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Building a Carbon Impact Agent: Boosting ROI with Sustainable AI in Design, Monitoring & Remediation
This talk was recorded at NDC London in London, England. #ndclondon #ndcconferences #developer #softwaredeveloper
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AI is reshaping industries from healthcare to energy, security to agriculture, but this progress comes with a significant environmental cost. Since 2012, the computational power required for cutting-edge AI models has doubled every 3.4 months, fundamentally altering global electricity demand. Training large models like GPT-3 alone has been estimated to produce more than 550 tons of CO₂ - the equivalent of 300 round-trip flights between New York and San Francisco. While these upstream impacts of sustainable model training are well-documented (e.g. model compression techniques, neuromorphic chips and renewable-energy powered infrastructure), the downstream footprint of everyday AI applications remains largely overlooked.
Today, most AI designs emphasise SOPs, data quality, and evaluation, but sustainability is rarely considered. When it is, it tends to be incidental, the byproduct of choosing a cheaper or smaller model. Once deployed, very few applications measure their ongoing consumption footprint. Yet with the right monitoring in place, clear and powerful strategie
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2026/02/11
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