| (S1) Infrastructure Requirements for AI Adoption at Scale |  | Multiple Dates Planned | Hosted via Zoom | See Registration Page for Details
Streamline the flow of data reliably and speed up analytics, training, and inference with your data fabric that spans from edge to core to cloud. Learn how the NetApp Data Science toolkit enables data scientists and data engineers to provision, destroy, clone, and snapshot data volumes in seconds and how the NetApp AI Control Plane enables you to unleash your AI and ML with a solution that offers extreme scalability, streamlined deployment, and nonstop data availability— when and where you need it. Hear how the NetApp AI portfolio delivers efficient and scalable performance for the most demanding ML/DL workloads.
Key Takeaways: - Improve your models - we help you create an end-to-end pipeline with 6-9x faster model training.
- Enable seamless Hybrid Cloud AI training and inferencing – Bring your data where your data scientist resides and let them seamlessly collaborate.
- Get a faster ROI from your AI investments – Faster results by eliminating days and months of configuration, support and other non-data science essential tasks.
- Future Proof – Protect your investment, start small with a POC and scale efficiently and limitless.
| | | | | (S2) End to end AI Data Management at Scale: A Deeper Dive | | Multiple Dates Planned | Hosted via Zoom | See Registration Page for Details
With NetApp and NVIDIA build an integrated data pipeline that spans from edge to core to cloud. ONTAP AI leverages your data fabric to unify data management across the data pipeline with a single platform. Use the same tools to securely control and protect your data in flight, in use, or at rest, and meet compliance requirements with confidence. Hear how the NetApp AI portfolio, including the NetApp Data Science Toolkit and AI Control Plane delivers efficient and scalable performance for the most demanding ML/DL workloads.
Key Takeaways: - NetApp integrates with standard open source tools that enable users to automate the ingesting of data from a variety of sources across disparate environments.
- NetApp enables customers to build an AI/ML/DL environment that spans edge, core and cloud, and is integrated with legacy and modern data sources.
- The NetApp Data Science Toolkit enables data scientist self-service by wrapping NetApp data management capabilities in a simple Python interface.
- The NetApp AI portfolio delivers efficient and scalable performance for the most demanding ML/DL workloads.
| | | | | (S3) Modernize Your Data Engineering Platform for Data Analytics | | Multiple Dates Planned | Hosted via Zoom | See Registration Page for Details
Get rid of what's holding you back. If your data analytics infrastructure is holding you back from enabling your organization to transform with data – resulting in slow time to release new services, escalating costs or an inability to drive AI or real-time predictive use cases, it might be time to advance to a modern, serverless, cloud-native, Kubernetes-based infrastructure. Learn with how with NetApp.
Key Takeaways: - NetApp is a leading provider of hybrid cloud data services, helping organizations build unique data fabrics that unleash the full potential of their data, accelerate innovation, and digitally transform operations.
- Move to a modern, cloud-native, Kubernetes-based infrastructure.
- Improve time to develop and deploy new AI services.
| | | | | (S4) NetApp in AI Healthcare and Life Sciences | | Multiple Dates Planned | Hosted via Zoom | See Registration Page for Details
In this session we will cover how AI can contribute to furthering the Quadruple AIm by improving patient care, reducing clinician burnout, helping the overall care experience, and lowering overall costs. We will discuss what is real and what is hype in this ubiquitous conversation. We will cover specific use cases, and focus on what is necessary to successfully start an AI program and deploy its results into production.
Key Takeaways: - NetApp and NVIDIA understand the pain points data science teams experience, and have solutions to improve their lives.
- The promise of AI in healthcare is being delayed due to friction introduced by infrastructure and data siloing; as well as poor data strategy and governance.
- NetApp can help consolidate data silos and craft an overarching data strategy.
- NetApp and NVIDIA can deliver much more than AI infrastructure.
| | | | | Meet the speakers (NVIDIA) | | | Tony Paikeday (S1)
Senior Director of Product Marketing, Artificial Intelligence Systems | | | | | | | | | | | Meet the speakers (NetApp) | | | | | | | Ray White (S1) | | | Americas Leader, Artificial Intelligence | | | | | | Dan Holmay (S1) | | | Globals AI Leader, NALA & US Public Sector | | | | | | | Mike Oglesby (S2) | | | Technical Marketing Engineer, AI | | | | | | Dave Arnett (S2) | | | Technical Marketing Engineer, AI | | | | | | | | | | Brett Albertson (S3) | | | Principal Technical Marketing Engineer for Active IQ | | | | | | Ray Deiotte (S4) | | | Chief Data Officer, Global Healthcare & Life Sciences | | | | | | | Esteban Rubens (S4) | | | Healthcare AI Principal | | | | | | | | FOLLOW US |  | | | | | | You are receiving this email because you are subscribed to enterprise emails.
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