generative ai

Generative Engine Optimization (GEO): Technical Grounding, Entity Resolution, and Verification Framework v1.0

A technical whitepaper and verification specification for Generative Engine Optimization (GEO). Introduces deterministic entity arbitration, multi-tier evidence grounding, RFC 9309 crawler governance, and open-source validation tooling for AI search engines.

Affective Bond Between AI-Generated Music and Human Listeners

Generative artificial intelligence is being applied to create music in an ever-widening range, but it has not been determined whether the results can effectively convey human emotions. A controlled-variable experimental design is used to explore the causal relationship between information density in prompts and listene...

Secondary School Teachers’ Interaction with Artificial Intelligence Systems: A Qualitative Investigation of Usability, Trust, and the Transformation of the Pedagogical Role

This research explores secondary education teachers" perceptions regarding the integration of Generative Artificial Intelligence (GenAI) into instructional practice. Through semi-structured interviews with a sample of ten (10) educators from diverse academic backgrounds, the study examines three core pillars: interacti...

Making What AI Cannot: Generative AI and Knowledge Through Making

Contemporary industrial designers have increasing access to Generative AI, computer-aided design (CAD), and fused deposition modelling (FDM) 3D printing. These tools can expand the possibilities available to individual designers, but their value cannot be understood only through the outputs they produce. This thesis ex...

Reverse Prompt Engineering in Generative AI: A Baseline for Deepfake, Deception and Disinformation Mitigation

Generative Artificial Intelligence (AI) has democratised content creation while scaling systemic threats in Deepfakes, Deception, and Disinformation (D3). As traditional content detection and watermarking are increasingly bypassed, this paper presents a position and baseline synthesis of Reverse Prompt Engineering (RPE...

Mechanisms of Brand Authenticity Erosion in AI-Generated Advertising: A Systematic Review

The rapid adoption of generative artificial intelligence (GenAI) in advertising since 2022 has transformed content production while raising concerns about the preservation of brand authenticity, a critical foundation of consumer trust and brand relationships. This study examines how AI-generated advertising influences...

Student perceptions of generative AI in accounting education: A thematic analysis

Generative AI has outpaced pedagogical and ethical guidance in accounting classrooms, leaving students and educators uncertain whether it supports or undermines the discipline's dual emphasis on procedural accuracy and professional judgment. To address this problem, this study examines how 92 business undergraduates pe...

CONCEPTUAL EMERGENCE & GENERATIVE INTELLIGENCE AT THE LIMIT Living Concept Civilization — Flagship Research Monograph 06 STARLI / White Rainbow Civilization · October 2026 ABSTRACT When do interactions among concepts, models, tools and people produce a genuinely new, independently verifiable capacity rather than a novel label or a misleading evaluation threshold? This English-language research monograph develops a falsifiable program for conceptual emergence and generative intelligence. Its research three-coupling is Interaction Generation × New-Function Identification × Counterfactual Verification. The proposed emergence expression compares held-out capability improvement with the strongest viable baseline and a contamination penalty, with all terms requiring operational definition and appropriate normalization before use. RESEARCH DESIGN The volume studies both smooth scaling and possible discontinuities, evaluation-metric sensitivity, training-data leakage, compositional generalization, simple-rule baselines, factorial component ablation, multi-agent collaboration, correlated errors, human-AI complementarity, multimodal grounding, causal interventions, tool-dependence, calibration, cross-model reproducibility, governance, and intergenerational handoff. A claimed capability must survive preregistered unseen tasks, strong comparators, counterfactual perturbations and independent reproduction. A fluent explanation, a generated new term or a model's assertion of consciousness is not evidence of functional emergence. MONOGRAPH STRUCTURE The 82 research chapters each present one distinct proposed chapter-wide operational equation, followed by twelve independently paginated study sections. Thirty advanced physics derivation routes appear in the preface with three-dimensional conceptual diagrams; they are existing physics statements within specified domains and do not establish laws of language or awareness. The concluding 200 Research Gates and 33 Phoenix Answer Embryos each feature one of 233 distinct physical equation anchors. These equations are methodological contrasts and educational prompts, not proof of the emergence hypotheses. A separate Excel workbook indexes chapters, sections, gates, candidate mechanisms and physics anchors. EVIDENCE AND ETHICS This monograph is a theoretical and experimental research agenda. It reports no new trials, controlled effects or validated discoveries; all proposed mechanisms, metrics, forecasts and outcomes are UNVERIFIED until independently tested. The distinction between appearance under a chosen test and a robust new function must be maintained. Consent, intellectual provenance, lawful data use, security and affected persons' right to refuse are hard constraints rather than offsettable penalties. OPEN RESEARCH INVITATION Research Gates reserve space for questions that can be rejected, refined or answered by future researchers. Phoenix Answer Embryos are provisional designs that can be falsified, decomposed, recombined or responsibly retired. The goal is not a permanent claim that machines awaken or that thought obeys physical equations; it is an enduring, contestable toolkit for recognizing and scrutinizing useful new functions. FOUNDATIONS Project source: Living Concept Civilization — Eighteen Tri-Coupled Flagship Research Programs, v2.0 (2026-10-13), Flagship 06. Wei et al., Emergent Abilities of Large Language Models (2022), https://arxiv.org/abs/2206.07682. Schaeffer et al., Are Emergent Abilities of Large Language Models a Mirage? (2023), https://arxiv.org/abs/2304.15004. Chollet, On the Measure of Intelligence (2019), https://arxiv.org/abs/1911.01547. Wilkinson et al., FAIR Guiding Principles (2016), https://doi.org/10.1038/sdata.2016.18.

CONCEPTUAL EMERGENCE & GENERATIVE INTELLIGENCE AT THE LIMITLiving Concept Civilization — Flagship Research Monograph 06STARLI / White Rainbow Civilization · October 2026 ABSTRACT When do interactions among concepts, models, tools and people produce a genuinely new, independently verifiable capacity rather than a novel...

From Instrument to Co-Creator: Authorship in Generative and AI Music

This paper presents the evolving concept of authorship in music creation as algorithmic and artificial intelligence systems impact the musical market. Based on Philip Galanter's definition of generative art, the paper discusses about the authorship of music in different senerios: when it is generated by tools like Nyqu...

Full stack academic publishing in seizures with artificial intelligence: a cautionary tale

Significance: There is potential for generative artificial intelligence (AI) to perform "full stack" academic publishing, including comprehensive manuscript fabrication, "peer"-review, and editorial decision making. This study evaluated the benefits and cautions in using AI for full stack academic publishing in clinica...

Critical Inquiry After the Answer: Reconstructing Understanding in Generative AI Education

Base-3, the First Mechanistic, Deterministic, Sovereign, Ultra-low compute Substrate Open Source

Generative AI has a profound grounding problem. When applied to physical, high-stakes environments, the binary logic of "prompt and completion" collapses. A Vision-Language Model cannot inherently understand 3D spatial geometry, structural load, or contractual scheduling; it simply guesses based on 2D pixel patterns an...