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Byron Galbraith is the Chief Data Scientist and co-founder of Talla, where he works to translate the latest advancements in machine learning and natural language processing to build AI-powered conversational agents. Byron has a PhD in Cognitive and Neural Systems from Boston University and an MS in Bioinformatics from Marquette University. His research expertise includes brain-computer interfaces, neuromorphic robotics, spiking neural networks, high-performance computing, and natural language processing. Byron has also held several software engineering roles including back-end system engineer, full stack web developer, office automation consultant, and game engine developer at companies ranging in size from a two-person startup to a multi-national enterprise.
Neural Information Retrieval and Conversational Question Answering:
One the main affordances of conversational UIs is the ability to use natural language to succinctly convey to a bot what you want. An area where this interface excels is in question answering (Q&A). Research into Q&A systems often falls at the intersection of natural language processing (NLP) and information retrieval (IR), and while NLP has been getting a lot of attention from deep learning for several years now, it’s only largely within the last year or so that the field of IR has seen an equivalent explosion of interest in employing these techniques. In this presentation, I will touch on challenges facing conversational bots, provide a high level overview into the emerging field of Neural Information Retrieval, discuss how these methods can be used in a Q&A context, and then highlight some lessons learned attempting to design and deploy a conversational Q&A agent-based product.