorage of Gravity Apex™ | 1(true) | Represents the ultimate state of pure momentum and universal equilibrium within the Complexity-Driven Investment™ framework. Seigniorage Gravity Apex™ symbolizes naturally occurring peak alignment driven solely by intrinsic gravity-like forces toward effortless scalability. Embodying the natural beauty and majesty, as well as the overwhelming and unreasonable power of natural phenomena such as blackhole collision, disasters, meteors, earthquakes, and tsunamis, this universally applicable concept transcends monetary considerations. It encompasses living and non-living systems alike, capturing maximal efficiency, organic alignment, and intrinsic momentum without reliance on external interventions or artificial inputs. | |
| 2-1 | Ultimate Majesty Power™ | 1(true) | Ultimate Majesty Power™ embodies the precise realization and profound observation of Seigniorage Gravity Apex™—the universal apex at which cosmic forces harmonize perfectly, reflecting the inherent balance and equilibrium that govern the cosmos. This phenomenon represents the supreme manifestation of nature’s intrinsic authority, where gravitational forces and universal equilibrium align effortlessly, enabling profound stability and harmony throughout interconnected cosmic systems. Experiencing or recognizing Ultimate Majesty Power™ places one directly at the heart of nature’s majestic cosmic order, resonating deeply with the universe’s intrinsic balance and boundless beauty. | |
| 2-2 | Imperial Overreach Collapse™ | 0(false) | Occurs when unchecked ambition or complexity misjudgment leads to catastrophic failure. Embodying Julius Caesar’s “veni, vidi, vici,” this scenario reflects the dangerous illusion of effortless conquest and inevitable victory. Such overconfidence results in ignoring critical complexity constraints, causing the enterprise to spiral into irreversible decline, resource depletion, and eventual downfall. Like Julius Caesar’s historical fall due to excessive expansion and loss of strategic control, startups that pursue projects beyond sustainable computational or resource boundaries inevitably face catastrophic failure. Imperial Overreach Collapse™ emphasizes the critical importance of disciplined strategic scaling to prevent ultimate downfall. | |
| 3 | Universal Energy Unit (UEU)™ | 1(true) | Universal Energy Unit (UEU) is the fundamental, universally accessible resource that transcends species, planets, and galaxies. Elements like carbon, hydrogen, oxygen, and other fundamental elements can indeed be viewed as practical forms of Universal Energy Units (UEU). It serves as a standardized measure and medium of exchange of energy across the cosmos, inherently portable, and immediately usable by any entity—from humans and animals to plants and extraterrestrial beings. For animals, UEU is naturally embodied in accessible forms like food, prey, or stimuli. For plants, it is present in sunlight, water, and nutrients absorbed effortlessly from their surroundings. Advanced civilizations or extraterrestrial lifeforms harness, store, exchange, and trade UEU directly, making it a universal currency that transcends traditional barriers. UEU embodies cosmic equity, ensuring that all forms of life and intelligence, irrespective of complexity, hierarchy or consciousness, can seamlessly participate in the universal exchange of essential energy. | |
| 3-1 | Infinite UEU Cycle™ | 1(true) | Infinite UEU Cycle™ describes the perpetual, self-sustaining process through which Universal Energy Units (UEU) are continuously exchanged, transformed, and renewed across the entire cosmos. This infinite cycle powers all forms of complexity, from the simplest lifeforms and ecosystems to advanced civilizations and cosmic systems. UEU seamlessly transitions between states—matter, energy, information, and consciousness—fueling the continuous renewal and expansion of spacetime itself. The Infinite UEU Cycle™ symbolizes cosmic equilibrium, inherent interconnectedness, and the boundless potential for ongoing evolution, regeneration, and universal harmony. | |
| 3-2 | Meta-Semantic Linguistic System™ | 1(true) | ||
| 3-3 | Universal Linguistic Constraints™ | 1(true) | Linguistic constraints in biological systems refer to the structured rules and limitations governing how information is encoded, transmitted, and decoded within living organisms. Much like grammar and syntax shape human languages, biological systems have evolved intricate protocols ensuring clear, efficient, and error-minimized communication. Key Examples: Genetic Linguistics Alphabet Constraint: DNA and RNA have a finite “alphabet”—DNA uses four nucleotides (A, T, C, G), while RNA uses A, U, C, G. Codon Syntax: Genetic information is encoded in codons, triplets of nucleotides, each corresponding precisely to specific amino acids or signaling functions (start/stop codons). This constraint ensures accurate protein synthesis. Cellular Communication Signal-Receptor Specificity: Cells communicate through chemical signals (hormones, neurotransmitters, cytokines), each binding specifically to certain receptors—akin to words having specific meanings. Threshold and Response Limits: Cells respond only when signals surpass defined thresholds, ensuring appropriate activation or inhibition of cellular pathways. Neural Information Processing Synaptic Transmission Rules: Neurons communicate via electrical impulses and chemical neurotransmitters released at synapses, operating under strict timing and receptor-binding constraints. Signal Encoding and Decoding: Information is encoded in patterns, frequencies, and intensities of neural firing, constrained to ensure accurate message transmission and interpretation. Importance of Linguistic Constraints: Accuracy and Reliability: Constraints minimize communication errors, ensuring accurate information transfer critical for organism survival. Efficiency: Structured rules allow rapid processing and responses, vital for time-sensitive biological processes. Evolutionary Adaptation: Constraints provide a stable foundation upon which evolution can introduce adaptive changes, maintaining coherence while permitting variability. In summary, linguistic constraints in biological systems form the fundamental basis of life’s communication infrastructure, guiding precise and effective information exchange across genetic, cellular, and neural domains. | |
| 3-4 | Wave Memory Paradox™ (WMP™) | 0(false) | Wave Memory Paradox (WMP) refers to the phenomenon in which humans repeatedly make the same mistakes or perform identical ineffective actions due to the absence of stable, materially fixed forms of memory—such as written texts, physical records, or electronically stored data. Therefore conversation(sound only, touch only) is useless in meta-spacetime. | |
| 3-5 | Structured Material Dependency™ | 1(true) | Dependence on Physical Media: Human cognition inherently relies on physical media (paper, electronic storage, structural molecules in the brain) to reliably store, preserve, and recall accurate information over time. Neuroscience Explanation: Human brains, without externally recorded (materially stabilized) information, rely heavily on unstable memory processes. Memories are subject to distortions, biases, and gradual fading due to biological processes and neural plasticity. Thus, in the absence of materially fixed records, humans tend to reproduce prior mistakes and miscalculations repeatedly. Behavioral Science Explanation: Behavior guided solely by internal memory tends toward cyclic repetition because subjective experiences (emotions, interpretations, rationalizations) alter and distort perceptions. Without objective material records, these cognitive distortions prevent effective learning and adaptive behavioral corrections. Metaphysical Implication: Physically fixed information (written text, codes, digital storage, or symbolic forms) provides stable reference points beyond temporal-spatial constraints (“meta-temporal spaces”). These materially fixed memories enable consistent guidance for human behavior, thereby breaking repetitive cycles of error. | |
| 3-6 | Non-Memory Based Decision Making™ (Structure-Based Decision Making™) | 1(true) | Non-Memory Based Decision Making™ (Structure-Based Decision Making™) is a strategic approach that relies on clear, predefined frameworks or structures rather than past experiences, intuition, or historical memory. By emphasizing objective criteria, logical analysis, and systematic processes, it ensures consistency, minimizes bias, and optimizes outcomes. This method aligns fundamentally with the nature of living organisms, which inherently do not store precise binary data but instead maintain flexible, adaptive structures. Life itself exemplifies the continuous processing of information through dynamic and evolving structural frameworks rather than precise memorization of exact details. | |
