Sustainable AI

The development and operation of AI consumes resources and emits greenhouse gases. However, there are various fields of action and options for minimizing this environmental pollution.

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Reducing the environmental impacts of artificial intelligence

Sustainable artificial intelligence

Computing power and energy is necessary for the development and operation of AI solutions. Depending on how efficient the used data centers are and how the energy is generated, large amounts of greenhouse gases can be emitted.

The resource requirements and the environmental impact of AI models has grown exponentially in recent years. In particular, the development and operation of large language models such as GPT-3 is highly resource-intensive, since trillions of parameters are trained on huge amounts of data.

Despite initial increases in efficiency, it is expected that the trend towards larger and larger models will continue in the coming years. It is all the more important that AI developers are aware of this and take measures during development to reduce energy consumption and the associated greenhouse gas emissions.

Benefits of sustainable AI

Sustainable AI is valuable for companies not only from an ecological perspective. Increasing the sustainability of AI solutions is often accompanied by a reduction of the necessary computing capacity and thus the corresponding costs.

Three fields of action for sustainable AI

Selection of data centers that are operated with a sustainable electricity mix.

Choosing a location that is optimized according to the electricity mix can reduce the CO2 emissions generated by power generation.

Usage of efficient and sustainable data centers and providers.

By selecting more efficient data centers, the energy required per computing power can be reduced dramatically.

Optimizing the efficiency of infrastructure, data and model architecture.

Efficient design of the infrastructure, data and model architecture can reduce the amount of energy required.