How AI Can Facilitate the Energy Transition Without Standing in the Way

According to ChatGPT, the energy consumed by artificial-intelligence (AI) systems varies depending on their usage and complexity. Generally, these systems need huge amounts of electricity to efficiently process and analyze data.

Estimates show that for this response generated by the chatbot, almost 10 times the electricity a Google search needs was used. With 100 million ChatGPT users weekly, the extra demand for energy has increased greatly. Keep in mind that this applies to users on this platform alone.

The increased demand for energy in this industry, primarily driven by the construction and running of data centers that operate and train artificial intelligence models, is contributing to greenhouse-gas emissions globally.

Recently, Microsoft announced its carbon-dioxide emissions had increased by almost 30%. The multinational corporation and technology company, which has invested in ChatGPT, revealed that the emissions had increased because of expansion of its data center. Goggle released a similar report last year, which revealed that its emissions were about 50% higher than they were five years ago. The company also tied the increase to a rise in the demand for energy from data centers.

It is expected that as artificial intelligence systems develop further and gain traction, the running of these models will increase data centers around the globe and in turn, place additional pressure on electrical grids while also increasing emissions.

To help mitigate global greenhouse-gas emissions, artificial intelligence needs to improve on energy efficiency. Reports show that AI has the potential to reduce global greenhouse-gas emissions by about 5% to 10% by 2030.

Researchers are already designing new hardware with new chip cooling methods and better performance. For instance, Nvidia is developing a new superchip that performs significantly better when running generative artificial intelligence services while using more than 20 times less energy.

The use of alternative energy options such as nuclear power to power storage technologies and data centers will also aid in the decarbonization of the grid. Additionally, companies investing in emerging technology, such as carbon removal, will also help reduce carbon dioxide emissions.

Artificial intelligence could also be used to transform the energy efficiency of carbon-intensive industries, helping optimize the performance of air conditioning and heating, predicting use of energy and improving manufacturing efficiency via predictive maintenance.

Furthermore, artificial intelligence could be used to accurately predict the production of energy, helping avoid wasteful consumption of energy, instability of the electricity grid and preventing overproduction, which reduces emissions.

For companies such as Meta Platforms Inc. (NASDAQ: META) whose AI systems demand the construction of larger data centers, the challenges of managing their emissions are even greater and should keep decision makers there alert so that AI can be harnessed to address the twin objectives of keeping emissions low while advancing the business interests of the company.

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