Ep 231: NVIDIA Making Money Moves: How they’re using AI to change financial services – An Everyday AI chat with Malcolm deMayo and Jordan Wilson

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Revolutionize Your Business with Generative AI: The Financial Sector's Next Frontier

The financial sector is on the brink of a technological revolution, and at the forefront of this wave of change is the integration of Generative AI. In a recent episode of Everyday AI, the potential of Generative AI in transforming the financial industry was discussed in great detail, shedding light on the practical applications, challenges, and future implications of this cutting-edge technology. As a business leader, understanding the impact and opportunities presented by Generative AI in the financial sector is crucial for staying competitive and meeting the evolving needs of customers and clients.

Reimagine Efficiency and Productivity

Generative AI offers a paradigm shift in how financial institutions can reimagine efficiency and productivity. By leveraging advanced AI models, organizations can automate tasks that were once labor-intensive and time-consuming. The integration of Generative AI can facilitate the conversion of legacy systems into modern programming languages, providing a significant boost to software development and productivity. This transformation enables financial firms to streamline operations, enhance the speed of data processing, and ultimately deliver improved services to their clients.

Enhance Customer Experiences

One of the most compelling aspects of Generative AI is its potential to enhance customer experiences. The implementation of AI-driven digital avatars, capable of providing real-time assistance to clients, presents a game-changing opportunity to revolutionize customer interactions. Imagine offering clients the ability to engage with lifelike digital assistants, simplifying complex processes, and providing immediate, personalized support. Supporting this transformation with AI-driven predictive analytics can enable financial institutions to tailor services and offerings to better meet the unique needs of individual customers.

Navigating Challenges and Building Guardrails

While the benefits of Generative AI in the financial sector are substantial, it is not without its challenges. Financial firms must navigate complexities such as analyzing vast amounts of unstructured data and ensuring the accuracy and reliability of AI-generated models. Fortunately, leading AI platforms equipped with advanced technologies like 'retriever augmented generation' provide the capability to engage in meaningful conversations with crucial data sources, significantly mitigating challenges associated with data analysis.

Furthermore, the integration of robust guardrails is essential to ensuring the responsible and secure use of Generative AI. Guardrails serve as a means to guide AI models, ensuring that they remain focused on relevant topics and sources, while also preserving the privacy and security of sensitive data. Forward-thinking financial institutions are investing in upskilling their employees, foraying into affordable and adoptable AI solutions, and transforming their data centers into AI factories, all while focusing on delighting customers and outmaneuvering the competition.

Seizing the Future with Generative AI

Looking ahead, the pace of AI development is only set to accelerate, and financial institutions that embrace Generative AI stand to be at the forefront of this transformative journey. The future of the financial sector will be defined by the effective integration of AI technologies, with Generative AI leading the charge. Business leaders are encouraged to make substantial investments in people, infrastructure, and technology to fully capitalize on the potential that Generative AI brings to the industry. As benchmarks and standards continue to evolve, navigating this technological landscape requires a proactive stance and an openness to embracing the groundbreaking capabilities of Generative AI.

In conclusion, the integration of Generative AI presents a plethora of opportunities for the financial sector. From driving efficiency and productivity to reshaping customer experiences, the possibilities are abundant. To effectively harness the benefits of Generative AI, business leaders in the financial industry must prioritize education, investment, and innovation, positioning their firms to thrive in the age of AI-driven transformation.

By leveraging Generative AI, financial institutions can position themselves to not only meet the existing demands of the clientele but also to anticipate and exceed future needs, offering unprecedented levels of service and support.

Topics Covered in This Episode

1. NVIDIA's Platform and Partnerships in Financial Services
2.  Application of Generative AI in the Financial Sector
3. Challenges and Risks in Adopting Generative AI
4. Future Outlook and Developments in Generative AI


Podcast Transcript

Jordan Wilson [00:00:17]:
Is NVIDIA more than just chips? A lot of you probably when you think of NVIDIA, you probably think computer graphics generated AI. But what you probably don't know is that because of all of that technology, NVIDIA has its thumb on the heart of everything, including financial services, which is what we're gonna be talking about today on Everyday AI. Thank you for joining us. Welcome. My name is Jordan Wilson. I am the host of everyday AI, your daily livestream podcast and free daily newsletter, helping everyday people learn generative AI and how they can leverage it to grow their companies and to grow their career. And if you're joining us on episode, like, 230 now, you're probably thinking this looks a little weird. This isn't how it normally is.

