Legends Live @Citi with Ruth Porat, President and Chief Investment Officer of Alphabet and Google

It's wonderful to be with you, Leon as always and thank you for that overly generous introduction.

It was very much like your family history. My grandfather was taken on Kristallnacht and at that point, my father realized he had to get out or he too wouldn't survive. He was in that tiny age group that was able to escape on a youth boat to Palestine. And as soon as he was of age, he enlisted in the British Army. Now, his high school had been closed down by the Nazis, so he never finished high school. He's fighting in the two battles of El Alamein and he said, if I'm ever going to get to a place of safety, I need a skill that somebody will value. He started to teach himself engineering and physics while fighting. As I think he told you, his fellow soldiers would tease him and say, you're never going to live to see the day when you can use that. He said, if I'm going to die, I'd rather die an educated man. After the war, he went to Palestine and eventually was able to get to the University of Manchester where without college or high school, he entered a master's program, ended up with a master's and a PhD in engineering and physics and still was unclear what the timeline was going to be to become a citizen. He said, I have to be a citizen of a country. He asked his professor, how do I do that? How do I get to America? Eventually, that got us to the United States. He ended up at Harvard and then at Stanford, where he designed the Atom Smasher. What he always said to us is education is a passport to freedom. And the most important thing in life is always to keep learning and to take risks with that knowledge. That's the base that opens every door. For me, that was the message that was enduring. That was the most important point always in life.

So what I find is I keep going back to the lessons from the financial crisis, and when I got to Google, I was asked about those lessons, which struck me as odd because Google had only seen really positive days and yet as I reflected on them, I realized those lessons, to your point, are relevant in good times and in bad. In every crisis, I felt that during COVID as an example, I pulled on the same ones. The key lessons, there are a couple of them that I would say guide me in every decision. First was know your greatest source of vulnerability and protect against it early. For those who lived through the financial crisis, it was clear it was liquidity in that August, September time period, you couldn't get liquidity at all, and yet six months earlier you could have. This notion of protect early is about fortifying yourself for the long haul. I think for us now, it's clearly innovation. It has been all along, we can come back to that. Yeah. The second one and it really hit me during AIG was the AIG collapse was not about the core AIG business, it was the risk in a derivative sub in the UK. The problem was they didn't have visibility about their counterparty exposure, about the risk they were taking on. The metaphor is you will not drive a car with mud on the windshield, you cannot run a bank with mud on the windshield, cannot run a company, you cannot run a country with mud on the windshield data and analytics clear that away, and then you can go faster and harder. All those investment in risk systems and transparency critical for speed and risk taking. Then the third really important one was actually something that Secretary Paulson. During the crisis. He said, you have to have the will and the means. Too often, by the time you have the, the political will to make a tough decision, you no longer have the financial means to do it, which is just, I think one of the best ways to capture the notion act fast because in a crisis, you're never going to have a good option. It's about the least worst option. I think that's again, true for each of us in good times and bad because it sets you dissipating resources in the wrong way at the wrong time and you can fortify for the long term. But you're also not aiming for perfection. In other words, which is one of the lessons I've taken away in this, which is, you know, if we're 70-80% correct, then we've actually done well and we'll fix the other 20, 30%, you know, once we know it.

Absolutely, and it's about a continuous learning again because understanding where you are setting metrics and then looking at how are you doing relative to that so that it can be continuous improvement is key.

Well, part of it was it wasn't a completely new world. As you said, I grew up in Silicon Valley. I went to Stanford. Stanford and Google campuses are almost like one continuous movement. I had run tech banking at Morgan Stanley, worked on the Google IPO, so knew a lot of the senior leadership and the board members. It wasn't completely foreign to me. That being said, your question is a really important one, which is, I was not coming in as a technologist. I think it's really important to realize that we each add value in our own way and it's important to understand how to work within a culture to deliver it so that you don't have organ rejection. Two examples. One thing I did often is I went back to some of the comments from the founders and quoted them. Sergey, the number of times I quoted Sergey who had said many years prior to my arrival, we have let 100 flowers bloom. It is now time to pull them together into a bouquet. And so what I was saying is the founder has this wisdom that we need to actually make choices, prioritize. Let me give you the language as to how you do capital allocation, how we deliver on what the founder wanted. When you're in an engineering culture, you're in an incredibly inquisitive culture. Again, if you're giving people the tools to understand why you're making the decisions, you build the followership. Another example was early on, I came in and I thought this is going to sound in the weeds, but there's a point to it. There was no centralized procurement. I'm like, Well, given the scale of what we do, that doesn't make sense. That's an easy win. But instead of just implementing it, I went to employee number eight, a fellow by the name of Urs Hölzle who built all of the technical infrastructure at Google, the data center, networking, everything. I said, here's where I want to go. Help me understand why this isn't obvious. And his answer was, well, if you can make it clear that it's about velocity and quality, we're all there. But if it's about cost cutting, that doesn't make sense because we'll think about upside downside risk and clearly it is velocity, quality and risk mitigation. Again, understanding culture is really key. Going back to something my dad said. At the Stanford Linear Accelerator Center, they discovered or one of the early discovers of the quark. And he said that if someone in his lab could not define a quark in less than 30 seconds, they didn't know what they were talking about. I use the quark test a lot, actually at Morgan Stanley alphabet on myself. If I can't explain something in 30 seconds in a compelling way, oftentimes with data, sometimes just succinctly, I don't know what I'm talking about, and people should question it.

