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Christina Shim, Global Head of Product, Sustainability Software, IBM Corp. 
Nancy Mahon, Chief Sustainability Officer, The Estee Lauder Company 
Moderator: Lindsey Stanberry, FORTUNE 

MPW Next Gen 2023 - Sustainability At Scale

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Christina Shim, Global Head of Product, Sustainability Software, IBM Corp. 
Nancy Mahon, Chief Sustainability Officer, The Estee Lauder Company 
 

Ginni Rometty, Former Chairman and CEO, IBM; Co-chair, OneTen; Author, Good Power (Virtual)
Interviewer: Michal Lev-Ram, FORTUNE 

MPW Next Gen 2023 - Good Power: Leading Positive Change 

For this next session. We're so excited to be joined virtually by someone who has graced the top of Fortune's most powerful women list for multiple years. And former chairman and CEO of IVM Ginia Ratti, since her retirement from IBM Rometty has spent the last few years joining the boards of companies like JP Morgan Cargill and the Brookings Institution. She is also the co chairman for 1 10, an organization focused on closing the opportunity gap for Black talent. And if that's not enough, she's recently written a book entitled Good Power, Leading Positive Change in our Lives. Work and World. She'll be interviewed by Fortune's editor at large, Mihal Levron. Please join me in welcoming them to the stage. Right, Jenny. Hello, are you there, Jenny? There you are. Um It's great to see you. Um I am going to start with a little bit of a long winded question for you. So bear with me and audience, bear with me. But um I first met you nearly 10 years ago. I profiled you in Fortune and I remember walking down the hallway at I B M headquarters in with you and there's this great series of gold framed portraits of I B MS CEO S, all of your predecessors at the time. Um All male. There are quite a few because I B M has been around for more than 100 years. And now there's a portrait of you in that hallway and I know you didn't set out with your career to shatter ceilings necessarily, but you did. And so I'm just curious, what did that unveiling feel like? What did it mean to you? Uh Well, since the time, well, first I should thank you for having me. And also just to comment to the last panel which I got to listen to. I thought the women did a great job. They were both introspective and practical in their comments. So allow me to say it and that no disrespect. I'm not there in person. I've crisscrossed the country three times this week, so I just couldn't do it. I'm getting old. So uh here I am now, pursue that point. Um It was funny, I went back for the portrait veiling, you know, it takes a while and some people think that's a corny uh tradition. I was the night CEO and there's something to be said for tradition. And when I went back, joined me for it and it did connect my past in my future together. And it just reminds you in so many start ups in the room that when the business has a purpose, uh You do really feel that weight of stewardship. And so in that moment, I, I really felt this sense of both. I had gratitude to run the company, but also like uh sharing with the others that are still, that's in front of them just that, you know, never, never take for granted that responsibility. So it, it was, it was a much more meaningful moment than I had ever imagined it would be. And I love, by the way that uh when you posted this on linkedin, Mary Barra commented and Karen Lynch, so uh good, good group of folks there. Um This is a good segue to your book, Good Power. And I uh for those who are not familiar with it, I want you to just define for us what is Good Power, what does it mean to you? Well, it, it really got and at the moment how you solve them could matter as much as what you do. And to me, it is about doing tough stuff but doing it in a good way, in a positive way. So not through fear, but through instead respect. Um It is not about polarizing people, it's about celebrating pro progress and it is about loving tension and loving conflict, which, you know, if people loved it, we'd probably solve more problems versus pity against each other. So that's kind of my short definition. OK, since you brought it up, um One of the things that you've talked about for, for quite a while and you talk about in the book is that growth and comfort, don't coexist. Um, having uncomfortable conversations is hard for. I'm pretty sure everybody in the room, most people don't run towards it. So, what have you learned over the years in your positions of leadership and your time at I B M about how to embrace them, how to go ahead and have those uncomfortable conversations when they need to happen. Yeah. And it didn't even, uh, it's, it's uncomfortable conversations or it could be something you're angry about or bully a person. It could be an issue. And to me, I, I observed by watching someone one day and I saw this person who, whenever there was a problem, they always wanted to say I'll do it, I'll do it. I'll go work on it. I thought I started watching. I thought, why does she always volunteer for the problems? And I started to witness that a, the problems were never as you always think they are at the beginning. Um, b that she always came out with a stronger relationship on the other side. Almost always. I mean, there are some bad situations but nine out of 10 and it started making me say, you know what? I actually think this is a good thing. And so I, I would start to go after it because otherwise it takes so much energy from you and when you're doing anything hard, a business starting something up, you got to really conserve the negative and positive energy, you know, reduce the negative stuff. And so you a lot of positive. So I found it is a really important way to build resilience was to go. Actually, I would start to look for those conflicts, right? And, and by the way, almost the alternate title of the book Growth and Comfort. Never Coexists because you guys know I've been on that stage many times and I've said it a million times and you know, the story it comes from, but um that was almost my alternate title. But I, I really believe it's one of the biggest things to run toward conflict is a way to build resilience. OK? I wanna talk a little bit more about um sort of the, the introductory chapters of your book. And again, for those who don't know, um you really opened up about your early