Jordan Wilson [00:01:00]:
Well, yes, this is actually our first in person, interview for a livestream. We're extremely excited to be broadcasting live at NVIDIA's GTC conference out here in San Jose, California. We're gonna have a lot more this week, but today we are talking financial services. And before we get into that, I do have to give a shout out because it's not too late. You can still join, the GCC conference for free. We're gonna have the link in the comments and in our newsletter as well as a way to earn DLI credits as well. Alright. So now after that big wind up, I wanna introduce our guest, Malcolm DeMeo, the vice president of Global Financial Services at at NVIDIA.

Jordan Wilson [00:01:41]:
Malcolm, thank you for joining the show.

Malcolm deMayo [00:01:43]:
Jordan, it's great to be here with Everyday AI. Really awesome, and it's awesome that that you're here at GTC. So thank you.

Jordan Wilson [00:01:49]:
Good to be It's it's been a it's been a 5 year, a 5 year, kind of delay of us just waiting back for this in person. Right?

Malcolm deMayo [00:01:56]:
Right.

Jordan Wilson [00:01:57]:
What's what's been your vibe so far kind of walking around here?

Malcolm deMayo [00:02:00]:
We're sold out. It's unbelievable. So, you know, it's great. It's gonna be an amazing week. So definitely, audience, tune in.

Jordan Wilson [00:02:10]:
Yeah. So, I mean, can can you tell us a little bit about what you do, in your role in Global Financial Services?

Malcolm deMayo [00:02:16]:
Sure. Thank you. So so most people think of NVIDIA, like you said in your intro, as a GPU or a microprocessor, and we are so much more than that. We've been involved in financial services for over 15 years. My role as, global head of financial services at NVIDIA is to make sure we have the right strategy, that we're building the right partnerships, that we're engaging with Lighthouse customers to what we call build our first bowl of soup, which is solving really hard problems with our accelerating new platform. We we sell nothing direct. We work through our ecosystem, and we believe that that everyone should win. Starting with solving the customer's problem, the partners should be winning, and we should.

Jordan Wilson [00:03:01]:
You know? Yeah. Even even going back to that, how does, in the end, in in NVIDIA actually play out in all of these partnerships? Right? Can you explain that for our audience? Because is it just, you know, a platform that, you know, banks and financial institutions log into that helps them, you know, better use their data? Or, you know, what does it actually look like in NVIDIA's partnership in the long run?

Malcolm deMayo [00:03:22]:
Sure. So take a step back. If you go back to, say, 2012, we helped JPMorgan Chase to accelerate their risk management trading platform, options trading platform. They saw an 80% reduction in total cost of ownership and a 40 x speed up in their trading. Fast forward, to today, AI exploded on the scene in 2022 with ChatGPT. And and and it's really hard, for these for for financial firms to leverage AI. There's a lot of work they have to do, and they need help. So there it requires ecosystem partners.

Malcolm deMayo [00:04:00]:
It requires their current ISV partners, their, you know, their software vendors to take our platform embedded in it so that they can deliver value to the customer without having to rip and replace their technology. And we deliver our platform through the hyperscalers. So all of the clouds are our biggest customers. They make our platform available to their customers. All of the large super OEMs, original equipment manufacturers, like Hewlett Packard, Dell, Lenovo, Supermicro. I don't wanna leave it out. That's all of them.

Jordan Wilson [00:04:32]:
You gotta get them all.

Malcolm deMayo [00:04:33]:
Yeah. And, they all live in our platform, and they have they have the expertise to help customers leverage, to help the financial firms leverage the capabilities in our platform. Mhmm. You mentioned DLI, our Deep Learning Institute, and it is a gem. It's sort of a hidden gem. DLI is free. It's free for anyone to come in and use to learn how to use our platform to build generative AI applications. Mhmm.

Jordan Wilson [00:04:59]:
You know, Malcolm, you said something there that's that's interesting. You know you know, you talked about kind of this explosion of of chat gpt, you know, onto the scene, you know, about 2 years ago now. How did you see that from your vantage point playing out specifically for financial institutions? Do you think it was maybe, kind of watching from afar and saying, okay. This isn't really for the financial sector? Or do you think that some, you know, banks and financial institutions were were quick with that?

