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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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Texas Hold'em where every AI seat is a different character played by a language model. From-scratch rules engine (side pots, split pots, chip conservation), 7 personas, a browser table with replay and ...

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A pair of tiny neural networks can generate and play five simple games on a Raspberry Pi Pico 2 W without conventional game ...

MIT CSAIL's "weight-space programming" has a frontier LLM read and edit neural network weights directly, with no gradient descent. Surgical edits ended Qwen's reasoning loops, but the results come ...

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.