years, um your childhood, how your family shape you and some of the resilience that came from that. And I was so struck by the fact that you come from this long line of women who have been widowed or abandoned at a, at a pretty young age as moms as, as and became single moms, um including your, your own mother, of course, your father abandoned the family. Um, you were the oldest of the kids and really helped raise your siblings. And I want to know, I mean, I guess a couple of things. Um Why did you decide to open up about this in a much bigger way than you had before during your, your tenure at I B M? And what do you think are the biggest ways that this background, this family history shaped you as a leader? That's a great question. And because you've known me a while and I spent decades not talking about these things and to be honest, when I first, I wasn't going to write a book at all. So those of us that know me would know. I've never talked about it. And as I was retiring, people said, but you know, you've had such a unique journey. There is a lot people could learn. And at first I was like, well, I started to mold with the idea and I really wanted to write about this topic of skills, first hiring for skills, not just degrees. And I started there. And then people were like, oh, that's a little bit boring to just go right to facts. And it forced me into this very slowly. They forced me into this. The only way people learn is through stories and being vulnerable. And there's a reason you believe these things. And so to your point when I've been raised by strong women, like women, I just saw on the stage a long line, my great grandma was the last person in her family to leave. It was Belarus at the time in the World War. She would never speak English. She would clean bathrooms in the Wrigley building at night third shift and she would put every dime she made, we were just talking about money and banks into us. Savings bonds. I mean, little did we know one day those bonds would be the only reason we'd have a car. And then my grandma, as you said, twice widowed and she would hand make lampshades. And then my mom at the age of 34 my dad would abandon us. I would happen to walk into the garage and hear it. And he would say to my mother, I don't care about you. I don't care about any of you. I don't care if you work in the street and I watched him turn around and leave and that would be it. And my mom had never worked a day outside our home. She had never gone to have a job. So, what did I learn? The three biggest things? So, after all these hard first, I did learn may be outdated, but that hard work always made something better. I watched my grandma, my great grandma, my mom, fine. And then my mom went back and got a little bit of education, got an hourly job, a little bit more, a little better job. She never did get a degree, but she got enough to get us off of food stamps and off of welfare and to keep a home and that taught me aptitude and access for two different things. And it's a really important point, meaning, you know, the world kind of gods spreads all of aptitude pretty evenly, but um not so much in this world and my mom wasn't dumb. She was pretty smart, but she never had the opportunity to get those kinds of education. And then the other part which you kind of wrote about this when you, when you and I first met and you did that cover story. But I said my mom taught me not by her words, but by watching that never let someone else define who you are, you know, only you define who you are and those would be, oh, I should say alas because this is ironic. I, I felt God no matter what I do, I am going to be independent financially. I don't have to, I never want to rely on another person, another man and I just had my 43rd wedding anniversary with my husband. So, you know, I feel like I married for a different reason than my mom. Right? Great. Um So I, I, I, I wonder, you know, in, in light of everything you just said and, and again, you know, I think we both mentioned that you weren't open about a lot of this background while you were ceo um what advice do you have to the leaders in the room on how to be strong, how to be authentic but also be vulnerable at the same time because it does impact others. It it impacts in really, really profound ways. So what advice do you, what takeaways do you have? Uh I guess my biggest takeaway was um probably the greatest thing as a leader was to be authentic over time. And I, and I'll always remember a sort of a saying once said to me that the leaders job is to paint reality and give hope. That turns out it's actually of Napoleon who said it, but that, you know, painting reality is facts, giving hope is emotion. And it's in the book, kind of, one of my biggest learnings from people was to build belief in something you got to speak to someone's head and heart at the same time. And so I, if you could just always remember, and now the only way to do that is to tell stories, you know, and you have to be vulnerable. So I would learn over time to do it at work, not everything because of course, even people who knew me well and read the book and like, I didn't know all of that. And I'm like, well, I didn't dwell on all of it. But the, I think that part and, and honestly, I think I felt better even leading in that way. And that's what I mean by good power. I think if you can speak to people's heads and hearts at the same time, the followership is, is quite large. And, and that to me is probably one of the biggest signs of success in this world now is followership. And another thing you were very open about in the book is the fact that not everything at I B M while you were ceo went, you know, splendidly, right? Um And you made a couple of very, very big bets. Um And it was a time of transformation, I mean, in a lot of ways I B M is still transforming itself again and there was declining revenue, you were dealing with a lot of different shifts. Technology was, you know, is still moving more, much more rapidly than before. So talk a little bit about just what you learned about communicating to a very large workforce during such a tough time. Um especially at a company that was used to being the top dog and then was looking at, you know, quite a few quarters of declining revenue. How did you lead through that? What do you think worked? What didn't work? Yeah. Well, oh, boy, I do write, I, I write