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Martin Frederik of Snowflake positions data quality as the cornerstone of AI-driven growth, arguing that organizations cannot scale model performance or translate predictions into business value without reliable, well-prepared, and trustworthy data foundations. Robust governance, standardization, and clear ownership enable faster analytics and generative AI delivery, reduce operational risk and bias, and support broader adoption across products and operations.

NVIDIA uses Climate Week NYC to outline how AI supports the sustainable energy transition by accelerating clean-energy research, improving forecasting, and optimizing complex systems such as power grids, renewables integration, and industrial operations. High‑performance computing and machine learning help cut time‑to‑insight, increase efficiency, and enable data‑driven decisions aimed at reducing emissions across the energy ecosystem.

Azure Cobalt 100 VMs are positioned to power real-world solutions by combining strong performance with improved efficiency for production workloads in the cloud, aligning compute capabilities to demanding application needs. Features targeting high core density and modern CPU instructions support better price‑performance, help optimize resource utilization at scale, and enable more predictable throughput for varied enterprise scenarios.

Agentic AI accelerates migration and modernization, with autonomous agents coordinating tasks across assessment, planning, code and data transformation, testing, and day‑two operations. The approach reduces manual effort, improves quality and traceability, and speeds delivery while maintaining governance, safety, and cost control during complex change programs.