AI Taking on Climate Change: An Inside Look at the New Frontier of Green Tech
Let’s talk about artificial intelligence, climate change, and the power of a good idea. Imagine a superhuman chemical engineer: a brilliant mind that never sleeps, powered by AI, dedicated to developing new, cleaner energy technologies. That’s the vision of London-based startup Orbital Materials. It’s bold, it’s ambitious, and it’s a glimpse of what the future might look like if we can successfully marry AI and climate innovation.
Picture this: they want to use generative AI, the same technology that powers tools like ChatGPT, to accelerate the development of green energy technologies. The goal? Using powerful computer models to find the best formulas for sustainable jet fuel or rare-earth mineral-free batteries. It’s a bit like those software engineers who create sleek designs for airplane wings or chic IKEA furniture, but for molecular science.
The Promise and Pitfalls of AI in Green Tech
But here’s the kicker: it’s not as easy as it sounds. Predicting the next word or sentence in a text, like ChatGPT does, is one thing. Predicting how a new molecule will behave, not only in a lab but in the real world, is another entirely. There have been attempts to use AI to find greener materials before. Some succeeded, others fell short. The tech isn’t quite there yet, and the clock is ticking.
We’re in a race against time to slash emissions and meet net zero targets. The timeline for new materials to go from discovery to market can take decades. That’s a luxury we simply can’t afford. If we want to decarbonize the planet, we need to do it fast. Cue AI researchers, convinced they can speed up the process.
AI and Material World: A Match Made In Tech Heaven?
Before launching Orbital Materials, co-founder Jonathan Godwin spent three years at Google’s AI lab, DeepMind, researching advanced material discovery. When DeepMind released AlphaFold, a model to predict protein structures, and tools like ChatGPT took off, Godwin saw the potential for AI to conquer the material world. “What I thought would take 10 years was happening in a matter of 18 months,”he said.
Using a method similar to AI image generators, Orbital Materials plans to train models with data on the molecular structure of materials. Imagine typing in a desired property and material, and the model spits out a proposed molecular formula. It sounds like magic, but it’s just good science.
The Future of Green Tech: A Profitable Venture?
Right now, tech investors are on the hunt for companies that can turn a profit by improving greener material production. And the markets for advanced materials in sectors like renewable energy, transportation and agriculture are set to grow by tens of billions of dollars in the coming years.
There’s a whole lot of potential here. Some researchers are setting up “self-driving labs”to search for new materials at unmatched speeds. Dutch startup VSParticle is developing machinery to create components for gas sensors and green hydrogen. And Orbital Materials, having raised $4.8 million in initial funding, has its sights set on carbon capture.
The Long Road Ahead
But let’s not get ahead of ourselves. There are bumps in this road. Developing advanced materials in areas like battery and fuel production involves working with huge incumbent enterprises and tangled supply chains. It’s a costly endeavor, and it’s not without risks. Heather Redman, a managing partner with Flying Fish Partners, which backed Orbital Materials, acknowledges these risks but believes in the long-term gain. “We love big hills as long as there’s a big gigantic market and opportunity at the top,” she said.
Whether the market is ready for this kind of innovation is still an open question. But I’ll tell you this: the potential is there. We’ve seen what AI can do in the realm of text prediction. Now, it’s time to see what it can do for green technology. The pitch is simple: “Look at ChatGPT. We can do the same thing for chemistry.”Now let’s see if the world is ready to buy what these AI researchers are selling.