a lot about it, right, because I feel some of it is distance you get now and some of it comes with stewardship. Um And because people, my mother would often say she'd watch TV, and she'd say, oh, you know, boy, these are some tough interviews or my little nephew once said to me, he said, auntie, does that upset you when they say bad things and about I B M or you. And I said to him, Michael, it's ok. Well, first I told my mother just turn it off for now. And then I said to him, I said I'm doing what I have to do. And I think that's the difference when you're over 100 years. I knew some of what I had to do would be really hard and I was never a victim of it, just like my mom was never a victim of my dad. You know, we each get handed our challenges of a moment and, and so some of what I learned, big bets I placed, I mean, many of the entrepreneurs in the audience play big bets boy, knowing the difference between when you're scaling or making a market, they're profoundly different and what it is that you do. And certainly with a I, you know, we were making a market that didn't exist at the time. I see so many of the issues now, right? We were exactly right, which is one decade early and uh that there hadn't yet been trust built in that technology. And so I feel, you know, I'm very honest about, I say, look, get comfortable that make decisions you may not see the benefit of. And so things that we did, right? Like Red Hat, which has now been the foundation for I B MS really return to growth. Um They just may take time, but probably the biggest lesson I write about. And I think it's relevant for anyone in the audience. I know this is the next gen group is this idea of when you're under so much pressure to become something, it's to also know what should change, but what should not change. And you know, what part of you has to endure. Even if it's modernized, I would get in trouble when I would get away from that because the pressure is so intense on you to succeed or become something else. And when I would go too far from what we were at our essence. So my, my, one of my big learnings is, you know, really know what you are in service of, be in service of something and have it really firm in your head and then be willing to change everything else. But then not that no one has to endure. And the other big learning for people in the room is you grow in your size. Is that like I said, there's one thing about what you make, but then it's how work gets done. And I would underestimate for the first few years. The how part at a huge scale. Meaning I said, I would tell people, come on, I look, I saw it happening and I knew we weren't prepared and I'm like faster, faster, faster. And I would look in their eyes and I could see they work. They were just getting tireder and things weren't faster, you know, and I would be like, ok, people don't wake up going. God, let's be slow today. I mean, they don't. And I said, OK, that is, you know, leadership's job to change how work is done. Meaning some of basic, you know, layers, levels, decisions, etcetera. But the other part are like tools and methods and processes and back then people didn't do agile with a half a million people or, or design thinking and we would have to go do all that and start to pay people for skills, not for just, you know, what work they did. So I, I say it's really underrated to think about how work gets done in your company versus just what it is you're making well and speaking of some public criticism or, or probing questions, uh the, the headline for the cover story I wrote about you back then was, can IBM be cool again? And I know in the book, you said that made you cringe. So I apologize for that. But, but um but I wonder like to, to your point. Um is that even the right? Is that even a question that needs to be asked? Because if you're looking at the, the DNA of the company and what makes this, the, what has made the company strong in the past? Is that something that you needed to worry about that when I say cringe because part of the book is all about. Um And this came up in the last session about living in a gray area and that, you know, the book is all about tensions, right? Because I think that is the world we live in. There are no clear, good and bad answers to almost anything of importance. It's always, you know, you could be serving one and then you hurt the other. I mean, it didn't matter what decision I made. There was always multiple stakeholders, always a good and a bad reason for everything. Attention. And so to your question, it gets to that point when I say cringe the cooler, I would try to make us the worst. That was because actually knowing in your heart, you know, this is one of my big learnings. I, I, I tell the story in the book because, you know, Arnie who Marriott and Arnie has passed out, but he was a good friend of mine and we were getting into marketing software and marketing on the cloud. And I can remember calling Arnie saying a um you know, I'm very, you can, I'm a very aggressive competitor and I knew him well, we'd grown up together and I'm like, I don't understand why we're not winning this. And he's like, Jenny, why do you even care about that? He's like, you know, I rely on you for property management, you know, reservation systems like that. Why do you care? And, and I always remember it because I said to myself about to be cool. Right. I'm like, you're right. That, that what we are is mission critical. I realize that's not always what a consumer sees and we live in this consumer world. And so some of the many companies in here, very consumer, but there are others that are not in kind of that knowing what you are. And like I say, even if to be modern, modernized, that to me was a really big, big, big learning to me. So in some ways, that question was a really good question. Yeah, see now that I'm older and more wiser, I could say that not, I can say this is a, this was a very insightful question because you know, you, you want to be respected but cool is not, you know, and you want people to want to work for you and believe in your purpose, right? But you don't necessarily need to become something you're not. Well, it made for a very cool cover and Jenny, it's always a pleasure talking to you. So thank you so much for being here with us even virtually and, and sharing your insights. Thank you. Hope it was helpful. Wish I could do this.

