Dr. Darren Pulsipher, Chief Enterprise Architect for Public Sector, author and professor, investigates effective change leveraging people, process, and technology. Which digital trends are a flash in the pan—and which will form the foundations of lasting change? With in-depth discussion and expert interviews, Embracing Digital Transformation finds the signal in the noise of the digital revolution.
People
Workers are at the heart of many of today’s biggest digital transformation projects. Learn how to transform public sector work in an era of rapid disruption, including overcoming the security and scalability challenges of the remote work explosion.
Processes
Building an innovative IT organization in the public sector starts with developing the right processes to evolve your information management capabilities. Find out how to boost your organization to the next level of data-driven innovation.
Technologies
From the data center to the cloud, transforming public sector IT infrastructure depends on having the right technology solutions in place. Sift through confusing messages and conflicting technologies to find the true lasting drivers of value for IT organizations.
Cloud outages don’t have to be a mystery—or a recurring fire drill. Host Dr. Darren interviews Dr. Helen Gu, professor at North Carolina State University and founder/CEO of InsightFinder, about how AI for cloud operations can detect, predict, and automatically fix outages before users feel the impact. ## Key Takeaways - AI can move beyond simple alerting to **predictive outage prevention**, spotting early warning signs before they become incidents. - **Unsupervised machine learning** helps discover hidden patterns in noisy machine data without requiring large sets of labeled examples. - Real-world cloud environments are complex, with thousands of parameters, dynamic workloads, and interacting microservices that make manual troubleshooting difficult. - A **closed-loop feedback system** lets teams review AI predictions, correct mistakes, and continuously improve model accuracy. - InsightFinder’s **composite AI** approach combines predictive AI, causal inference, behavior learning, and small language models for more reliable operations. - The same data-driven approach can support **cloud monitoring, edge environments, critical infrastructure, and other machine-generated data streams**. ## Chapters - 00:00 Introduction to AI that prevents cloud outages - 01:05 Helen Gu’s origin story in NASA-funded Mars research - 04:10 From video streaming on Mars to machine learning for reliability - 07:00 Why machine data is harder than it looks - 09:20 Unsurvised learning vs. supervised learning - 12:10 From research to Google Cloud anomaly detection - 14:40 Detection, prediction, and automatic remediation - 17:10 Why cloud systems are so complex - 19:45 The future of AI agents, models, and infrastructure monitoring - 23:10 Hallucinations, false positives, and feedback loops - 26:00 Composite AI and online learning in production - 29:10 Adapting AI models to different environments
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