📚 Academic Citation: Ivchenko, O. (2026). How Our War Prediction Model Anticipated the Iran Conflict. War Prediction Series. Stabilarity Research Hub, ONPU. DOI: 10.5281/zenodo.18816597 Abstract On February 28, 2026, the United States and Israel launched coordinated military strikes on Iran, marking the most significant Middle Eastern conflict escalation since the Iraq War. Our Stabilarity War…
Author: Admin
When AI Finally Beats the Experts: DeepRare and the End of the Diagnostic Odyssey
📚 Academic Citation: Ivchenko, O. (2026). When AI Finally Beats the Experts: DeepRare and the End of the Diagnostic Odyssey. Future of AI Research Series. O.S. Popov Odesa National University of Telecommunications.DOI: 10.5281/zenodo.18730582 Abstract A new AI system published in Nature has achieved what many thought impossible: diagnosing rare diseases more accurately than experienced physicians….
The Cognitive Shift: A Creative Vision of How AI Will Change the Way We Think and Perceive
📚 Academic Citation: Ivchenko, O. & Grybeniuk, D. (2026). The Cognitive Shift: A Creative Vision of How AI Will Change Human Thinking. Future of AI Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.14865432 Authors: Oleh Ivchenko, PhD Candidate & Dmytro Grybeniuk, MSc Affiliations: Odessa National Polytechnic University | Irvine Valley College; Odessa National Polytechnic University Series:…
The ROI Timeline — Realistic Expectations for Enterprise AI Projects
📚 Academic Citation: Ivchenko, O. (2026). The ROI Timeline — Realistic Expectations for Enterprise AI Projects. Cost-Effective Enterprise AI Series. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18672405 Abstract The single most damaging piece of misinformation in enterprise AI is the promise of rapid return. Vendor decks routinely project ROI within 6-12 months; the empirical reality is…
AI Maturity Models — Assessing Your Organization’s Readiness and Investment Path
📚 Academic Citation: Ivchenko, O. (2026). AI Maturity Models — Assessing Your Organization’s Readiness and Investment Path. Cost-Effective Enterprise AI Series, Article 6. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18662988 Abstract Organizations consistently overestimate their AI readiness while underestimating the investment required to bridge maturity gaps. Through analysis of 47 enterprise AI implementations across financial services,…
Gap Analysis: Explainability-Accuracy Tradeoff in High-Stakes Domains
📚 Academic Citation: Dmytro Grybeniuk & Oleh Ivchenko. (2026). Gap Analysis: Explainability-Accuracy Tradeoff in High-Stakes Domains. Anticipatory Intelligence Series. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18662985 Abstract The explainability-accuracy tradeoff represents one of the most economically consequential yet technically intractable gaps in anticipatory AI systems. High-stakes domains—healthcare diagnostics, financial underwriting, legal risk assessment, and autonomous systems—demand…
Cost-Effective AI: Deterministic AI vs Machine Learning — When Traditional Algorithms Win
Cost-Effective AI: Deterministic AI vs Machine Learning — When Traditional Algorithms Win Author: Oleh Ivchenko Lead Engineer, Enterprise AI Division | PhD Researcher, ONPU Series: Cost-Effective Enterprise AI — Article 5 of 40 Date: February 2026 DOI: 10.5281/zenodo.18650875 | Zenodo Archive Analysis of 156 enterprise implementations reveals that 34% of deployed ML systems would achieve…
Cost-Effective AI: Total Cost of Ownership for LLM Deployments — A Practitioner’s Calculator
📚 Academic Citation: Ivchenko, O. (2026). Cost-Effective AI: Total Cost of Ownership for LLM Deployments — A Practitioner’s Calculator. Cost-Effective Enterprise AI Series. Odesa National Polytechnic University. DOI: 10.5281/zenodo.18630010 Abstract Large Language Model deployments present enterprises with a deceptively complex cost structure that extends far beyond simple API pricing. After analyzing 47 enterprise LLM implementations…
AI Economics: Model Selection Economics — The Hidden Cost-Performance Tradeoffs That Make or Break AI ROI
AI Economics: Model Selection Economics — The Hidden Cost-Performance Tradeoffs That Make or Break AI ROI Author: Oleh Ivchenko Lead Engineer, Enterprise AI | PhD Researcher, ONPU Series: Economics of Enterprise AI — Article 16 of 65 Date: February 2026 DOI: 10.5281/zenodo.18629905 | Zenodo Archive Abstract Model selection represents one of the most consequential economic…
AI Economics: Bias Costs — Regulatory Fines, Legal Liability, and the Economics of Reputational Damage
📚 Academic Citation: Ivchenko, O.. (2026). AI Economics: Bias Costs — Regulatory Fines, Legal Liability, and the Economics of Reputational Damage. AI Economics Series. Odessa National Polytechnic University. DOI: 10.5281/zenodo.18627664 Abstract Algorithmic bias represents one of the most economically significant risks in enterprise AI deployment, yet its true costs remain chronically underestimated in project planning….