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DeepMind uses the capabilities of neural networks to combat climate change.
DeepMind, a Google-owned company specializing in artificial intelligence (AI) research, uses the capabilities of neural networks to solve problems related to climate change. This was stated in an interview with Sims Witherspoon, a sustainability specialist at DeepMind.
According to her, AI can help in three main areas:
1. Forecasting and monitoring of climate change. For example, recently DeepMind models have learned how to accurately predict precipitation for several hours in advance. This opens the way to modeling even more complex natural processes.
2. Optimization of existing systems and infrastructure. AI can be used to improve the energy efficiency of infrastructure facilities without creating advanced equipment from scratch. The company tried to use AI in data centers and managed to save 30% of energy, which is very important for reducing CO2 emissions.
3. Accelerating scientific progress in green technologies. As part of one of the projects, the neural network was taught to control the shape of plasma in a real thermonuclear reactor. This is an important step towards creating a perfect, environmentally friendly energy source.
At the same time, DeepMind is aware that using AI on such a large scale requires a lot of energy, and they are trying to optimize algorithms to reduce the amount of computing resources used. The company publishes its research results in the public domain.
Experts note that neural networks are a universal and scalable tool. When applied correctly, they can significantly simplify the work of scientists and show impressive results.
However, it is still unclear when the benefits of implementing AI in the field of ecology will outweigh the costs of training it. DeepMind tries to solve problems locally, making algorithms more energy efficient. Experts see the greatest potential of smart technologies in such areas as energy, transport, carbon capture and storage, agriculture and reforestation.
DeepMind, a Google-owned company specializing in artificial intelligence (AI) research, uses the capabilities of neural networks to solve problems related to climate change. This was stated in an interview with Sims Witherspoon, a sustainability specialist at DeepMind.
According to her, AI can help in three main areas:
1. Forecasting and monitoring of climate change. For example, recently DeepMind models have learned how to accurately predict precipitation for several hours in advance. This opens the way to modeling even more complex natural processes.
2. Optimization of existing systems and infrastructure. AI can be used to improve the energy efficiency of infrastructure facilities without creating advanced equipment from scratch. The company tried to use AI in data centers and managed to save 30% of energy, which is very important for reducing CO2 emissions.
3. Accelerating scientific progress in green technologies. As part of one of the projects, the neural network was taught to control the shape of plasma in a real thermonuclear reactor. This is an important step towards creating a perfect, environmentally friendly energy source.
At the same time, DeepMind is aware that using AI on such a large scale requires a lot of energy, and they are trying to optimize algorithms to reduce the amount of computing resources used. The company publishes its research results in the public domain.
Experts note that neural networks are a universal and scalable tool. When applied correctly, they can significantly simplify the work of scientists and show impressive results.
However, it is still unclear when the benefits of implementing AI in the field of ecology will outweigh the costs of training it. DeepMind tries to solve problems locally, making algorithms more energy efficient. Experts see the greatest potential of smart technologies in such areas as energy, transport, carbon capture and storage, agriculture and reforestation.
