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AI boosts agricultural productivity with enhanced crop growth techniques

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AI boosts agricultural productivity with enhanced crop growth techniques

In central India, tomato farmers are grappling with extreme weather. Severe droughts over the last decade have led to substantial crop losses, threatening their livelihoods.

Halfway across the globe, Silicon Valley’s ClimateAi is crafting an AI platform to assess crop vulnerability to climate change. This tool scrutinizes climate, water, and soil data to predict future agricultural viability.

Maharashtra, India, became an early test subject in 2021. Farmers used the ClimateAi app to input seed types and planting locations. The app’s simulations forecasted a 30% drop in tomato yields over two decades due to heat and drought. It urged growers to adapt their strategies.

This advice was a game-changer. Tomato producers shifted to hardier seed varieties and altered planting schedules. Thanks to ClimateAi, co-founded by India-born Himanshu Gupta, what once took ages now unfolds in minutes, cutting costs significantly.

Gupta, in a conversation with CNN, described AI as a time and effectiveness multiplier against climate change. AI isn’t just about cool consumer tools like ChatGPT; it’s a pivotal player in climate research. Experts see AI speeding up everything from pollution reduction to enhancing weather models.

Fengqi You, a Cornell professor, notes AI’s strengths in predictive capabilities. These range from understanding molecular structures to broader climate systems. AI is fast-tracking scientific discoveries. It’s analyzing large datasets, identifying patterns, and conducting experiments at breakneck speeds.

Dan Keeler, of impact investing firm Newday, highlights AI’s role in coastal restoration. It models optimal locations for seagrass replanting, considering factors from water toxins to the impact on local sea life and tourism.

In the Arctic, where warming is alarmingly rapid, AI aids scientists like Anna Liljedahl of the Woodwell Climate Research Centre. AI helps make quicker permafrost forecasts, crucial for understanding Arctic changes.

Google DeepMind’s 2019 project demonstrated AI’s potential in renewable energy. It predicted wind power availability, boosting its value for wind farmers. AI also forecasts energy demand peaks, aiding grid operators in managing power supply.

Gupta emphasizes AI’s role in integrating renewable energy into existing grids. It can real-time match renewable sources with consumer demand, optimizing the green energy landscape.

AI’s applications extend to carbon capture research and flood forecasting. The Cool Down media company plans to launch an AI tool to guide sustainable living. Co-founder Anna Robertson aims to simplify climate action choices for individuals.

Yet, AI’s energy demands raise environmental concerns. Data centers, crucial for AI, are power-hungry and often reliant on fossil fuels. They also need water for cooling, a scarce resource in some regions.

Cornell’s You warns of AI’s growing energy footprint. But companies like Amazon Web Services are addressing this. They’re pledging to be “water positive” and even aiding farmers with spent cooling water.

Data center locations can be strategic, like in colder regions, reducing cooling needs. Scandanavia, with its cold climate and renewable energy sources, is becoming a data center hub.

Regulators globally must weigh AI’s climate benefits against its environmental impact. Tech experts stress making AI affordable and accessible, especially for low-income nations facing climate crises.

ClimateAi’s Gupta believes we’re just beginning to unlock AI’s potential in both business and humanitarian impacts. The journey with AI and climate change is just starting, and the possibilities are endless.

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