Applying the latest developments in AI to combat climate change and build a more sustainable, low-carbon world
AI is a powerful technology that will transform our future. So how can we best apply it to combat climate change and find sustainable solutions?
Our Head of Climate and Sustainability, Sims Witherspoon, spoke at TED Countdown on how AI can accelerate our transition to renewable energy, explaining: “Climate change is a multi-faceted problem with no single solution. We must go beyond discussion What we can do this and start focusing on how we can do it.”
The effects of climate change on Earth’s ecosystems are incredibly complex, and as part of our efforts to use AI to solve some of the world’s toughest problems, here are some of the ways we are working to advance our understanding, optimizing existing systems, and accelerating scientific advances on climate and its effects.
Understanding weather, climate and their effects
Better understanding the fundamental problems and their effects is an essential first step in tackling climate change. In collaboration with the UK Met Office, we have developed a precipitation nowcast model to better understand climate change. This nowcast model is more accurate than the existing state of the art and is much preferred by the Met’s expert meteorologists. Our climate and weather research covers short-term (less than two hours) and medium-term (ten days) forecasts, which can have a huge impact on how we optimize renewable energy systems based on natural resources .
From model the behavior of animal species across the Serengeti to support machine learning projects that advance conservation projects in Africa, we help scientists monitor and better understand the effects of climate change on ecosystems and biodiversity. In the future, our team also relies on AI systems used to identify bird song in Australia, by helping to advance tools for monitoring the evolution of wildlife on a large scale.
Additionally, we partner with a non-profit organization AI on climate change fill important gaps in climate-related data. Currently, this partnership is focused on creating a comprehensive list of datasets whose availability would advance AI solutions for climate change. We will make this wishlist available to the general public when it is completed.
Optimize existing systems
As we move to more sustainable infrastructure, we must optimize the systems the world depends on today. For example, current IT infrastructure, including AI itself, is energy intensive. To help solve some of these problems, we have developed AI that can improve existing systems, including optimize industrial cooling And more efficient IT systems.
Since our energy grids do not yet run on clean energy, it is important that we use our resources as efficiently as possible as we work to transition to renewable energy. Accelerating the global transition to renewable energy sources can also significantly reduce carbon emissions.
In 2019, our climate and sustainability team worked with domain experts at a Google-owned wind farm to increase the value of wind energy – ultimately, aiming to support growth across the sector. By developing a custom AI tool to better predict wind energy production and another model to recommend commitments to deliver this anticipated energy to the power grid, this tool has significantly increased the value of wind energy. Cloud is currently developing a software product using this model, which is driven by French power company ENGIE.
“We will run out of time in the climate countdown if we do not build broadly applicable solutions. »
– Sims Witherspoon, climate and sustainable development manager
Accelerate scientific advances
Beyond optimizing our existing infrastructure, we need scientific breakthroughs to help us build a sustainable energy future. One area of particular promise is nuclear fusion, an incredibly powerful technology with the potential to provide unlimited carbon-free energy. Fusion reactors are powered by a pressurized plasma of ionized hydrogen hotter than the core of the sun. The intense heat means that this plasma can only be held by a rapidly adjusted magnetic field – a notoriously difficult technical challenge.
Mastering the magnetic control of plasma is a fundamental element in meeting the challenge of controlling the nuclear fusion process and harnessing the abundant green energy it could provide. So we collaborated with the Swiss Plasma Center at EPFL to develop an AI system that has learned to succeed predict and control plasma in a tokamak nuclear fusion reactor. And not just to contain the plasma, but to “sculpt” it into a range of experimental shapes.
Bring us your challenges
To create effective AI solutions, researchers must fully understand the challenges faced by individuals around the world. This involves accessing data representative of the issues, collaborating with domain experts to ensure we build reliable systems, following policy guidance on regulatory structures, and finding concrete opportunities to test these systems. For these reasons, collaboration with affected communities, scientists, industry professionals, regulators and governments is at the heart of our sustainability efforts.
If you are an expert in an industry field or a climate scientist with a specific challenge to solve that could help the world understand, mitigate or adapt to climate change, our climate and sustainability team would like to hear from you.
Get in touch: contact-gdm-sustainability@google.com