Totally agree and avoid jargon. And jargon because it just looks so sloppy.

Exactly. I still to this day feel privileged to be part of an organization with this long history. If you lose sight of that and you think you're coming in with something up and over the top, you're missing the ethos of the place. A company that changed the world, which is profound.

So there are two other things in the IPO prospectus that I would anchor bank back to. One is the mission. Yeah, I had that. Organize the world's information, make it universally accessible and useful is such a guiding principle for all of us. What that means, the ability to go back to my story about my dad to open information to everyone, access to information, knowledge, markets. What that does, if you have this ethos, which is education is a passport for life. That's basically what our mission is in many respects. Much of what guides the work is how can you actually deliver globally? In a way that opens doors for billions. Now we're looking at, I know how passionate you are about the application of AI to health. Well, there's an entire new set of data and content that can unlock solutions that are profound and really exciting for all of us. The other is that we're not a conventional company and we never will be. So, take those three things from the IPO prospectus and really important. I think the core one keeps coming back to what can we do that's better and different and transformative. I look at what, as an example, Demis Hassabis, who leads Google Deep Mind, has talked about. When he embarked on this journey, that ended up winning the Nobel Prize. The Nobel Prize was for predicting the protein structure for all proteins known to humanity. Prior to him embarking on this, it took a couple of years just to predict one protein structure. We're talking about hundreds of millions of scientists years to predict all of them. At the time, scientists around him said, how could this even be possible? His answer was, why not? I keep quoting why not in everything that we do. It's like, why not think about better delivery of healthcare. Why not discover cures for diseases? Why not improve education everywhere? This is part of the ethos part of it, the mission and the ethos. To the other part of your question on all the regulatory work, I think what's really important is to tell our team, we have great lawyers who are working on policy and regulatory litigation related issues. The only thing you should focus on is continuing to improve the products, the experiences, the solutions. There again, I go back to something that Sergey said around the financial crisis. During the financial crisis in the founders letter, he wrote something along the lines of, there are dark clouds all around us. They will pass at some point. The most important thing for all of us to focus on is the products and solutions that our children and grandchildren will experience for decades to come. Those will be enduring. I think that notion of what's transient and what's enduring and innovation is enduring and innovation begets innovation is the way we keep everyone focused on the main event.

It's absolutely critical. Otherwise everyone gets dragged down. Frankly, unqualified people end up worrying about things that they shouldn't be involved in.

First of all, I think we are all extremely privileged to live in this time in history. People describe AI as a general purpose technology like the printing press, like the steam engine. That does not come along very often. To be at this time in history where we're at the front end of something so transformative is truly invigorating, exciting, and we need to get on the program with each of us. Um, we look at really four upside opportunities with AI. The first is economic upside, 4 trillion theoretical GDP upside in the US alone by 2030, 20 trillion globally. But that only happens if there's adoption and what economists call diffusion across industries, across companies. It's really about the application of it, and so that's one really exciting area. The next is all around cybersecurity and just making sure that we're ahead of the curve individually as organizations fortifying the bad guys are. This gives you the ability to see in ways that you haven't otherwise seen connect dots across every part of the globe. Then we get to an area I know you're super passionate about, which is the opportunity to advance science. I already talked about what Demis Hassabis and John Jumper, they jointly won the Nobel Prize, what they did with AlphaFold. But this is extraordinary, the opportunity to contribute the biggest breakthrough in drug discovery in our lifetime to think about What can we do to advance cures for diseases is truly exciting. Demis believes that we will have an AI benefiting drug and the FDA in the very near future. This is transformative. The ability to detect disease, metastatic cancer earlier than you otherwise would. That as one oncologist has said, anyone anywhere around the US or around the globe gets the same quality early detection as the best doctors here at Memorial Sloan Kettering or any of the other amazing hospitals in New York City is extraordinary because the difference between early detection and can be the difference between life and death. These to me are really exciting areas that we're spending time on or quantum computing. You know, being at the front end of quantum computing, to be able to imagine, again, for everything from life science to manufacturing, what that can be. Then finally, it's the delivery of better education outcomes, better health care outcomes. So all of those fall into where are we looking those four areas.

