As generative AI becomes increasingly ubiquitous, concerns are growing about its environmental impact. Large language models (LLMs) are particularly energy-hungry, with some estimates suggesting they produce up to 50 times more CO₂ emissions than others. Experts warn that the carbon cost of training models, manufacturing and maintaining hardware, and the scale of AI’s adoption will only exacerbate the problem.
Forecast for 6 months: In the next 6 months, we can expect to see increased scrutiny of AI companies’ energy consumption and carbon emissions. This may lead to calls for greater transparency and accountability in the industry.
Forecast for 1 year: By the end of 2024, we may see the development of more energy-efficient AI models and hardware, driven by growing concerns about the environmental impact of AI. This could lead to a shift towards more sustainable AI practices.
Forecast for 5 years: In the next 5 years, AI’s energy consumption is likely to become a major concern for governments and regulatory bodies. We may see the introduction of new regulations and standards to mitigate the environmental impact of AI.
Forecast for 10 years: By 2033, AI’s energy consumption is likely to have become a major factor in the development of new AI technologies. We may see the emergence of more sustainable AI models and hardware, and a shift towards more environmentally friendly AI practices.
