Astra AI Post on Qwen Weights Misleading About Capabilities
Original title: The 'Astra can read and write weights to improve Qwen' post is misleading
Astra model experiments on Qwen use code execution to edit weights rather than reading them directly for improvements.
A blog post claiming Astra can read raw weights to understand trained networks and write game-playing models from scratch is misleading. The experiments involve different techniques: some read weights, others run code to edit or generate networks. The Qwen math improvement uses weight editing after running models on practice problems. No single technique covers both reading and writing capabilities as described.
- Qwen experiment requires Python code execution and multiple model runs.
- Small game networks tested used different methods than Qwen fix.
- No evidence of direct weight reading without tools for large models.
- Improvements achieved through iterative task design and sampling.
- Organizations
- Honnibal
- AI models
- AstraQwen3.5-0.8BGemma 3
From the original article
3 min read at honnibal.dev
One iteration uses a gimmick prop, the next one shows you the prop isn’t gimmick but that one palms the object, the third time was a forced choice etc. When you watch the performance you assume there’s only one technique, so each time they do it they seem to debunk your hypothesis about how it This is pretty much how the experiments in the ‘Astra can read and write weights to improve Qwen’ post work.
By syllogism · honnibal.dev
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