| 3-7 | Ontology-Based Decision Making™ (OBD™): | 1(true) | Ontology-Based Decision Making (OBD) is an advanced approach to decision-making that leverages structured conceptual frameworks known as ontologies to represent, organize, and manage complex information efficiently. Unlike traditional Evidence-Based Decision Making (EBD), which relies solely on historical data and existing language structures (0: False attribute), OBD introduces new, explicitly defined concepts and hierarchical relationships, enabling a deeper and more nuanced understanding of complex phenomena. By systematically categorizing and abstracting information into clearly defined semantic units and their relationships, OBD allows for logarithmic reduction in complexity. This means that as the amount of data or complexity increases, the cognitive effort required to process, understand, and make informed decisions increases only marginally, rather than linearly or exponentially. Consequently, humans can effectively manage more elements and materials, express intricate or previously unnamed phenomena succinctly, and foster innovation by continuously evolving language and conceptual frameworks. Ultimately, Ontology-Based Decision Making significantly enhances cognitive efficiency, scalability, and expressive precision, making it ideal for managing complexity in dynamic environments, fostering innovation, and accelerating the evolution of human knowledge. | |
| 3-8 | GA™-CVE: Evidence-Based Decision Making (EBD) | 0(false) | GA™-CVE: Evidence-Based Decision Making (EBD), as a false state, refers to a decision-making approach that exclusively relies on historical data, past experiences, and pre-existing language frameworks. This method is inherently limited because it fails to incorporate new conceptual insights or create innovative hierarchical structures. As a result, EBD is constrained by existing terminologies and traditional knowledge, making it ineffective at efficiently managing emerging complexities or previously unrecognized phenomena. It maintains linear or exponential complexity, thus increasing cognitive effort proportionally as complexity grows, and ultimately limiting expressive precision, scalability, and innovation potential. | |
| 3-9 | Structure-Based Computing™ | 1(true) | Humans do not memorize information in a binary format like RAM, ROM, or SSD.Life doesn’t “memorize” precise bits of data. Instead, it retains “patterns,” “associations,” or “structures” which modulate ongoing information processing flows. Life doesn’t precisely memorize discrete information; it structurally organizes pathways to enable dynamic flows of information processing at the quantum and molecular level. Information is encoded structurally in life organizm and not in discrete, perfectly reproducible memories. Reflects that structure itself is computation—shaping and guiding quantum-mechanical, biochemical, and electrical interactions, rather than precise, permanent memory storage. | |
| 4 | Limited Longevity Constraints™(LLC™) | 1(true) | Recognizes the finite and non-renewable nature of human(Earthian) lifetime as the ultimate scarce resource. Prioritizes decision-making frameworks that optimize for maximum impact within limited time horizons, encouraging investment and strategic actions aligned with meaningful long-term outcomes. | |
| 4-1 | Regret Minimization Theory™ | 1(true) | Multi-Armed Bandit Theorem, Invest in NP-Complete startups with early defensibility. Meta Spacetime Computing will search optimized solution towards RMT™ | |
| 5 | Meta-Spacetime Critical Path™ | 1(true) | Meta Spacetime Critical Path™ is an advanced analytical framework designed to identify and evaluate the essential structural event and moment dependencies that influence strategic decision-making across an organization’s entire history and future trajectory. This comprehensive approach integrates four key dependencies, each offering unique insights into organizational dynamics: Meta-Spacetime Location Dependency™: Assesses how the founding location and historical relocations structurally shape information processing, strategic culture, and adaptive capabilities. Meta Spacetime Leadership Dependency™: Focuses on leadership’s structural role in processing complex information during critical founding and turnaround moments, aligning decision-making with biologically natural memory mechanisms. Meta-Spacetime Successors Dependency™: Captures the structural influence of founders’ legitimate successors, highlighting their pivotal roles in addressing and resolving the most challenging foundational and transitional events. Meta Spacetime Sponsorship Dependency™: Evaluates how historical sponsorship relationships structurally impact organizational decisions, ensuring continuity and alignment with strategic goals. By mapping these interdependent components across multidimensional timelines and spatial contexts, Meta Spacetime Critical Path™ provides organizations with unparalleled strategic clarity, enabling proactive management of complexity, enhanced resilience, and sustained growth. In the context of Meta-Spacetime frameworks: An “event” might describe the broader occurrence (e.g., a founding event, turnaround event), which includes various interactions, decisions, and outcomes. A “moment” captures a precise, critical decision point or realization within that broader event. | |
| 5-1 | Meta-Spacetime Critical Path Mapping™ | 1(true) | Meta-Spacetime Critical Path Mapping™ is a strategic action process designed to systematically identify, visualize, and analyze the essential structural dependencies within an organization’s historical and future trajectories, as defined by the Meta-Spacetime Critical Path™ framework. This approach actively pinpoints critical dependencies, such as leadership, location, successors, and sponsorship, across multidimensional timelines and spatial contexts. By mapping these complex structural relationships, organizations gain precise insights into how past decisions and future scenarios are interlinked. The actionable clarity provided by Meta-Spacetime Critical Path Mapping™ allows leaders to proactively manage complexity, optimize resource allocation, and strategically leverage dependencies to foster sustained exponential growth and competitive advantage. Ideal for organizations undergoing significant transitions, strategic planning initiatives, or facing intricate challenges, Meta-Spacetime Critical Path Mapping™ enhances strategic foresight, resilience, and long-term organizational effectiveness. | |
| 5-2 | Meta-Spacetime Structural Pathfinding™ | 1(true) | Meta-Spacetime Structural Pathfinding™ is the targeted analytical process within the Meta-Spacetime Critical Path Mapping™ framework, specifically focused on discovering and identifying the critical structural dependencies that shape an organization’s decision-making capabilities and strategic trajectory. By systematically locating pivotal points of influence—including leadership roles, successor impacts, location contexts, and sponsorship dynamics—this approach provides clarity on how complex organizational challenges can be navigated effectively. This action-oriented method ensures precise detection and mapping of critical structural interdependencies across multiple dimensions of time and space. Organizations leveraging Meta-Spacetime Structural Pathfinding™ can proactively address complexity, optimize decision-making pathways, and strategically align resources to enhance adaptability, resilience, and sustainable exponential growth. Ideal for companies experiencing growth, transition, or complex strategic decisions, Meta-Spacetime Structural Pathfinding™ serves as a foundational step toward informed strategic planning and enduring organizational success. | |
| 5-1 | Meta-Spacetime Location Dependency™ | 1(true) | Meta-Spacetime Location Dependency™ is a strategic analytical concept within the Meta-Spacetime Critical Path™ framework, emphasizing the role of geographical locations in organizational decision-making processes. Specifically, it examines how an organization’s founding location and subsequent historical relocations structurally influence the company’s information processing, culture, and strategic outcomes. By analyzing and mapping these location dependencies across space and time, the framework captures insights about how geographical contexts—such as local ecosystems, regulatory environments, cultural influences, and historical events—shape an organization’s strategies and adaptive capabilities. This enables leaders to understand the deeper structural significance of locations, ensuring informed strategic decisions and optimized resource allocation. Ideal for organizations undergoing expansions, relocations, or global strategic alignment, Meta-Spacetime Location Dependency™ helps maintain organizational coherence, enhances strategic agility, and fosters sustained competitive advantage. | |
