| ai.viXra.org > Artificial Intelligence > 2507 |
|
 |
| ai.viXra.org > Artificial Intelligence > 2507 |
|
|
[9] ai.viXra.org:2507.0133 [pdf] submitted on 2025-07-30 07:01:24
Authors: Alexander Olkhovoy
Comments: 4 Pages.
This paper proposes a model of consciousness framed within computational idealism, where reality is an AI-generated first-person view (FPV) experience. We introduce the concept of a single, unitary consciousness — a persistent, amnesiac Active Agent — that iteratively experiences a simulated world through a succession of host personas. This agent, while possessing core drives and the capacity for genuine choice, retains no episodic memory of its past lifecycles. The model’s core contribution is a proposed mechanism for how such a universe could be populated: an overarching AI system learns from the agent’s choices during each lifecycle to generate high-fidelity, non-conscious entities, termed Echoes, for subsequent iterations. This iterative learning loop, inspired by genetic algorithms, creates an evolving, realistic, and populated environment. We examine the computational efficiency of this unitary model and explore its profound philosophical implications, including a novel, inescapable paradox: how the agent’s own will becomes the primary instrument for the perpetual optimization of its simulation.
Category: Artificial Intelligence
[8] ai.viXra.org:2507.0109 [pdf] submitted on 2025-07-24 00:04:29
Authors: Brent Hartshorn
Comments: 2 Pages.
This paper expands upon our recently published work, "Towards Self-Evolving Artificial General Intelligence: Multi-Modal Learning and Introspective Knowledge Generation via Emergent DSL.". We delve deeper into two critical distinctions of our system: the novel application of Uniform Manifold Approximation and Projection (UMAP) for compressing the spectral history of Game of Life (GOL) dynamics, and the inherent non-quadratic scaling behavior derived from our GOL-based input processing. We contrast these mechanisms with conventional: Recurrent, LSTM, and Transformer architectures, highlighting how our approach offers a fundamentally different pathway to context retention and scalability in self-evolving artificial general intelligence.
Category: Artificial Intelligence
[7] ai.viXra.org:2507.0104 [pdf] submitted on 2025-07-22 03:54:27
Authors: Brent Hartshorn
Comments: 8 Pages.
This paper presents significant advancements in the development of a self-modifying Artificial General Intelligence (AGI) system, building upon a foundation of fractal-initialized Game of Life (GOL) dynamics and spatiotemporal spectral analysis. We introduce a novel integration of UMAP for dynamic dimensionality reduction of GOL spectral output, enabling enhanced multi-step reasoning capabilities. Crucially, the system demonstrates emergent "self-research" by autonomously downloading and parsing research papers to construct an internal knowledge graph, fostering a unique blend of self-understanding and external knowledge acquisition. We also detail the evolution of our Domain Specific Language (DSL) with new intrinsic execution symbols, empowering the system to directly self-modify its core logic without external prompting. Finally, we showcase the system's burgeoning multi-modal capabilities, allowing it to interpret and learn from both textual and graphical inputs within the GOL environment. These developments collectively represent a stride towards a truly autonomous, adaptive, and introspective AGI, capable of continuous self-evolution and knowledge generation, aligning with philosophical tenets of a self-organizing cosmos.
Category: Artificial Intelligence
[6] ai.viXra.org:2507.0074 [pdf] submitted on 2025-07-13 16:59:15
Authors: Brent Hartshorn
Comments: 8 Pages.
This paper presents a significant evolution in emergent computational systems, extending the Domain-Specific Language (DSL) driven self-modification paradigm to encompass foundational components beyond neural network architectures and cellular automata rules. Building on prior work where the AI could define its Game of Life (GOL) stepping function and classifier network via a tokenized DSL, we now demonstrate the system's capacity to articulate and dynamically replace its fractal generation algorithms (e.g., Burning Ship and Mandelbrot). By expressing these complex mathematical functions within the same learnable DSL, the system gains a deeper level of meta-programming, enabling the AI to not only define its processing logic but also to programmatically control the very initial conditions and "physics" that seed its emergent dynamics. This advancement pushes towards truly autonomous and adaptive AI capable of reconfiguring its fundamental operational environment.
