Embedding CPUs in LLM Weights: Determinism vs Flexibility?
Developers embedded a RISC-V CPU into Qwen3.5 weights, using GDN layers as RAM. This 'Qwenputer' runs C code and arithmetic internally without external tools, with >97% accuracy. Compared to standard tool use, this doubles model size and slows speed but ensures internal control.
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Known and confirmed
- Developers embedded a RISC-V CPU into Qwen3.5 weights, using GDN layers as RAM.
- This 'Qwenputer' runs C code and arithmetic internally without external tools, with >97% accuracy.
- Compared to standard tool use, this doubles model size and slows speed but ensures internal control.
Unknown or unverified
- 长期性能优化能否解决当前速度慢和体积大的问题
- 这种架构对复杂逻辑推理（非纯算术）的实际提升程度
- 主流厂商是否会采纳这种改变模型训练范式的实验性技术
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If future AIs widely adopt this 'embedded hardware' architecture, which core advantage do you value more?
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