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Explore the environmental impact of artificial intelligence in this 41-minute conference talk that examines the carbon emissions generated by AI systems and large language models. Learn about the massive CO2 footprint of training models like GPT-3.5, which produces emissions equivalent to 800 Paris-New York flights, and understand the environmental cost of everyday AI queries and coding assistants like GitHub Copilot. Discover the carbon implications of training, fine-tuning, and deploying custom LLMs as organizations increasingly develop their own AI solutions. Gain insights into measuring and reducing AI's environmental impact through good hosting practices, GreenOps methodologies, and available tools that help balance AI advancement with environmental responsibility. Understand practical strategies for confronting what the speaker calls the "invisible monster" of AI carbon emissions while still benefiting from technological progress.
