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The Efficiency Trap: China Won The Cost Curve, The US Owns The Cash Register
Beyond Token Prediction: The Architectural Case for Truth-Grounded AI
The Day After AGI: Davos 2026 and the Intelligence Transition
The Complexity Transition: Why Human Intelligence Must Redefine Itself in the Age of Artificial Cognition
The Sovereignty Transition: Reclaiming Control in a High-Velocity AI Environment
AI sovereignty isn’t about replacing vendors, it’s about controlling intent. In a world where models evolve every six months, enterprises must own the logic that governs decisions while treating execution as swappable. Control the architecture, not the tools.
The Logic Ownership Problem: Building AI-Native Architecture Without Vendor Lock-In
Enterprises face a false choice: vendor lock-in or costly rip-and-replace. The third path: sovereignty-first architecture. Own the logic that defines strategy, delegate execution to vendors through interfaces that preserve inspectability, overridability, and portability.
Nvidia's Strategic Imperative: Navigating the Next Decade of AI Dominance
GPUs made Nvidia dominant. CUDA made it irreplaceable. Now it's expanding into inference, robotics, and vertical integration. This isn't a hardware company, it's an AI platform consolidating power.
The Nvidia–Groq Transaction: Architecture, Power, and The Consolidation of Inference
AI's bottleneck isn't compute—it's memory. GPUs sit idle 99% of the time during inference, waiting for data. Groq proved deterministic architectures can solve this. Nvidia's response? Strategic absorption. By integrating Groq's approach into Rubin, Nvidia closes the inference gap.
The Sovereignty Trap: How Enterprises Lose Control Through Their Tools
Sovereignty isn't lost in one decision, it’s transferred in a thousand integrations. Control resides not in data ownership, but in who owns the logic that decides what to do with it. Stop drifting into dependence on multi-tenant logic.