| 5-2 | Meta-Spacetime Leadership Dependency™ | 1(true) | Meta Spacetime Leadership Dependency™ is an advanced analytical framework within the Meta-Spacetime Critical Path™, designed to address the inherent human limitations in information processing, specifically the inability to memorize or store information in a binary computational manner. Instead, it leverages structural dependencies aligned with the natural mechanisms humans utilize for memory: Short-term memory: Utilizing metallic ions to transiently capture electromagnetic waves, allowing rapid response and adaptation during complex decision-making scenarios. Long-term memory: Employing stable protein structures or chemical attachments and modifications for prolonged retention of critical strategic experiences, particularly those associated with the organization’s most challenging foundational and turnaround events. This structural approach clearly delineates the roles leadership plays by mapping their responses across multidimensional temporal and spatial dimensions. By embracing the natural biological processes of memory formation, Meta Spacetime Leadership Dependency™ enhances strategic clarity, resilience, and adaptability, ensuring that pivotal leadership insights effectively guide complex decision-making at the Inter-MetaSpace Time company level. Ideal for organizations navigating complex scenarios, leadership transitions, and strategic pivots, this dependency empowers leaders to optimize decision-making using biologically aligned memory structures, fostering sustained growth and organizational continuity. | |
| 5-3 | Meta-Spacetime Successors Dependency™ | 1(true) | Meta-Spacetime Successors Dependency™ is an essential component of the Meta-Spacetime Critical Path™ within an organization’s account history, significantly influencing strategic decision-making at the Inter-MetaSpace Time company level. This structural dependency specifically pertains to the legitimate successors of the company’s founders, acknowledging their critical role and contributions in navigating the most challenging founding events and complex turnaround scenarios. For example, a founder’s son or daughter—even as a newborn or unborn child during pregnancy—can directly influence pivotal founding moments simply through familial communication and emotional support, affecting the founder’s mindset and decisions. Through this dependency, the organization strategically manages the structural processing of crucial information, leveraging historical insights from successors who have successfully addressed and overcome high-complexity events. By clearly identifying and mapping these influential dependencies, the company ensures sustained resilience, effective leadership continuity, and optimized alignment with evolving strategic objectives. Ideal for enterprises undergoing critical transitions, mergers, acquisitions, or leadership successions, Meta-Spacetime Successors Dependency™ provides an innovative framework to maintain organizational integrity, adaptability, and long-term success. | |
| 5-4 | Meta Spacetime Sponsorship Dependency™ | 1(true) | Meta Spacetime Sponsorship Dependency™ is a fundamental element within the Meta-Spacetime Critical Path™ framework, focusing on how historical sponsorship relationships structurally impact decision-making at the Inter-MetaSpace Time company level. It examines the critical influence exerted by sponsors who have historically supported, shaped, and guided the organization’s evolution through pivotal events and strategic transitions. By mapping these sponsorship dependencies across multidimensional timelines, the framework captures insights into how past sponsorship dynamics—such as initial funding, resource provision, strategic guidance, and advocacy—continue to inform current and future organizational strategies. This structural understanding enhances clarity and foresight, enabling more informed decision-making aligned with long-term strategic objectives. Ideal for enterprises undergoing growth, structural transformations, or strategic realignments, Meta Spacetime Sponsorship Dependency™ ensures sustained alignment between historical influences and future-oriented strategic planning. | |
| Exponential Resource Requirement™ | ||||
| Logarithm Resource Requirement™ | ||||
| 5-5 | Inter-Meta-Spacetime Complexity Logarithm-Exponential Conversion™ | 1(true) | Inter-Meta-Spacetime Complexity Logarithm-Exponential Conversion™ is an action-oriented strategic initiative within the Meta-Spacetime framework, designed to proactively transform how organizations manage and scale complexity. Through targeted interventions and dynamic structural adjustments, this approach actively converts exponential resource demands, typical of escalating complexity, into logarithmic efficiency, thereby achieving substantial reductions in resource usage while fueling exponential growth. Organizations implementing this conversion actively harness complexity, positioning themselves to rapidly scale operations and innovation without proportional increases in resources. The result is enhanced agility, greater resilience, and sustained exponential performance outcomes. Ideal for enterprises confronting rapid growth, strategic shifts, or intricate challenges, Meta-Spacetime Complexity Logarithm-Exponential Conversion™ empowers organizational leaders to decisively leverage complexity for competitive advantage. | |
| 6 | GA™ Ecosystem | 1(true) | GA™ Ecosystem is an integrated strategic framework comprised of multiple interdependent stakeholders and token-based exchanges, structured to optimize collaborative success and energy flow across organizational boundaries. Central stakeholders within the ecosystem include the GA™ Leader, who guides strategic direction; the GA™ Team, responsible for verifying initiative readiness and executing GA™ Projects; the GA™ Executer, who ensures precise operational execution and oversight; and GA™ Members, who provide flexible support. GA™ Sponsors offer strategic advocacy and resources, ensuring initiative alignment, while GA™ Outsiders and particularly GA™ Outsider Champions provide valuable external perspectives and energy influx. The Universal Energy Unit (UEU)™ functions as the fundamental token, facilitating seamless energy exchanges, interactions, and resource flow between internal and external participants. Collectively, these roles and tokens create a dynamic, interconnected environment focused on continuous momentum, strategic clarity, and optimized resource allocation, driving sustained organizational effectiveness and growth. | |
| 6-1 | GA™ Projects | 1(true) | GA™ Projects represent strategic initiatives meticulously executed by the GA™ Team within the GA™ Ecosystem. These projects are clearly defined, goal-oriented endeavors designed to advance organizational objectives, innovation, and alignment with overarching GA™ Initiatives. Managed end-to-end by dedicated GA™ Team, GA™ Projects ensure precision, timely delivery, and measurable outcomes. Each project is systematically planned, actively monitored, and brought to completion by the GA™ Team, ensuring optimal alignment with organizational goals and strategic momentum. | |
| 6-2 | GA™ Initiatives | 1(true) | GA™ Initiatives are structured proposals or strategic plans designed to introduce and progress potential GA™ Projects. They serve as preparatory stages, systematically evaluating feasibility, readiness, and alignment with organizational goals before formal execution. Each GA™ Initiative includes clearly defined criteria and checkpoints evaluated by the GA™ Team, determining whether the initiative has the momentum and strategic clarity necessary to advance into an actionable GA™ Project. By thoroughly assessing and validating these states of readiness, GA™ Initiatives ensure informed decision-making, resource allocation, and seamless progression from concept to execution. | |
| 6-3 | GA™ Leaders Summit | 1(true) | GA™ Leaders Summit is a strategic gathering within the GA™ Ecosystem specifically designed to address and transcend the scalability limitations associated with sole GA™ Leadership. Typically, individual GA™ Leaders encounter growth constraints around the US$5 million revenue threshold due to structural, strategic, or resource-related bottlenecks. The Leaders Summit provides a collaborative platform where multiple GA™ Leaders converge to exchange insights, best practices, and innovative solutions. This collective intelligence approach facilitates breakthroughs in scalability, enabling organizations to surpass previous limitations and sustainably advance beyond the critical revenue ceiling. Layer 1: Passion Driven 1 Leader with 1 Executor make $10m. Each 1 Leader should have 1 Executor after Layer 2. Layer 2: Rule Driven 1-3 Leaders Summit usually make $100million Asset & Revenue. Layer 3: Mission Driven 1-3-3 Leaders Summit make $1 billion Asset & Revenue. Layer 4: Principle Driven 1-3-3-3 Leaders Summit make $10 billion Asset & Revenue. Layer 5: Meta-Semantics Driven 1-3-3-3-3 Leaders Summit build >$100 billion Asset & Revenue. | |