Malcolm deMayo [00:05:28]:
I think that today, 2024, most people and and there's still some who are skeptical. You know, in the business, there were a couple of technology waves like like blockchain. Alright? That had a huge hype cycle, and still, it's it's going to be a valuable technology, but it didn't deliver on the hype. And so there's a few doubting Thomases out there. But for the most part, everyone understands today that generative AI is a game changer. It is a tsunami wave size game changer for financial services, for every industry, but in particular, financial services. And, when ChatGPT was announced, when generative Ives exploded on the scene in 2022, executives, not just the data scientists who learn how to use the technology and use the technology to improve the efficiency, operational efficiency of these firms to improve productivity, and to get and to create new revenue streams in partnership with the practitioners, the banking practitioners, the trading practitioners, the, network payments firm practitioners. They they, started to come to see us.

Malcolm deMayo [00:06:38]:
The executives started to come to see us because they want they in our business. So 2023, Jordan, was the year of experimentation for financial services. How can we leverage this to generate better, experiences for our customer? If you read any 10 k today from a financial firm, one common theme is we need to improve customer experience, and this technology is enabling that in call centers with digital assistants. For wealth managers, you you have copilots that are capable of being, very smart in real time helpers. And, you know, the financial firms also wanna be careful not to not to, kill the next generation of bankers, because a lot of young bankers coming into the business are in an apprenticeship. So using the technology requires require that experimentation and understanding how are we going to use it in the firm. This year, 2024, is the year of AI going into production. Mhmm.

Malcolm deMayo [00:07:50]:
And we're gonna see some really exciting things.

Jordan Wilson [00:07:53]:
You know, something something that's interesting there is, you know, even mentioning these partnerships that have been going back a very long time. And and with, artificial intelligence, it's it's not new to the financial sector.

Malcolm deMayo [00:08:05]:
Right? Very long.

Jordan Wilson [00:08:06]:
You know, machine learning, deep learning has has been, pivotal, for for the industry for many decades. But with with generative AI, it seems like kind of like what we were even saying. All of a sudden, the executives are paying attention, and it's not necessarily, you know, people in IT or your, you know, chief technology officer, etcetera. How should those in the financial, sector be looking at generative AI specifically even when we're talking about large range models?

Malcolm deMayo [00:08:33]:
Yeah. Well, so very, they they should approach it, I think, with, enthusiasm, and you wanna embrace this technology. The the reality is, generative AI is very good, and AI in general. Pre generative AI was amazing at classifying information, and we just do a ton of that in banking, a ton of classification, document classification, etcetera. Very good at making predictions, used to make predictions. But generative AI takes it kicks it up a notch and allows you to, really, for the first time, analyze the vast mountain of unstructured data. And that's data that the document data, written data. That's video.

Malcolm deMayo [00:09:22]:
That's images. So for the first time, they have the opportunity to harvest all of this knowledge that exists in all the data. And and the thing you need to keep in mind is that generative AI is while it's very good at analyzing and finding, insights in all of this this giant haystack of data, what it's not it it can't replicate the way humans make decisions. And we probably, as humans, make thousands of decisions a day and don't even realize it. And we we just generally go through this decision tree of thinking, this the logic, the way our brains are wired, generalize that multistep thinking isn't there yet. So it's a great tool to help people understand. So think about a wealth manager. Instead of having to collect data from 15 different systems on their institutional client, Jenny, I can do that for him.

Malcolm deMayo [00:10:15]:
He can summarize it. He can do the extraction. But you still need that wealth manager to understand the customer's goals, to understand the risk tolerances, and to build a, a really good strategy for them and plan and help them execute it. Mhmm.

Jordan Wilson [00:10:30]:
So in your role at NVIDIA, you've been able to to see this Gen AI implementation in the financial sector from many different angles. I'm I'm I'm curious, you know, so far, not saying we're at a, you know, halfway point of Gen AI implementation or anything like that, but, you know, how would you grade the financial sector right now in terms of keeping up or actually implementing, generative AI? Maybe can you talk about just from from your vantage point some of the, kind of challenges and triumphs that you've seen as well.