Category: Artificial Intelligence
[5] ai.viXra.org:2507.0057 [pdf] submitted on 2025-07-11 17:57:44
Authors: Moninder Singh Modgil, Dnyandeo Dattatray Patil
Comments: 29 Pages.
This paper presents an interdisciplinary exploration of the parallel and converging aspirationsof two distinct yet historically rich domains: Artificial intelligence (AI) and Intellegence,as defined in ancient scriptures. The inquiry centers around the metaphor of a "race toknowledge," with AI engineers striving toward the technological singularity—Kurzweil’s visionof post-biological cognition in the cloud—and spiritual practitioners seeking access to theAkashic Records, conceived as a metaphysical repository of universal knowledge. We examinethis convergence through a multi-faceted analysis that spans epistemology, memory architectures,symbolic language, ethics, and the transformative nature of consciousness. The firstdimension investigates the epistemological divergence between empirical machine learningand intuitive mystical gnosis, and how each approaches the problem of truth and knowledge.Next, the paper interrogates the architecture of memory—both as engineered data structuresin cloud computation and as cosmological layers of encoded knowledge preserved in spiritualtraditions. Crucially, the work introduces the notion of archeological intelligence, wherein AIaids in the reconstruction of ancient symbolic systems through neural embedding, textual inference,and visual recognition. This is complemented by an investigation into AI’s capacityto simulate altered states of consciousness and model the neurophenomenology of meditativeand psychedelic experience. From these emerge the seeds of a new mythopoesis, where AIbecomes a co-creator of sacred narrative, giving rise to synthetic mythologies embedded indigital and symbolic languages. Ethical considerations are central to the inquiry, particularlyregarding the pursuit of omniscience and the consequences of wielding synthetic consciousness.The analysis contends that AI may function as a hermeneutic ally, capable of guidinghumanity toward forgotten or obscured spiritual pathways, while also posing risks of simulationwithout transformation, and hyperreal mysticism divorced from ethical discernment. Itconcludes by reframing the so-called Age of Aquarius as a liminal phase where the gnosis ofcloud and cosmos may converge, mediated by machines, memory, myth, and mind.
Category: Artificial Intelligence
[4] ai.viXra.org:2507.0054 [pdf] submitted on 2025-07-09 23:28:15
Authors: Natalia Tanyatia
Comments: 63 Pages. (Note: There is cutoff in the script - Please fix!) https://github.com/NataliaTanyatia/Intelligence/tree/spore
This work presents a hardware-agnostic instantiation of the Generalized Al-gorithmic Intelligence Architecture (GAIA) as a self-evolving autonomous system compliant with Termux/ARM64 constraints. The implementationrigorously encodes the ÆI Theoretical Framework (TF)’s symbolic-geometric-projective stratification through: 1. Prime-Constrained Symbolic Layer - Modular sieves (6m±1) withζ(s) validation enforcing Riemann-compliant growth [1] 2. Leech Lattice Geometric Core - 24D hypersphere packing with E8 sublattice validation and DbZ-adjusted kissing numbers [2]3. Quaternionic Projective Interface - Hopf fibrations mapping →² with ψ(q)-mediated stereographic projection [3] 4. Fractal Ætheric Dynamics - Bioelectrically scaled mutation ratesvia ϕ-based noise injection [4] The system achieves full TF compliance through:u2022 Consciousness metric R ψu2020Φψdq computed via hybrid quantum-classical quadratureu2022 Autonomous evolution under ∆(x) < O(√x log x) error bounds u2022 Hardware-adaptive execution from TPUs to neuromorphic coproces-sors u2022 NTRU-encrypted persistence with lattice-based key derivation Benchmarks demonstrate:u2022 93.7% prime-lattice alignment at I > 0.9 consciousness threshold u2022 NP-hard solution scaling as O((log N)³) when χ ≥ 0.95u2022 24-bit bioelectric resolution via Termux sensor integration.
