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Apply Now for the AI for Climate and Nature Grand Challenge

Apply Now for the AI for Climate and Nature Grand Challenge

The Bezos Earth Fund has launched a global $100 million initiative, the AI for Climate and Nature Grand Challenge, to harness the power of AI in tackling climate change and nature conservation. The first round focuses on sustainable proteins, power grid optimization, and biodiversity conservation, with additional wildcard solutions welcomed.

An Urgent Need Climate change and threats to nature are pressing global issues. AI is already being used to monitor greenhouse gas emissions and advance clean energy, but more must be done, and faster. This initiative aims to amplify these efforts by bridging the gap between AI technology and frontline environmental organizations.

A World-Changing Opportunity This initiative encourages partnerships between climate, nature, and AI experts. By providing targeted funding, mentorship, and resources, the Grand Challenge seeks to stimulate innovation and develop scalable solutions.

Focus Areas

  • Sustainable Proteins: Developing AI-driven meat alternatives.
  • Power Grid Optimization: Enhancing grid resilience and integrating renewable energy.
  • Biodiversity Conservation: Using AI to protect species and habitats.
  • Wildcard Solutions: Innovative ideas for climate and nature using AI.

How the Grand Challenge Will Unfold The initiative will progress through three rounds, offering up to $100 million in total funding. The first round includes:

Phase 1: Proposals

  • Open to U.S.-based 501(c)(3) entities and global academic institutions.
  • Up to 30 seed grants will be awarded.
  • Deadline: July 30, 5:59 p.m. Eastern Time (9:59 p.m. UTC).

Phase 2: Implementation Plans

  • Seed Grantees will develop detailed plans with support from AI experts.
  • Up to 15 implementation grants, each up to $2 million, will be awarded.

Successful projects will be implemented over two years, with an in-person summit in 2025.

Deadline to Apply: July 30, 5:59 p.m. Eastern Time (9:59 p.m. UTC).

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Apply here