The episode on AI infrastructure debt highlights that weak data foundations limit AI potential, with organizations misidentifying performance challenges as only GPU issues. Experts stress the necessity of a hybrid cloud approach, emphasizing the importance of resiliency, human accountability, and modernization as a strategy for business acceleration amidst rapid data growth.
### Chapters
- (00:00:00) - Introduction and AI Infrastructure Debt Stats
- (00:03:01) - Sponsor Thanks: Hitachi Vantara
- (00:04:07) - Capacity Mistakes in AI Infrastructure
- (00:06:48) - Drivers of Capacity Growth and Technical Debt
- (00:11:14) - Panel: Capacity Lag and Growth Curve Discussion
- (00:13:17) - Agent Scaling and Data Movement Strategies
- (00:15:21) - Infrastructure Gaps and Cyber Resilience Risks
- (00:16:51) - Business Value vs Capacity Planning Pitfalls
- (00:18:54) - Workload-Based Capacity and Predictability
- (00:22:01) - Hardware Scarcity and Capacity Planning Horizon
- (00:26:27) - Governance, Data Sovereignty, and Data Quality
- (00:31:03) - Break and Sponsor Message / Houston Roundtable Invite
- (00:32:13) - Closing Capacity Thoughts and Transition to Resilience
- (00:33:37) - Cyber Resilience in AI Infrastructure
- (00:36:19) - Legacy Systems and AI Resilience Risks
- (00:38:22) - Monitoring, Predictability, and Response Automation
- (00:41:19) - AI Accountability, Human Oversight, and Risk of Harm
- (00:47:02) - Kill Switches and Extending Cyber Resilience
- (00:48:02) - Cloud vs On-Prem: Hybrid Infrastructure Decisions
- (00:52:17) - Building the Business Case for Modernization
- (00:58:52) - Closing Remarks and Sponsor Thanks
