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Leveraging the Power and Performance of NLP and Transformer Architectures – GTC21 Presentation

Organizations across industries are realizing the value of natural language processing (NLP) and are implementing it to deliver better digital products, services, and customer tools, and to increase operational efficiencies or gain novel capabilities. As one of the fastest-growing areas of AI R&D across FSI, health care, and retail, NLP enables organizations to now search, query, detect anomalies, understand relationships, and parse trillions of transactions in real-time. Though advances in language representation models yield impressive accuracy for these use cases, teams still struggle to realize value from development, testing, and production systems. We examine leveraging GPU-optimized capabilities and pre-trained AI models, determining when to leverage task-specific or customized models, and discuss state-of-the-art benchmarks for layered and mixed-modal text analysis applications while accelerating deployment via TensorRT, NVIDIA Triton Inference Server, and cloud-based methods.

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