Dario Gil, Director of Research, IBM 
Interviewer: Brian O’Keefe, FORTUNE


Brainstorm Tech 2022: When Does Quantum Become Real, And How?

When Does Quantum Become Real, And How?


Brainstorm Tech 2022: When Does Quantum Become Real, And How?


All right. I want to start with a quick show of hands how many people in this room think you can explain quantum computing. Nobody's raising their hands. How many people here have at least heard of a cubit? Alright, alright. That's pretty good progress. Yeah. Not the video game, the computing thing. Um So uh sorry, this is a pretty savvy group but they're still brave enough to admit they don't really understand quantum computing. So let's turn to you the expert first. Let's start with uh Maybe you could just give us a quick refresher course on what quantum computing is, what it means, how it works. You know how it's different from classical computing. Just like give us like that quick overview so we can dive into sort of the details. Well, the first thing to understand is that quantum computing is the first time that the category of computing and I mean computing with a capital C. Has branched. So that's not an everyday occurrence that that happens. And we moving forward, you already refer to the term that we will adjudicate to all the computers that we built to date, which will be called classical computers. And then there's this new branch called quantum computers. And it's you know, nothing less than a re foundation of the world of information technology. If you look at how we have built the modern information technology edifice, it actually began back to uh you know, fundamental idea that was put forward by live in. It's the great philosopher and mathematician co inventor of calculus with Newton. That envision envision it was, you know, creature of the renaissance. This idea of creating perfect logic. And he understood that you could encode almost all information in a in binary digit And the idea was you could reason over it and you could create this perfect reasoning machines. He didn't know how to build them. So it took until the 1940s with Claude Shannon and then on touring and others to start building and creating those ideas. And we introduced the term the binary digit, the bit, the zero and one. And in that abstraction we understood that the zeros and ones could be separated from their physical manifestation meaning hey, you could build a computer with vacuum tubes or you could build it with semiconductors and with transistors. And we've made, you know, the story of moore's law has been the story of making those bids more more efficient and cheaper and so on. At this separation between the zeros and ones and their physical manifestation bothered a number of physicists. And they started probing into this question. And it turns out long story short is that there is a relationship between physics and information and there's a set of properties from quantum physics and from physics in general uh called superposition entanglement and interference that get mixed with this idea of information such that we can represent it much more richly meaning instead of just having two states and build machines that process those two states. Now the information is more rich. The representation is more diverse and quantum computers are nothing less than the ability to create these new expanded representation of information to create these quantum bits that have an exponential number of states present in them. If you build the machines properly and to manipulate that information in such a way that you can perform computations that you simply couldn't do classically or to do them much more efficiently. So new generation of machines that have re founded the very idea of information. It doesn't even preserve the idea of the zero Under 1. Okay, so let's get quickly now into the central question of our discussion, which is when does it become real? And let's start with just is it real now? I mean like you know, I I've seen you know stories about mixed results in the comparison of quantum computing results versus classical computing in terms of where we aren't now with quantum computing but we have obviously IBM but google and Microsoft and amazon and a lot of inter backed startups investing a lot of money in this field. There seems to be a lot of their there. But what can we look at right now to see that uh that quantum is actually starting to go from theory to you know, brilliant theory to real world manifestation and and what are sort of some of the signposts that we're seeing that mark that progress. Well, first of all quantum computers are real and they exist right now. Just to give you some some grounding at IBM we have over 20 computers to 20 quantum computers right now on IBM cloud at clients and uh and the community can use every day all over the world again to give you a measure. 