Report on Accelerated Computing’s Role in Advancing Sustainable Development Goals

Enhancing Energy Efficiency and Climate Action (SDG 7, SDG 13)

Technological Advancements in Sustainable Computing

• Energy efficiency in large language model inference has improved by a factor of 100,000 over the past decade, establishing accelerated computing as a form of sustainable computing.
• NVIDIA is showcasing how accelerated computing propels the sustainable energy transition and advances climate research at Climate Week NYC.

AI’s Contribution to Energy Grid Stability and Climate Resilience

• Artificial intelligence plays a critical role in stabilizing energy grids by rapidly identifying anomalies, allowing operators to respond efficiently and prevent widespread issues. This supports SDG 7 (Affordable and Clean Energy).
• AI-driven, high-resolution weather models strengthen energy systems and reduce vulnerability to climate events, directly contributing to SDG 13 (Climate Action).
• These simulations enable utilities to proactively manage infrastructure, such as clearing obstacles near power lines before storms, enhancing grid resilience.

Fostering Sustainable Industry, Innovation, and Infrastructure (SDG 9, SDG 11)

Projected Energy Savings Across Key Sectors

• According to the Net-Zero America Project, the full adoption of AI applications is projected to save nearly 4.5% of total energy demand in 2035 across the industry, transportation, and buildings sectors.
• These savings support the development of sustainable infrastructure and cities, aligning with SDG 9 and SDG 11.
• Forecasted AI-induced energy savings by 2035 include:

1. Industry Sector: 2-8%
2. Transportation Sector: 3-7%
3. Buildings Sector: 1-4%

Innovations in Energy-Efficient AI Infrastructure

• NVIDIA is collaborating with Emerald AI, an NVIDIA NVentures portfolio company, on an NVIDIA Omniverse Blueprint to build high-performance, grid-friendly, and energy-efficient AI infrastructure.
• This reference design aims to transform data centers into fully integrated AI factories, optimizing every watt of energy for intelligence generation.
• The initiative seeks to unlock 100 gigawatts of untapped power grid capacity, promoting affordable, reliable, and clean power grids in line with SDG 7 and SDG 9.

Promoting Responsible Consumption and Production (SDG 12)

Reduction of Product Carbon Footprint

• NVIDIA has achieved a 24% reduction in the embodied carbon emissions intensity between its HGX H100 and HGX B200 baseboards.
• This commitment to reducing the environmental impact of its products directly supports the principles of SDG 12 (Responsible Consumption and Production).
• The company will continue to publish product carbon footprint summaries for newly released products to maintain transparency and demonstrate ongoing improvements.

Corporate Operational Sustainability

• All offices and data centers under NVIDIA’s operational control run on 100% renewable energy.
• The company purchases carbon-free electricity to cover 100% of its leased data centers’ footprint.
• These operational practices exemplify a corporate commitment to responsible production and consumption patterns.

Strengthening Partnerships for the Goals (SDG 17)

Collaboration at Climate Week NYC

• NVIDIA’s participation in Climate Week NYC facilitates dialogue and partnership among researchers, startups, scientists, technologists, and policymakers to advance climate action.
• Panel discussions with partners like Crusoe Energy Systems and Emerald AI centered on AI’s role in advancing sustainability solutions, from grid scaling to energy optimization.
• This collaborative approach is essential for achieving global sustainability targets, as emphasized in SDG 17 (Partnerships for the Goals).

Supporting a Sustainable Startup Ecosystem

• Through the NVIDIA Inception program’s Sustainable Futures initiative, the company supports startups pioneering developments in green computing, sustainable infrastructure, and conservation.
• These partnerships foster innovation and accelerate the development of technologies crucial for achieving the Sustainable Development Goals.

Applying AI to Advance Climate Science (SDG 13)

AI-Driven Climate and Weather Modeling

• AI-driven climate models are set to increase the adoption and use of renewables by lowering costs and improving efficiency.
• Grid operators can use these models to accurately forecast power generation from wind and solar sources, helping to manage load and stabilize the grid.
• These insights provide a clear path toward decarbonizing the energy grid, a primary objective of SDG 13.

