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We need to use AI, quantum and supercomputers to supercharge material discovery

Technological advances will help us tackle some of the world's biggest problems, but only if society prioritizes scientific research, argues Darío Gil, the director of IBM Research.

Inside the IBM Cloud in Dallas, Texas

New forms of computing will help supercharge the discovery of materials, some of which we haven't been imagined yet.

Image: Connie Zhou for IBM

Science underpins progress, helping us deal with myriad challenges, many of them existential. From pandemics to climate change, poverty to pollution, food security to surging energy demands, problems keep piling up. The world needs science more than ever; the cost of procrastination is dangerously high.

To address global challenges, one of the things we need to do is accelerate the pace of discovery of new materials, which are critical to the global economy and all facets of life. It's new materials that are helping researchers develop better antivirals and more efficient batteries. It's new materials that enable us to design less toxic photoresists – tiny but essential components of our electronics– and find more sustainable ways to grow crops. New materials will help us save the world.

But how do we accelerate the material discovery process?

Advancements in high-performance computers, artificial intelligence and quantum computing will help us tackle this problem in a fundamentally new way — but society will have to grasp the urgency with which science must be applied if we're to realize the full benefit of these new technologies.

From serendipity to precision

For centuries, material discovery has been largely serendipitous. This is how we came about plastic, Teflon, Velcro, Vaseline and vulcanized rubber. Even graphene, an atom-thick layer of carbon and the thinnest and strongest material known, was discovered by chance – when physicist Kostya Novoselov found discarded Scotch tape in his lab's waste basket. Besides happy accidents, material design has also hugely depended on deep expertise and specialized knowledge of researchers, creating information bottlenecks and limiting innovation.

The typical discovery process is linear; it's also long, tedious and costly. It usually starts with a query: "What if we were to create a new type of plastic that would recycle itself by disintegrating into its original parts?" Scientists then develop a hypothesis about different ways to achieve the desired outcome and conduct time-consuming tests to validate or discard the result. If they discard it, the process starts all over again and may take years.

Enter HPC, AI and quantum. Working together, these three technologies are bound to usher in the era of accelerated discovery.

High-performance computers have been fueling progress for decades and are getting ever more powerful. Working alongside AI, they are simulating molecules for new materials and automating technological processes every day.

As for AI itself, its deep neural networks are great at recognizing patterns on the fly and generating models outlining a new material's desired properties. Overall, AI reduces bottlenecks, turning the material discovery process into a closed loop that will run increasingly autonomously. First, we pose a question and form a hypothesis. Next, AI designs a model with the desired properties of a material and HPC performs simulations to choose the best chemical structure. Researchers then test the result to validate or refute it. And critically, the result may spark a new question – continuing the loop and generating more knowledge.

Finally, quantum computers promise to revolutionize computation, simulating ultra-complex molecular systems and dealing with problems a classical computer could never solve. Today, quantum computers are just entering the phase of commercialization through the cloud, but they could reach the so-called quantum advantage — outperforming any classical computer in certain use cases — within this decade.

When that happens, the world will no longer be the same. Together, HPC, AI and quantum should be able to process the vast amount of data and knowledge to boost all aspects of material design. Complementing each other, they should allow us to reduce the environmental impact of fertilizers to feed our surging population, come up with more sustainable electronics and accelerate drug design. They should pave the way to truly personalized medicine and better robotic prosthetics, more efficient bio-printing of organs and much more rapidly developed vaccines. AI is already helping classical computers to speed up medical imaging and data analysis. Quantum computers could, in the future, assist AI algorithms to find new patterns, further advancing imaging and pathology.

Side with science

But that will all only happen when the entire world decides to stand with science — you, me, academia, businesses and governments.

Why? Because to fully develop our next generation computing ecosystem that will propel the pace of material discovery, we need a movement that rekindles our commitment to science and to progress. We need to implement scientific thinking at all scales in corporate and academic innovation, and — crucially — in policymaking, so that a desire for progress is ingrained in everything we do. Today, we often make sporadic decisions based on intuition, on a hunch, on our upbringing and cultural and societal values — and not on science. Just recall how nations reacted when the first wave of COVID-19 washed over the world. Many policymakers had no idea whether to impose lockdowns or not, and if so, for how long. They were like rabbits caught in the headlights, yet science was there to guide them along the way.

But it's not that easy if there are no or few scientific experts in positions of power, including in governments. There should be many, many more. A significant step would be to propel many more top researchers in different fields into the halls of power, so that they can take important steps underpinned by science to help heal the world. Getting more scientists into positions of power around the world should help create a societal shift, and hopefully trigger more public and private funding of research and development. It should also lead to more and better national and international collaborations, including partnerships between industry and academia, bringing together the best scientific talent, because science knows no borders.

Along with many other benefits, this would lead to new scientific approaches that yield new materials. New life-saving drugs. Safer aircraft and cars. A more sustainable future. A healthier and more prosperous us.

We need to act with urgency — because if we don't act now, it may be too late.

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Image: Roblox

On this episode of the Source Code podcast: First, a few takeaways from another blockbuster quarter in the tech industry. Then, Janko Roettgers joins the show to discuss Big Tech's obsession with the metaverse and the platform war that seems inevitable. Finally, Ben Pimentel talks about Robinhood's IPO, and the company's crazy route to the public markets.

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