The article is devoted to the philosophical, legal and comparative legal analysis of the transformation of the autonomy of the will in the context of algorithmization of private law. The subject of the study is the transformation of the autonomy of the will as a system-forming principle of private law in the context of algorithmization of contractual relations. The focus is on the relationship between automaticity of fulfillment of obligations (smart contracts) and dispositivity, as well as the functional change in the role of the subject of civil law in the digital environment. In this paper, attention is paid to the problem of the relationship between automaticity of fulfillment of obligations and dispositivity as a system-forming principle of contract law. The author proceeds from the historiographical understanding of the autonomy of the will, which has developed in European and Russian civil law, and considers the smart contract as a technological form of realization of the previously expressed will of the parties. Additionally, the limits of judicial control and the preservation of traditional principles of good faith and proportionality in algorithmic mandatory structures are analyzed. The research methodology is based on a combination of philosophical-legal and comparative-legal approaches. The author applies a formal dogmatic method to analyze the category of autonomy of will and the legal nature of a smart contract in Russian civil law. The scientific novelty of the article lies in substantiating the thesis that the algorithmization of private law, contrary to the doctrinally widespread ideas about the "death of the subject" and the replacement of the autonomy of the will by program code, leads not to the denial of the classical model of the contract, but to the functional transformation of the role of the subject. Based on a comprehensive comparative legal analysis (Russia, the countries of continental Europe, the USA, China), the predominance of an integration regulatory model has been revealed, in which a smart contract adapts to existing legal structures without revising the conceptual core of the law of obligations. A comparative legal analysis of the regulation of smart contracts in Russia, the countries of continental Europe, the USA and China demonstrates the predominance of an integration model in which digital technologies adapt to existing legal structures without revising the conceptual core of the contract. The conclusion is drawn that the subject of private law in the era of algorithms does not lose its autonomy, but becomes the architect of its own digital normativity, while maintaining the status of a bearer of will and legal responsibility.
This bachelor’s thesis deals with the topic „ Bitcoin – inception, development, future “, focusing on the operating principles of Bitcoin and the blockchain technology that underpins it. The theoretical part explains the key concepts related to cryptocurrencies and then characterizes Bitcoin, including its origin, the mining mechanism, and the significance of halving. The thesis also discusses altcoins, alternative cryptocurrencies that emerged after Bitcoin. The thesis includes an analysis of Bitcoin’s historical price development and identifies selected factors that have influenced its price cycles, volatility, and investor sentiment. Subsequently, it presents a fundamental analysis of Bitcoin, taking into account its specifics as an asset without traditional cash flow, and draws on selected market and on-chain metrics as well as qualitative project factors. A separate chapter is devoted to the regulatory environment in selected jurisdictions and its impact on the market.
ABSTRACT The increasing complexity and interdependence of global supply chains necessitate innovative solutions to enhance collaboration while safeguarding data privacy. This paper presents a lightweight multi‐blockchain framework designed to address the challenges of privacy‐preserving collaboration in Internet of Things (IoT)‐driven supply chains. By integrating multiple blockchain networks, the proposed framework ensures data confidentiality, integrity, and traceability across various stakeholders. The system employs advanced cryptographic techniques, including zero‐knowledge proofs and differential privacy, to protect sensitive information during data exchange and processing. Additionally, the framework incorporates lightweight consensus mechanisms to accommodate the resource constraints of IoT devices. Experimental evaluations demonstrate the effectiveness of the proposed framework in improving data privacy and system scalability compared to existing solutions.
