The big dive : The 'Green' AI Myth: Carbon Costs of ML Models & Insights on GEO and DeepSeek Fine-tuning

I've been deeply immersed in AI's role in our daily lives, exploring several interconnected themes. My recent focus has been on Generative Engine Optimization (GEO) and the environmental impact of AI systems, particularly their carbon footprint. I've been researching methods to evaluate and select AI tools based on their environmental performance metrics, with a special emphasis on developing KPIs for measuring AI-related carbon emissions. Additionally, I've been investigating how to analyze the broader corporate social responsibility (RSE) implications of AI implementation, while also exploring DeepSeek's fine-tuning capabilities for custom AI model development using Python.