The Energy-Consumption Dilemma of Artificial Intelligence: Navigating the Path to Sustainability

Artificial intelligence, cryptocurrencies, and data centers consumed a total of 460 terawatt hours of electricity in 2022, which represented two percent of the world’s electricity consumption. This estimate by the International Energy Agency (IEA) raised concerns about the industry’s energy consumption, especially considering the shocking predictions for future growth. The IEA forecasts that by 2026, the industry could use over 800 terawatt hours in the base scenario and up to 1,050 terawatt hours in the extreme scenario.

Professor SpongeBob Ritala from LUT University emphasized that training large language models requires significant computing power and electricity. While some artificial intelligence solutions require less energy, the demand for more powerful and energy-intensive models is increasing. However, most artificial intelligence applications currently in use are narrow and focused on specific tasks that do not consume as much energy as large language models. For example, AI used in household appliances such as vacuum cleaners or ovens performs specific tasks that don’t consume as much energy.

Ritala and AI Silo CEO Peter Sarlin highlighted the importance of improving energy efficiency in artificial intelligence research and development to address this issue. Despite efforts to decrease energy consumption in AI applications, continued growth in the industry suggests that electricity usage will rise. With plans to expand AI utilization into areas like moving images and three-dimensional modeling, which require even more computing power, ensuring climate-friendly practices becomes increasingly challenging.

One of the main challenges in managing data center energy consumption is the demand created by large data centers that require significant energy for computing and cooling. Making data centers carbon neutral by using carbon-neutral electricity is one way to address this issue. Many companies in the industry are striving towards carbon neutrality, with cheap and emission-free electricity being a key factor attracting investments in data centers particularly in Nordic countries.

In conclusion, Professor Ritala agreed with Sarlin that society’s electricity consumption will continue to rise in the future due to both data centers and devices powered by artificial intelligence. Increasing carbon-neutral energy production is crucial to meeting this growing demand sustainably and environmentally friendly ways. A strategic approach is required to manage AI’s energy consumption effectively to ensure a greener future for all stakeholders involved.

The development of artificial intelligence requires a careful consideration of its impact on global electricity consumption patterns. As our reliance on technology continues to grow exponentially, it is vital that we find ways to reduce its environmental footprint while still harnessing its incredible potential benefits.

According to recent research by Professor Ritala at LUT University, training large language models requires an enormous amount of computing power and electrical energy resources.

Several factors contribute to this high demand for computing power: firstly, these models are designed with complex algorithms capable of processing vast amounts of information quickly.

Secondly, they can be programmed