Physical Foundation Models (PFMs) — Fixed hardware implementations of large-scale neural networks where parameters are realized directly in physical substrate dynamics. Use when: designing specialized inference hardware, exploring optical/nanoelectronic neural implementations, analyzing energy efficiency of fixed-weight networks, considering trillion-parameter hardware inference. Triggers: physica
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Type: Agent skill (SKILL.md) · Category: LLM & Model APIs · Source: https://github.com/hiyenwong/ai_collection/tree/HEAD/collection/skills/ai-ml/phy
| Capabilities (fewer powerful permissions = higher) | 50/50 |
| Maintenance | 21/35 |
| Documentation | 15/15 |
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