The world’s biggest oil company is betting on a Google spinoff to profit from pollution.
Saudi Aramco, which pumps more crude than any rival, has partnered with SandboxAQ, a $5.6 billion artificial-intelligence company spun out of Google’s parent firm, Alphabet, in 2022. Aramco’s goal is to transform its carbon emissions into profitable products using AI.
This is crucial for the company, which has promised to eliminate its carbon footprint by 2050. Traditional methods of finding green solutions would take too long and cost too much.
The partnership aims to solve one of climate change’s trickiest puzzles: how to turn carbon dioxide from a costly waste product into profitable materials such as plastics or aerospace components.
For oil companies, “capturing” carbon entails trapping carbon dioxide gas that would normally escape into the air. Instead of releasing this greenhouse gas that warms the planet, companies like Aramco collect and store it.
Jack Hidary, SandboxAQ’s CEO, explains how AI could transform not just Aramco but the entire energy industry’s approach to emissions.
This interview has been edited for clarity and brevity.
What is SandboxAQ doing for Aramco, and how does Quantum AI help?
SandboxAQ is helping Aramco transform captured carbon dioxide into valuable products such as advanced materials and plastics. Think of it like giving Aramco a virtual chemistry lab where they can test thousands of new recipes in days instead of years.
Quantum AI is our secret weapon here. While traditional AI like ChatGPT can only tell you what’s already known from textbooks, our Quantum AI uses the fundamental rules of how atoms behave to predict what will happen in brand-new chemical reactions that have never been tried before.
It’s like having a crystal ball for chemistry — we can discover new materials and processes without the massive time and cost of physical experiments. For Aramco, this means finding profitable ways to turn their carbon emissions into sellable products much faster than ever possible.
Can you explain large quantitative models in everyday terms?
Think of the difference between a cookbook and a test kitchen. ChatGPT and similar AIs are like having access to every cookbook ever written — they can tell you about existing recipes. Large quantitative models are like having a test kitchen where you can experiment with ingredients that have never been combined before.
Instead of words and sentences, we work with numbers and equations that describe how the physical world works. When Aramco wants to know “what happens if we combine carbon dioxide with this catalyst at this temperature,” our models can predict the answer without anyone having to spend years in a lab finding out.
If this works for Aramco, every other energy company will race to adopt it.
Why should everyday people care about this partnership?
Three big reasons. First, this could make fighting climate change profitable instead of expensive. If oil companies can make money from their carbon waste, they’ll want to capture it instead of letting it escape into the air.
Second, the products created could improve your daily life. These could be stronger, lighter materials for cars and planes, new types of plastics that break down naturally, or better batteries for your phone.
Third, if this works for Aramco, every other energy company will race to adopt it. It could fundamentally change how quickly we transition to cleaner energy.
Could this technology work for U.S. oil companies and infrastructure?
It already is. We’re working with the U.S. Army to create stronger, lighter materials for military vehicles. We’ve tackled “forever chemicals” — those toxic substances that won’t break down naturally — by running our AI across over a million computer processors simultaneously.
U.S. infrastructure faces the same challenges as Aramco: aging equipment, pressure to reduce emissions, and the need for new energy solutions. The beauty of our system is it’s just software running in the cloud. Any company or government can use it without building special facilities.
Where else could this type of AI make a difference?
Everywhere you have a “finding a needle in a haystack” problem. Drug companies use it to find new medicines in months instead of decades. The military uses it to design better protective equipment. Banks use it to spot fraud patterns too complex for humans to see.
We’re focused on AI that discovers new materials and solves real-world physics problems.
We’re even developing navigation systems that work without GPS by sensing Earth’s magnetic field — crucial for everything from delivery drones to emergency response. The key insight is that most of the world’s biggest challenges aren’t about processing words or images; they’re about understanding how physical things interact.
How does being a Google spinoff help you compete globally?
Google gave us two things: world-class scientists and the ambition to solve seemingly impossible problems. But we’re not trying to build a better chatbot. While others race to make AI that writes better emails, we’re focused on AI that discovers new materials and solves real-world physics problems.
The real competition isn’t between tech companies. It’s between the slow, expensive traditional way of doing science and our accelerated approach. When it comes to climate change, every year we save in research could mean millions of tons less carbon in the atmosphere. That’s a race where everyone wins if we succeed.
Great Job Divsha Bhat & the Team @ Rest of World – Source link for sharing this story.
