The Twin Crises of Modern Vision AI: Progressive Tensor Core Decay and Geometric Blindness -A Zig-Native Architectural Countermeasure by mouad tarif

This research identifies two simultaneous crises in modern vision AI systems. First, Tensor Cores suffer from progressive, cumulative degradation under sustained AI workloads due to a cache inefficiency gap that, based on first-principles memory locality analysis, forces reliance on slower memory, generating thermal hotspots and theoretically reducing effective GPU lifespan from five years to approximately two years. Second, current vision models—including Vision Transformers and Mamba—suffer from geometric blindness: they flatten 2D images into 1D sequences, losing spatial relationships and causing edge distortion, dimensional incoherence, and presence-absence ambiguity. This work proposes a theoretical alternative architecture built on the Zig programming language. The architecture operates on spatial coordinates rather than pixels, reducing data volume by an estimated 99 percent. It employs the ZR2ViM (Zigzag Recursive Vision Mamba) model to preserve spatial dimensions, and implements a stress-aware CUDA scheduler to theoretically mitigate Tensor Core decay. Based on extrapolations from existing Zig projects (ZML, cudaz) and published results from the ZR2ViM paper, this work projects a theoretical speedup of 12.8x over Python baselines (193 vs 15 tokens per second), 98 percent edge detection accuracy, extension of effective GPU lifespan from two years to five years, and statistically significant artist attribution accuracy using geometric signature extraction. All projections are theoretical and require empirical validation. This work challenges the peak performance paradigm, introduces geometric blindness as a fundamental limitation of current models, and demonstrates that a complete Zig-native vision stack already exists. The architecture offers a new theoretical direction for hardware-software co-design in vision AI, with implications for industry, academia, open-source development, and digital art history. This research was previously published on Academia.edu on June 10, 2026. Link:https://www.academia.edu/168428523/The_Twin_Crises_of_Modern_Vision_AI_Progressive_Tensor_Core_Decay_and_Geometric_Blindness_A_Zig_Native_Architectural_Countermeasure_by_mouad_tarif For academic correspondence, you may contact me at: [email protected]. Please note that this email is reserved for academic and research-related communication only.