Malcolm deMayo [00:11:03]:
Sure. Well, so just to just to put a punctuation mark on the question, we're at the very beginning. We're not in the middle, and, we're at the end of what you would consider general purpose compute, and we're at the very beginning of an ex a new era of compute called accelerated compute. And what's driving that is generative AI. And so today or yesterday, financial firms have thousands of applications, 100 or thousands of applications they've written. Tomorrow, in the future, that's all going to be done by AI Mhmm. And, and as an assistant to a developer. And you'll have instead of thousands of applications that are hard coded and have and require developers to go in and rewrite and modify, AI is gonna do all of that.

Malcolm deMayo [00:11:54]:
So now you have, the opportunity to to do higher level things. And, so, you know, I I from a grading perspective, I would say that financial services industry gets a very high grade. Very, very good at adopting technology. This is what they've done for decades. They have to be careful because they're highly regulated. The data that they use is highly sensitive, and they need to protect it. They are the custodians of their customer data, and they do an amazing job at it. The the uses of technology by bad guys is escalating, and they fight them every day on behalf of their clients.

Malcolm deMayo [00:12:33]:
So I would give them a very high mark. Let's let's talk a little bit more about that because, it's it's very easy to see the wins for generative AI. You know, you gave the

Jordan Wilson [00:12:43]:
example of, you know, someone having to look into multiple different areas for data, and now generative AI can do that for them. What are some of the challenges specifically in the financial, you know, sector that people need to be aware of? You know? Because sometimes people just want to just go out and, you know, leverage generative AI and figure it all out later. So what are some of those risks or, you know, things that people should be concerned about?


Malcolm deMayo [00:14:15]:
Well well, there's a that's kind of a 22 pronged question. For for financial firms, the challenges are this isn't easy to do, and the technology is changing so fast that it's hard to keep up. And so working with an accelerated compute platform like NVIDIA's takes that burden off their shoulders. We are keeping up. We make sure that every time a new model comes out, it's optimized to run on the platform. That we we have, financial firms coming to us and asking the question, how do we know if my model's good? How do I know if this thing's, you know, accurate? How do I how do I measure that? And, you know, the manage the metrics for models today are things like, can it take the MCAT? Can it take the LSAT? Can it take the GMAT? Can it take the blah blah blah test? And, that was a technical phrase, by

Jordan Wilson [00:15:05]:
the way. I I yeah. I I failed that test. So

Malcolm deMayo [00:15:08]:
and so, you know, they may want to show that the model is very, very accurate and can take the CPA exam. They may wanna show that the model can take they can cannot take the the certified financial adviser test. And so we've built all of that all of those evaluators into our platform. So you're gonna hear all about this week, at NVIDIA. That was a sneak preview. From a risk perspective, you know, the the the biggest challenge and and so it's very hard to work with, mountains of data. It's it's very hard to work with a model that's frozen in time, and so we've built a platform that helps them do that. So for example, the frozen in time.

Malcolm deMayo [00:15:52]:
If you use if you use an API service and you ask it a question, a current question, you'll get an answer back something like, I've only been trained through September 2023. Right? So, we use a technique called, retriever augmented, generation, and and this is a this this was, created by Meta, But we've baked that into our platform so that customers can now have a conversation with their most important data sources. Imagine just being able to ask a question in English and get an answer from your most important data source instead of having to sit down, write a structured code, test the code, etcetera. That's how this is changing the industry.

Jordan Wilson [00:16:31]:
Mhmm.

Malcolm deMayo [00:16:32]:
From a risk perspective, there's the there's the risk of hallucination. And so what we've done is build guardrails, And our guardrails ensure that, a model stays on topic. It it's not gonna talk about religion. It's not gonna talk about anything politics. It's not gonna talk about anything his mom taught you not to talk about. You know, we make sure that the model is only connecting to trusted sources. That's another guardrail. We and and the ability for customers to build their own guardrails using our open source platform is really and they can do it again anywhere in cloud, on prem, through through, all of our partners.

Jordan Wilson [00:17:11]:
Could you maybe just walk us through the whole process, whether it's an an actual example or or theoretical of how financial institutions either are or can, really push forward, save time, improve efficiencies, by by using, NVIDIA's platform?

Malcolm deMayo [00:17:27]:
Sure. Couple examples. First of all, the industry, banking at its core is a batch system that was developed in the 19 sixties. These are mainframe based platforms. And, running in COBOL, which is sort of your father your grandfather's programming language. I did learn COBOL. But, at any rate, what what we're able to do today is use a use a a an AI assistant to essentially analyze that code and write it in something modern like Java as a as a first step and then maybe a second step to something that's more modern like Python, etcetera. So or c plus plus, which is very fast.

