As AI capabilities advance at an unprecedented pace, the infrastructure needed to support AI workloads is under pressure to keep up, both in performance and cost-efficiency. Traditional cloud providers charge a premium for GPU access, while a new category of GPU-optimized "neocloud" platforms has emerged with compelling, yet still maturing, alternatives. For many teams, there’s no clear blueprint for building scalable AI systems without overspending or taking unnecessary risks.
This webinar brings together a panel of experts working hands-on with AI infrastructure and orchestration. We’ll share practical guidance and emerging patterns from the frontlines—cutting through hype to provide a clear view of what works today and where things are headed.
What you'll learn:
How the AI infrastructure landscape is evolving—and what that means for your team
Key trade-offs between traditional clouds and emerging GPU-focused platforms
Architecture patterns that reduce cost and risk while supporting scalability
How distributed systems practices are adapting to support AI integration at scale
By registering today, we will send you a link to the on-demand recording after the live session concludes.
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