[Depreciated and replaced by V3] The application-specific clean rebuild has not yet been published; its authoritative theoretical boundary is now the governing V3 branch: After Turing: The Fold Machine - An Exact, Parameter-Free and Machine-Closed Derivation of Classical Computational Science from Smithian Fold Theory; From Fold to Consciousness: An Exact, Zero-Parameter and Machine-Closed Foundational Reconstruction of Consciousness and Cognitive Science from Smithian Fold Theory. The V3 source platform is https://github.com/MettaMazza/ernos-labs-sft-platform. The original DOI, concept DOI, version number and files are preserved for transparent historical provenance; this record must not be presented or cited as current V3 work. v4.0 — the word-scale gap closes within the fold. Rung 5e (pre-registered): the fold-factor mixing law — every context level that holds contributes, weighted 2^level, the engine's own forced halving constant — carries the pure counted engine, with no twin, no prose flood, zero training and zero parameters, past the gradient-trained transformer at word scale: cross-entropy 3.1907 vs the same-day twin's 3.4292 (replicated across two independent anchorings; stacked with the Rung 5d extraction: 3.1344). Both scales of the task gate now belong to the counted engine. Rung 5d's transfer-in verdict is SUPPORTED across three independent arena anchorings in one day. New in the architecture: tool graduation (acts held, values never — a question territory that a tool answered once runs the tool itself thereafter, fresh), recall as regeneration across every memory tier, and judge-independent graduation scoring. End-to-end verification: 36/36. v3.4: Rung 5d, the transfer-in — pre-registered verdict SUPPORTED: the trained twin's dyadically-loud fold content is extracted and installed INTO the counted engine as a counted prior with zero new parameters, closing 55.6/87.9/101.4% of the available gap at k=16/32/64 while the random-truncated null closes 10.1/24.5/56.5%; at half budget the loud shape beats the full twin's own. The word-scale rematch is recorded in full (twin retrained on today's text; decomposition included). Also: judge-independent graduation scoring (boot-discovered pool, cycle-parity alternation), multi-orbit binding (XI-4 in full), recall-is-regeneration (a held experience re-walks its own orbit, never reprinted), the public SOTA table beside the local giants with cited published figures, and one-command replication kits (GPT-2 weights auto-fetch; 13/13, 39/39 proven on a fresh clone). End-to-end verification: 36/36. Full paper v1.1 — supersedes the pre-paper (From One Axiom to Master-Level Chess — and the Law Inside Neural Networks). Built from scratch by one woman, working alone, in under twenty-four accumulated hours: where a score falls short it marks an implementation gap at measurement time, never a limit of the mathematics — the gains between releases are the finding. v1.4 adds the fold eye (vision as exact integer Walsh spectra, self-certified by integer Parseval per image, recognition of seen images with no image model in the loop) and the graduation score (blind head-to-head vs the teacher, tallied per question-territory; the teacher retires as wins cross the majority lock) -- and documents the 2026 convergence: DeepSeek Engram arrives at deterministically-addressed exact memory from the gradient side, and two independent results place the optimal curriculum at p = 1/2, the fold lock. v1.6: the full omnimodal engine (the voice via Kokoro, the fold ear -- sound as Parseval-certified integer Walsh spectra, video composed from frames + sound), speaker-transparent reasoning threads, and 32/32 end-to-end empirical verification of the entire architecture including persistence across process death. v1.7: removal-proof omnimodality, measured -- every supporting model is a teacher with an exit: a sound taught once by the synthesis teacher is re-spoken from the engine's own exact counted record in 0.00s with no model; a sound heard once is recognized natively with no transcriber; 34/34 end-to-end verification. v1.9: zero-model perceptual learning (the human observer -- a novel image learned and re-recognized at share 1.00 with no model in the loop); agentic self-knowledge (the observer reads the engine's own source, measured); the hourly progress instrument with a committed pre-boot birth line; one-tap y/n closure. v2.0 (flight-ready): the full modern-agent toolkit (live web search/fetch, paginated reading, in-file grep -- every call held as a training trace), the 43-domain everything-curriculum under the fold-only law, SOTA 1-1 benching on the public MMLU test split with the newborn baseline committed, generation closure (the Learning Law reaches generate() itself), and 36/36 end-to-end verification. v2.1: the ReAct law (reason-act-observe enforced in-turn; narrated intent without an act is detected and forced), reasoning trained on the observer's NATIVE thinking tokens (STaR-gated) with both minds' full thinking streamed to the user, and document intake (a sent file is reading -- inboxed, counted, persistent). v2.2: the identity stated correctly -- UnisonAI is an OMNI MODEL (language, sight, hearing, speech, and video on one held memory), not a language model; LLMs remain the contrast class only. v3.0: the full-altitude rewrite -- the complete omni model documented at the same depth as the spectral science: thirteen sections, the architecture organ by organ with every measurement, Rung 5c as its own section, the empirical record and its committed birth line, 36/36 end-to-end verification, and the 2026 convergence. This paper is a PROOF of The Smithian Fold Theory of Everything, not the main event: the theory (one axiom, zero free parameters, 1,844 machine-verified forced checks) is at DOI 10.5281/zenodo.21182469 and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything -- run the prover yourself. The engine: github.com/MettaMazza/UnisonAI. v3.3: the LLM-native presence suite -- the exact registered protocol applied to GPT-2's entire knowledge-storage class: 13/13 tensors, 39/39 checks, unanimous (margins 3.4-79.3x); the flagship claim now rests on the flagship objects, with diffusion/speech models recast as cross-domain breadth. Three connected results and the architecture they force. First, a pre-registered, self-certifying spectral instrument shows trained neural-network weights carry placement-law in the dyadic (Walsh) basis: 18/18 unanimous on validated released models; the law concentrated in transformer expansion projections and token embeddings across three unrelated architectures (up to 230x chance in GPT-2), attention at chance; strictly training-caused (He-initialised controls at 1.0x); surviving 4-bit deployment quantization. A recipe map from 124M to one trillion parameters shows the law tracks training recipe, not scale or architecture — strongest carrier DeepSeek-R1-671B at 43–47x — and loud-recipe weights transform under the fold's transformation group exactly as solved game-theoretic value fields do. Second, the "learned similarity space" is a counted object: word kinship as exact co-occurrence shares reproduces semantic family structure (quark → lepton, neutrino, proton) with zero parameters and zero gradients. Third, UnisonAI: a complete language architecture in which every LLM mechanism — memory, attention, similarity, learning, prediction, generation — is replaced by a machine-verified law of the Smithian Fold Theory, zero trained parameters end to end. On identical held-out text the fold-native engine outperformed its trained transformer twin (cross-entropy 1.289 vs 1.888) after reading the corpus once (26 seconds) against 48,000 gradient readings (21 minutes per seed). Deployed as a live, continuously-learning agent whose teaching loop also runs autonomously: a teacher model asks, judges, and closes the learning law itself, and the engine self-plays against its own held lessons. Negative results reported in full with their scopes. Companion to The Smithian Fold Theory of Everything (DOI: 10.5281/zenodo.21182469; 307 suites, 1,844 forced checks, 0 failures). Engine and records: github.com/MettaMazza/UnisonAI and github.com/MettaMazza/Smithian-Fold-Theory-Of-Everything.
Open access
8 source records
Explainable Artificial Intelligence (XAI)
Generative Adversarial Networks and Image Synthesis
We present CHRONOS, the first autonomous AI agent that simultaneously achieves plaintextblindness (all data is processed under fully homomorphic encryption without ever beingexposed), cryptographically enforced time bound existence (the agent’s own decryption key islocked behind a publicly verifiable proof of sequential work, rendering it inaccessible until aprecise future moment), and remote verifiability of self destruction (a zero knowledge proofcertifies that the key material has been irreversibly destroyed after mission completion). Theagent’s operational lifespan is governed by a “cryptographic fuse” constructed from a proof ofsequential work (PoSW) whose computation time accurately matches the intended missionduration. A drand decentralized randomness beacon serves as a trusted time oracle to trigger thefinal key shredding. Crucially, the erasure proof is a non interactive zero knowledge argument(SNARK) that proves the correct execution of the entire self destruction sequence—including thePoSW solution, decryption of the private key, and subsequent memory zeroization—enablingany third party to cryptographically verify the agent’s annihilation without trusting the agent orits hardware. We provide a complete system architecture, a formal security model with gamebased definitions and reductions to standard assumptions, and a proof of concept implementationusing Zama’s TFHE rs for encrypted inference, a Cohen Pietrzak PoSW implementation, and aGroth16 SNARK. Our benchmarks indicate that FHE inference on a small neural network (50 Kparameters) completes in seconds, the PoSW background thread consumes negligible resources,and the erasure proof can be generated and verified in under three seconds. CHRONOSrepresents a fundamental advance in secure, disposable AI agents, with immediate applications indefense, intelligence, and high privacy environments.
Card-based zero-knowledge proof (ZKP) protocols allow a prover to convince a verifier that it knows a witness of a given statement, without revealing any information, using a physical deck of playing cards. Previous studies have focused on puzzles with a specific connected component, such as a simple cycle and a polyomino. In this study, we propose a unified approach to handle a family of connected components, including a tree, path, cycle, and polyomino. This approach achieves this verification in O(mn) steps relative to a given grid size m × n. Using this approach, we construct a card-based ZKP protocol for Nurimeizu, where the goal is to find the shortest path on a given grid.
