AI Data Center Design: High-Impact Network Infrastructure Technologies from Edge to Hyperscale | Kisaco Research

The hypergrowth of the AI market has brought innovation and acceleration to the entire IT technology stack in just a few years time. Advancements in the network fabric, protocols, optics, and operations are coming from not only from the vendor community, but from end-users themselves as they uncover new challenges. This session explores the highest impact technologies for data center operators of all sizes, including the impact of AIOps itself on the full cycle of deployment and growth. You’ll learn how these technologies can confidently be used as high points of leverage to accomplish more, in less time.

Speaker(s): 

Author:

Clayton Wagar

Principal Consulting Engineer, Cloud Strategy
Nokia

Clayton Wagar is the Principal Consulting Engineer for Cloud Strategy in Nokia’s IP Division. He leads activities in both network infrastructure for AI, as well as AI operations and network automation. His career has included a variety of roles in strategy, sales, architecture, and product management in a variety of fields including core networking, broadband, wireless, and streaming media. Currently a Nokia delegate to the Ultra Ethernet Consortium, Clayton has previously contributed to key industry standards activities and emerging technology groups.

Clayton Wagar

Principal Consulting Engineer, Cloud Strategy
Nokia

Clayton Wagar is the Principal Consulting Engineer for Cloud Strategy in Nokia’s IP Division. He leads activities in both network infrastructure for AI, as well as AI operations and network automation. His career has included a variety of roles in strategy, sales, architecture, and product management in a variety of fields including core networking, broadband, wireless, and streaming media. Currently a Nokia delegate to the Ultra Ethernet Consortium, Clayton has previously contributed to key industry standards activities and emerging technology groups.

Time: 
5:30 PM - 5:50 PM
Agenda Track No.: 
Track 4
Session Type: 
Track
Session Stage: