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Framing the Opportunity
Currently, most AI systems attempt to replicate human intelligence by leveraging various algorithms to detect patterns in data, be that unstructured text or structured data from disparate sources. However, these systems are often difficult to reuse or reapply to new domains. They are able to perform impressive inferences in a narrow domain but fail to be able to reuse this effectively or broadly. In this way these systems lack a feature of intelligence we see in humans, the ability to take what they've learned in one domain and reapply it elsewhere. In this respect, there is not much real reasoning or understanding.
How Businesses Benefit
Semantic technology engages the challenges of data integration, management, processing and analytics with a conceptual framework. This conceptual framework can take the form of semantic networks of linked concepts and semantic data models like ontologies. Ontologies describe the concepts themselves and also clarify the relationships between concepts, providing context and a common vocabulary for practitioners who need to share information in a domain, facilitating deeper insights into your data.
More Intelligent Machines
With semantic technology, data integration is easier to achieve and users can leverage their data in combination with the conceptual framework to infer new meaning from their concepts. Technologists can develop analytic environments that can be more easily reused, reducing data onboarding work and facilitating easier variable management and explanation generation.