Malcolm deMayo [00:18:07]:
So, that's one example. And if you have code being generated about 40% of the code in GitHub today is generated by AI. Think about it. If you're a financial firm and you have 10,000 software developers, and they're now 40%, 50% more productive. Alright? You that means you can get 40, 50% more work done. That's more value to your clients. That's more capability for your clients to use. Another example is in the call center.

Malcolm deMayo [00:18:34]:
You call your bank on Saturday morning or on lunch break during the week, and you get the infamous, touch 1 for blank, touch 2 for blank, touch 3 for blank, or wait for the next available assistant. Right? Yeah. Nobody likes that. 30 minutes later, a very nice person gets on and helps you. With Digital Copilot, you're going to be able to have the option to, say, you know what? I just have a simple question. If 7 out of the 10 questions that are asked on a call center are just complaints, help me with something. Alright? A digital a digital avatar, a human, which we build in our platform. So a very lifelike person will come on and say, hi.

Malcolm deMayo [00:19:15]:
How can I help you? I need to reset my password. Here's how you do it. Or I I don't understand how to transfer money using Zelle. Well, here's how you do it. Mhmm. Alright? And so the opportunity to take those 30 minute wait queues down to, you know, immediate, real time. And so what have you done? You've improved customer experience. And the customer's gonna walk away at one good experience, all the surveys today.

Malcolm deMayo [00:19:39]:
One good experience means they're going to use more of your products.

Jordan Wilson [00:19:42]:
You know, yeah, we've we've talked a lot about how, NVIDIA's advancement in in this sector have changed things for the financial institutions that are wealth management, etcetera. But we haven't talked too much about on the customer side or on the client side. So do you see that as as maybe the future of where we're heading and instead of, yeah, like, waiting on the waiting on the line forever? Is there maybe just, speaking with a digital twin avatar? You know, is is it going to be that personalized even you know, you talked about Rag. Right? Like, would my even data be accessible with with a digital avatar? Like, would I be able to instantly make changes like that, whether it's my personal banking, wealth management, etcetera? Is that where we're going?

Malcolm deMayo [00:20:23]:
You're gonna have AIs helping AIs. You're gonna have AIs watching AIs, so that, you know, if the very first thing will be, do you do you actually need access to this information? Do you have the right authority to have access to this information? But yeah. Think think about, today, everything is so siloed. It's very hard for customers and bankers to have a converse a holistic conversation that all that's gonna change. We're desiloed. AI is helping firms desilo. So it's gonna be exciting.

Jordan Wilson [00:20:57]:
So speaking of exciting, this we're in a very exciting environment here at at GTC, in San Jose. What can you talk about where you're headed in the future? Because I know we're always gonna get, you know, some some big announcements and, some some things that I'm sure that that this sector is gonna be reacting to in in the weeks months to come. But what is in the near future, for NVIDIA, especially in in your space?

Malcolm deMayo [00:21:22]:
People always wonder, what what do you guys do? And we started there. And, Jordan, what the first thing to understand is that there's a lot of GPU and hardware accelerators. There's FPGAs, GPUs, ASICs. These are all hardware accelerators. There's lots of them. But there's only one accelerated compute platform, and that's ours. And we started building this after AI's big bang in 2012. Jensen saw the correlation between AI and compute and started investing heavily so that when the world was surprised in 2022 with AI's iPhone moment, ChatJBT, we were ready.

Malcolm deMayo [00:22:02]:
Alright? Most most firms are trying to build what we have. And what we're going what you're going to continue to see from us is an amazing. In the last 10 years, we've developed we delivered a 1,000,000 x speed up to our customers, and we're gonna do the same thing in the next 10 years starting today at GTC at 1 o'clock at Jensen's keynote. Don't miss it. He's going to be announcing so many cool things. And so the first observation is that we're a full stack platform, and nobody else is. The second observation is that we're available everywhere. And as we generate speed ups, it makes this more affordable and more adoptable.

