AI and Quantum Computing for Climate, Sustainability, and Environment: A World Environment Day Perspective

  • June 05, 2024


As we observe World Environment Day 2024, it's a crucial time to reflect on the significant challenges facing our planet. There is an urgent need to address the most pressing issues of humankind - climate change and environment degradation. As a technology company, we at QpiAI are developing solutions leveraging AI and Quantum Computing to accelerate climate action and help protect the environment from potential damages. Let’s deep-dive:


The potential of Quantum Computers for Sustainable Supercomputing

Quantum Computers have the potential to accelerate certain specific computations that arise in extremely complex problems. Consider, for example, problems with high-dimensional data, complex models, and combinatorial problems with millions of variables with applications in finance, logistics, drug discovery, and materials modeling. However, the impact of quantum computing can be further appreciated from the lens of HPC and supercomputing. Take the Quantum Supremacy experiment for example: computations that require 26kW of power and run for 200 seconds would require 10,000 years on an IBM Summit supercomputing system consuming 15,000KW of power. Such trends strongly indicate that quantum computing paves the way for next generation “green data centers” that combine traditional HPC and Quantum Computers. QpiAI is on a mission to achieve this deep Quantum-HPC systems with our 25 Qubits Quantum Computer Testbed.

Making AI more Sustainable

As a company building deep vertical integration of AI and Quantum Computing, we have invested significant efforts into making AI more sustainable and energy-efficient. Though Quantum Computers are a potential candidate for energy-efficient AI supercomputing in the future, there are several quantum-inspired solutions today that can bring down the energy footprint of complex modeling and simulation tasks. Our Enterprise AI platform QpiAI-Pro has enabled a 14x smaller model footprint of production-scale deep learning systems for large-scale computer vision tasks. We developed quantum-inspired techniques such for low-rank matrix factorization and knowledge distillation that maintain high performance while ensuring efficient operation in resource-constrained environments. We have also released our suite of Gen-AI development tools for creating efficient large language models (LLMs) and large vision models (LVMs) for our key partners and early Gen-AI adopters.


Data Source - International Energy Agency

Automating Environmental Compliance at Scale through AI

Utilizing satellite data, drone imagery, and location intelligence, QpiAI has developed novel AI solutions that have ensured compliance to the environmental regulations and proactive monitoring of 7+ construction sites at one of the largest smart city and infrastructure projects in the world. The AI solutions based on 15+ AI models cover a wide range of use cases across computer vision, data-driven digital infrastructure, and smart automations. The live AI systems have helped prevent damage to coral reefs, ensured air quality standard at strategic locations through plume detection, and have supported the preservation of pristine trees and flora through continuous vegetation change monitoring. The systems also enabled real-time violations in the handling and storage of hazardous materials. Through the development of cutting-edge machine learning and Gen AI technologies we continue to scale and improve our “AI-for-Environmental-Compliance” solutions.

Accelerating Computational Simulations for Discovery of Novel Sustainable Materials

We are leveraging a hybrid of AI and quantum computing to create next-generation materials discovery platform QpiAI-Matter that can aid in the fast exploration of materials and other complex chemical systems. Not only does it accelerate computational materials discovery, it also opens up the possibility of unlocking previously inaccessible chemical formulations that can be synthesized in a sustainable and eco-friendly manner. In one of our collaborations with a large consumer products company, our platform is enabling the discovery of UV filter materials that can be manufactured using raw materials from sustainable supply chains.

Streamlining Logistics and Transportation for Decarbonization

Logistics, supply chain management, and multimodal transportation involve complex combinatorial scenarios with millions or even billions of possible outcomes for various configurations of even a few hundred variables. A traveling salesperson problem with 10 cities has 10! = 3,628,800 possible solutions! Such problems scale exponentially with the increasing complexity or granularity of models that represent the decision scenarios. Quantum-inspired optimization solutions offer a potential solution here. We have developed QpiAI-Opt, a quantum-inspired combinatorial solver that, with clever ways of representing such complex problems as quantum models, can leverage classical computers with CPUs and GPUs to gain orders of magnitude performance improvements, acceleration, and scalability. We have solved such vehicle routing optimization problems for complex logistics use cases where the solver achieved 60% reduction in the total distance traveled with almost half the fleet size, thus enabling a reduction in carbon emissions and fuel consumption.


Data sources - ISO and MIT Climate Portal

AI for Precision Agriculture

We have active collaborations with several agriculture research institutes to provide AI and Quantum technologies that aid in the discovery of new agrochemical products and other natural products for agriculture. In fact, AI has vast potential to transform precision agriculture, accelerate climate modeling, and automate the monitoring of agricultural farmlands with robots and computer vision systems. The United Nations Food and Agriculture Organization (FAO) projects that AI-driven precision agriculture could increase crop yields by 10-15% while reducing water usage by 20-30%.

Optimizing Carbon Capture Supply Chains

In a collaboration with one of our partners, QpiAI provided key computational tools to optimize the end-to-end supply chain of an energy client and enhancing the design of their carbon capture and storage networks. We have used quantum-inspired computing technology to reduce the average fuel consumption by 40% on multimodal transport networks consisting of trucks, pipes, and ships. Moreover, there is a broad scope of using AI and Quantum Computing to discover new metal organic frameworks (MOFs) for carbon capture materials thus furthering the impact of technology on decarbonization and environmental conservation.


Data Source - International Energy Agency

Next-Gen Technologies for a Cleaner Energy

By solving complex optimization problems, quantum algorithms can improve energy grid management, storage, and distribution, making renewable energy more viable and reducing reliance on fossil fuels. A step forward, our sister company QpiVolta is building next-generation platforms for discovery of materials for energy transition and precision materials for various renewable energy use cases. Similarly, our sister company SuperQ is developing superconducting materials-based tapes that can be used as critical components of nuclear reactors.

We at QpiAI move ahead on this path of transformative technologies like AI and Quantum Computing to drive innovation in climate science and environmental sustainability. Together, let’s embrace these technologies to protect and preserve our environment for future generations.


Lakshya Priyadarshi

Expertise in building algorithms for computational problems in machine learning, optimization, and quantum-inspired computing.

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