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This essay examines the constraints on current AI paradigms and proposes alternative architectures for overcoming these limitations.

May 26, 2026Open Access

The Silicon Illusion and the Neuromorphic Dawn: Deconstructing AI Stagflation, the Limits of Brute-Force Scaling, and the Event-Driven Path Beyond Next-Token Prediction

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This essay examines the constraints on current AI paradigms and proposes alternative architectures for overcoming these limitations.
Analyzed the limitations of classical von Neumann architectures for AI scaling.
Identified key constraints: data wall, silicon wall, and power wall.
Presented a speculative infrastructure watchlist for future AI development.
Identified current AI models facing limits due to physical and economic constraints.
Proposed in-memory neuromorphic architectures as a promising long-term solution.
Described 'AI stagflation' where increased investment yields reduced returns.

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Perspective essay explores the limits of current AI scaling methods, suggesting a shift to neuromorphic designs for future progress.

Sankar Balu (2026) studied this question.

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