Emma Strubell

AI researchers Emma Strubell and Sasha Luccioni discuss the environmental impact of large language models, addressing carbon emissions, water and energy consumption. They emphasize the need for education, transparency, and awareness within the AI community. The podcast also covers AI's negative effects on dating apps, ethical concerns in relationship advice, debunking misconceptions about AI capabilities, and the potential negative impact of large language models in generating hateful content.

Emma Strubell, an Assistant Professor at Carnegie Mellon’s Language Technologies Institute, dives into the environmental impacts of Google’s Gemini AI model. She challenges claims that the model has negligible resource consumption per query, urging a deeper examination of energy and water usage. The conversation covers best practices for making AI more resource-efficient and the need for standardized reporting in the tech industry. Strubell highlights the tension between AI's potential benefits and its environmental costs, pushing for greater transparency.

In this discussion, Emma Strubell, a visiting scientist at Facebook AI Research and future professor at Carnegie Mellon, dives into the environmental costs of NLP model training. She reveals findings from her pivotal paper on the carbon emissions linked to deep learning despite accuracy improvements. Emma also discusses how businesses are responding to environmental concerns and the importance of developing efficient, sustainable NLP practices. Her insights bridge cutting-edge research with real-world applications, offering a vision for greener AI.