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Morning Edition · Thursday, July 23, 2026Published at 2:03 AM EDT · New York

Researchers Propose Subquadratic Operators That Keep a Global View of Multi-Dimensional Data

Input-dependent long convolutions aim to give images and video attention-like receptive fields without attention's quadratic cost or the rasterization recurrent models require.

Researchers Propose Subquadratic Operators That Keep a Global View of Multi-Dimensional Data

A paper on native multi-dimensional subquadratic operators targets a persistent tradeoff in efficient architectures. Subquadratic alternatives to attention tend to compromise on multi-dimensional data: standard convolutions lack a global re…

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Frontier Model Efficiency Gains

Capability per unit of training and inference compute keeps improving, letting newer models match prior frontier performance far more cheaply and gradually loosening the link between raw scale and capability.