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CodeCarbon integrates with the software code written in Python. The programme also offers recommendations for software developers to reduce emissions by using cloud infrastructure located in regions where low-carbon energy sources are used.
The programme works as follows: it records the amount of electricity used in infrastructure equipment installed by both the largest cloud solution providers and privately owned data centres.
Then, using information from open sources, it estimates the amount of CO2 equivalent emissions produced based on the energy balance of the electricity network to which the computing equipment is connected. After calculating its CO2 equivalent emissions, the programme stores data on emissions for all projects and for the entire organisation.
This gives companies an idea of the amount of emissions generated by their computer systems connected to the power grid at a given location. The summary board presents this amount of information in a "tangible" form, the equivalent of simple and familiar concepts: the distance travelled by car, hours spent watching television and the daily energy consumed by an average US household.
The developers of CodeCarbon therefore believe that this AI system will contribute to greater transparency about harmful emissions by providing an opportunity to measure and report on emissions associated with computer networks.
source: bcg.com
The programme works as follows: it records the amount of electricity used in infrastructure equipment installed by both the largest cloud solution providers and privately owned data centres.
Then, using information from open sources, it estimates the amount of CO2 equivalent emissions produced based on the energy balance of the electricity network to which the computing equipment is connected. After calculating its CO2 equivalent emissions, the programme stores data on emissions for all projects and for the entire organisation.
This gives companies an idea of the amount of emissions generated by their computer systems connected to the power grid at a given location. The summary board presents this amount of information in a "tangible" form, the equivalent of simple and familiar concepts: the distance travelled by car, hours spent watching television and the daily energy consumed by an average US household.
The developers of CodeCarbon therefore believe that this AI system will contribute to greater transparency about harmful emissions by providing an opportunity to measure and report on emissions associated with computer networks.
source: bcg.com