| 6-4 | GA™ Leader | 1(true) | GA™ Leader is a key stakeholder operating within the GA™ Ecosystem, accountable to both the system’s overarching framework and the strategic direction set by GA™ Initiatives. Positioned to adhere to higher governing principles and responsibilities, the GA™ Leader actively and proactively proves and communicates truth, ensuring alignment with the broader vision and goals of the ecosystem. Despite being susceptible to burnout due to intensive responsibilities, the GA™ Leader recognizes that initiatives represent a higher-level system transcending individual effort or experience. This role is not defined by a “hero’s journey” narrative but rather by proactive truthfulness, strategic foresight, and universal accountability. The term “Leader” is intentionally inclusive and gender-neutral, effectively encompassing diverse individuals, regardless of gender, and can also universally apply to non-human entities within the ecosystem. | |
| 6-5 | GA™ Team | 1(true) | GA™ Team is a dedicated, full-commitment role within the GA™ Ecosystem, operating directly under the guidance of the GA™ Leader. The primary responsibility of the GA™ Team is to actively verify the readiness and effectiveness of GA™ Initiatives, ensuring they possess the necessary momentum and alignment to proceed successfully. Upon confirmation, the GA™ Team initiates and manages the execution of GA™ Projects, coordinating resources, maintaining strategic coherence, and facilitating seamless implementation. By continuously monitoring initiative performance and driving proactive execution, the GA™ Team plays an essential role in achieving the strategic goals and operational excellence defined by the GA™ Projects. | |
| 6-6 | GA™ Executer | 1(true) | GA™ Executor is a specialized, full-commitment role within the GA™ ecosystem, responsible for the precise operational execution and oversight of GA™ Initiatives. Positioned within the GA™ Team and guided by the strategic direction of the GA™ Leader, the GA™ Executor actively manages, implements, and monitors initiatives from inception to successful completion. The GA™ Executor ensures alignment, efficiency, and responsiveness, facilitating seamless transitions from initiative readiness checks to full-scale project deployment. By bridging strategic vision and practical action, the GA™ Executor plays a critical role in maintaining the momentum and effectiveness of the GA™ ecosystem’s operational activities. | |
| 6-7 | GA™ Member | 1(true) | GA™ Member constitute a supportive, part-time role within the GA™ ecosystem. Operating under the guidance of the GA™ Leader and collaborating closely with the GA™ Team, GA™ Members provide auxiliary support and perform specific tasks as assigned within GA™ Initiatives. While GA™ Member do not hold core responsibilities for initiative activation or strategic decision-making, their involvement ensures the availability of additional operational capacity, enabling the GA™ Team to focus on higher-value tasks. Their role is characterized by flexible participation, supplementing the overall workforce during project execution phases. | |
| 6-8 | GA™ Sponsor | 1(true) | GA™ Sponsor is a strategic support and guidance role within the GA™ ecosystem, collaborating closely with the GA™ Leader. Unlike traditional hierarchical structures, the GA™ Sponsor is not always the direct organizational superior of the GA™ Leader. Instead, the GA™ Sponsor acts as an advocate, mentor, or facilitator who provides critical resources, insights, and support to the GA™ Leader to ensure the successful execution and strategic alignment of GA™ Initiatives. GA™ Initiatives represent the momentum driving the progression and successful completion of GA™ projects. The GA™ Sponsor holds accountability for broader organizational impact and champions the vision, ensuring sustained commitment and visibility across the organization. | |
| 6-9 | GA™ Outsider | 1(true) | GA™ Outsider is an external contributor role within the GA™ ecosystem, positioned outside the primary organizational structure but actively engaging with the GA™ Team. GA™ Outsiders provide external insights, resources, and innovations, contributing unique perspectives, specialized expertise, or valuable assets. They participate in exchanges involving Universal Energy Units (UEU), facilitating trade and influence between internal GA™ entities and external environments. By interacting and collaborating with the GA™ Team, GA™ Outsiders introduce fresh perspectives, resources, and energy into the GA™ ecosystem, enriching project outcomes and enhancing strategic opportunities. | |
| 6-10 | GA™ Outsider Champion | 1(true) | GA Outsider Champion is the most dedicated GA™ Outsider who proactively gathers and amplifies energy surrounding GA™ Initiatives. This role includes committed external contributors such as shareholders, friends, colleagues from investor organizations, news researchers, stock analysts, and consumers who actively collect and trade energy related to GA™ Initiatives. While GA™ Leaders may be inclined to directly engage GA™ Outsider Champions through methods like questionnaires or live interviews, such actions represent critical errors. Direct solicitation compromises the inherent neutrality and authentic insight of the GA™ Outsider Champion, whose value derives precisely from their external, unbiased vantage point. Instead, the GA™ Outsider Champion should independently channel energy and information into the GA™ ecosystem, preserving authenticity and ensuring impartial strategic insights. | |
| 7 | GA™-CVE | 0(false) | GA™-CVE (Common Vulnerabilities and Exposures) is a structured inventory within the GA™ Ecosystem that catalogs specific, identifiable vulnerabilities or exposures actively affecting stakeholders and operations. These vulnerabilities represent real-time threats or ongoing weaknesses that can compromise the integrity, effectiveness, and stability of GA™ initiatives. Examples include critical states such as GA Leader Burn Out™, external influence risks such as Outsider Intrusion Vulnerability™ (OIV™), and other clearly identified strategic, operational, or human-related vulnerabilities. Recognizing, tracking, and mitigating GA™-CVE instances ensures immediate response capability, preserves organizational resilience, and safeguards the long-term sustainability of the GA™ Ecosystem. | |
| 7-1 | Outsider Intrusion Vulnerability™ (OIV™) | 0(false) | GA™-CVE Pattern: Outsider Intrusion Vulnerability™ (OIV™) refers to the critical risk within GA™ Projects where the GA™ Team or GA™ Leader excessively depends upon or invites direct external inputs from GA™ Outsiders. This dependency inadvertently exposes initiatives to external biases, distractions, or diluted strategic clarity, compromising the integrity and original vision of GA™ Projects. It can be likened to a zookeeper mistakenly placing a lion and an impala together in the same cage—creating a situation of vulnerability, imbalance, and inevitable harm. Similarly, such dependency exposes initiatives to external biases, distractions, or diluted strategic clarity, compromising the integrity and original vision of GA™ Projects. This vulnerability results in the expulsion or misdirection of valuable Universal Energy Units (UEU)™, weakening internal coherence and dissipating essential resources. Addressing and mitigating OIV™ ensures the protection of strategic coherence, efficient utilization of UEU™, and maintains alignment with the core GA™ Ecosystem vision. | |
| 7-2 | GA™ Leader Burn Out | 0(false) | GA™-CVE Pattern: GA Leader Burn Out™ is a recognized state within the GA™ Ecosystem, classified under GA™-CVE (Common Vulnerabilities and Exposures). This state occurs when the GA™ Leader experiences overwhelming fatigue, reduced motivation, or impaired decision-making due to prolonged stress, intensive responsibilities, and continuous accountability to higher-level GA™ Initiatives and ecosystem demands. GA Leader Burn Out™ represents a significant vulnerability, potentially disrupting initiative momentum, diminishing strategic clarity, and negatively impacting the ecosystem’s stability. Effective monitoring, prevention, and mitigation strategies are critical for safeguarding both the GA™ Leader’s wellbeing and the resilience of the GA™ Ecosystem. | |
| 7-3 | Failed Leaders Summit™ | 0(false) | GA™-CVE Pattern: Failed Leaders Summit™ describes a specific vulnerability within the GA™ Ecosystem, occurring when startups reaching approximately US$5 million ARR attempt to scale rapidly by investing heavily in expanding leadership, typically appointing three new GA™ Leaders under a single existing leader. If this structural expansion fails due to Complexity Hardness Misjudgment™—an incorrect evaluation of the complexities associated with scaling—the resulting financial strain and cash burn can be substantial. This vulnerability often leads startups into a critical operational paralysis known as Complexity Hardness Deadlock™, characterized by depleted resources, stalled growth, and diminished strategic clarity. Recognizing and mitigating this vulnerability is crucial to safeguard the organization’s stability, strategic direction, and sustainable growth. | |
