ON DEMAND WEBINAR

Distributed Training at Scale: Speeding up Innovation for Any Industry

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What will you learn?

Our panel of experts will share:

Whether distributed training is the right solution for your AI/ML challenges

How distributed training will affect your training time and GPU utilization

An example of distributed training in action for lane detection in autonomous vehicles, and other use cases

Deep learning models are becoming more ambitious by the day, but their supporting infrastructures often struggle to keep up.

Enter distributed training, the solution for training deep learning models and large data sets. In distributed training, storage, compute power and batch size are magnified with each added GPU, dramatically reducing training time.

We'll share solutions to speed up model training and increase throughput that you can apply to AI/ML in any industry.

Watch Recording

Learn how NetApp, Run:AI, and Microsoft Azure teamed up to tackle the challenges of autonomous vehicle lane detection using distributed training >

Expert Panelists

Sam Charrington

Sam Charrington

Host of The TWIML AI Podcast

Sam is a sought after industry analyst, speaker, commentator and thought leader. Sam’s research is focused on the business and consumer application of machine learning and AI, bringing AI-powered products to market, and AI-enabled and -enabling technology platforms.

Verron Martina

Verron Martina

Cloud Solution Architect for Azure Alliance at NetApp

Verron helps migrate enterprise NAS workloads to the cloud by leveraging NetApp storage and cost optimization solutions in Azure. He has a long tenure in the IT industry, and for the past 15+ years has been in the storage and virtualization realm. Verron is an Azure Certified Solution Architect and holds an Azure AI engineer certification.

Muneer Ahmad Dedmari

Muneer Ahmad Dedmari

AI Solutions Architect – Data Scientist at NetApp

Muneer specialized in the development of Machine Learning and Deep learning solutions. After researching and working on various ML/DL projects industry-wide, he dedicated himself to scalable, production-ready solutions in hybrid cloud scenarios, in order to simplify the life of data scientists and AI lifecycle management (MLOps).

Gijsbert Janssen van Doorn

Gijsbert Janssen van Doorn

Director of Technical Product Marketing at Run:AI

Gijsbert is a passionate advocate for technology that will shape the future of how organizations run AI. He comes from a technical engineering background, with six years in multiple roles at Zerto, a Cloud Data Management and Protection vendor.

Run:AI, 2022