3.5 billion quantum circuits are run every day on IBM quantum computers. Since we put the first quantum computer on the cloud, it was May 2016 over one trillion quantum circuits have been run on actual quantum computers. We have gone from the first generation that we put out had just five cubits. We went from 5 to 27 last year we broke the 100 cubit barrier. We have now a system that has 127. This year we will deliver a system with 433 cubits. Next year there'll be one in 2023 with over 1000 and by 2025 or plan is to build a machine with over 4000 cubits. So first of all the reel machines, you can program them, you can run things on it. Over 1000 scientific publications have been run on IBM quantum computers as an example. So it's a real technology that is present. I would say the experimental aspect of building real devices and real quantum computers has been the food of the last 20 years But really has been the last decade and specifically the last 5-6 years will be seeing this very, very sophisticated advancement now at the same time no one has yet built quantum computers that for a practical application can outperform what you can do with a classical computer. That threshold, what we call quantum advantage is something that you know we're all hard at work on the field and that is expected. That certainly is going to happen this decade. But it's likely that some first demonstrations can happen as early as the next few years. So that's the big next milestone in the in the field. But there's now hundreds of thousands of people who are writing programs on quantum computers. Quantum computing is being taught in universities the world over and there's a very rich and energetic environment of venture capital as well and major companies. So I mean when you are you're talking about your roadmap for building these devices with more and more cubits Like I don't really understand what that means. Other than its more cubits. More cubits sounds better, sounds more powerful. But when you go from 127 Cubits processing power to 4000 express like how that makes a difference or you know does it just is it gonna be like a moore's law of cubits where we always need more and more cubits on you know or is there like a sort of threshold you need to meet to kind of do the things you need to do to get that quantum advantage. Yeah good question because there is an exponential underneath it. So the number, remember I told you that the number of states that you'll get to represent, you get to represent information more richly than with just zeros and ones. So to be precise the number of states you get to represent is two to the end where n is the number of Cubans. So that's an exponential right there and just a good number of states. So just translate that. So like if you're if you're analyzing a problem instead of two things at once, you can analyze infinite number based on how many cubits you have to process that. This scenario. That's right. So basically how an algorithm works in a quantum computer and it's gonna sound a little bit abstract for a second but just bear with me for a minute. So imagine for um for a second that you have a fear right in So picture of fear and in classical world you can put a zero in the north pole of your sphere or a one in the south pole of that fear. Now in quantum world the first thing you use is you put the computer in a superposition of states and what that means is that imagine that if you put it in the equator now you would have a linear superposition of zero and one. But the reality is you can put them anywhere in your sphere. So you have all these potential combinations of representing information. So imagine that you have in that fear is populated with like a huge number of those dots in the surface of this sphere, each one of those is represented by an amplitude and a face like those little dots on that sphere like moons that can rotate. So what the next thing you do in an algorithm is you put data into the computer in practice. What it means is that you take those little moons that are in that here and you rotate it slightly different. Now your machine has all the possible states that they can represent based on the number of cubits data is encoded in the state of that machine. And now the magical act of quantum computers is that you get to actually interfere information like waves in the ocean. So the right answer is maximized. And other things you don't care about cancels out notice is so different than what we learn about having zeros and ones and transistors or switches. And you use boolean algebra to be able to do calculation. Okay, I want to stick with that for a second. I do want to remind you if you have a question, raise your hand will get you a paddle. And uh So we'll get some questions in a second. But like all right. So you just described beautifully the wave the crescendo of the wave of all the possible solutions. But like can you translate that to you said people are running these every day in large numbers. What's an example of one challenge that you solve with the quantum and how you'd reach the solution differently than if you were running a super powerful regular computer. Yeah, just Okay, so, good question. So, so they're working there was the original idea around the possibilities of why build a quantum computer, Why why do this? Was to actually model nature better? So