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UID:https://www.brighttalk.com/webcast/679/657047
DTSTAMP:20260227T084531Z
ORGANIZER:MAILTO:noreply@brighttalk.com
LOCATION:BrightTALK
URL:https://www.brighttalk.com/webcast/679/657047?utm_campaign=communi
 cation_reminder_24hr_registrants&utm_medium=calendar&utm_source=bright
 talk-transact
DTSTART:20260611T180000Z
DTEND:20260611T190000Z
SUMMARY:Live webcast: AI Meets Storage: Comparing On-Prem, Cloud, and 
 Hybrid Architectures Across the AI Lifecycle
DESCRIPTION:Click here to attend: https://www.brighttalk.com/webcast/6
 79/657047?utm_campaign=communication_reminder_24hr_registrants&utm_med
 ium=calendar&utm_source=brighttalk-transact\n\nPresenter: Rohan Mehta,
  Micron Technology; Erik Smith, Dell Technologies; Himabindu Tummala, 
 Dell Technologies\n\nIn today’s evolving IT landscape, selecting the r
 ight storage architecture is critical for optimal performance, scalabi
 lity, data governance, and cost-efficiency. Furthermore, AI workloads 
 have uniquely influenced how we meet these demands from our storage in
 frastructure. This webinar provides a technical deep dive into three f
 undamental storage deployment models – on-premises, cloud, and hybrid 
 – examining their architectures and operational trade-offs through the
  lens of two key concepts: indirection (accessing data through mapping
  layers that provide flexibility and abstraction) and redirection (rer
 outing data requests to enable failover, load balancing, and optimized
  performance). \n\nWe are going to take some of the key stages of AI l
 ifecycle development as sample use-cases (such as data ingestion, prep
 aration, training, inferencing, and retrieval) and compare how each st
 orage model can serve these use-cases across varying access patterns, 
 data volumes, and performance requirements.\n\nAttendees will gain a p
 ractical framework for aligning AI workloads with the most suitable st
 orage architecture, balancing cost, scalability, and latency. Whether 
 you are building AI infrastructure from scratch or optimizing existing
  deployments, this session will help you make informed decisions for A
 I-ready storage.\n\nLearning Objectives and Key Takeaways:\n\n• Introd
 uction to the 3 different types of storage deployment models – on-prem
 , cloud, and hybrid\n• Trade-offs for each deployment model\n• Importa
 nce of indirection and redirection\n• Understand how AI-specific data 
 types and access patterns (e.g., embeddings, checkpointing) influence 
 storage performance and design\n• Evaluate trade-offs in latency, scal
 ability, security, and cost when choosing storage for different stages
  of the AI pipeline\n• Gain a decision-making framework for selecting 
 the right storage model based on workload characteristics and infrastr
 ucture goals
SEQUENCE:1781113754
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