HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE FOR
WHAT IS AI FOR CLIMATE?
We explore the use of today's most advanced technologies to mitigate the risk of environmental crises in the world and to activate the economy in the poverty-stricken communities around nature reserves.
There is no doubt that the global health crisis we are experiencing requires us to rethink our current production models and our relationship with the natural world. Our right to a healthy sustainable environment must become our top priority to prevent future environmental and social crises.
The global initiative AI for Climate is created to address this challenge. Our purpose is to build a bridge between the conservation and AI worlds. It aims to deepen the questions and accelerate concrete actions on the use of AI to fast-track humanity's response to Climate Change and biodiversity loss.
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OUR LINES OF ACTION
GLOBAL LEARNING PLATFORM
We are bridging silos between tech innovation, the climate, and conservation fields by creating spaces to share best practices, technologies, and resources. This includes annual high-level global forums, and much more.
AI LIVING LABS FOR CONSERVATION
We are harnessing the power of AI to strengthen the protection and management of public and private nature reserves around the planet. Our aim is to create a global network of AI-driven Living Labs of natural reserves.
OPEN DATA POOL FOR AI TRAINING AND CARBON ACCOUNTING
We are accelerating access to open robust data to train AI models to fast-forward the world’s conservation and restoration solutions, as well as provide a viable, AI-powered alternative for blue carbon accounting.
Using AI to amplify the protection and management of public and private nature reserves around the planet, collaborating with industry, government, academia leaders, and local communities to find and co-design the best strategies.
OPEN DATA POOL
We are collaborating with leading AI groups to help accelerate the availability of robust data and develop the most effective open AI models based on local contexts, as well as provide a viable, AI-powered alternative for blue carbon accounting (that can complement the carbon accounting for land ecosystems).