Artificial Solutions Advocates the Hybrid Approach at Conversational Interaction
Artificial Solutions, the natural language interaction (NLI) specialist that enables users to have a meaningful, humanlike interaction with technology announced today that it is speaking at the Conversational Interaction conference in San Jose this week on the company’s unique hybrid approach to conversational application development.
In his presentation, Linguistic vs machine learning? Why the real winner is a mixed approach, Zachary Wilkins, Senior Computational Linguist at Artificial Solutions explains the benefits behind Teneo’s hybrid approach to linguistic and machine learning in NLI applications.
This includes enabling enterprises to start development with very little training data, which is one of the biggest constraints in building intelligent conversational UIs.
“In the past, enterprises have been forced to choose between linguistic and machine learning models when building conversational applications. Both have their advantages, and their challenges. As businesses have already discovered, these challenges can lead to long build times, escalating costs and abandoned projects,” says Andy Peart, CSO of Artificial Solutions.
“By considering a hybrid approach, using the best of both worlds—machine learning and linguistic learning seamlessly integrated—it’s possible for enterprises to reach the perfect balance of flexibility, speed and control in developing conversational applications.”
The Conversational Interaction Conference brings together key industry figures to discuss how companies and application developers can take advantage of natural language—including resources for creating bots and digital assistants, delivering a conversational aspect within customer service operations, best practices, examples of deployed solutions, and other commercial opportunities generated by the rise of natural language.
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Avoiding the “False Choice” Between Linguistic Models and Machine Learning. The backbone of Artificial Solutions’ Teneo platform is a linguistic-based algorithm with the key ability to embed and operate in tandem with machine learning algorithms.