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45% Less Carbon: Routing AI Workloads for Climate-Aligned Computing
The expansion of artificial intelligence (AI) is accompanied by a massive environmental cost, as the millions of computers housed in data centers consume staggering amounts of electricity and water for cooling. Since most of this power is generated by fossil fuel-burning plants, AI contributes directly to air pollution and climate change.
UC Riverside engineering scientists offer a blueprint for a solution called the Federated Carbon Intelligence, or FCI. This novel system outlines a method to dramatically reduce the pollution caused by AI processing in large data centers while also extending the life of the hardware doing the work. No existing system combines these two crucial goals.
The FCI system recognizes that sustainability in AI cannot be achieved by focusing on clean energy alone; the aging and heating of AI systems and their changing efficiency have a measurable carbon cost. The framework integrates environmental awareness—gauging the carbon intensity of electricity at a given time and place—with real-time assessments of the condition of the servers in use, including temperature, age, and physical wear.
By monitoring server health, FCI prevents overworking stressed machines, helping to avoid costly breakdowns, reducing the need for energy and water-intensive cooling, and keeping servers running longer. The system dynamically determines where and when to process AI workloads, using this integrated data to send the task to the server best suited to handle it with the least impact on the machine and the planet.
Simulations backing this proposal showed that FCI could reduce carbon dioxide emissions by up to 45 percent over a five-year period. Crucially, the system could also extend the operational life of a server fleet by 1.6 years. By slowing down hardware degradation, FCI addresses the complete lifecycle carbon footprint, including the embodied emissions from manufacturing new servers. Implementing this adaptive framework would not require new equipment, only smarter coordination across the systems already in place. Researchers state that frameworks like FCI show that climate-aligned computing is achievable without sacrificing performance, paving the way for NetZero-aligned AI infrastructure worldwide.
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By Koloza LLCThe expansion of artificial intelligence (AI) is accompanied by a massive environmental cost, as the millions of computers housed in data centers consume staggering amounts of electricity and water for cooling. Since most of this power is generated by fossil fuel-burning plants, AI contributes directly to air pollution and climate change.
UC Riverside engineering scientists offer a blueprint for a solution called the Federated Carbon Intelligence, or FCI. This novel system outlines a method to dramatically reduce the pollution caused by AI processing in large data centers while also extending the life of the hardware doing the work. No existing system combines these two crucial goals.
The FCI system recognizes that sustainability in AI cannot be achieved by focusing on clean energy alone; the aging and heating of AI systems and their changing efficiency have a measurable carbon cost. The framework integrates environmental awareness—gauging the carbon intensity of electricity at a given time and place—with real-time assessments of the condition of the servers in use, including temperature, age, and physical wear.
By monitoring server health, FCI prevents overworking stressed machines, helping to avoid costly breakdowns, reducing the need for energy and water-intensive cooling, and keeping servers running longer. The system dynamically determines where and when to process AI workloads, using this integrated data to send the task to the server best suited to handle it with the least impact on the machine and the planet.
Simulations backing this proposal showed that FCI could reduce carbon dioxide emissions by up to 45 percent over a five-year period. Crucially, the system could also extend the operational life of a server fleet by 1.6 years. By slowing down hardware degradation, FCI addresses the complete lifecycle carbon footprint, including the embodied emissions from manufacturing new servers. Implementing this adaptive framework would not require new equipment, only smarter coordination across the systems already in place. Researchers state that frameworks like FCI show that climate-aligned computing is achievable without sacrificing performance, paving the way for NetZero-aligned AI infrastructure worldwide.