Foundation models are increasingly central to digital economies, yet their market structure remains sparsely quantified. This article asks how economic dynamics of winner‑take‑all markets manifest in the foundation‑model sector, what barriers to entry shape competitive equilibrium, and how switching costs influence firm behavior. We address these questions through a three‑pronged empirical stra...
Treaty monitoring traditionally relied on manual reviews of satellite archives, customs ledgers, and financial disclosures. Recent pilots in the North Atlantic Treaty Organization and the Financial Action Task Force show how AI can process petabytes of data to surface anomalous patterns quickly. This article investigates AI pipelines that support modern treaty verification and addresses three r...
Artificial intelligence (AI) is increasingly viewed as a strategic lever for value creation, yet organizations struggle to translate experimental projects into measurable returns on investment (ROI). This article investigates the latency — defined as the elapsed time from project approval to the first observable quantifiable benefit — across four major industry verticals: financial services, lo...
The integration of artificial intelligence tools into scholarly workflows has transformed how research is conducted, disseminated, and evaluated [1] [1]. Among the most visible manifestations of this shift is the emergence of human-AI co-authorship, where AI systems contribute substantively to the intellectual content of academic papers [2] [2]. This phenomenon raises critical questions about r...
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The rapid advancement of vision-language models (VLMs) has expanded their applicability across scientific domains, yet systematic evaluations of their real-world utility remain fragmented. This article addresses the gap between general benchmark scores and domain-specific performance by presenting a structured benchmarking framework for VLMs on scientific and engineering tasks. We pose three re...
The rapid integration of artificial intelligence (AI) into Safety‑Critical and High‑Performance Computing (HPC) domains demands formally verifiable assurance techniques that can certify model behavior against formally expressed specifications. Traditional software engineering employs code‑coverage criteria such as Modified Condition/Decision Coverage (MC/DC) and branch coverage to demonstrate t...
The rapid expansion of digital platforms has transformed labor markets, but tax compliance remains uneven due to fragmented reporting of gig worker income. This article quantifies the tax gap created by under-reporting of platform-generated [REDACTED]gs in the European Union and the United States, and evaluates emerging artificial intelligence–driven data‑matching techniques that reconcile plat...
The rapid adoption of large language models (LLMs) for commercial applications has shifted focus from isolated inference to shared, multi‑tenant serving environments. While existing studies address scaling and latency optimization, they often neglect the equitable allocation of compute resources across distinct business units, leading to SLA violations and cost imbalance. This article investiga...
Academic Citation: Ivchenko, Oleh, Ivchenko, Iryna (2026). The Inference Cost Collapse: Economic Implications of 10x Annual Price Reductions for LLM APIs. Research article: The Inference Cost Collapse: Economic Implications of 10x Annual Price Reductions for LLM APIs. Odessa National Polytechnic University, Department of Economic Cybernetics. DOI: 10.5281/zenodo.21363672 · View on Z...