Hosted by Information Management
This on-demand presentation introduces and reviews current trends in computer-enabled artificial intelligence, or “AI”, providing a basic understanding of methods and technologies, practical applications and risks to avoid.
Robert will briefly describe the two major directions in current AI. Machine Reasoning (MR) builds on newer (“NoSQL” “Graph” and “Semantic”) AI-enabling database technologies to provide expert systems. MR applies linked data models or “ontologies” for deductive reasoning, entailment and decision-support, even with incomplete datasets. Machine Learning (ML) applies various statistical analyses for “training” and “learning” using example datasets with features (e.g., variables) and outcomes (e.g., results). ML applies supervised and unsupervised algorithms to analyze these training datasets, to identify features that are or seem to be related to outcomes for inductive hypothesis generation and to facilitate pattern identification for decision support.
Next, practical risks to avoid with AI will be reviewed. This will address basic requirements for successful AI applications and will give insight into misconceptions and pitfalls associated with different forms of AI. Finally, case studies that show where and how AI can accelerate real world business goals will be presented. Case studies will include applications of MR and ML for retrieving and creating high quality data from dirty, unstructured data sources as well as for discovery and application of patterns.
|Robert A. Stanley
Senior Project Director
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