# Introduction Artificial intelligence is revolutionizing smart home lighting optimization. The new BitRL-Light model combines Llama with the Deep Q-Network (DQN) of deep learning to optimize energy consumption and improve user comfort. # Functionality The model uses an innovative approach that combines 1-bit quantized Llama with DQN. This allows the AI to learn optimal lighting policies based on user preferences. # Benefits The BitRL-Light model offers several benefits, including a 71.4% reduction in energy consumption compared to full-precision models. The model also maintains intelligent control capabilities and can learn from implicit feedback through manual overrides. # Validation tests The model was tested on Raspberry Pi hardware and achieved an energy savings of 32%. Additionally, the model demonstrated a user satisfaction rate of 95%. # Integration with Google Home/IFTTT The model can process natural language commands via integration with Google Home and IFTTT. # Conclusion The BitRL-Light model represents a significant breakthrough for deploying artificial intelligence on resource-constrained IoT devices. This enables intelligent home automation without cloud dependencies.