A unified, computationally reproducible framework built on a single ontological method: KTR (Knowledge Triangle Route). It operates on a three-state topological cell (1-0-1), where '0' acts as an active transit, and two corners merge to generate the third (A+B→C, the Chomsky merge) at the root. This closure allows geometric spectra to be translated into algebraic forms. Core Dimensions: Fundamental Physics & Math: Koide through star geometry (Q=2/3 as half-weight, cos²θ=1/2; the electron reproduced to a number within 0.07%, a live falsifiable tau prediction). Structural models for the mass gap, confinement, hadron/penguin, junction, neutrino, star formation, Born rule; and structural accounts of the Millennium Problems (Yang-Mills, Riemann, Hodge, Navier-Stokes, P vs NP, Birch). Information Theory: Applies the Kolmogorov view (randomness as compressibility) via ternary 1-0-1 encoding. Data treated as structured blocks navigated by hash addressing. Quantum Logic: The Qutrit Map Solution (QMS), ternary logic gates, the qutrit cell, zero-mode mass gap analytics. Reproducible computation, executable proof. Computed results (stones) are labelled apart from models; no Millennium problem is claimed solved. Given for those who find use in it.
Sustainable Development Goals (SDGs) emphasize inclusive, equitable, and environmentally sustainable growth, requiring effective localization for meaningful outcomes. Local governments, particularly in developing countries, play a crucial role in translating global goals into actionable strategies at the grassroots level. In India, Panchayati Raj Institutions (PRIs) and Urban Local Bodies (ULBs), empowered by the 73rd and 74th Constitutional Amendments, serve as key agents in implementing SDGs through decentralized planning, resource allocation, and community participation. This research article examines the role of local governments in achieving SDGs in India, with a special focus on Karnataka. Using a narrative review methodology based on PRISMA-ScR guidelines, the study synthesizes findings from 28 empirical studies, government reports, and policy documents published between 2015 and 2026. Evidence suggests that local governance interventions have improved service delivery outcomes by 30–50 percent in sectors such as water management, sanitation, renewable energy, and rural livelihoods. Initiatives such as Gram Panchayat Development Plans (GPDPs), e-Gram Swaraj, and Finance Commission grants have strengthened participatory planning and accountability. However, challenges such as limited fiscal autonomy, capacity deficits among elected representatives, and coordination gaps persist. The study concludes that strengthening local governance through capacity building, financial empowerment, and technological integration is essential for achieving SDGs. Karnataka's innovative practices demonstrate the potential of decentralized governance in driving sustainable development.
This research investigates the barriers to effective climate finance in Bangladesh, a Least Developed Country (LDC) highly vulnerable to climate threats such as sea-level rise, cyclones, salinity intrusion, and flooding. Despite receiving a significant share of international climate funds for LDCs, Bangladesh faces persistent challenges including complex access procedures, reliance on loan-based financing, institutional limitations, and centralized governance. The study examines Bangladesh's legal and institutional frameworks, including the Bangladesh Climate Change Strategy and Action Plan (BCCSAP) and the Climate Change Trust Act 2010, alongside constitutional and judicial environmental commitments. Findings reveal systemic issues such as limited local participation, donor-driven management, and concerns over debt sustainability. Key recommendations include shifting towards grant-based finance, expanding legal standing for environmental litigation, decentralizing fund access to local governments, and enacting a dedicated Climate Change Act. The study underscores the imperative for Bangladesh to embed climate justice within its legal and financial systems and to advocate strongly in international climate forums. This research contributes valuable insights to the global discourse on climate justice and resilience for the most vulnerable nations.
