Is it possible for machine learning to reverse severe climate change?

Hi, AI Enthusiasts ✨

(and if you’re getting this newsletter for the first time ever, welcome!)

The question of whether machine learning (ML) can reverse severe climate change is complex and honestly, a little multifaceted.

To begin with, what is this big ol’ mighty climate change anyway? 🤔

Is it when the room stays a little hotter than usual during the day, cos it’s scorching hot outside, or is it just the sun doing its thing as it should?

Welp, get comfy 😉 ’cos i have the deets!

Climate change, as a whole, are long-term shifts in temperature, weather patterns, and other atmospheric conditions.

It's like the planet’s thermostat is stuck on the "too warm" setting, causing a cascade of changes like frequent heatwaves, intense storms, rising sea levels, and shifts in wildlife habitats.

Scientists have even pointed out that 100 years ago, the global average temperature was about 1°C (1.8°F). Since the late 19th century, the Earth's temperature has risen by ~2°F (1.1°C).

So far, 2023 has been recorded as the warmest year since people starting taking note of it in 1850 and now, 2024 has broken that record!

Now that you’re up to speed about all of that, let’s talk about how ML can come in! 🫡

Machine Learning is a subset of AI, and it involves algorithms that can learn from and make decisions with data. As countries scramble for effective ways to reduce the effects of climate change, ML is increasingly being seen as a potential game-changer in that fight.

ML is a powerful tool that allows computers to identify patterns, make predictions, and continuously improve their performance without explicit programming.

AI and its offshoot, machine learning, will be a foundational tool for creating social good as well as business success.

In the context of climate change, ML can be applied to solve problems across several key areas, some of which include:

- Climate modelling, to better prepare for hurricanes or droughts.

- Carbon sequestration prediction, which is just a fancy way of describing computers can look at pictures from space to keep an eye on forests, oceans, and soil. They can figure out how much carbon dioxide these areas can hold, which helps us decide where to plant new trees or protect existing areas for better carbon management.

- Building smart grids that can optimise electricity distribution by predicting demand and integrating renewable energy sources more efficiently.

- Water resource management and precision farming, and a host of other things

For the challenges that might hinder this? They aren’t quite straightforward 😅

For example, training complex ML models requires significant computational power, which then increases the carbon footprints that we’re trying to reduce in the first place!

Not to mention, if the data used to train the model doesn't account for rapid climate changes or it lacks diversity in geographical representation, its predictions can be off.

Lastly, while ML can assist in reducing future emissions and improving efficiency, the actual "reversal" of damage that has already been done, like bringing back extinct species or reversing ocean acidification, is beyond its direct capabilities.

I believe that using ML to combat severe climate issues only seems like it's addressing the symptoms, not the root cause.

It's cool, but without systemic changes in how we produce, consume, and govern, we're just putting a band-aid on a much deeper wound. Do you agree?

What’s a tool that can understand your words, learn from your needs, and help you create content effortlessly?

You guessed it— LLMs!

Large language models are transforming the way we write, interact, and innovate, bringing AI-powered communication to life in ways you've never seen before.

Next week tuesday, i’ll tell you all the nitty-gritty details that you wanna know about it 😉

Join the AI for Connectivity Hackathon in Geneva!

Calling all innovators, developers, and problem-solvers!

The AI for Connectivity Hackathon invites you to tackle one of the world’s biggest challenges: bridging the digital divide.

This exciting event focuses on using AI and Open-source telecom infrastructure to scale and optimise school connectivity in underserved regions.

Why participate?

- You can secure a spot in the 6-week GIGA & lablab NEXT Incubator Program.

- Collaborate with world-class mentors and global tech leaders.

- Build solutions that make a real difference in education and connectivity.

** Selected participants may be eligible for travel and accommodation coverage.

Don’t miss your chance to innovate, connect, and create meaningful impact!

🗓 Date: 24-26 January
📍 Location: Online & Geneva

Register here