NVIDIA NGC Catalog
From precise product recommendations to accelerated drug discovery, enterprises are adopting AI to deliver cutting-edge products and services. Unfortunately, leveraging AI for applications is challenging for many reasons. And, the complicated science required to build and train deep learning neural networks, and set up and maintain the supporting infrastructure required to develop, deploy, and manage these applications at scale, presents substantial barriers.
However, cloud computing enables enterprises with easy access to scalable, on-demand infrastructure so that data scientists and developers can get AI applications up and running quickly. The real need is for an integrated platform that combines the power of GPUs with a secure environment that streamlines the development-to-deployment process.
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Akhil Docca is a senior product marketing manager for NGC at NVIDIA, focusing in HPC and DL containers. Akhil has a Master’s in Business Administration from UCLA Anderson School of Business and a Bachelor’s degree in Mechanical Engineering from San Jose State University.
Krishna Anumalasetty is a principal program manager for Azure Machine Learning at Microsoft. He’s worked as a program and product manager at Azure cloud services and AI org for the last eight years, enabling enterprise customers with on-premises and cloud hybrid scenarios, helping them scale up and out in the cloud and implement security protections and easy to deploy ML models in the cloud. Krishna is a founding member of Microsoft’s AutoML team. He holds a master’s degree in computer science from Arizona State University.
Abhilash Somasamudramath is a Product Manager for NGC at NVIDIA, focused on creating seamless experiences for users to build AI faster than ever on the cloud leveraging the company's portfolio of GPU-optimized AI software available on NGC. Abhilash has a Master’s in Business and Engineering from Columbia University and a Bachelor’s degree in Computer Science.
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Date & Time: Wednesday, April 22, 2018