Redrawing the not-so-pretty energy footprint of AI | Current Affairs | Vision IAS

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Redrawing the not-so-pretty energy footprint of AI

2 min read

Generative Artificial Intelligence and Energy Consumption

Generative AI, while beneficial for tasks like creating art, comes with a significant energy cost, leading to environmental concerns. For instance, the use of advanced AI models results in high electricity consumption and hardware stress, such as GPUs overheating.

Current Energy Impact

  • AI usage is heavily reliant on electricity from data centers, primarily powered by fossil fuels.
  • Projections suggest that by 2030, data centers could use up to 10% of the world's electricity.

Transparency and Sustainable Development

  • AI companies should disclose their energy consumption, sources, and efforts to reduce usage.
  • This transparency can guide research towards sustainable AI models.

Nuclear Energy as a Solution

Nuclear energy, specifically Small Modular Reactors (SMRs), offers a potential solution to the energy demands created by AI advancements.

Advantages of SMRs

  • SMRs are compact, scalable, and can be deployed closer to facilities with high energy demand.
  • They provide constant, zero-carbon electricity, unlike intermittent renewable sources.
  • Modular construction reduces time and costs, with enhanced safety features and the ability to operate in diverse environments.

Challenges and Considerations

  • Policy changes are needed for safety, waste management, and public acceptance.
  • High initial investments are required, although costs are expected to decrease.
  • Coordination with renewable energy efforts is crucial for optimal synergy.

Conclusion

A public-private partnership model is suggested to address the challenges of sustainable AI development by integrating SMRs and renewable energy solutions.


  • Tags :
  • Generative AI
  • Small Modular Reactors (SMRs)
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