Jaehong Kim

** Jaehong Kim is a researcher focusing on the development of the Convergent Fusion Paradigm (CFP) theory, a novel framework that redefines the relationship between data and algorithms through Hilbert space-based abductive reasoning. His work spans causal inference, explainable AI, generative models, and philosophical approaches to AI transparency and accountability. His recent research explores the limitations of distance-based optimization in latent spaces and proposes alternative mathematical formulations to address identifiability, emergence, and generative capacity.

Present

Causal Inference, Generative Models, Latent Space Geometry, Abductive Reasoning, Quantum Computing and AI

2023 – Present

Hilbert Space Modeling, Reinforcement Learning, Large Language Models

2023 – Present

Law and Artificial Intelligence, GDPR, Deep Learning Philosophical Framework, eXplainable AI, Explainability, Counterfactual Method

2021 – Present

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