Humans are generating a large amount of information regarding the natural environment. This data includes satellite and drone images, land-based photographs, and microscopic observations. These visuals complement the growing body of written information from conservation and climate scientists. An ideal scenario would involve leveraging this data along with climate models to provide insights for healing the planet.
AI can play a significant role by analyzing this information, enabling decision-makers to make informed choices. AI could serve as a 'Co-Pilot' for policymakers, assisting in making decisions that benefit the planet, such as assessing the impact of new developments. However, there are notable challenges, primarily the lack of sufficient hardware, energy, and accessible data.
Data acts as fuel for AI, and accessing it, especially published journal papers, is difficult. The government aims to create a National Data Library to facilitate access to vast amounts of knowledge while maintaining privacy. Currently, the scattered nature of data makes it challenging for researchers and policymakers.
The availability of GPUs, necessary for modern algorithms, is another hurdle, with substantial resources required to meet the demand. Additionally, AI's significant energy consumption is a concern. Recent advancements aim to make AI's energy use more efficient. Overcoming these barriers will significantly enhance AI's ability to address climate and biodiversity crises.
Cambridge is making collaborative efforts to harness AI's potential by working with leading experts globally. According to Anil Madhavapeddy, "There has never been a greater opportunity to develop solutions for our planet’s future – and to help rebalance the relationship between humans and nature across the world."
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