Advances in AI research have led to great innovations based on image and voice recognition, and 2017 will see further advances in the field of language, including the creation of more literate machines—those that can comprehend and communicate with humans but also machines that begin to model innate human-like skills.
Machine literacy will provide opportunities to enhance and develop new products and services that help knowledge workers. Mohamed Musbah explores key research areas and explains how they will power new products and services in language understanding, giving you a deeper understanding of the implications and opportunities that language understanding AI services will bring.
Beginning with an overview of machine comprehension and goal-oriented dialogue systems, Mo discusses the fundamental problems that researchers are solving, including common-sense reasoning, information seeking, transfer learning, decision making, and creativity. Mo then shares examples of how these capabilities will lead to innovations that will help enterprise adopt AI, including services capable of ingesting and processing vast amounts of structured and unstructured data and then providing intelligent question and answering and decision-making capabilities.
These use cases are transformative. To give just one example, knowledge workers and employees would no longer need to desperately search through an organization’s directories, repositories, emails, and other channels to find a specific document. Instead, the employee would communicate with an AI agent leveraging machine comprehension capabilities. The agent would be capable of answering the question in a security-compliant manner by having a deep understanding of the contents of the organization’s documents instead of simply retrieving based on keywords.
Mohamed Musbah is vice president of product at Maluuba, a Canadian AI company that’s helping machines to think, reason, and communicate seamlessly with humans (acquired by Microsoft in January 2017). Maluuba’s technology is deployed in more than 50 million devices globally, and the company recently opened an R&D lab in Montréal, a global hub for AI research. Mo leads the development of products at Maluuba alongside the company’s language understanding and deep learning teams. Previously, Mo worked in product management at Microsoft and Facebook. He holds a BS in software engineering from the University of Waterloo.
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