Knowledge Engineering: The AI Supercharging Ingredient

first_imgKnowledge Engineering is the ability of an Artificial Intelligence (AI) algorithms to emulate the reasoning, judgment and behavior of an expert in a particular field. Knowledge Engineering algorithms represent the distilled knowledge and wisdom of humans. Knowledge Engineering rewrites human knowledge in terms of data structures, semantic models and heuristics. Examples of knowledge engineering are expert systems. Forrester Research wrote that “while ML (Machine Learning) is exceptional at analyzing data to create models that make predictions, recognize patterns, and automate decisions, it lacks human reasoning capabilities. In 2019, enterprise AI mavericks will rediscover knowledge engineering and digital decisioning platforms to extract and encode inferencing rules and build knowledge graphs from their expert employees and customers. ML’s strength is data. Knowledge engineering’s strength is human wisdom. Used together, enterprises can dramatically accelerate the development of AI applications.”center_img Stephane Nappo, Chief Information Security Officer at OVH, said that “turning technical brute force into real artificial intelligence requires a deeper understanding of human thinking based on knowledge engineering and reasoning mechanisms.”last_img

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