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GTC On-Demand

AI Application Deployment and Inference
Presentation
Media
Deep Learning Implementers Panel: Field Insights for Accelerating Deep Learning Performance, Productivity and Scale

This customer panel brings together A.I. implementers who have deployed deep learning at scale using NVIDIA DGX Systems. We'll focus on specific technical challenges we faced, solution design considerations, and best practices learned from implementing our respective solutions. Attendees will gain insights such as: 1) how to set up your deep learning project for success by matching the right hardware and software platform options to your use case and operational needs; 2) how to design your architecture to overcome unnecessary bottlenecks that inhibit scalable training performance; and 3) how to build an end-to-end deep learning workflow that enables productive experimentation, training at scale, and model refinement.

This customer panel brings together A.I. implementers who have deployed deep learning at scale using NVIDIA DGX Systems. We'll focus on specific technical challenges we faced, solution design considerations, and best practices learned from implementing our respective solutions. Attendees will gain insights such as: 1) how to set up your deep learning project for success by matching the right hardware and software platform options to your use case and operational needs; 2) how to design your architecture to overcome unnecessary bottlenecks that inhibit scalable training performance; and 3) how to build an end-to-end deep learning workflow that enables productive experimentation, training at scale, and model refinement.

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Keywords:
AI Application Deployment and Inference, AI and DL Business Track (high level), Data Center and Cloud Infrastructure, AI for Business, HPC and Supercomputing, GTC Silicon Valley 2018 - ID S8194
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AI and DL Business Track (high level)
Presentation
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From Dark Matter Detection to Deep Learning in Enterprise
Advancements in deep learning are enabling enterprise companies to make meaningful impacts to bottom-line profits. Enterprises capture thousands of hours of customer phone call recordings per day. This voice data is extremely valuable because it contains insights that the business can use to improve customer experience and operations. We'll follow Deepgram CEO Dr. Scott Stephenson's path from working in a particle physics lab two miles underground to founding a deep learning company for voice understanding. We'll describe applications of cutting-edge AI techniques to make enterprise voice datasets mineable for valuable business insights. Companies today use these insights to drive the bottom line.
Advancements in deep learning are enabling enterprise companies to make meaningful impacts to bottom-line profits. Enterprises capture thousands of hours of customer phone call recordings per day. This voice data is extremely valuable because it contains insights that the business can use to improve customer experience and operations. We'll follow Deepgram CEO Dr. Scott Stephenson's path from working in a particle physics lab two miles underground to founding a deep learning company for voice understanding. We'll describe applications of cutting-edge AI techniques to make enterprise voice datasets mineable for valuable business insights. Companies today use these insights to drive the bottom line.  Back
 
Keywords:
AI and DL Business Track (high level), Telecom Industry Solutions, Speech and Language Processing, NVIDIA Inception Program, GTC Silicon Valley 2018 - ID S8274
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