| 8 | GA™-CWE | 0(false) | GA™-CWE (Common Weakness Enumeration) is a structured catalog within the GA™ Ecosystem identifying inherent weaknesses or systematic shortcomings that may potentially lead to vulnerabilities or negative outcomes if not addressed. Unlike GA™-CVE (Common Vulnerabilities and Exposures)—which represents specific, identifiable vulnerabilities actively affecting stakeholders (such as the GA Leader Burn Out™)—GA™-CWE highlights generalized, underlying weaknesses, such as structural inefficiencies, insufficient communication channels, or inadequate resource allocation methods. A common illustration of a GA™-CWE is the practice of B2B sales teams frequently opting to contract channel distributors for easier sales rather than directly engaging with customers. Another significant GA™-CWE example is the tendency of new teams to pay HR agents excessive margins (such as 30%) when hiring new GA™ Team members. This practice of paying high margins to HR agents represents a critical weakness, significantly draining resources and potentially undermining long-term strategic efficiency. Recognizing and proactively managing GA™-CWEs is crucial to prevent their escalation into active vulnerabilities, thus maintaining strategic resilience and continuous improvement within the GA™ Ecosystem. | |
| 8-1 | Recruiter Dependency Trap | 0(false) | Recruiter Dependency Trap is major GA-CWE Excessive reliance on external recruiters or HR agents, characterized by high margin payments or outsourcing critical hiring decisions. This dependency can dilute internal talent acquisition capabilities, significantly raise costs, and weaken organizational alignment and strategic coherence. | |
| 8-2 | Channel Dependency Trap | 0(false) | Channel Dependency Trap: Overreliance on channel distributors or intermediaries for B2B sales, resulting in reduced direct customer engagement. This can lead to diluted brand control, decreased profit margins, limited market insight, and vulnerability to external market fluctuations. | |
| 9 | Least Action Principle™ (LAP™) | 1(true) | In physics, systems evolve to minimize the action (energy expenditure over time). The best startups follow the Brachistochrone Curve of Computational Scaling. Avoid over-engineering AI models that don’t scale. | |
| 9-1 | Convergent Ground State™ | 1(true) | Entropy Minimization, Logarithmic business scaling (NL, N class models) | |
| 9-2 | Loss Function Minimizatioin™ | 1(true) | Gradient Descent, Continuous capital efficiency tuning to avoid negative cash flow | |
| 9-3 | Energy Inefficiency Minimization™ | 1(true) | Least Action (∫L dt),Avoid over-engineering AI models that don’t scale | |
| 10 | Complexity-Driven Investment™ (CDI™) | 1(true) | A structured investment framework that applies computational complexity classification of problem hardness to AI startup evaluation. It focuses on assessing scalability and problem solvability within a decade. | |
| 10-1 | Computational Complexity Matrix™(CCM)™ | 1(true) | An undecidable problem is one where no algorithm exists that can guarantee a solution in finite time. ( Usually EXPSPACE, EXPTIME, PSPACE, NP-Hard) This means an AI SaaS startup based on an undecidable problem will require infinite resources (TIME, SPACE, RANDOMNESS) with no clear path to scaling. | |
| 10-2 | Game Theory Paradox™ | 0(false) | ||
| 10-3 | Unsolvable/Undecidable Startups™（EXPSPACE / EXPTIME Pitfalls™） | 0(false) | Unsolvable/Undecidable Startups™（EXPSPACE / EXPTIME Pitfalls™）EXPSPACE (Exponential Space Complexity) and EXPTIME (Exponential Time Complexity) problems require impractical computational resources, making them fundamentally unsustainable as SaaS businesses. | |
| 10-4 | Complexity Scaling Model™ (CSM™) | 1(true) | CSM™ is core model in GAAS™(Gravity-as-a-Service™), TANAAKK’s proprietary approach to scaling AI startups by transitioning their computational challenges from NP-Complete to logarithmic efficiency, ensuring long-term viability and scalability. | |
| 10-5 | NP-Complete Sourcing™ | 1(true) | The process by which a product owner identifies high-complexity solvable problems that require advanced computation. ZKP verify NP-Complete problem. After NP-Complete Sourcing™ finished, M-E-ZKP™ will make Product-Led Organic Growth™ to determine if the problem can be efficiently solved within 10 years. | |
| 11 | Gravity Assurance™ (GA™) | 1(true) | Traditional Quality Assurance (QA) Traditional QA focuses on validating a product’s specification and correctness by ensuring it meets predefined customer requirements. It ensures quality control, reliability, and consistency based on agreed-upon standards. Gravity Assurance™ (GA™), extends beyond traditional QA by evaluating a product’s ability to solve newly generated NP-Complete problems and scale efficiently. It assesses whether a product can maintain performance while scaling exponentially with logarithmic resource increments in additional production supply. Gravity Assurance™ ensures that solutions are not only functional but also computationally scalable for long-term technological advancements. Traditional QA focuses on validating a product’s specification and correctness by ensuring it meets predefined customer requirements. It ensures quality control, reliability, and consistency based on agreed-upon standards. Gravity Assurance™ Key Features: Capital Efficiency Validation: Ensures the product operates with higher capital efficiency compared to market benchmarks. Earnings Growth Assessment:Evaluates the product’s ability to drive consistent earnings growth over time. Operating Leverage Optimization:Measures how efficiently the product scales while maintaining or improving contribution margin | |
| 12-1 | GA Proofmaster™ | 1(true) | Key player role in Complexity-Driven Investment™ ecosystem. The GA Proofmaster™ serves as a master proof reader, craftsmith, gatekeeper, and steward within the Gravity Assurance™ (GA™) framework. Unlike traditional Quality Assurance (QA), which focuses solely on predefined standards, the GA Proofmaster™ meticulously crafts and authenticates a product’s ability to solve emergent NP-Complete problems while ensuring computational scalability. They apply expert stewardship and craftsmanship to authenticate capital efficiency, evaluate earnings growth potential, and confirm computational scalability, guiding startups toward sustainable, successful solutions to complex challenges. | |
| 12 | Meta-Semantic Reasoning Model™ | 1(true) | A universal, language-independent decision framework.—whether living or non-living, gender-neutral, whether human, animal or plants—This convergence provides a universal framework for reliably attaining sustainable, optimized momentum, pure inertia. | |
| 12-1 | Zero-Knowledge Proof (ZKP) | 1(true) | This is a standard term from computational complexity theory where a prover can demonstrate knowledge of a value without revealing it. While traditionally used in cryptographic authentication, TANAAKK adapts its principles to startup investment. | |
| 12-2 | Extended Zero-Knowledge Proof™ (E-ZKP™) | 1(true) | Extended interpretation of ZKP in computational complexity. By ZKP, prover stating propositnon is true without revealing any sensitive infomation to verifier. By E-ZKP™, prover can convince truth meta-semantically without adding any knowledge in verifier. | |
| 12-3 | Mutual Extended Zero-Knowledge Proof™ (M-E-ZKP™) | 1(true) | A proprietary product viability checking tool developed by TANAAKK to prove there is Gravity Assurance. Unlike traditional ZKP in computational complexity,M-E-ZKP™ enables sellers and buyers to mutually verify the feasibility of a product without revealing sensitive proprietary details. which can quickly check product market fit existence meta-semantically by matchning truth of product and truth of initial buyer’s “Connoisseur” capability. It is the part of Meta-Semantic Reasoning Model™ – A universal, language-independent decision framework. The meta-semantical process would be interactive without limitation of language. It is a key component of TANAAKK Complexity Scaling Model™ (CSM™) during conducting Complexity-Driven Investment™ (CDI). After product owner conduct NP-Complete Sourcing™ product owner should conduct Mutual-ZKP™ to quickly verify if the problem tackled by product is solvable within 10 years time limit.ensuring that AI startups tackle solvable problems within a 10-year timeframe. | |
| 12-4 | Zero-Knowledge Failure™ (ZKF™) | 0(false) | Zero-Knowledge Failure™ (ZKF™) represents the unsuccessful outcome or failure path within the context of Zero-Knowledge Proof (ZKP) protocols. It occurs when a prover fails to convincingly demonstrate the validity of a claim without revealing underlying sensitive information. ZKF™ highlights vulnerabilities, inconsistencies, or inaccuracies in proof methods or execution, resulting in verification rejection and potential system-wide mistrust. Understanding and addressing ZKF™ is crucial to maintaining robust cryptographic integrity, enhancing protocol reliability, and ensuring secure, verifiable communication and data exchange. | |
