The Environmental Cost of AI: Energy Consumption and Carbon Footprint
AI models require massive computational resources, contributing significantly to energy consumption and environmental impact.
Environmental Impact
- High energy consumption for training
- Continuous server infrastructure needs
- Carbon emissions from data centers
- Electronic waste from hardware upgrades
The Numbers
- GPT-3 training: 1,287 MWh of energy
- Daily ChatGPT usage: ~500,000 kWh
- Carbon footprint: Equivalent to 300+ cars annually
// Every AI query has environmental cost:
const aiResponse = await openai.complete({
prompt: "Generate a simple function",
// This single request uses energy equivalent to:
// - Charging a smartphone 120 times
// - Running a laptop for 3 hours
// - Powering LED bulb for 2 days
});
Consider the environmental impact of AI usage in development workflows.
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