Artificial intelligence (AI) is evolving towards hybrid models that combine statistical machine learning with semantic ontologies, creating verifiable and trustworthy systems. This level of integration allows organizations to manage vast data streams while ensuring accountability and transparency in decision-making. Ontology-driven clustering is a key method, enhancing traditional machine learning to produce more understandable and contextually relevant outputs. This approach functions effectively across sectors like finance, healthcare, and cybersecurity, where semantic overload can obscure true meanings. By structuring knowledge based on domain-specific frameworks, hybrid AI allows for clearer analysis and faster strategic decisions, transforming raw data into actionable insights. The ongoing interplay between machine learning and ontologies leads to continuous improvement in AI systems, fostering a dynamic environment for adaptive intelligence and data interoperability.
👉 Pročitaj original: CIO Magazine