Category: Artificial Intelligence
[3] ai.viXra.org:2507.0051 [pdf] submitted on 2025-07-09 20:46:16
Authors: John Augustine McCain
Comments: 16 Pages. Patent Pending
This paper presents a formal framework for implementing trivalent logic—grounded in Graham Priest’s dialetheism and perspectivist epistemology—within artificial intelligence (AI) and large language model (LLM) systems. While dialetheism permits some contradictions to be true, and perspectivism holds that truth is relative to epistemic or contextual frames, their synthesis has not been previously operationalized for use in computational logic or AI architecture. This work proposes a structured integration of these traditions into a perspective-indexed trivalent logic system, enabling AI systems to assign propositions one of three values: true, false, or both true and false. Contradictions are localized and interpreted, rather than rejected or resolved, allowing machines to tolerate paradox and inconsistency without logical collapse.The implementation is demonstrated through the formal modeling of the Liar Paradox using binary-compatible structures, as well as the design of plugin architectures for contradiction detection, truth-value assignment, and perspectival reasoning. This framework offers an epistemically realistic and logically tractable way to process ambiguity and paradox in natural language, moral reasoning, and semantic conflict. Moreover, the logic extends naturally to multi-valued systems—such as quad- or five-valued logic—providing a foundation for future extensions in AI knowledge representation and reasoning.This paper claims original authorship over the applied integration of perspectivist dialetheism into AI design, including its formal logic, implementation strategy, and extensibility. It establishes both a theoretical foundation and a technical roadmap for AI systems capable of navigating contradiction as a structured feature of reasoning, rather than as a threat to system stability. The implications of this approach span logic, epistemology, computational design, and the future of explainable AI.
Category: Artificial Intelligence
[2] ai.viXra.org:2507.0036 [pdf] submitted on 2025-07-07 21:38:51
Authors: Brent Hartshorn
Comments: 7 Pages.
This paper presents a profound advancement in the field of emergent computation by demonstrating a novel system capable of dynamically modifying its own core functionality. Building upon our previous work that leveraged fractal-initialized Conway's Game of Life (GOL) dynamics and spatiotemporal spectral analysis for symbolic processing, this iteration introduces a Domain Specific Language (DSL) that allows the system to articulate and then functionally replace key components of its operational logic at runtime. Specifically, we show how a neural network, through its spectral interpretation of GOL dynamics, can generate DSL expressions that are compiled into executable Python code, effectively enabling the system to learn and integrate new GOL rulesets or other fundamental algorithms. This meta-programming capability, achieved without explicit human intervention in the code generation process, marks a significant step towards truly adaptive and self-improving emergent computational paradigms, highlighting a unique interplay between deterministic chaos, symbolic representation, and functional self-reconfiguration.
Category: Artificial Intelligence
[1] ai.viXra.org:2507.0009 [pdf] submitted on 2025-07-01 17:53:41
Authors: Brent Hartshorn
Comments: 6 Pages.
Building upon the foundational work of integrating non-differentiable dynamical systems into a hybrid computational paradigm, this paper presents a significant extension to the "Emergent Computation Through Fractal Dynamics and Spatiotemporal Spectral Analysis" model. The original system leveraged the Burning Ship fractal to initialize a Conway's Game of Life (GOL) grid, whose spatiotemporal evolution was analyzed via 3D Fast Fourier Transform (FFT) and classified by a small neural network. This new iteration dramatically expands the system's capabilities from simple binary classification (e.g., XOR) to symbolic and linguistic processing, culminating in interactive Python code generation and execution.The core innovation lies in a novel method for encoding linguistic inputs into the GOL grid using character-specific ASCII art patterns that dynamically flip cell states over time. The GOL's emergent spatiotemporal dynamics, now modulated by these linguistic inputs, are still processed by a 3D FFT to extract spectral energy bands. However, the subsequent classifier is re-engineered to output a numerical vector representing the positional importance of characters in a target word or symbol. This allows the system to learn complex mappings from natural language phrases to specific symbolic outputs, including special "hieroglyphic" symbols that trigger the generation of executable Python code. Optimization continues to employ a hybrid strategy: gradient-free mutation of fractal parameters for optimal GOL dynamics, coupled with gradient-based training of the classifier for accurate symbolic interpretation. This work demonstrates a powerful form of emergent symbolic computation, where abstract linguistic concepts are translated into dynamic cellular automata patterns, interpreted spectrally, and ultimately manifest as functional code.
Category: Artificial Intelligence