Tony Paikeday
Tony Paikeday is the director of product marketing for the NVIDIA DGX portfolio of AI supercomputers and NVIDIA accelerated data science platform. Previously, Tony was with VMware, responsible for bringing desktop and application virtualization solutions to market, as well as key enabling technologies including GPU virtualization and the software-defined data center. Earlier, he built data center solutions at Cisco. He started his career as a manufacturing engineer at Ford Motor Company, where he later held business development roles working with enterprise and service provider accounts. Tony holds an engineering degree from the University of Toronto.
At NetApp INSIGHT 2022, Dive Into NVIDIA DGX BasePOD and NetApp ONTAP AI
As more businesses seek to operationalize AI use cases faster and more cost effectively, IT platforms are becoming central to that effort. At this week’s NetApp INSIGHT, a conference on… Read article >
New NVIDIA DGX System Software and Infrastructure Solutions Supercharge Enterprise AI
At GTC today, NVIDIA unveiled a number of updates to its DGX portfolio to power new breakthroughs in enterprise AI development. NVIDIA DGX H100 systems are now available for order.… Read article >
Bring on the INSIGHT: Enterprises Find Flexible Options to Support AI Development
AI has transitioned from being an experimental “science project” to mission-critical implementations for many businesses. However, it’s often a challenge for enterprises to support the lifecycle of AI, from development… Read article >
Secure AI Data Centers at Scale: Next-Gen DGX SuperPOD Opens Era of Cloud-Native Supercomputing
As businesses extend the power of AI and data science to every developer, IT needs to deliver seamless, scalable access to supercomputing with cloud-like simplicity and security. At GTC21, we… Read article >
An Engine of Innovation: Sony Levels Up for the AI Era
If you want to know what the next big thing will be, ask someone at a company that invents it time and again. “AI is a key tool for the… Read article >
How NVIDIA and NetApp Simplify and Speed AI Deployments for Businesses
Many business leaders know their company’s future is intertwined with the successful adoption of AI, but struggle with how to operationalize the technology at scale. Transitioning from experimentation into business-impacting… Read article >
How to Avoid Speed Bumps and Stay in the AI Fast Lane with Hybrid Cloud Infrastructure
Cloud or on premises? That’s the question many organizations ask when building AI infrastructure. Cloud computing can help developers get a fast start with minimal cost. It’s great for early… Read article >
New NetApp ONTAP AI Solution Based on Latest NVIDIA DGX A100
From analytics to training to inference, we built the NVIDIA DGX POD to support the end-to-end lifecycle of AI development. Based on NVIDIA DGX A100 systems, it’s a single platform… Read article >
Closing the AI Divide with Platform-as-a-Service
Many organizations embarking on AI projects quickly come to realize that a strategic commitment to data science expertise isn’t enough to create production-ready apps that can crank out insights from… Read article >