NVIDIA’s Climate Crusader: AI’s Innovative Role in Battling Environmental Crisis
NVIDIA and the Potential of AI
Efforts to tackle climate change and achieve energy efficiency have long involved NVIDIA, and a recent study highlights the potential of AI and accelerated computing to do just that.
“Rethinking Concerns About AI’s Energy Use” is the title of a well-researched article that delves into the ways AI can fulfill these important demands, and in many instances, already does. A new study found that machine learning is already assisting many different industries in significantly improving their energy efficiency.
The study, which is based in Washington and authored by the Information Technology and Innovation Foundation (ITIF), argues that governments should speed up the adoption of artificial intelligence (AI) as a powerful new tool to improve energy efficiency in many industries. The study cites dozens of sources to support its claims.
When it comes to optimizing energy efficiency, data centers of all sizes can benefit from artificial intelligence and faster computing.
Take FourCastNet, an AI-powered weather prediction model developed by NVIDIA. It outperforms state-of-the-art methods by a factor of 45,000 while using 12,000 less energy. Using GPU and DPU accelerators instead of CPUs for all AI, HPC, and networking offloads may result in a staggering annual power savings of 19 terawatt-hours for data centers, according to NVIDIA’s calculations. That’s the same amount of energy that 2.9 million passenger automobiles would use in one year.
This past year, the primary open science facility of the United States Department of Energy detailed its accomplishments in the field of accelerated computing. In studies conducted at the National Energy Research Scientific Computing Center, energy efficiency was shown to have improved by an average of five times across four critical scientific applications while using NVIDIA A100 Tensor Core GPUs. Gains of approximately ten times were recorded by a weather forecasting application.
Analyzing the AI Data
According to Daniel Castro, who wrote the study, contemporary AI expectations are just a rehash of the overblown predictions made during the internet boom over twenty years ago.
Efforts to tackle climate change and achieve energy efficiency have long involved NVIDIA, and a recent study highlights the potential of AI and accelerated computing to do just that. The study, which is based in Washington and produced by the Information Technology and Innovation Foundation (ITIF), argues that governments should speed up the adoption of artificial intelligence (AI) as a powerful new tool to promote energy efficiency in various sectors. The study cites dozens of sources to support its claim. This paper details the many ways in which machine learning is assisting many industries in lessening their negative effects on the natural world.
Artificial intelligence is helping farmers reduce their water and fertilizer usage. For the purpose of improving the electric grid’s efficiency, utilities are implementing it. It helps logistics operations improve delivery routes, which in turn reduces fuel usage. In order to save energy and cut down on waste, factories are using it.
In order to “assist the public sector in reducing carbon emissions through more efficient digital services, smart cities and buildings, intelligent transportation systems, and other AI-enabled efficiencies,” it is also suggested that AI be widely implemented across government departments.
Read: 10 AI In Manufacturing Trends To Look Out For In 2024
Streamlining Operations in Data Centers
When it comes to optimizing energy efficiency, data centers of all sizes can benefit from artificial intelligence and faster computing. Take FourCastNet, an AI-powered weather prediction model developed by NVIDIA. It outperforms state-of-the-art methods by a factor of 45,000 while using 12,000 less energy. According to Bjorn Stevens, director of the Max Planck Institute for Meteorology, this bodes well for the efficiency of supercomputers worldwide that run nonstop to offer regional forecasts. Stevens made this announcement on his blog.
Using GPU and DPU accelerators instead of CPUs for all AI, HPC, and networking offloads may result in a staggering annual power savings of 19 terawatt-hours for data centers, according to NVIDIA’s calculations. That’s the same amount of energy that 2.9 million passenger automobiles would use in one year.
Read: 10 AI In Energy Management Trends To Look Out For In 2024
This past year, the primary open science facility of the United States Department of Energy detailed its accomplishments in the field of accelerated computing. In studies conducted at the National Energy Research Scientific Computing Center, energy efficiency was shown to have improved by an average of five times across four critical scientific applications while using NVIDIA A100 Tensor Core GPUs. Gains of approximately ten times were recorded by a weather forecasting application.
New scientific tools are being developed to better understand and fight climate change as a result of the integration of AI and faster computing. Building a digital twin of Earth on a supercomputer that can simulate climate on a global scale was announced by NVIDIA in 2021 as part of their Earth-2 effort. It’s one of a small number of global initiatives with comparable lofty goals.
Destination Earth is one such initiative. It’s a pan-European endeavor to build digital twins of the planet combining acceleration computing, artificial intelligence, and “collaboration on an unprecedented scale,” according to Peter Bauer, the project’s head and a veteran with over 20 years of experience at the leading weather forecasting center in Europe. When it comes to improving sustainability, experts in the utilities sector agree that AI is crucial.makes an effort.
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