EmbedGenius automates embedded IoT system development by combining LLMs with hardware expertise, eliminating manual intervention and reducing development complexity.
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https://arxiv.org/abs/2412.09058
🤖 Original Problem:
→ Embedded IoT development requires extensive cross-domain knowledge of hardware and software
→ Manual development is time-consuming, error-prone, and demands significant expertise in handling diverse hardware modules and dependencies
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🔧 Solution in this Paper:
→ EmbedGenius introduces component-aware library resolution to handle hardware dependencies automatically
→ It implements library knowledge generation to inject domain expertise into LLMs
→ The system uses auto-programming with nested reasoning loops for compile and flash verification
→ Memory-augmented LLMs generate task prompts and automate system programming
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💡 Key Insights:
→ Automated library selection significantly improves coding accuracy by 10.8%
→ Selective memory pick-up reduces token consumption by 26.2%
→ Auto-programming with feedback loops ensures 95.7% coding accuracy
→ The system works across 71 hardware modules and 4 embedded platforms
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📊 Results:
→ 95.7% coding accuracy across 350+ IoT tasks
→ 86.5% task completion success rate
→ Outperforms baselines by 15.6%-37.7% in coding accuracy
→ Reduces development time to 2.6-3.1 minutes for complex systems
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