 I've always been a little bit obsessed with understanding how the natural world around me works. My parents instill in me the importance of questioning everything. My father used to always ask me about things that he would observe in daily life. Can you figure out how this works and explain it to me? And I think like that inquisitive nature. My people I chose science, it was a way of satisfying that curiosity to discover. We find ourselves in a moment of enormous potential in our technology but also extraordinary challenges that it would be hard to overstate how deep and profound they are. On one hand we just think about the challenges that the world is facing in sustainable development goals like water, poverty, food, health care and climate. Climate change is also my upbringing. I came from a developing nation where I have seen the impacts of climate change. And we are all witnessing the impact of a global pandemic and the realization that it will probably not be the last one. We didn't have the luxury of decades to solve that. We needed to find a solution fast. In health care it takes 17 years on average between the time when scientifically we know that something can work to the time when it's available for use. We are just building knowledge so quickly it's become very difficult, almost impossible for even scientists to keep up. If we can compress the time to discovery we can find solutions to some of the most pressing challenges that we're facing today. Those are daunting, massive challenges and without accelerating the rate at which we discover solutions there is no path to be able to address these fundamental challenges. We really don't have much time to waste. IBM Research is a community of scientists, engineers and designers of all sorts of disciplines. We have mathematicians and physicists and chemists and experts in AI and quantum. And we come together to create and imagine new ways to process information and generate the next advances in computing. IBM Research has played through our history and continues to play a central role of creating new solutions and imagining new ways to bring computing to solve some of our hardest problems. And if we weren't here I think we would lose a massive vector of progress for the world. I'm Dario Gil. I am Senior Vice President at IBM and I am responsible for all of the research activities of IBM worldwide. I'm Saida Nasario. I joined IBM Research because I wanted to make quantum computing a reality. We need to pull together the power of all these new technologies that are emerging. The moment we find ourselves is the convergence of not just one technology, but three technologies that are going to alter how we practice science and how we develop technology. I like to summarize them as bits plus neurons plus qubits. The world of bits is a digital world, the computers that we all know. Now enter the world of artificial intelligence. That's the world of neural networks that have inspiration from the biological brains and they allow us to solve problems differently, to learn from data. And then enter the third element of the equation is a blend of physics and information in the world of qubits. We should say promise of quantum computing. All combined together. With that purpose and focus to discover faster. Our objective is to accelerate the rate of discovery by a factor of 10x. So we want something that would have taken 10 years to do in one year or something that cost 100 million to do it in 10 million. I think what the world hasn't grasped yet are the implications of the convergence of these technologies in the context of accelerating scientific discovery. We really have set ourselves a target of not a little bit better, but really a significant jump. We have hybrid cloud. We have quantum computing that's on the horizon. There's a lot of progress that has happened in AI. I think it's going to be important for us to figure out how we're going to make them more accessible so that scientists do what they do best, which is really focusing on tough problems. My name is Saul Menacefa and I'm a vice president at IBM Research. I lead strategy related to climate and impact science. Ultimately the vision that we have is how do we develop the tools, the framework and the hybrid cloud-based platform so that it's accessible for someone with just a computer and an idea. Let's say we have a scientist in the lab, a university fresh postdoc all she has is a computer, some simulation software and some ideas. She could use deep search to go through years of publication. She doesn't have to download all of the documents, she can just access the cloud. Instead of a few months, it could be a few hours. That's where the power of the cloud is. AI is a very important and powerful capability that allows us to harness data in new ways to achieve tasks that were previously impossible. So one of the key things that our teams at IBM are working on are AI technologies that can ingest scientific articles. And essentially the computer in some sense is reading those articles. And that trains AI models to help advance the scientific process. The role of the computer here is really to augment human capability. My name is John Smith and I'm a research scientist at IBM. A team at IBM Research used the tools of accelerated discovery to speed up the process of designing antimicrobial peptides. Antimicrobial peptides can help with challenges around antibiotics. What the team at IBM Research did is essentially train a set of AI models to create a generative model and that generative model then could be applied to propose a truly novel new designs for antimicrobial peptides that no team of scientists have ever come across before. In this case it worked. The IBM Research team got a publication in Nature this past summer, 2021. This is a really big deal and it's a big deal in two ways. On one hand it is about going faster. It's a remarkable speed up in the ability to discover something new but it's also hugely significant because the