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🗞️ Driving the news: Generative artificial intelligence (AI) is increasingly being used for a range of tasks, but new research reveals that these AI systems come with significant hidden environmental costs
• The energy required to power large AI models can be up to 10 times more than a standard Google search, contributing to higher carbon emissions, especially when using more complex AI models
🔭 The context: AI systems, particularly large language models, rely on massive data centers powered by fossil fuels to process requests
• As AI models become more advanced, the energy required to run them increases, leading to a significant environmental impact
• This issue is compounded by the lack of transparency from AI companies regarding their energy consumption and carbon emissions, making it difficult to gauge the full environmental cost of AI interactions
🌍 Why it matters for the planet: As AI technology becomes integrated into daily life, its environmental footprint continues to grow
• While AI has the potential to solve complex problems, its carbon emissions from data centers powered by coal or natural gas could undermine efforts to mitigate climate change
• Increased energy consumption from AI systems contributes to global warming, requiring careful consideration of AI's role in a sustainable future
⏭️ What's next: To reduce AI's environmental impact, users can choose smaller, task-specific models that consume less energy, and be more deliberate in their interactions with AI
• Greater transparency from AI companies on their energy usage is crucial, as is the need for regulations that incentivize energy-efficient models
• In the longer term, innovations in software efficiency could mitigate AI's carbon footprint
💬 One quote: "We don’t need generative AI in web search. Nobody asked for AI chatbots in (messaging apps) or on social media," – Sasha Luccioni, climate lead at Hugging Face
📈 One stat: Complex AI queries can produce up to six times more carbon emissions than simple queries
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