Artificial intelligence is expanding beyond the boundaries of models and APIs—into real-world agents, high-fidelity simulation, and strategic infrastructure. This talk offers a practical, forward-looking perspective on AI strategy, based on insights gathered at NVIDIA’s GTC 2025, one of the most influential events in the global AI ecosystem.

We begin with a personal reflection: why attending GTC as an AI consultant helped reset my strategic thinking after experiencing the common challenges of fragmented data, isolated tools, and innovation fatigue. From there, we’ll explore key emerging trends—agentic AI, synthetic data generation, and real-time digital twins—and discuss their broader implications for how we design, train, and deploy intelligent systems.

The second part of the talk focuses on convergence: how disciplines such as robotics, healthcare, simulation, and cloud infrastructure are blending, creating new demands for cross-functional collaboration. A brief clustering analysis of 500+ GTC sessions will illustrate this shift.

We’ll conclude by examining strategic changes in AI infrastructure—especially the rise of powerful, local AI systems—and draw lessons from unexpected collaborations (such as Disney, DeepMind, and NVIDIA) that reveal how innovation often happens at the intersection of domains.

This talk is intended for developers, data scientists, and technical leads who want to broaden their understanding of where AI is headed and how to align today’s decisions with tomorrow’s possibilities.

Talk Outline: • Introduction: personal motivation and strategic perspective on GTC 2025 • Key trends: agentic AI, synthetic data, and real-time simulation • Interdisciplinary convergence: how domains like robotics, biology, and infrastructure intersect • Case study: the Disney–DeepMind–NVIDIA collaboration and its broader lessons • Strategic implications: shifts in AI infrastructure and a call for action-oriented, cross-domain thinking