nature? Uh, the environment around us obeys the laws of quantum mechanics. So if you actually want to understand the properties and how you know, physics operates and materials and chemistry, let's say you want to build a better battery technology uh, for electrification or let's say you want a better fertilizer for agriculture or a better catalyst for industrial process or a better alloy. Right. If you're an aerospace, that's a process of trial and error in materials development And with the advent of computers, we had the opportunity to calculate things. However, the calculations that you perform with traditional computers, the characteristic that they have is that there's an exponential number in their meaning, as you try to say, model two molecules to build a better lithium chemistry as you start looking at the interactions, the electron orbital's of the atoms are present in there. The number of calculations that you have to solve classically grows exponentially. So the reality is that even with the best supercomputers, the best we can do is to approximate an answer in quantum you don't have that problem. So the idea is to build machines that behave quantum mechanically to be able to model these problems. So for all the industrial sectors that rely on advances in materials in chemistry and physics around that this will have a huge impact. Now, interestingly enough, what happened is that clever people discover other problems that had nothing to do with modeling nature. And that also delivered you an exponential advantage compared to classically. And the most famous example of that has to do with factoring. And the reason that that matters a great deal is because that the fact that it is hard to factor numbers in classical computers is the basis of most if not all encryption that we rely to secure the modern digital economy. So now we have these two vectors of everything that has to do about modeling our world, the natural world and now this ram of like mathematics that also is going to have big implications for industry and for society. Okay, I'm seeing hands which is good. We're gonna we're gonna see what questions people have will go right here first. Could you just stand just give us your name and company franklin. Hey daria, how are you with Marsh a quick question. So I think you just answered it though. So classic computing. Quantum computing you're not saying that quantum computing will replace all classics. I thought certain datasets lend themselves more to quantum computing solutions than classic computing. But can you confirm that or? Absolutely right. So quantum computers will not replace all classical computers by any stretch of the imagination. The future is classical and quantum working in concert. In fact to run a quantum computer, you need classical computers uh to be able to do that. And it is indeed the case that for example, for lots and lots of applications running your spreadsheet or you know your word document or playing a video or so on, you're not gonna need quantum computers. There will be a subset of problems that but but the interesting thing about quantum is not that they're slightly better than a classical version. There are classes of problems that we will never be able to solve. Exactly. Never with classical computers. That's what's so exciting is because the only technology that alters the equation between what's possible and impossible to solve, but it's all about the combination. In fact I have this little sort of pseudo equation that I like to share with people that the future of computing is bits plus neurons plus cubits. And what I mean by that it's a form of high precision calculations that we do with a lot of our machines. The neural networks are the basis of artificial intelligence and the sort of cubic technology based on quantum. And I say that to emphasize the pluses each vector is fascinating. But I think what the world has been yet fully grasped is the implications of the convergence of these technologies. So the future of workloads will be you to take your problem and behind the scenes we will partition the problem to figure. What do you run with high precision calculations? What do you run with neural networks and what do you run with quantum machines and then bring it back sort of in a transparent fashion to the user? We have a question over here. Hey, my name is jake, I'm with Bushel from Fargo North Dakota. Thanks for having us here so on. Would you say on the Ai side, would you argue that quantum computing capabilities have changed the assumption around ai, could you argue that today that not just neural networks but the next level of because we know that neural networks are interesting but they're still solving for approximation sort of outcomes. Would you say this is likely the path or has this created a much more likely outcome where we'll have true human AI capabilities in quantum computing. Would would that be an argument? Well, what what I would say is that for many decades we were in um sort of intellectual and computational straitjacket, which was you know, very precise forms of like microprocessor