Generative artificial intelligence is reshaping every industry’s competitive landscape. In this video series, Portfolio Manager and Sr. Research Analyst Daniel Pilling explores the global dynamics of model training versus real-time inference, the economics and energy demands of massive compute workloads, and the infrastructure constraints—from power grids to chip supply—that will determine AI’s future scale. He demonstrates how falling per-compute costs unlock applications in public safety, logistics and enterprise software, examines the geopolitical and regulatory tensions at play, and uses scaling laws and valuation insights to pinpoint the companies best positioned to benefit over the long term.
AI Adoption Becoming a Matter of Survival
AI infrastructure has evolved from optional investment into an existential imperative. Hyperscale compute delivers sub-year paybacks and fortifies resilience against downturns.
Reimagining Work and Value in the AI Age
Compute growth and synthetic training environments will fuel industrial and domestic robots, unlocking efficiencies and redefining time’s value.
Exploring AI’s Ever-Evolving Value Chain
Discover how evolving GPU technology, chip manufacturing bottlenecks, and geopolitics drive the next wave of AI innovation.
AI at Scale: The Forces Shaping the Next Decade
Daniel Pilling, Portfolio Manager at Sands Capital, explains why we believe artificial intelligence isn’t just a new frontier—it’s a complete economic replatforming. In this 30-minute video, he reframes AI adoption not as an optional upgrade, but as a survival imperative—comparable to the arrival of electricity 100 years ago.
Valuations Don’t Reflect Potential of Gen AI
Portfolio Manager Daniel Pilling argues that semiconductors and hyperscalers are fairly priced given yet-to-be-realized revenue opportunities in evolving industries, such as robotics and autonomous vehicles.