Deployment considerations and best practices for your AI workloads from Mastercard (sponsored by Dell Technologies)
There are many different decisions to make when choosing the right solutions and infrastructure. Drawing on real-world considerations, use cases, and solutions, Nick Curcuru discusses different decisionsand the associated considerations and best practicesMastercard exercised to build and deploy a successful AI.
| Talk Title | Deployment considerations and best practices for your AI workloads from Mastercard (sponsored by Dell Technologies) |
| Speakers | Nick Curcuru (Mastercard), Anthony Dina (Dell EMC) |
| Conference | O’Reilly Artificial Intelligence Conference |
| Conf Tag | Put AI to Work |
| Location | New York, New York |
| Date | April 16-18, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Artificial intelligence has become the hottest commodity in recent years, and business, academia, and government have embraced it to propel complex use cases. As AI becomes more woven into the fabric of organizations (and its criticality increases), enterprise infrastructure becomes essential. AI is only as strong as its weakest link. The ability to build out use cases, deploy into production, scale, and secure all relies on the supporting solutions and infrastructure. There are many different decisions to make when choosing the right solutions and infrastructure: On-premises or off? GPUs or CPUs? Which storage system and framework to use? The list goes on. Drawing on real-world considerations, use cases, and solutions, Nick Curcuru discusses different decisions—and the associated considerations and best practices—Mastercard exercised to build and deploy a successful AI.