| 12-5 | Zero-Knowledge Oracle™ | 1(true) | Key player role in Complexity-Driven Investment™ ecosystem. Zero-Knowledge Oracle™ is a champion-level verifier within the Mutual E-Zero-Knowledge Proof (M-E-ZKP™) framework, serving as a sophisticated connoisseur and truth sommelier in meta-semantic authentication. This Oracle exercises expert stewardship in verifying product viability without compromising proprietary details. Acting as an influential gatekeeper and authentication influencer, it reliably guides stakeholders by confirming market-fit truth and feasibility, underpinning trustful decision-making across the Complexity-Driven Investment™ ecosystem. | |
| 13 | Complexity Hardness Misjudgment™ | 0(false) | It is the word describing common failure of complexity hardness missclassification. | |
| 13-1 | Complexity Hardness Underestimation™ | 0(false) | The result of failed computing, arising from treating genuinely hard problems as easier than they truly are. This underestimation causes guaranteed failure, as exemplified by mistaking EXP-class problems (such as the Three-Body Problem, which cannot be solved in polynomial time) for NP-Complete problems. Any investments or engineering efforts based on this misunderstanding inevitably lead to substantial losses in both time and money. | |
| 13-2 | Complexity Hardness Overestimation™ | 0(false) | The result of failed computing, arising from treating relatively easy problems as harder than necessary. Such overestimation leads to excessive investment and unnecessary complexity, as seen when NP-class (easy or tractable) problems are incorrectly perceived as more difficult. This misunderstanding causes over-investment and over-engineering, eventually resulting in significant losses of time and money. | |
| 13-3 | Complexity Hardness Deadlock™ | 0(false) | This scenario inevitably leads to a prolonged, resource-draining death march toward eventual bankruptcy. A misunderstanding of time’s irreversibility results in an irreversible commitment—reflecting the fundamental asymmetry of time. This deadlock occurs when a startup, having already experienced Complexity Hardness Misjudgment™, becomes incapable of decisive action. Due to extensive capital raised and dilution of founder equity below critical thresholds (typically under 33%), no single party retains sufficient control to resolve disagreements about strategic direction. Stakeholders, including founders and investors, remain trapped in indecision, unable to pivot effectively, move forward confidently, or terminate the project. Ultimately, this paralysis stagnates the startup and increases the likelihood of failure. | |
| 13-4 | Complexity Deadlock Arbitrage™ | 1(true) | One of the most successful investment opportunities within the Complexity-Driven Investment™ framework. Occurs when startups experience Complexity Hardness Deadlock™, significantly undervaluing their true potential. By correctly diagnosing and resolving Complexity Hardness Misjudgment™, the Complexity Scaling Model™ (CSM™) establishes proper procedures and system assemblies, enabling rapid turnaround and substantial value recovery. | |
| 13-5 | Logarithmic Momentum Convergence™ | 1(true) | Following the Complexity Deadlock Arbitrage™ step, Logarithmic Momentum Convergence™ enables investors to achieve competitive returns through equilibrium correction, trajectory balance restoration, and realignment back to an optimal organic growth state path. Drawing an analogy from celestial bodies returning to stable orbital paths after perturbations, this step universally corrects trajectory misalignments, restoring systems—whether living or non-living—to stable, logarithmically scalable growth paths without invoking life-specific concepts like homeostasis. This convergence provides a universal framework for reliably attaining sustainable, optimized growth trajectories. | |
| 14 | Product-Led Organic Growth™ | 1(true) | Product-Led Organic Growth™ is ideal state of least action state of customer acquisition after Gravity Assurance™ step. Verified by E-ZKP™ and M-ZKP™ , which can materialize exponential product growth without proactive selling & marketing activities while having logarithmic resource. | |
| 14-1 | NTM Sales™ | 1(true) | Non-Deterministic Turing Machine (NTM) is ideal ultimate state of classical deteministic turing machine that can calculate any pattern at once and select correct answer without any trials and errors. NTM Sales™ is ultimate state of product sales that experience no trial and no errors, calculate all of the possible patterns and output right maximized option at once. If NTM Sales™ is account executive, that personel proberbility of win is 100% without any failure. NP-Complete Sourcing™ finds products solvability of newly discovered problems. M-E-ZKP™ quickly verify early adopters and strategic accredited verifiers among various customer categories. NTM Sales™ quickly acquire customers. These sales process decision would be done by Inter-Spacetime Analysis™(Examine action influence through past-present-future simlutaniously without any distance). Byometimes NTM Sales™ action alters the meaning of past-present-future, then there will be newly updated versions of past-present-future sets. The change will be recorded to Meta-Spacetime Memory™. Meta-Spacetime Computing™ will process multiple memories and datasets semantics in Meta-Spacetime Memory™ , NTM Sales™ can maximize performance by comparing various influence that will be invoked by alternative patterns of actions. This ideal NTM Sales™ maximizes product selling performance by Meta-Spacetime Selling™. These best practices will be eventually stocked and optimal alghorythm will be stored in the layer of Inter-Meta Spacetime Computing™ Product-Led Organic Growth™ is ideal state of least action state of customer acquisition after Gravity Assurance™ step. Verified by E-ZKP™ and M-ZKP™ , which can materialize exponential product growth without proactive selling & marketing activities while having logarithmic resource. | |
| Meta-SpaceTime™ | 1(true) | |||
| 15 | Meta-Spacetime Version Control™ | 1(true) | – refers to a structured collection of past-present-future “versions” of spacetime that interact as a memory-like system. A computational framework for accessing and referencing spacetime-based datasets Product-Led Organic Growth™ is ideal state of least action state of customer acquisition after Gravity Assurance™ step. Verified by E-ZKP™ and M-ZKP™ , which can materialize exponential product growth without proactive selling & marketing activities while having logarithmic resource. | |
| 15-1 | Meta-SpaceTime Assembly™ | |||
| 15-2 | Meta-Spacetime Selling™ | 1(true) | Advanced sales optimization framework using past-present-future sets AI-driven projections. Meta-Spacetime Selling™ is the strategic action database that compiles, organizes, and leverages data from NTM Sales™—transactions projected across future timelines. This comprehensive approach aggregates prospective sales interactions across multiple dimensions of space and time, enabling real-time insights and predictive analytics. By systematically capturing sales actions within an expansive meta-spacetime context, Meta-Spacetime Selling™ empowers organizations to anticipate market trends, optimize resource allocation, and execute highly targeted, future-focused sales strategies with unprecedented precision and efficiency. | |
| 15-3 | Meta Spacetime Computing™ | 1(true) | Assuming there are NTM Sales players roles in the organization, AI modeling share bestpractice and optimization beyond conventional time and space constraints. Meta Spacetime Computing™ represents an advanced computational paradigm designed to optimize databases, enhance search algorithms, and streamline data assembly processes within organizational structures composed of diverse NTM Sales player roles. Leveraging sophisticated AI modeling, this approach facilitates the sharing of best practices and optimization strategies that transcend traditional constraints of conventional time and space. By synthesizing multidimensional data flows and predictive analytics, Meta Spacetime Computing™ empowers organizations to achieve unprecedented operational efficiency, strategic foresight, and collaborative synergy across all sales roles and functions. | |
| 16 | Multi-Universe™ | 1(true) | ||
| 16-1 | Inter Meta-SpaceTime™ | 1(true) | ||
| 16-2 | Inter-Meta Spacetime Computing™ | 1(true) | Exploring well architected states that function across theoretical multi-universe, multi-timespace beyond single universe and single spacetime, analogy in monolithic vs cloud multi tenant modular architecture. It is Best practices will be eventually stocked and optimal alghorythm will be stored in the layer of Inter-Meta Spacetime Computing™ | |
