Episode 8: Denise Reilly-Hughes on Navigating Technology in Government

The Real AI Arms Race Isn’t About Models. It’s About Where the Power Comes From

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Noam Maital

The AI boom is often framed as a race for bigger models and faster chips, but the real bottleneck is far more basic: power. AI runs on compute, compute runs on electricity, and electricity is constrained by grids, permitting, and infrastructure that move at government speed. As demand for AI data centers explodes, delays in transmission, interconnection, and approvals are shaping where and how AI can scale—sometimes pushing capital to consider extreme alternatives like space-based compute. The takeaway for governments is clear: responsible AI leadership is no longer just about policy.

AI Governance After Trump’s New Executive Order | The Rules May Change, But Your Responsibilities Didn’t

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Yam Atir

The Trump administration’s new Executive Order seeks to preempt strict state regulations on private AI development to reduce compliance burdens, but it explicitly leaves state & local government authority over internal AI use and procurement intact. While federal agencies look to challenge provisions of state laws on private sector use of AI, impacted public agencies retain full responsibility for managing their own AI tools, making internal governance a critical and immediate priority.

The Keyboard Is a Mirror for Our AI Moment

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Noam Maital

Darwin’s CEO and Co-Founder, Noam Maital, explores how the evolution of writing tools, from early keyboard systems like China’s Wubi method to modern AI-powered prediction, reveals the quiet but powerful ways technology shapes how we communicate. Noam argues that as AI becomes more involved in finishing sentences, drafting language, and guiding ideas, the real priority is preserving human intent and authorship. What is critical, however, is intentional design that gives users control, ensures transparency, and protects diverse voices, positioning language technology as essential civic infrastructure. His message is clear: AI should accelerate our work, not define it, and trust is built when people remain firmly in the author’s seat.