Energy consumption of AI poses environmental problems

Article by Tech Target

🌍🔌 Addressing AI’s Energy Dilemma
The vast energy consumption of AI isn’t just a technology problem — it’s an environmental crisis. Training top-notch AI models demands not just skills and data but a massive amount of energy. 💻

Take GPT-3, for instance. OpenAI trained it on a massive 45 terabytes of data. 🔋 The process consumed an equivalent of almost the yearly energy consumption of three average households combined.

Data centres, which also store and process the vast amounts of data needed for AI, are highlighted as major energy consumers. IBM’s Weather Company alone processes 400 terabytes of data daily, demanding over the equivalent to powering 80,000 U.S. households. 🏢⚖️

The environmental impact is alarming, as the CO2 emissions from AI usage exacerbate climate change, trapping heat and disrupting ecosystems. 🌿🌡️

Businesses can mitigate their environmental impact by focusing on high-quality data, deleting unnecessary data, and selecting AI technologies tailored to specific use cases, thereby optimizing energy consumption. ♻️

When employing AI, choose purpose-built solutions tailored to specific needs.

🔍 Dive deeper in unraveling AI’s environmental impact by reading the full article: https://lnkd.in/dsP9K5yx

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