Malcolm deMayo [00:22:44]:
And and when we put it in cloud and you can use it as a pay for use, it means that more and more enterprises have access to it. Is there

Jordan Wilson [00:22:53]:
a scenario in in your mind when you look in the coming, you know, year or 2? Do you see just development going even even faster? You know, I even think of my own, you know, personal experience with generative AI, and I feel, you know, in the last, like, couple of months, it's hard to keep up. So, specifically, even in the financial sector, you know, like like you said, it's AI and machine learning. Deep learning has had been in play for a decade. Do you think and maybe with what's announced today, right, is is it going to go into hyperdrive in the coming months and, you know, maybe a year ahead?

Malcolm deMayo [00:23:30]:
Well, the last three waves, sort of the Internet, mobile, and cloud took 20 years, to to mature and and, to be fully adopted or or largely adopted, maybe is the way to say it. And, you know, compared to AI, that's glacier movement. Yeah. AI is moving at light speed. The announcement is every day. There's another research paper published. There's another innovation. There's another and so you need a company like NVIDIA who is on top of this and billing and who are our biggest customers? It's the it's the clouds.

Malcolm deMayo [00:24:06]:
It's the server providers who build all of this and make it and and make it available to the everyday person. So, so so, yeah, you're gonna see in the trading business the half life of an alpha signal. Alpha signal is there in is the industry, sort of description for above average profits Mhmm. Or returns. Alright? That the half life of a signal now continues to shrink because the market's moving so fast, and everybody's competing in a world where they all have access to the same data. And so how they use that data, how you know, is is the differentiator, how curious they're and how talented their, their team is, and how expert they are at what they do, and how good at using the platform we built they are is what's going to allow them to win.

Jordan Wilson [00:24:58]:
What would you say what's what's your biggest piece of advice? Maybe whether it's, you know, people at extremely large firms who are still tackling, you know, gen AI implementation because it is an ongoing process. Right? What's what's your best piece of advice, for people working in large financial firms? Maybe they're going back and forth. Maybe they're not on, you know, in in NVIDIA's platform yet. But what's your best piece of advice for them to, first understand generative AI in large edge models? But how should they be actually looking, or or what problems should they be trying to solve?

Malcolm deMayo [00:25:30]:
So first first thing is embrace this, and don't get left behind. The ship's leaving the dock. Don't stand on the dock. Embrace this. Lots of ways to do that. We have a launch pad. It's free. You can experiment on that launch pad for 2 weeks and and try something out.

Malcolm deMayo [00:25:48]:
Use our DLI, our Deep Learning Institute, to learn. Come visit us. Our executive briefing center is whirring right now. It is just jam packed. But when you leave, you will have a very good understand. When when customers walk in, they're like, we know this is for real. We just don't understand necessarily. When they leave, they're like, wow.

Malcolm deMayo [00:26:06]:
So number 1, embrace it. Number 2, make the investments in your people upskilling them, and 2, in the infrastructure. Because the infrastructure in everyone's data centers today is yesterday's infrastructure. They need an accelerated compute platform, and you can start small and build as time goes. But over the next few years, they need to transform their data center from a data center, which is a cost and expense item. It stores emails, you know, to an AI factory, which allows them to generate AIs that improve productivity, improve operational efficiency, and and help them grow revenue by doing a better job with the with in with delighting their customers depending on what segment they're So those are the 3 things. It's 1, embrace this. 2, upskill your people.

Malcolm deMayo [00:26:55]:
And 3, invest in the right technology.

Jordan Wilson [00:26:58]:
Yeah. Well, speaking of investing in the right technology, hopefully, you're doing that with us. Today, like we mentioned, Jensen's keynote coming up at 1 PM Pacific. Malcolm DeMayo, vice president of Global Financial Services at NVIDIA, thank you so much for joining us.

Malcolm deMayo [00:27:11]:
It's great to be here, Jordan.

Jordan Wilson [00:27:13]:
Alright. Hey. And as a reminder, stay tuned with us. We're gonna be here throughout the rest of the the whole week with, bringing you exclusive guests, insider insights. And also check out the show notes. We do have that giveaway going on, so you can sign up, for free to watch the conference virtually no matter where you are. Maybe you can't make San Jose. We'll be giving away that free GPU as well as the credits.

Jordan Wilson [00:27:38]:
So thanks for tuning in. Make sure to go to your everyday ai.com. Sign up for that free day in the newsletter, and we'll see you back tomorrow and the rest of this week at GTC for more everyday AI. Thanks.

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