In this episode of Environment Variables, host Chris Adams welcomes Scott Chamberlin, co-founder of Neuralwatt and ex-Microsoft Software Engineer, to discuss energy transparency in large language models (LLMs). They explore the challenges of measuring AI emissions, the importance of data center transparency, and projects that work to enable flexible, carbon-aware use of AI. Scott shares insights into the current state of LLM energy reporting, the complexities of benchmarking across vendors, and how collaborative efforts can help create shared metrics to guide responsible AI development.