architecture is a particular way that there was a uniformity in computing with ai over the last decade has demonstrated, is that specialized forms of computing can deliver tremendous value for very specific kind of mathematics. So in implementing neural networks and they multiply accumulate function that is inherent in there. You can have Gpu s as an example, there are much more efficient compared to a traditional CPU, there's a lot of excitement and it's a new field but it's a research field around the possibilities about this intersection between quantum and machine learning. So it's a new area, right? It's a new scientific discipline and so on. And it will require not just to cast the same problem as we've done with Gpu. S with machine learning, but to reformulate the possibilities of how do you do neural networks and how do you do training using quantum machines? So one of the most important things about to be successful in the quantum world is not to be in the mode of I run something today. This is my software today. My algorithms today. I just want the quantum machine to run it faster. That's actually a recipe for going down the wrong track. It's about giving this new way to represent information. What should I think of differently? How should I explore new possibilities of performing computation calculations in novel ways? So it requires a lot more creativity to be able to do that. But the application of quantum machine learning is one of the most exciting areas in terms of a research endeavor. I think we have one more question here in the back. Sure, My name is Blair Lacorte. I'm from a company called Ai it's actually a E Y E. But ai every time you know we build really sophisticated sensor networks. Used to be targeting systems and I. S. R. Systems now our cars need to virtualize the environment. It actually occurred to me maybe this is a bad assumption but we model things all the time whether we get you know, RGB um you know vector analysis and orthogonal data because we have to model the world almost like creating virtual reality for a car to see. But wouldn't this kind of technology be better for modeling the metaverse? I mean for modeling environments that are very sophisticated that you want to replicate quantum physics in? Okay. Sexier, if you attach metaverse to it. Yeah. I try not to have like a bingo of tech books you know. But um well you said something different so I I don't know about like the generic metaverse story but like if you were trying to model environments that behave you know quantum mechanically or behave like you know, according to the laws of physics in a way that you needed to have that level of fidelity you could imagine down that stack of doing that modeling of a combination of classical plus quantum where there will be an element of quantum computing coming uh to um you know to to help with that. So in some ways it's gonna be a little bit behind the scenes, the way, sort of like we are going to do the algorithmic primitive calculations and so on, but that doesn't mean it's gonna be, it's not going to be incredibly important. Um And what I mean by that is behind the software of the future, I'm absolutely convinced we will always have behind the scenes this element of ai behind the scenes, this element of sort of very deterministic high precision calculations. And there will be quantum algorithms behind the scenes as well. And and I think that that's that's the world that we're trying to create. But you know, I sort of close with the thought of this is actually the most exciting time in computing in many decades. There's nothing equivalent to what is happening right now than the equivalent of what happened in the 1940s and 1950s. With the advent of those like beautiful computers that you would see in bloodshed park and places like that, where people were imagine the possibilities around this. And I think it's a moment that calls for a lot of like creativity and enthusiasm around imagining possibilities. And it's the reason why there's so many institutions right now embarking on this journey, even if you tell them, hey, I cannot solve a problem better right now, but they understand that this is gonna be possible this decade and that's why the field is advancing so rapidly Dario thanks for sharing your enthusiasm for expanding our minds And hopefully now everybody can raise their hand and say they understand quantum computing. Thank you. Thank you, thank you.

LaFawn Davis, Group Vice President, Environmental, Social and Governance, Indeed 
Francine Katsoudas, Executive Vice President, Chief People, Policy and Purpose Officer, Cisco
Nickle LaMoreaux, Senior Vice President and Chief Human Resources Officer, IBM 
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Most Powerful Women 2021 - The Great Hybrid Experiment 

LaFawn Davis, Indeed 
Francine Katsoudas, Cisco
Nickle LaMoreaux, IBM 
Colleen McCreary, Credit Karma

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2019	$79,591	$8,728
2017	$79,919	$11,872
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2015	$94,128	-

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