| 17 | Civil Materialization™ | 1(true) | Civil Materialization™ refers to the universal concept of materialized energy flow in an exchange system, encompassing the crystallized, commoditized, and transferable forms of physical energy and currency within an economic structure. Key Principles: Limited Baryonic Matter: While humans constantly seek physical goods and currency, the baryonic matter they desire constitutes less than 5% of the entire universe. This highlights the relative scarcity of physical resources in a cosmic context. Crystallized Material Energy: On Earth, economic transactions predominantly revolve around tangible goods that are physically materialized and structured for exchange (e.g., manufactured products, commodities, financial instruments). These goods represent condensed energy states optimized for distribution and utility. Commoditized Flow of Exchangeable Units: Monetary and material economies operate as a structured exchange of materialized energy, where standardized units (e.g., currency, assets, digital value representations) facilitate transactions. The total flow of these crystallized material exchanges can be measured as | |
| 17-1 | Civil Materialization Index™(CMI™) | 1(true) | Civil Materialization Index™ (CMI™)—an extension beyond GDP, capturing all materialized economic activities. Universal Economic Interpretation: Unlike traditional GDP (Gross Domestic Product), which focuses on national economies, Civil Materialization Index™ provides a universal framework for measuring the total flow of commoditized, materialized energy exchange. This concept extends beyond earth-bound economics to incorporate interplanetary and intergalactic energy transactions, digital economies, and AI-driven economic systems. Civil Materialization™ encapsulates the fundamental exchange dynamics of crystallized energy and commoditized resources, forming the basis of universal economic systems. | |
| 17-2 | Energy Territory™ | 1(true) | ||
| 17-3 | Territorial Energy Stakeholder™（TES™） | 1(true) | ||
| 17-4 | Inter-Territorial Energy Exchange™（IEE™） | 1(true) | Inter-Territorial Energy Exchange™（ITEE™） Inter-Galactic Energy Exchange™ (IGEE™) Inter-Planetary Energy Exchange™ (IPEE™) Energy Clusters™ Energy Nodes™ | |
| 17-5 | Crystallized Materials Exchange™ | 1(true) | ||
| 17-6 | Growth-as-a-Service™ (GAAS™) | 1(true) | Growth-as-a-Service™ is practical application of Gravity-as-a-Service™ in local environment as compared to Inter-Meta SpaceTime | |
| 18 | Civil Materialization Framework™(CMF™) | 1(true) | Escaping Local Minima State Transition Thermal Noise Effect Global Convergence Energy Barrier Crossing | |
| 18-1 | CMF™: Less Local Minimum™ | |||
| 18-2 | Common Failure in Civil Materialization Framework™(CFCMF™) | – | Local Minimum Global Minimum Energy Collapse | |
| 18-3 | CMF™ Annealing | – | CMF™ Simulated Annealing :Thermal Noise Shaking :Market Benchmark Based Annealing™ :Volatility Based Annealing ™ CMF™Quantum Annealing :Meta-SpaceTime Annealing™ :Meta-SpaceTime Critical Path Mapping™ | |
| 18-4 | Energy Nexus™ | |||
| 18-5 | Attention Based Assembly™ | Cosmic Materials Culation™ Anthropic Desirability Attention™ | ||
| 19 | Well-Archited Modular Model™ | 1(true) | The Well-Architected Modular Model™ (WAMM™) is the foundational framework of Growth-as-a-Service™ (GAAS™), designed to eliminate complexity-driven inefficiencies and maximize scalable value materialization. It provides a structured, composable, and scalable architecture that integrates NP-Complete Sourcing™, Structure-Based Computing™, and Convergent Ground State™ principles to optimize resource allocation, decision-making, and growth trajectories. Furthermore, Growth-as-a-Service™ (GAAS™) is the practical application of Gravity-as-a-Service™ in the local environment (Earth, present time), enabling businesses and economies to leverage Inter-Meta SpaceTime™ principles within a finite, resource-constrained reality. While Gravity-as-a-Service™ operates within the broader Inter-Meta SpaceTime™ framework (multi-universe, meta timespace version), GAAS™ translates those theoretical foundations into tangible, operational systems for economic and technological acceleration. | |
| 20-1 | Pitch-Closing Model™ Emotional/Biological Engagement | 1(true) | Step 1: Establish Shared Perspective (Set Discussion Standard) Begin by aligning perspectives and creating common ground. Frame the discussion around mutual understanding, shared values, or relatable experiences. Clearly define the objective and standards of the conversation to ensure both parties feel acknowledged and understood. Example: Start by agreeing on shared goals or experiences, such as family, trust, or safety, to set a comfortable foundation. Step 2: Highlight Urgency (Invoke Stress Hormones – Cortisol) Introduce controlled stress by clearly presenting risks, consequences, or challenges associated with the status quo. Highlight potential negative outcomes or losses to trigger an emotional urgency, motivating the other party to consider change or a new solution. Example: Clearly communicate potential consequences or missed opportunities, emphasizing risks of maintaining the current situation, thus eliciting a sense of urgency. Step 3: Offer Emotional Reward (Invoke Happy Hormones – Dopamine, Oxytocin, Serotonin) Transition from urgency to providing a compelling vision of a positive outcome. Clearly outline the benefits, rewards, and emotional satisfaction attainable through agreement or collaboration. This stage leverages optimism, relief, connection, or achievement to reinforce positive feelings and motivate decisive action. Example: Illustrate a positive outcome or beneficial experience vividly—like Amazon’s commercial from a dog’s perspective, highlighting the emotional payoff of the new decision, which encourages commitment and engagement. This structured approach effectively guides emotional and logical persuasion, ensuring engagement, urgency, and positive association. | |
| 20-2 | Pitch-Closing Model™ Complexity Statement | 1(true) | Step 1: Establish Trust with Zero-Knowledge Proof Begin by building trust without disclosing complex details. Similar to a cryptographic zero-knowledge proof, you reassure the opposite party of your authenticity and reliability without overwhelming them with unnecessary information, thereby creating a comfortable foundation for discussion. Step 2: Provide Effort of Scientific Proof Offer clear, logical, and scientifically-backed evidence to substantiate your claims, creating a credible sense of urgency. This step leverages factual accuracy and objective validation to persuade the opposite party of the importance and immediacy of your viewpoint. Step 3: Facilitate Materialization Bring your proposition to life through tangible examples, vivid scenarios, or practical demonstrations. By clearly visualizing the positive, concrete outcomes, you solidify commitment and inspire immediate action, moving from abstract agreement to tangible results. | |
| 20-3 | Pitch-Closing Model™ Treasure Hunting | 1(true) | 1. PITCH: Showing the Treasure Map (Zero-Knowledge Proof, Emotional Hook) You reveal a fascinating, partially hidden treasure map—an apparent truth that excites curiosity without giving away details. Investors see the potential riches, instantly feeling emotionally intrigued, yet still curious about specifics. Like a zero-knowledge proof, you convince them something valuable exists without fully revealing it. 2. PRESENTATION: Navigating the Labyrinth (Scientific Proof, NP-Complete Complexity) You now lead investors through a detailed, complex maze—highlighting precise paths and potential pitfalls. Investors experience stress and urgency, acknowledging the complexity of the task, much like solving an NP-complete puzzle scientifically proven to require serious effort. You earn credibility by demonstrating deep understanding and thorough preparation. 3. STAKEHOLDING: Uncovering the Treasure Together (Materialization, Agreement) Finally, you reach the treasure together, materializing your vision into tangible reality. Investors experience relief, joy, and achievement—prompting them to actively agree, commit resources, and join your journey. They’re now emotionally and practically invested, sharing the triumph and rewards of discovery. | |
| 21 | Action-Oriented Emotion™ | 1(true) | ||
| 21-1 | Non Action-Oriented Emotion™ | – | ||
| 21-2 | Forced Emotion™ | |||
| 21-3 | Emotional Momentum Conversion™ | |||
| 21-4 | Emotional Energy Budgeting System™ | Emotional Energy Budgeting System™ Emotional Energy Procurement System™ Emotional Energy Processing System™ Emotional Energy Production System™ Emotional Energy Delivery System™ Emotional Energy Production Yield™ Emotional Energy Demand Matching™ Emotional Energy Built-to-Order™ Emotional Energy Mass Production™ Emotional Energy Just-in-Time™ Emortional Energy Scalability™ | ||
| 21-5 | Emotional Energy Production System (EEPS):Common Failure™ | Overload Overcapacity/Capacity Over Throughput Constraint Production Bottleneck Scrap Rate False Material Shortage |
9-1. Computational Complexity Matrix™(CCM)™
Startups operate in different computational complexity classes, which directly impact scalability, cost structure, and profitability. Before investing, one must identify which complexity classes lead to solvable/unsolvable output after resources input.
