The Cambridge Bitcoin Power Consumption Index has been updated to reflect the hardware distribution and hash rate increase.

Cambridge researchers revised the widely cited index in response to evidence indicating periodic overestimation of Bitcoin mining power consumption.

Cambridge Bitcoin Power Consumption Index has been updated to reflect hardware distribution and hash rate increase News Join us on social networks

The researchers behind the renowned Cambridge Bitcoin Electricity Consumption Index (CBECI) have officially revised its methodology to improve the accuracy and reliability of the index's estimates for the first time since its inception in 2019.

The CBECI was launched in July 2019 with the aim of providing reliable, data-driven information on issues related to the energy-intensive nature of Bitcoin mining and its environmental impact.

Speaking exclusively to Cointelegraph before the announcement of the review, chief researcher Alexander Neumueller explained the role of the index by providing a relatively accurate estimate of the power consumption of the Bitcoin (BTC) network and contextualizing the data in a way understandable to the layman. in the street.

Key takeaways from the revised methodology included the focus on recent developments in Bitcoin mining hardware and hash rate, as well as whether the CBECI accurately reflected the changing landscape. Researchers have looked into the causes of the substantial increase in hash rate in recent years, as new mining equipment eclipsed older models in terms of computing power.

Related: Fastest Growing Nuclear and Gas Power Sources for Bitcoin Mining: Data

Neumueller and his fellow researchers noted that the paucity of hardware-related data was a significant challenge because it limited the CBECI's ability to accurately assess the types of hardware used by miners as well as their pervasiveness.

>

This led researchers to create a methodology that simulates a daily hardware distribution based on real hardware performance and power consumption data. Neumeuller notes that the backbone of the previous CBECI methodology assumed that each profitable hardware model released less...

The Cambridge Bitcoin Power Consumption Index has been updated to reflect the hardware distribution and hash rate increase.

Cambridge researchers revised the widely cited index in response to evidence indicating periodic overestimation of Bitcoin mining power consumption.

Cambridge Bitcoin Power Consumption Index has been updated to reflect hardware distribution and hash rate increase News Join us on social networks

The researchers behind the renowned Cambridge Bitcoin Electricity Consumption Index (CBECI) have officially revised its methodology to improve the accuracy and reliability of the index's estimates for the first time since its inception in 2019.

The CBECI was launched in July 2019 with the aim of providing reliable, data-driven information on issues related to the energy-intensive nature of Bitcoin mining and its environmental impact.

Speaking exclusively to Cointelegraph before the announcement of the review, chief researcher Alexander Neumueller explained the role of the index by providing a relatively accurate estimate of the power consumption of the Bitcoin (BTC) network and contextualizing the data in a way understandable to the layman. in the street.

Key takeaways from the revised methodology included the focus on recent developments in Bitcoin mining hardware and hash rate, as well as whether the CBECI accurately reflected the changing landscape. Researchers have looked into the causes of the substantial increase in hash rate in recent years, as new mining equipment eclipsed older models in terms of computing power.

Related: Fastest Growing Nuclear and Gas Power Sources for Bitcoin Mining: Data

Neumueller and his fellow researchers noted that the paucity of hardware-related data was a significant challenge because it limited the CBECI's ability to accurately assess the types of hardware used by miners as well as their pervasiveness.

>

This led researchers to create a methodology that simulates a daily hardware distribution based on real hardware performance and power consumption data. Neumeuller notes that the backbone of the previous CBECI methodology assumed that each profitable hardware model released less...

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