Action Principles in Startups
Disclaimer: This note is not about pure computational complexity but rather meta-semantically leverages its theoretical framework to materialize startup earnings growth.
Startups can succeed effortlessly(naturally)
Startups can succeed effortlessly (naturally), provided they understand the fundamental laws of nature. The key challenge lies in grasping the meta-semantics that exist before nature becomes “science.” Imagine standing on a beach and witnessing one exceptionally large and unusual wave among a thousand ordinary ones—patterns, parity, time-reversal symmetry, and deviations from the norm—this is precisely the type of anomaly we need to recognize. These are the kinds of phenomena we must identify to drive safely through the exciting startup journey.
1. Is a Startup a Natural Science?
A startup operates like an NP-complete problem, where it claims that an unknown problem is true and seeks a verifier to validate it. A legitimate verifier (accredited verifier) can confirm the truth of an NP-complete problem without gaining any additional information. This principle, verifiability through ZKP(Zero Knowledge Proof), where the objective is achieved with minimal energy, closely resembles the action principles found in natural sciences.
Theorem of Startup Success and the Mutual Zero-Knowledge Proof (ZKP) Framework
1-1. Every NP has a ZKP
In 1986, Oded Goldreich, Silvio Micali, and Avi Wigderson proved in their paper “Proofs that Yield Nothing But Their Validity or All Languages in NP Have Zero-Knowledge Proofs” that every NP language can have a zero-knowledge proof ZKP. This includes NP-complete problems such as 3-SAT and Hamiltonian Cycle Problems, which can be validated without revealing additional information. The proof technique relies on an interactive proof system IPS.
2. NP-Complete Problems verified by ZKP, analogy to Action Principles
An NP-complete problem is a set of problems where ideal NTM(Non-deterministic Turing Machine) can solve. If NP-complete is true, it can be verified in polynomial time, but finding the solution to prove it is difficult. Startups tackle unknown problems that are evidently true but take time to prove. If NP-complete is true, a ZKP must exist—implying that truth can be verified without understanding the reasons behind it, which minimizes energy expenditure.
Startups should focus on developing systems that follow action principles in physics—such as the principle of least energy or the principle of least action—where physical systems converge to a stable state by minimizing loss functions. NP-complete problems and ZKP can be viewed as manifestations of the principle of least action.
2-1. Correspondence Between NP-Complete Problems and the Principle of Least Energy
- Physics Perspective: NP-complete problems are akin to searching for the state of minimum energy (ground state). Physical systems converge to a stable state by minimizing loss functions.
- Mathematical Perspective: NP-complete problems have solutions that are difficult to compute but must exist—similar to how physical systems optimize local energy states.
2-2. Does ZKP Verify Action Principles?
The principle of least action in classical and quantum mechanics states that a system evolves along a path that minimizes action (energy integral). ZKP proves a proposition is true without revealing additional information(by minimum cost). Action principle resembles ZKP’s ability to verify truth efficiently.
For example, by applying ZKP concepts, we might be able to verify that a system’s ground state has achieved minimum energy without revealing additional data. NP-complete problems correspond to the principle of least energy, and ZKP serves as a method for its physical verification.
3. Relationship Between “Being True” and Energy Convergence
If NP-complete problems can be validated through ZKP with 99.999% accuracy in a single transaction, it resembles natural ground state phenomenon. For example, electrons have a 99.9999% probability of existing around the nucleus in their ground state. This reflects a natural law where matter’s energy converges to nearly 100% certainty at equilibrium.
3-1. Truth and Quantum Mechanics
- In quantum mechanics, a particle’s position and state are described by probability wavefunctions, with probabilities determined by the squared magnitude of the wavefunction.
- In the ground state, existence probabilities take their most stable form.
- Quark Confinement: Quarks are bound within the atomic nucleus by strong interactions, and their existence probability approaches 100% when energy stabilizes.
3-2. Truth and Logarithmic Functions
Interpreting “truth” as a state approaching 100% probability mirrors the mathematical behavior of logarithmic convergence, much like how the Napier number e (2.718…) emerges from exponential functions.
3-3. Defining “Truth” in Physics
A physical state reaches minimum energy, making its existence probability approach 100%. Just as the shortest curve between two points follows a curve, systems naturally optimize their loss functions.
3-4. Defining “Truth” in Computing
In machine learning, models minimize their loss function to converge toward ground truth. Geoffrey Hinton’s backpropagation and Boltzmann Machines operate within this parameter optimization framework, adjusting weights to reduce errors and approach the optimal representation (“true representation”).
4. The Relationship Between Startups and Action Principles
4-1. Startups Operate Under the Laws of Nature
- Startups should solve NP-complete problems, which describe energy-minimization principles for which proofs have not yet been found.
- In physics, the ground state is the optimal solution; in computing, NP-complete problems seek convergent optimal solutions.
- ZKP is a method to verify startup claims, analogous to how physics verifies the principle of least action.
- Observing how systems naturally optimize paths is akin to using ZKP to formally verify truth without revealing details.
- “Truth” aligns with a system’s energy convergence toward a stable state with 100% certainty.
For example, grabbing a coffee can and successfully drinking from it, without spilling, has a probability approaching near 100%—this is analogous to the natural ease with which startups should succeed if they follow these principles. Zero-knowledge proofs can drive product-led organic growth by minimizing the energy required for verification.
4-2. Revealing Meta-Semantics
Computational theory (NP-complete & ZKP), computing (machine learning) and physics (least energy & quantum mechanics) are connected at a fundamental level. This implies that startup growth and problem-solving rely on recognizing natural cycles—like the cosmological pattern (sunrise every day) or the hydrologic cycle (water moving from mountains to oceans to clouds to rain). Exploring meta-linguistics, meta-semantics meta-spacetime might help startups identify underlying opportunities.
5. Recognizing the Laws of Nature
5-1. Opportunities Are Everywhere
TANAAKK asserts that hyper-growth startups should adhere to fundamental truths (the principle of least action) in natural science, physics, and economics. However, these ideas are not universally accepted yet—they remain NP-complete problems, not NP-easy solutions. This means there are still vast opportunities in 21st-century startups.
5-2. Startups Can Succeed Effortlessly (Naturally)
Since most companies and governments do not follow natural laws, NP-complete problems are abundant, making startup success inevitable and effortless. If success were not easy, it would contradict action principles.
Success is as easy as:
- Waking up in the morning.
- Washing your face.
- Brushing your teeth.
All life operates under the energy utilization of the solar system, and all matter is subject to gravitational and mass effects. As proven by E=mc^2, mass contains enormous energy. Nature is too strong to defeat, rather we should comply it. Humans cannot achieve anything beyond what is naturally possible.
A startup is a lifestyle—if the team observe nature accurately, the insights gained from daily life differ, leading to natural success.