1. Artificial Intelligence (AI), technologies that simulate human thinking and decision-making, has seen rapid advancement since the 1950s due to improved computing power and increased data availability.
2. The global AI market is currently valued at $200 billion and is projected to contribute up to $15.7 trillion to the global economy by 2030.
3. The U.S. has announced the Stargate Project with over $500 billion in AI infrastructure investments planned over four years, while in India, Reliance Industries is partnering with Nvidia to build the world's largest data center in Jamnagar.
4. India has announced plans to develop its own Large Language Model (LLM) to compete with existing platforms like DeepSeek and ChatGPT.
5. According to the International Energy Agency (IEA), data centers, which form the backbone of AI operations, contribute 1% of global greenhouse gas emissions, with electricity demand expected to double by 2026.
6. Generative AI models like ChatGPT require 10-100 times more computing power than earlier versions, increasing the demand for graphic processing units and expanding the environmental footprint.
7. The training of advanced AI models like GPT-3 can emit up to 552 tonnes of carbon dioxide equivalent, comparable to the annual emissions of dozens of cars.
8. At COP29, the International Telecommunication Union emphasized the need for greener AI practices, and over 190 countries have adopted non-binding ethical AI recommendations addressing environmental concerns.
9. The European Union and the U.S. have introduced laws to curb AI's environmental impact, though such policies remain scarce globally.
10. Companies can reduce emissions by transitioning to renewable energy sources, purchasing carbon credits, and strategically locating data centers in areas with abundant renewable resources.
11. Google's DeepMind has demonstrated AI's potential for environmental benefit by using Machine Learning (ML) to improve wind energy forecasting and grid integration.
12. A study by Google and the University of California, Berkeley, revealed that Large Language Models' carbon footprint can be reduced by a factor of 100 to 1,000 through optimized algorithms, specialized hardware, and energy-efficient cloud data centers.
13. The AI industry needs standardized frameworks for tracking and comparing emissions to ensure consistency and accountability in environmental impact measurement.
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