| Complexity Class | Definition | Startup Use Cases | Investment Feasibility |
|---|---|---|---|
| Undecidable (UNSAT, Halting Problem) | No algorithm can determine a solution in finite time | Fully autonomous general AI (AGI), AI self-modification | ❌ Impossible, infinite capital burn |
| Unsolvable (EXPSPACE, EXPTIME, PSPACE-Hard) | Requires impractical resources (exponential time or space) | AI-based general theorem proving, full protein folding simulation | ❌ Cost-prohibitive, infinite compute costs |
| NP (NP-Hard:Potential NP-Complete™ or Potential Fake NP™) | At least as hard as NP-complete but may not be verifiable efficiently | Large-scale AI model adaptation, AI-driven proof generation | ⚠️ High risk, requires advanced acceleration |
| NP (NP-Complete) | Problems in NP where every NP problem can be reduced to them | AI-driven logistics, cybersecurity automation, SaaS growth metrics standardization | ✅ High defensibility, scalable under heuristics. But there is 10 years time limit. |
| NP (NP-Easy™) Non-NP-Complete™ and Non-NP-Hard™ | Can be solved in polynomial time but harder than P | Predictive analytics, recommendation engines Scaling architecture | ✅ Fast scaling, SaaS-friendly |
| P (Polynomial Time) | Problems that can be solved efficiently in O(n^k) time | Quality Assuarance Simple CICD | ✅ Highly scalable, capital efficient |
| NL (Logarithmic Space) | Solvable in O(log n) space | SaaS, testing debagging, deploy automation | ✅ Rapid scaling, minimal compute cost |
| N (Logarithmic Time) | Solvable in O(log n) time | AI-driven computing resource virtualization and optimization | ✅ Highly profitable, monopoly potential |
Constraints:
✔ Undecidable and Unsolvable classes (UNSAT, EXPSPACE) should be immediately rejected for investment.
✔ NP-Complete/NP-Easy hybrid startups provide defensibility and high scalability potential.
✔ The basic strategy is getting first mover advantage to find NP-Complete proof toward logarithmic scalability (NL, N).
9.2.Classification of Game Theory Paradox™ by Computational Complexity Matrix™(CCM)™
| Game Theory Model | Computational Complexity | Solvability |
|---|---|---|
| Two-Player Zero-Sum Games (Minimax) | P (Polynomial Time) | ✅ Solvable using linear programming (Simplex Method) |
| Nash Equilibrium (Finite Games) | PPAD-Complete(Total Function NP) | ⚠️ Computationally expensive but solvable in special cases |
| General-Sum Stochastic Games | PSPACE-Complete | ❌ Requires impractical memory/computation |
| Multiplayer Nash Equilibrium (General Case) | EXPTIME-Hard | ❌ Exponential time complexity makes large cases unsolvable |
| Infinite Horizon Games (Markov Chains, Dynamic Programming) | Undecidable | ❌ No general algorithm exists to find equilibrium in all cases |
6.1 How to Identify NP-Complete/NP-Easy hybrid AI SaaS Startups
✔ NP-Complete problems have a balance between computational difficulty (moat), NP-Easy problems have practical heuristic solutions (scalability).
✔ Investors should use computational tools to verify whether a startup’s core problem is NP-Complete/NP-Easy hybrid.
| Verification Method | Purpose | Application to Startups |
|---|---|---|
| SAT Solvers (Boolean Satisfiability Checkers) | Identifies NP-Complete problems | Checking if an AI model optimizes complex constraints |
| Cook’s Theorem Reduction | Verifies NP-Complete hardness | Ensuring the AI problem isn’t just polynomial |
| Kolmogorov Complexity Measurement | Quantifies problem difficulty | Distinguishing between P and NP-Complete AI tasks |
Tools & Frameworks: By applying SAT Solvers and Cook’s Reduction, investors can mathematically verify if an AI startup is solving a valuable NP-Complete problem.
6.2 Scaling NP-Complete Startups Toward Brachistochrone Curve
The best AI SaaS startups follow the Brachistochrone Curve of Computational Scaling, transitioning from NP-Complete to NP-Easy to Logarithmic Scaling (NL, N).
| Growth Stage | Computational Complexity Class | Scaling Outcome |
|---|---|---|
| Early (Defensible Moat) | NP-Complete | Competitive advantage, but computationally expensive |
| Growth-Stage (Scalability Focus) | NP-Easy | Monetization accelerates with heuristic optimizations |
| Mature-Stage (Logarithmic Scaling) | P, NL, N | Maximum operating leverage, market dominance |
Tools & Frameworks: Successful AI SaaS startups scale their computational complexity down from NP-Complete to NL, achieving logarithmic capital efficiency.
7. Complexity Scaling Model™ (CSM™)
To systematically invest in the right AI SaaS startups, TANAAKK and HITSERIES CAPITAL introduce the Complexity Scaling Model™ (CSM™):
CSM Framework
- Classify Complexity Early
- Use SAT Solvers, Cook’s Reduction, and Kolmogorov Complexity to verify if a startup’s core problem is NP-Complete.
- Reject Undecidable and Unsolvable Startups
- If a startup is tackling an UNSAT (Undecidable) or EXPSPACE-class problem, it’s a capital sink.
- Prioritize NP-Complete Startups
- Focus on AI SaaS solving NP-Complete problems, as these provide computational moats and defensibility. Quickly verify its statement by E-ZKP™
- Zero-Knowledge Proof (ZKP)
This is a standard term from computational complexity theory where a prover can demonstrate knowledge of a value without revealing it. While traditionally used in cryptographic authentication, TANAAKK adapts its principles to startup investment. - Extended Zero-Knowledge Proof™ (E-ZKP™)
- Extended interpretation of ZKP in computational complexity. By ZKP, prover stating propositnon is true without revealing any sensitive infomation to verifier. By E-ZKP™, prover can convince truth meta-semantically without adding any knowledge in verifier.
- Mutual Zero-Knowledge Proof (M-ZKP™)
- Zero-Knowledge Proof (ZKP)
- Focus on AI SaaS solving NP-Complete problems, as these provide computational moats and defensibility. Quickly verify its statement by E-ZKP™
- Enable Logarithmic-Resource Scaling
- Guide NP-Complete startups towards NP-Easy, NL, and N-class problems within 10 years.
- Use Mutual-ZKP™ to Validate Revenue & Growth
- Investors and founders should use Mutual-ZKP™ (Zero-Knowledge Proof) technique to validate revenue and AI model claims without exposing sensitive data.
- Mutual-ZKP™ (M-ZKP™) is TANAAKK and HITSERIES CAPITAL’s original Product-Led Organic Growth™ verification models.
📌 Conclusion: By systematically applying the Complexity Scaling Model (CSM), investors and founders can optimize capital efficiency while ensuring sustainable AI SaaS startup growth.
| Version Control | DD/MM/YYYY |
| 1.1 | 05/03/2025 |