Tauri/Rust
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Project ARIS: AI in Astronomy
Read Full Article: Project ARIS: AI in AstronomyProject ARIS demonstrates a practical application of local Large Language Models (LLMs) by integrating Mistral Nemo as a reasoning layer for analyzing astronomical data. Utilizing a Lenovo Yoga 7 with Ryzen AI 7 and 24GB RAM, the system runs on Nobara Linux and incorporates a Tauri/Rust backend to interface with the Ollama API. Key functionalities include contextual memory for session recaps, intent parsing to convert natural language into structured MAST API queries, and anomaly scoring to identify unusual spectral data. This showcases the potential of a 12B model when equipped with a tailored toolset and environment. Why this matters: It highlights the capabilities of LLMs in specialized fields like astronomy, offering insights into how AI can enhance data analysis and anomaly detection.