Well, one of the incredible privileges in this role is actually spending time around the globe with heads of state who want to see us or others, hopefully us, investing in their country. The way I look at it is I say what we want to do is unlock the products and services for your country, which requires investing in data centers and technical infrastructure and it also requires training your people, training people so they're ready for this new era of AI and what's the educational foundation that's needed. To your point, the stories are stunning. As in a in one country in Southeast Asia and what the prime minister said is, I want to ensure that we lift up the bottom economic strata of our country. That's about helping farmers, which, of course, with AI, we can do. In other areas, the question in Africa, I was with Minister of Transformation who said, if the average age on the continent is 19, by definition, half of our population under 19, how can we possibly provide the number of teachers we need to educate the number of students and what happens when you don't give people hope, you don't provide them with the education they need. Went on to say, in many countries, there are multiple languages. Historically, as an example in Togo, three languages, if you wanted to learn math, you first had to learn French. Now with Google Translate, you actually can just have everything translated and so this on ramp to learning math is so much easier. Those are the stories. When you say what motivates our engineers, it's the ability to address all of these issues. We're doing some work with an organization out of Kenya, Jacaranda Health. Which this is through google.org, which is looking to address maternal health. There's still women dying in childbirth for reasons that are so easy to intervene to fix. Or one more, I get excited about all of these. I talked about early detection of disease. When you have diabetes, you're at risk of blindness. It's called diabetic retinopathy. Again, working with partners in particular in the global South, what we're finding is that we can provide them with an AI based scan and we have now done 600,000 scans, taking it to 6 million. It's huge.

Well, the keyword is evolving. Google searches always evolved. When you think about it, it started with ten blue links. When I got to Google back in 2015, there was a big question as to whether Google could move from desktop to mobile. And that obviously worked out all right. What we find is that the easier you make it, the more responsive you make it, you're actually more helpful to users and queries grow, expand in ways that we've not seen. The number of queries every day that's new for us with trillions of queries is pretty profound. Moving from desktop to then mobile, next thing is how about multimodal? How many people for the first time, what they're doing is they're searching by taking a photo on their camera on their phone. I'm really doing well with English today. Just do Google Translate will be much better and search that way. What's stunning is we're just continuing to evolve. Right now with AI overviews, which hopefully everybody sees, billion and a half people on the planet are already using AI overviews and what we're seeing is the depth of the queries is changing in particular for younger demographics, we're seeing to engage. Changing all of us. I mean, I'm using it in ways that I wouldn't have done it. It's allowing me to do some fun research and some important research, as opposed to asking someone a question, I can do it myself.

Yeah, I think it will be profound for Citi and also the way you interact with your customers. I'm going to leave you with one really important for me, another visual I keep going to, which is about Google Translate, and then I'll get to your question specifically because it goes to the importance, very much to your point of just get the puck on the ice and move and you will keep evolving as you do. I mentioned Google Translate. We now translate in 250 languages. We've been on this journey for 20 years. In the last ballpark nine months, we added 110 of those 250 languages. Think of it this way. You motor along and then you hit an inflection point. What's really important about that inflection point and very much to your question, you cannot be at the back end of an inflection point and think you're ever going to be ahead of your peers. You have to be at the front end. That's the pace every one of the curves we're looking at when we have product introduction are curves that we've not seen before. And so going to your point on Citi, what's been wonderful working with Jane and your full team is that ethos, which is we want to be at the front end, with the AI accelerator, we want to make sure that we're thinking about customer engagement, onboarding, what we can do internally with operations, and that ethos is absolutely critical because this is early. The notion of the feedback loop, and I know here that's been an important part which we've loved so that you can continually improve it and tailor it to what's needed for Citi for your specific needs has been really key. I think for all of you as a former investment banker who engage with customers, every company needs to be thinking through their strategy for AI implementation and AI is part of their business. Thomas Kurian, who Leon mentioned he's the CEO of Google Cloud. He at one point said to me, if companies try and let 1,000 flowers bloom, they're going to end up with 1,000 dead flowers. The important thing, whether it's in Citi or the way you engage with your customers, your partners, is how do you do triage on the most important elements? There are so many examples, one of my favorite is applying AI customer service support because initially, that was a cost saving mechanism. It was also a pain point. It was a pain point that became a cost saving an opportunity that increased customer satisfaction scores and saved money. But then what everyone is finding is, wait a minute, now that I'm capturing this information, why am I getting so many calls? What is helping do, depending on industry is helping you with product assortment, it's helping with R&D guidance. It's also helping legal departments say, Wait a minute, why am I getting so problems with this, what about my warranty costs or some of my obligations? The repository of data, your data that you can then mine in ways that improve revenue, improve customer growth is pretty extensive.

Well, and to your point, it also goes to a key element of AI. It goes to search, it goes to what we're doing internally in the enterprise. It's the query. It's understanding the prompt, what is it? Keep asking the why not, the why not? What more?