Conclusion: The 0.016% weight edit fixed "premature termination due to thinking loops," and even unedited models can reach an ...
Scores jumped without learningOn November 2, an experiment published on a research blog by a team at MIT (Massachusetts ...
✨︎ Resumen (TL;DR): Simon Willison ejecutó Qwen3.8-27B en una laptop y acertó tres de cuatro juegos representados por los ...
Qwen3.8-27B identificó tres de cuatro juegos a partir de pesos de redes pequeñas en una prueba local de Simon Willison.
Simon Willison ran the 17-gigabyte open-weight model locally and fed it floating-point arrays from four reinforcement-learning policies. Without calculators or code execution, Qwen identified Breakout ...
Article by Shenchao TechFlowNo training required, no data needed, no gradient descent.Researchers at MIT fed the weights of ...
The MIT CSAIL team has proposed a "weight-space programming" method that enables GPT-6 Astra to directly read and modify ...
static DECLARE_ALIGNED(16, int, f20_0_8) [ 8][8][2]; static DECLARE_ALIGNED(16, int, f34_0_12)[12][8][2]; static DECLARE_ALIGNED(16, int, f34_1_8) [ 8][8][2]; static ...
Copyright (c) 2015-2025 The Brenwill Workshop Ltd. MoltenVK provides the ability to configure and optimize MoltenVK for your particular application runtime ...
GPT-6 Astra edited Qwen’s weights and raised MATH-500 from 7.9% to 48.1% in author-run tests. How weight-space programming works—and its limits.
Some doubts ...
MIT CSAIL researchers say GPT-6 Astra edited 0.016% of Qwen3.5-0.8B weights to fix reasoning loops, lifting MATH-500 from 7.9% to 48.1% without training.
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