How much is AI hurting the planet? Big tech won't tell us
Major tech companies are not disclosing AI energy usage, with Google's emissions rising 48% since 2019. Data center demand is expected to increase significantly, raising environmental concerns about water and carbon emissions.
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The energy consumption of artificial intelligence (AI) technologies is a growing concern, yet major tech companies like Google, Microsoft, and OpenAI are not disclosing specific data on their energy usage and carbon footprints. This lack of transparency has frustrated researchers, who estimate that the energy required for AI operations is significant, with Google's greenhouse gas emissions rising by 48% from 2019 to 2023, largely attributed to AI-related activities. The demand for data centers, which are essential for AI processing, is expected to increase by 160% by 2030, leading to a potential doubling of carbon emissions from these facilities. While AI's energy consumption is still less than that of other technologies like cryptocurrency, its pervasive use across various sectors complicates the assessment of its environmental impact. Additionally, the water usage for cooling these data centers has raised alarms, with instances of excessive water consumption reported. Although some companies are exploring renewable energy sources, the rapid growth of AI is outpacing the transition to greener energy solutions. The debate continues on whether AI can contribute positively to environmental efforts, but current usage trends suggest that it is not significantly aiding in combating climate change.
- Major tech companies are not disclosing AI energy usage and carbon emissions.
- Google's emissions rose by 48% from 2019 to 2023, largely due to AI.
- Data center energy demand is projected to increase by 160% by 2030.
- AI's water consumption for cooling data centers has raised environmental concerns.
- The growth of AI is outpacing the transition to renewable energy sources.
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6 commentsWhat would this look like exactly? What earmarks the power usage as AI, opposed to regular server cost? Just inference and training, or does this also include cost of accumulating and cleaning the data?
It seems like there's no real metric defined here, and as a result any self reported cost by compute breakdown would be largely meaningless.
It's great to know XYZ is using N units of energy per day per person or per user but it's not useful unless we can compare against car, planes, ships, trains, TVs, computers, phones, refrigerators, etc...
But some guy says you should ignore that because he wants you to be angry.
Related
Google's carbon emissions surge nearly 50% due to AI energy demand
Google's 2024 environmental report reveals a 50% rise in carbon emissions from 2019, hindering its 2030 net-zero goal. Increased data center energy use and AI demand are key contributors. Microsoft also faces similar challenges.
Google emissions jump nearly 50% over five years as AI use surges
Google's greenhouse gas emissions surged by 48% in 2023 due to AI data center expansion. Despite challenges, Google aims for net zero emissions by 2030 through clean energy deals and supply chain improvements.
Can the climate survive the insatiable energy demands of the AI arms race?
Google's emissions spike 50% in 5 years due to AI energy needs, posing climate challenges. Tech firms invest in renewables, but face infrastructure hurdles. AI advancements may paradoxically drive energy consumption.
Can the climate survive the insatiable energy demands of the AI arms race?
Google's emissions spike 50% in 5 years due to AI energy demands, posing climate challenges. Datacentres crucial for AI consume much electricity, with predictions of doubling consumption by 2026. Tech firms invest in renewables, but scaling challenges persist. AI's pursuit of advanced models intensifies energy use, raising sustainability concerns.
Google reported a 13% increase in its emissions footprint in 2023
The environmental impact of AI is concerning, with emissions rising due to increased energy consumption in data centers. Efficient practices are needed to balance AI's benefits and its environmental costs.