IBM team was able to create fundamentally new technology foundation that can be applied again and again and again in so many other scientific discovery contexts. If you want to model nature, if you want to understand like chemistry works and physics work, you should build machines that work like nature. And that's really a core element of the story of quantum. Quantum computing is a completely different paradigm of computation. We are accustomed to what we call classical computing, using zeroes and one to process information. Quantum computing does the processing of information and manipulates information in a completely different way. You want to design a better molecule, let's say a better lithium chemistry to build a better battery to electrify transportation. You either experiment, you try theory and computation to make calculations but with quantum because it's designed to work like nature you can actually calculate it with a totally different level of fidelity. That's its power. It brings something which is just mind-blowing to the space. It is not just faster, it's just a completely different paradigm and you need to understand how it can benefit you, the science that you do or the operations in the business that you conduct and start preparing. Because that's the revolution that's coming. You can solve problems using quantum computation that are intractable that you cannot solve even with the most powerful classical computers. Quantum is a promise of what the future can be. We have an amazing partnership that we started with the Cleveland Clinic. They are one of the best hospitals in the world and they just celebrate their centennial. And they ask themselves this actually important question to say what does the next 100 years look like? And one of the conclusions that they reach which is very common across industries is that it will be the combination of their feel, the world of discovery of life sciences and healthcare combined with the world of information, right? And with the world of computation. What gets me up in the morning every day are two things. Equally important to me, patients and research. Our mission statement in Cleveland Clinic is caring for the sick, researching for health and educating those who serve. I'm Dr. Lara J. Hi. I'm the chief research information officer for the Cleveland Clinic Health System. There are hundreds of steps that we need to go through in the context of a single research project. These months add up to years. And with this partnership, we are hoping to accelerate that from the years to the days and the weeks. If you are a patient who is dealing with heart disease, you are dealing with this disease now. If you knew that that answer was in a lab somewhere and it's not getting to you until 17 years from now, how are you going to feel? How is that acceptable? A commitment towards research is an intangible quality that is very difficult to describe. But for people who work in research, it is one of those things where you know it when you see it. And it was pretty obvious from our earlier conversations with IBM that that intangible quality is there. Science is a creative process. It's about imagination. It's about being able to navigate a discovery space or a design space that is practically infinitely vast. So it really requires a flash of insight, some imagination, some creativity. The ability to land on something that is novel, maybe surprising even, which is at the heart of what scientific discovery is about. That discovery mindset can be used in the world of business, in the world of policymaking, new areas of problems that may have absolutely nothing to do with science. But the act of creativity as an element of the scientific process is the act of imagination, the act of hypothesis generation. You pose a hypothesis and then go through different steps in order to discover a solution. And that's a very important part of the scientific method, that aspect of sharing and building on each other. And it's a loop, it's a continuous loop of doing that process. I always associate with frontiers. You look on the horizon and you're curious as to what's next. And there is a process and a method to go and look. This is not a purely scientific endeavor. It's creativity throughout. I believe that non-scientists use the process of discovery more than they might realize. Supply chain resiliency, for example, we can actually discover faster what kind of disruptions could happen in the future. Another example, policy intervention, is a very, very complex space. Governments could create a hypothesis and try it out fast and figure out what is the best policy intervention to solve some of the hardest problems. We can apply to every sector, every company, every area in the world. We are eager for partners to join us in this journey to discovery because the problems that we're facing are really tough problems. But when we have great challenges, it focuses the mind of lots and lots of people and lots of institutions. We need all the help we can get. We need the openness to experiment, to try out different solutions, different paths. It's a commitment to never be comfortable with the status quo. It's not about science for science sake. On one hand, it is about a faster pace in accelerated discovery, but it is also about scaling and translating faster to make real impact. It's always the right moment for big thinking big strides in trying to solve problems. What is different now versus before is that we have better tools to do that now. We have to bridge the gap when it comes to making science more accessible. We have tools that can help us do that more efficiently and faster, and we should take advantage of those tools. The history of computation has been amazing over the past 60 years, but it's not written yet. And we're about to start a new chapter. I look at all the progress that has happened, and I'm hopeful we are going to figure this out. And we're going to meet the challenge that we have in front of us.