Ayush

Startups and nonprofits are using computer vision to detect illegal logging.

AI is helping map wildfires and predict where they also might spread.

In short, AI gives us a bird's eye view of the Earth and lets us act before it's too late.

Think of it like traffic lights that reduce idling or buildings that adjust lighting and heating based on occupancy.

Even garbage collection routes are being optimized with AI to reduce fuel waste.

In renewable energy, it's unpredictable.

AI helps balance wind and solar supply with demand, preventing blackouts while reducing fossil fuel reliance.

Here comes the twist.

Training a single large AI model can emit as much as

as much carbon as five cars in their lifetime.

Data centers also consume huge amounts of water for cooling.

Straining resources is in an already drought-prone region.

Companies are shifting to renewable powered servers, experimenting with liquid cooling and optimizing model training to cut waste.

We also have to talk about inequality.

Most green AI projects start in wealthy nations, but climate change hits developing countries hardest.

Without equity, AI could widen the gap, where rich countries clean up their act while poorer ones face the worst damage.

AI isn't just about sensors and predictions, it's about its influencing policy too.

But biased or incomplete data can mean flawed predictions, which could lead to ineffective or even harmful policies.

Let's imagine two futures.

In one, AI runs cities powered by renewables entirely, self-adjusting buildings, smart transits, and zero waste.