The NVIDIA Earth-2 Platform

• The NVIDIA Earth-2 platform offers tools and services for developers to simulate and visualize weather and climate predictions at a global scale.
• This technology empowers the scientific community to develop applications that can better predict and mitigate the impacts of climate change, contributing directly to the goals of SDG 13.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article discusses advancements in AI and computing technology, focusing on their application for energy efficiency, climate research, and sustainable infrastructure. Based on this, the following Sustainable Development Goals (SDGs) are addressed:

• SDG 7: Affordable and Clean Energy: The core theme of the article is improving energy efficiency through technology. It discusses how AI can optimize energy grids, increase the adoption of renewables, and lead to significant energy savings across major sectors.
• SDG 9: Industry, Innovation, and Infrastructure: The article highlights innovation in computing (accelerated computing, AI factories) and the upgrading of infrastructure (energy grids, data centers) to be more sustainable, efficient, and resilient.
• SDG 12: Responsible Consumption and Production: This is addressed through NVIDIA’s efforts to reduce the carbon footprint of its products. The publication of product carbon footprint reports and the reduction in embodied carbon emissions demonstrate a commitment to more sustainable production patterns.
• SDG 13: Climate Action: The article is framed around Climate Week NYC and directly discusses using AI for climate action. This includes developing advanced weather and climate models to mitigate risks and building resilience in energy systems against climate events.
• SDG 17: Partnerships for the Goals: The article emphasizes collaboration between various entities. It mentions partnerships between NVIDIA, startups (Emerald AI), research institutions (Princeton, Columbia), non-profits (CSIS), and other corporations (Google, AWS) to advance sustainable technology and climate solutions.

2. What specific targets under those SDGs can be identified based on the article’s content?

Several specific SDG targets can be linked to the information provided in the article:

1. Target 7.2: By 2030, increase substantially the share of renewable energy in the global energy mix.
   • Explanation: The article states that NVIDIA’s own offices and data centers run on “100% renewable energy.” Furthermore, it explains how AI-driven climate models can “increase the adoption and usage of renewables across the energy grid” by making solar and wind power more predictable and manageable for grid operators.
2. Target 7.3: By 2030, double the global rate of improvement in energy efficiency.
   • Explanation: This is a central theme. The article opens by stating that “Energy efficiency in large language model inference has improved 100,000x in the past 10 years.” It also projects that AI applications could save “nearly 4.5% of projected energy demand in 2035” across key sectors.
3. Target 9.4: By 2030, upgrade infrastructure and retrofit industries to make them sustainable, with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies.
   • Explanation: The article describes the development of “grid-friendly and energy-efficient AI infrastructure” and the transformation of data centers into “fully integrated AI factories.” The use of AI to induce energy savings in industry, transportation, and buildings, as shown in the table, is a direct example of retrofitting industries with clean technology for efficiency.
4. Target 12.6: Encourage companies, especially large and transnational companies, to adopt sustainable practices and to integrate sustainability information into their reporting cycle.
   • Explanation: NVIDIA’s publication of “product carbon footprint reports” and its commitment to “continue to publish” them for new products is a direct implementation of this target, promoting transparency and sustainable practices.
5. Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.
   • Explanation: The article details how “high-resolution, AI-powered weather models are helping strengthen energy systems and reduce vulnerability to unpredictable climate events.” This technology allows utilities to proactively manage infrastructure, such as clearing obstacles near power lines before storms, thereby strengthening resilience.
6. Target 17.17: Encourage and promote effective public, public-private and civil society partnerships.
   • Explanation: The article showcases numerous partnerships, such as NVIDIA’s collaboration with the startup Emerald AI, its participation in Climate Week NYC alongside policymakers and non-profits, and its work with universities on climate research. These collaborations are aimed at developing and deploying sustainable solutions.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article contains several specific quantitative and qualitative indicators that can be used to measure progress:

• Improvement in Energy Efficiency: The article provides a direct metric: “Energy efficiency in large language model inference has improved 100,000x in the past 10 years.” This serves as an indicator for progress on energy efficiency in computing (relevant to Target 7.3).
• Projected Energy Savings: The forecast that AI can save “nearly 4.5% of projected energy demand in 2035” is a key indicator. The accompanying table provides more granular indicators for specific subsectors, such as a “3% savings in Iron and Steel” or a “6% savings in Buses” (relevant to Targets 7.3 and 9.4).
• Share of Renewable Energy in Operations: The statement that NVIDIA’s offices and data centers “run on 100% renewable energy” is a clear indicator of the adoption of clean energy by a corporation (relevant to Target 7.2).
• Reduction in Product Carbon Footprint: The “24% reduction in embodied carbon emissions intensity between NVIDIA HGX H100 and HGX B200 baseboards” is a specific, measurable indicator of progress in creating more sustainable products (relevant to Target 12.6).
• Development of Climate Modeling Tools: The creation and application of the “NVIDIA Earth-2 platform” to “simulate and visualize weather and climate predictions” serves as a qualitative indicator of increased capacity for climate adaptation and research (relevant to Target 13.1).
• Number of Sustainability Reports Published: The article mentions the release of NVIDIA’s “first product carbon footprint summary comparison” and its plan to continue publishing them. The number and frequency of such reports can be used as an indicator for corporate sustainability reporting (relevant to Target 12.6).

4. Summary Table of SDGs, Targets, and Indicators

Source: blogs.nvidia.com