What is the amount of the CO2-Footprint of AI, blockchains and smart home applications?
However, in August 2022, Ethereum switched from the computationally intensive proof-of-work to the proof-of-stake process and, according to its own statements, now consumes 99.95 percent less energy.
Ethereum last had its consumption estimated in September. The Germany-based Crypto Carbon Ratings Institute (CCRI) found that the network now consumes just 2.6 megawatt hours annually, equivalent to emissions of one megaton of CO2 is equivalent to.
As I said, exact estimates are hardly possible, and the providers’ own statements should be treated with caution. Here is a comparison from the Deloitte Canada study: Solana 11.05, Polygon 0.79 and Flow 0.18 megawatt hours per year.
AI, Machine Learning and Big Data – Smart Pollution?
Humanity is already benefiting enormously from AI applications – for example in medical diagnostics, but also in climate protection and making energy supply more efficient. In addition to time, money and high-quality data, training an AI model requires a lot of energy.
The more parameters a model has, the more energy-intensive the calculations are – at least that’s what you can say, but the different models also use different amounts of electricity.
Thousands of Petaflops
For example, OpenAI’s GPT-3 natural language processing program is what is known as an autoregressive Transformer Language model. In 2020 it consisted of 175 billion parameters, the previous model GPT-2 had only 1.5 billion parameters when it was launched a year earlier.
While GPT-2 took a few tens of petaflop days to train, GPT-3 required several thousand — a massive amount of computation and power. The unit flops or floating point operations per second describes the processing speed of computers, one petaflop corresponds to one quadrillion floating point operations per second.
Long explanation for a total of 936 megawatt hours of electricity or 400 megatons of CO2which only costs the training, not the operation of the AI.
Green Hope IoT – Smart Homes and Autonomous Vehicles
In order to calculate the additional costs for the smart home, you have to measure the power consumption of the devices in stand-by mode in addition to the new hardware to be procured. In fact, depending on the manufacturer – for example smart speakers – these often differ greatly from each other.
A modern Apple HomePod mini on stand-by only consumes 0.6 watts, 5.42 kilowatt hours per year, i.e. almost 2.3 kilograms of CO2. An old Amazon Echo consumes around five times as much electricity per year and thus causes over 10 kilograms of greenhouse gases.
Users of a complete smart home get 250 to 500 kilowatt hours a year for stand-by operation; in CO2 That’s around 100 to 200 kilograms. Of course, this can save energy on another level, such as heating or lighting.
Car refuels Internet
Many people also hope that autonomous vehicles will lead to a green turnaround in traffic, but according to a current Fraunhofer study, this hope can quickly be reversed.
A critical factor is data exchange. In test vehicles, the volume was between 1.4 and 19 terabytes per hour. As soon as more than 0.8 TB/h were transferred, the efficiency gain compared to conventional vehicles would be used up.
• The Energy Footprint of Blockchain Consensus Mechanisms Beyond Proof-of-Work (2022)
• Carbon Foodprint of NFTs (2022)
• Ethereum Energy Consumption (2022)
• Doing AI without breaking the bank yours or the planets (2021)
• Open AI AI and Compute (2018)
• Meet M6 — 10 Trillion Parameters at 1% GPT-3’s Energy Cost (2022)
• AI is harming our planet (2022)
• AI Power Consumption exploding (2022)
• Estimation of energy consumption in machine learning (2019)
• Energy and Policy Considerations for Deep Learning in NLP (2019)
• Sustainable AI: Environmental Implications, Challenges and Opportunities (2022)
• Smart Home – Energy consumption and savings potential of intelligent devices (2019)
• Smart framework conditions for saving energy and resources in networked household products Short study commissioned by the Bund für Umwelt und Naturschutz Deutschland eV (BUND) 2018
• Car refuels internet. Impact of Automated and Connected Driving on Vehicle Energy Consumption, Data Transmission and Infrastructure (2020)
• How harmful to the climate are Netflix & Co.? (2021)
• Energy requirements of digitization (2022)
• Germany on the way to climate neutrality: What opportunities and risks does digitization bring?
• Calculating the Carbon Footprint of Streaming Media: Beyond the Myth of Efficiency
• Environmental Impacts of Shifting from Movie Disc Media to Movie Streaming: Case Study and Sensitivity Analysis