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Enterprise AI Infrastructure 101: From Proof of Concept to Production
Why 87% of AI projects fail—and how to be in the 13% that succeed.
This comprehensive talk covers the complete journey from POC to production, including:
- The gap between POC and production (8 dimensions you didn’t budget for)
- Real cost breakdowns: When $5K becomes $57K per model
- Three proven infrastructure patterns (Hybrid, GPU Pooling, Model Optimization)
- Architecture decision framework for enterprise AI
- Industry-specific patterns for Healthcare, Financial Services, and Manufacturing
Perfect for CTOs, platform engineers, and business leaders planning enterprise AI deployments.
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New videos on enterprise AI infrastructure, Kubernetes for ML, cost optimization, and production deployment strategies.
Topics Covered
Enterprise AI Infrastructure
Building production-grade AI platforms that work in regulated industries
Kubernetes for AI/ML
Practical deployment patterns, GPU scheduling, and multi-tenancy
Cost Optimization
GPU utilization strategies, hybrid cloud economics, and TCO analysis
Compliance & Governance
HIPAA, SOX, GDPR compliance for AI systems in regulated industries
MLOps & Platform Engineering
KServe, KubeFlow, model serving, monitoring, and production best practices
From the Community
Videos feature real-world case studies, technical deep-dives, and insights from the Tampa Bay Enterprise AI Community meetups.
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