Does every artificial intelligence trigger global warming?

Yapay intelligence systems require high calculation power, especially large language models and deep learning algorithms. This increases energy consumption of data centers. For example, a ChatGPT query spends about 10 times more energy than a traditional Google search. This increasing energy needs of data centers is about 1.5 percent of global electricity consumption. This rate can increase with the further prevalence of artificial intelligence.

Universal consumption: Opening of artificial intelligence in water]
] Data centers where artificial intelligence systems work, produce large heat and require strong cooling systems to control this heat. Most of these systems perform the cooling process with water. For example, about half liters of water for an average of 20 artificial intelligence queries. This figure points out a serious water consumption when millions of queries are thought. Water consumption increases environmental pressure in areas that are particularly limited to resources, risk of drought. This consumption, which does not appear, becomes a critical problem in terms of sustainability of digital technologies, is becoming a necessity to develop more environmentally friendly cooling methods. [

Free additive: share of artificial intelligence in the climate crisis
The operation of artificial intelligence systems is largely based on electricity energy. An important part of this energy is still produced with fossil fuels, although artificial intelligence is indirect, there is a serious effect on carbon release. Training and continuous operation of large language models, can lead to tons of carbon dioxide release. This makes artificial intelligence not only a digital tool but also a system with physical effects. Of course it is possible to see technology as a solution tool while fighting climate change. But to ignore the effects of these technologies on the environment, being part of the solution, it can cause the problem to become more. Data centers and energy efficient software solutions that work with renewable energy to reduce carbon footprint can be the key to making technology more sustainable.

Sustainable solutions[
Here are measures that can be taken to reduce the environmental effects of artificial intelligence...
Energy efficiency: artificial intelligence-supported cooling systems can be used to improve energy efficiency in data centers. For example, Google’s DeepMind team developed an artificial intelligence-supported optimization system to reduce energy consumption up to 40 percent in data centers.
Renewable energy usage:[] to turn to renewable energy sources to meet the energy requirement of data centers, reduce carbon emissions.
] Avoid unified queries:[] Avoid unnecessary and very long queries when using artificial intelligence systems, reduce energy consumption. It is highlighted that every query creates load on systems and leads to cost even if it is micro-level.

Artificial intelligence should be taken into consideration while offering many innovations that facilitate our lives. Factors such as energy and water consumption, carbon emissions, cause us to question the sustainability of this technology. Therefore, it is important for the development and use of artificial intelligence in an environmentally friendly way.