Expert.ai has been recognized in the Gartner “Emerging Technologies and Trends Impact Radar: Artificial Intelligence, 2021” research as a Sample Vendor in the Composite AI (or Hybrid AI) category which refers to “the combined application of different AI techniques to improve the efficiency of learning to broaden the level of knowledge representations and, ultimately, solve a wider range of business problems more efficiently”. [1]
“After a long period of promotion and debate of employing a single methodology (machine learning or symbolic) to solve complex language problems an advanced approach has emerged as the optimal solution,” said Marco Varone, expert.ai CTO. “By bringing together the best of AI-based knowledge and learning models to understand natural language data, hybrid AI is the most effective way to unlock the value of the ever-increasing enterprise unstructured data with the accuracy, speed and scale required by today’s businesses”.
The Case of Hybrid NL
Machine learning (ML) and deep learning (DL) can support specific language-intensive applications; however, they are very limited from delivering optimal results and fail short in case of more complex use cases. According to Gartner*, “The days of singular AI techniques are coming to an end. Software and service providers that cannot provide solutions combining multiple AI techniques (such as machine learning, rule-based systems, optimization techniques, knowledge graphs, natural language technologies) will quickly find themselves at a disadvantage compared with those that can. The introduction of composite AI techniques, even within existing products, will have a profound impact on their capabilities”.[1]
The solution lies in artificial intelligence that combines different techniques, complementing learning models (ML/DP) with a knowledge-based approach or symbolic AI. Symbolic AI involves the explicit embedding of human knowledge and is based upon pre-established linguistic rules. The brain behind symbolic AI is knowledge graph. It’s the knowledge graph which provides the explicit representation of knowledge to support the logical explanations of reasoning outcomes. Combining that with machine learning enables a larger participation of subject matter experts with limited machine learning expertise in the development phase of machine learning models while preserving machine learning as a useful technique that can save good amounts of time in some scenarios.
“We are happy to be recognized as a Sample Vendor for Composite AI in the 2021 Gartner Impact Radar dedicated to Emerging Technologies and Trends for Artificial Intelligence – continued Marco Varone – enterprise AI is delivering on its potential and the benefits of hybrid NL are becoming a tangible reality”.
*Gartner Research “Emerging Technologies and Trends Impact Radar: Artificial Intelligence, 2021”, Annette Jump, Eric Goodness, Jim Hare, Alys Woodward, Erick Brethenoux, Danielle Casey, Martin Reynolds, Svetlana Sicular, Eric Hunter, Jonathan Davenport, Alan Priestley, Sept 21, 2021.
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