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UID:pretalx-bnog-2026-LCKLX8@pretalx.balticnog.org
DTSTART;TZID=EET:20260924T113000
DTEND;TZID=EET:20260924T115500
DESCRIPTION:This is a continued presentation around Artificial Intelligence
  (AI) from the BalticNOG 2025 where I covered the fundamental difference b
 etween AI for Networks and AI Networks - the intent of this talk is to cov
 er more details around the challenges posed by AI workloads in data center
  infrastructure for TRAINING and INFERENCE\, as these workloads pose some 
 challenges around the data center infrastructure. This talk will cover fun
 damentals around how data is collected and structured/cleaned up for train
 ing usage as well as once the training is done how the model will be used 
 for inference. It will look at data center design including AI Fabrics\, s
 cale-up vs. scale-out designs\, challenges\, and protocols used and provid
 e some future guidelines around enhancements to such challenges under work
 s within the UEC (Ultra Ethernet Consortium). UEC goal is to deliver a co
 mplete architecture that optimizes Ethernet for high performance AI and 
 HPC networking\, exceeding the performance of today’s specialized techno
 logies.  UEC specifically focuses on functionality\, performance\, TCO\
 , and developer and end-user friendliness\, while minimizing changes to on
 ly those required and maintaining Ethernet interoperability
DTSTAMP:20260920T211112Z
LOCATION:ROOM ALFA
SUMMARY:Is My Data Center Infrastructure Ready for AI Workloads - Mikael Ho
 lmberg
URL:https://pretalx.balticnog.org/bnog-2026/talk/LCKLX8/
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