26 September 2018

The Importance of Semantic AI

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Jeremy Bentley, CEO and Founder of Smartlogic Semaphore Inc, a key Partner to Mentum Systems, presents an informative view on the importance of semantic AI.

Implementing AI applications is an important topic for organizations embracing digital transformation. According to Gartner’s Top 10 Strategic Technology Trends for 2018: Intelligent Apps and Analytics, by 2020, thirty percent of CIO’s will include AI in their top five investment priorities.

Semantic AI is more than “another machine learning algorithm,” It combines a number of AI technologies including machine learning, natural language processing and semantic processing as a collaborative interplay between humans and machines to drive analytics, automation and insight. This approach allows machines, as well as people, to understand, share and reason on data, be it structured, semi-structured or unstructured; internal or external to the enterprise. From a UX perspective, semantic AI provides far more intelligent, capable, relevant, and responsive interaction than with traditional information technologies alone.

Different from traditional information processing methods, Semantic AI encodes meaning and context separately from data, content files, and application code. This allows analytics, insight, and information automation projects to be quickly implemented and deliver high data veracity. Crucially, meaning and context are controlled and moderated by subject matter experts capturing their domain knowledge in ontologies (models). The Semantic AI engine, in our case Semaphore, delivers this as high-quality metadata – which is “reasoned through” data.

Semantic AI provides an abstraction layer on top of existing IT technologies that enable bridging and interconnection of data, content, and processes without human intervention every time there is a change. With semantics, adding, changing and implementing new relationships or interconnecting programs in a new way can be as simple as changing the external model the programs share.

Traditional information technology requires meanings and relationships are predefined and “hard-wired” into data formats and application program code at design time. This means that when something changes, humans must get involved. Off-line, the parties must define and communicate between them the knowledge needed to make the change, recode the data structures and program logic to accommodate it, and then apply these changes to the database and the application. Then, and only then, can they implement the changes.

Semantically enriched data provides value to the enterprise:

  • Data veracity: Semantically enriched data provides a basis for improved data quality, which results in a higher precision of prediction
  • Data-driven decision making: Semantic AI provides a holistic view of all enterprise
  • Transparency: Semantic AI provides an infrastructure that eliminates information differences
  • Standards-based: Linked data, based on W3C Semantic Web standards, promotes reuse and links

Smartlogic, a key partner of Mentum Systems focuses on enabling our solutions to solve complex data challenges within Global 2000 information-intensive organisations.

Semaphore Q3 2018 Newsletter.