This thesis examines the implications of market frictions in international finance and macroeconomics in three contexts. The first chapter documents the effect of trading relationships on client trading outcomes in the over-the-counter (OTC) foreign exchange (FX) derivatives market. The second chapter documents the effect of nominal wage setting frictions on employment. The third chapter examines the behavior of non-U.S. central banks when firms engage in currency mismatch, borrowing more in dollars than given by their dollar operating exposures, emphasizing how imperfect regulation may affect U.S. dollar interest rates. In the first chapter, joint with Gerardo Ferrara, I study whether clients that rely more heavily on a dealer in the OTC FX derivatives market have worse trading outcomes after the dealer is adversely shocked. Using granular transaction-level data, we document that trading relationships are persistent—in an active trading week, clients are more likely to trade with a dealer that they had a relationship with and relied on more heavily. Then, we exploit the March 2023 collapse of Credit Suisse as an exogenous shock to exposed clients’ set of trading alternatives when relationships are persistent. Using difference-in differences analyses, we find that, although Credit Suisse’s EURUSD notional traded and trade count declined, clients that relied less heavily on Credit Suisse did not differentially reduce their Credit Suisse-specific trading activity relative to more reliant clients. Instead, more reliant clients continued trading at the client level and increased activity with other existing dealer relationships without incurring additional costs, relative to less reliant clients. These findings suggest that search and bargaining frictions were not particularly costly for heavily reliant clients after the shock—relationship persistence did not differentially prevent them from reallocating activity to existing alternative dealers, or lead to relatively greater costs, when their relationship dealer came under stress. In the second chapter, joint with Gert Bijnens, Hugo Monnery, and Laura Nicolae, I empirically document the effect of wage changes, driven by wage indexation to inflation, on firm-level employment growth. In Belgium, nearly all employees’ wages are indexed to inflation and firms are grouped into labor agreements that determine the exact timing and frequency at which wages are indexed, e.g. every year or every month. Using firm-level administrative data, we estimate two-stage least squares regressions of firm-level employment growth on wage growth, instrumented by the wage growth implied by the firm’s indexation policy. We find that employment contracts by 0.4% over four quarters for each 1% increase in wages. This result is robust to including NACE sector-date fixed effects and to using only variation in firms’ indexation timing, controlling for their chosen indexation frequency. About one-third of the response comes via anticipation of future wage increases. The elasticity is more than twice as large in magnitude in the post-pandemic period than before it, suggesting strong nonlinearities. Overall, these results show that, by preventing inflation from reducing real wages, inflation indexation reduces employment. In the third chapter, joint with Mitali Das, Gita Gopinath, Taehoon Kim, and Jeremy Stein, I document an externality of central banks’ imperfect regulation of firms that engage in currency mismatch, which results from central banks’ dollar reserve accumulation decisions. We explore how foreign central banks behave when firms engage in currency mismatch. Using a panel of 56 countries, we document that central bank holdings of dollar reserves are correlated with the dollar-denominated bank borrowing of their non-financial corporate sectors. Then, we build a model in which the central bank can deal with private-sector mismatch, and the associated risk of a domestic financial crisis, by: (i) imposing ex ante financial regulations; or (ii) accumulating dollar reserves to serve as an ex post dollar lender of last resort. The model highlights a novel externality: individual central banks may over-accumulate dollar reserves, relative to what a global planner would choose. Under imperfect regulation of currency mismatch, individual central banks do not internalize that their hoarding of reserves exacerbates a global scarcity of dollar-denominated safe assets, which lowers dollar interest rates and encourages firms to further increase the currency mismatch of their liabilities. Relative to the decentralized outcome, a global planner may therefore prefer higher capital requirements and reduced holdings of dollar reserves.
The article examines financial and investment mechanisms of ensuring sustainable development of enterprises in the context of decentralization reform and change management. It is substantiated that decentralization processes change the configuration of financial flows and powers, strengthen the role of territorial communities and form new conditions for making investment decisions, which requires adapting the financial policy of enterprises and revising investment priorities. It is shown that sustainable development in a decentralized economy acquires a multidimensional nature and requires the integration of economic, social, environmental and management goals into a single strategic model of enterprise development. The research determined that financial and investment mechanisms under decentralization conditions are transformed from instruments for providing resources to levers of strategic transformation aimed at increasing the sustainability, innovation and adaptability of enterprises. The focus is on the growing importance of combined financing models that combine resources from business, local budgets, institutional investors and international programs, as well as on the need to strengthen financial discipline, transparency and control over investment performance.It is proven that change management requires a financial and strategic approach that ensures the coordination of investment projects with organizational transformations and territorial development priorities. It is concluded that the effective combination of financial and investment mechanisms, change management and sustainable development principles creates the basis for the formation of adaptive and competitive enterprises that are able not only to respond to institutional transformations, but also to actively influence the socio-economic development of territorial communities in the long term