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Episode: How AI is Transforming Manufacturing and Other Industries: Interview with Linda Yao, Lenovo [AI Today Podcast]

Author: AI & Data Today
Duration: 00:12:12

Episode Shownotes

CIOs everywhere are gearing up for increased investments in AI, while facing challenges and overcoming barriers that come with implementing and scaling AI. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer interview Linda Yao. Linda is COO and Head of AI Solutions and Services at Lenovo.

AI’s Impact on CIOs Recently, Lenovo conducted a global survey of CIOs. Continue reading How AI is Transforming Manufacturing and Other Industries: Interview with Linda Yao, Lenovo [AI Today Podcast] at Cognilytica.

Full Transcript

00:00:01 Speaker_01
The AI Today podcast, produced by Cognolitica, cuts through the hype and noise to identify what is really happening now in the world of artificial intelligence.

00:00:10 Speaker_01
Learn about emerging AI trends, technologies, and use cases from Cognolitica analysts and guest experts.

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Hello and welcome to the AI Today podcast. I'm your host, Kathleen Malch.

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And I'm your host, Ron Schmelzer. The thing about AI, as we keep talking about, it is really the topic of every conversation.

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Whether we're talking about casual things we're implementing on our own, with our friends, with our family, for business applications, for government applications, for education, for health care.

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Well, pretty much every application now is really AI as a core component of it. And that's because as a transformational technology, it's just as transformational as the internet and computing and mobile and social. It is the latest wave.

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And even though AI is, as we say, the oldest new technology since 1956, it's had many struggles to gain adoption and acceptance. But it seems like, at least in this latest wave of AI, AI is here to stay.

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And hopefully we want to encounter some of those AI winters that we've talked about in episodes in the past. So if you haven't listened to AI Today, this is your first time. We really encourage you to listen to all of our episodes.

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We have, oh my goodness, well over 460 episodes all together. This is our seventh season. And we spend a lot of time interviewing thought leaders and folks who are really making AI work today. That's why we are AI Today.

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in the world as well as of course going over key topics and glossary items of what AI is all about, but also we have our soft skills series we just finished up, lots of things on AI best practices, our trustworthy AI series, all sorts of stuff of course, our very popular generative AI series, and so many things, and we're here to help you make the most

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of AI today. And we're really thrilled to have you here listening to our podcast as we interview our thought leaders, as well as some of the folks who are supporting and sponsoring our podcast, including today's guest, our friends from Lenovo.

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So I'll shift it over to my colleague, Kathleen, and we'll get that interview going.

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Exactly. We're so excited to have with us on today's podcast, Linda Yao, who is COO and head of AI solutions and services at Lenovo. So welcome and thanks so much for joining us today. Thank you, Kathleen and Ron. It's great to be here.

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We're really looking forward to today's discussion. We'd like to start by having you first introduce yourself to our listeners and let them know a little bit about your background and now your current role at Lenovo.

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Sure. So I'm Linda Yao. I work at Lenovo and I lead strategy operations and AI. for our solutions and services group.

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You know, this group was really built and incepted three and a half years ago to help companies and to help our customers embark on digital transformation and realize the value from their technology investments.

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And so we were really in the perfect position to now help customers with this gen AI catalyst and this AI revolution to take advantage of everything that is emerging now in the ecosystem. So it's super exciting.

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AI, as you mentioned, is a little bit of everywhere, and it is the oldest new technology on the block.

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So we are very excited and passionate about having these AI services and building this AI center of excellence to help customers tackle the opportunity.

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Yeah, that's great. And I think, you know, it's interesting because the way that people are interacting with AI is actually changing quite a bit.

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You know, sort of in the early days, a lot of the things when we were talking about AI in our interviews, a lot of, you know, big cloud-based data servers and, you know, AI sort of out there and use building your own from scratch and all that sort of stuff.

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But now we're starting to see AI. in people's devices and their fingertips at the edge. And people now are starting to see the differences and all sorts of stuff.

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And it's actually kind of interesting, especially from your perspective of kind of where and how you're seeing AI be put into use.

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And maybe you could talk to us a little bit about what you're finding to be some of the more surprising or significant trends regarding AI implementation, especially among global CIOs and others that you are spending your time with.

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Sure. I mean, I totally agree, Ron. AI is so ubiquitous, right? And the way that we think about it at Lenovo is we meet the customer where they are, right? Or we meet the user where you are on your journey.

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We call it hybrid AI because sometimes AI is most useful in the public cloud. Sometimes AI is more useful in your own private lockdown data environment.

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And oftentimes, AI is very useful or entertaining when you have personal AI on your own device, in your own home, in your own ecosystem that knows you very personally.

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So some of the things that have kind of surprised me are when I talk to CIOs and CTOs and CAIOs and CDOs about AI, most of them, 96% of them in our recent CIO study,

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have said they are prepared to invest even more in a in the coming year right but one of the fascinating things is the majority of them also don't completely feel ready for the ai that they're going to invest in for the ai that they're asking their people to adopt and so one of the things that excites me the most.

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Is that we at lenovo we kind of dog food and battle tested a lot of a implementation again with this being the oldest new technology on the block we've been doing for decades like a lot of the large technology powerhouses out there.

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In this latest wave, generative AI is the great flavor currently. This latest wave is helping us to use AI as the rising tide that raises all ships, raises all ships of technology advancement, digitization.

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We can take a lot of the best practices in the playbook that we've used in the past to successfully adopt and adapt to new technology. and now apply it to AI and Gen AI as well.

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Yeah, I like that you called it a journey because we talk about that a lot, right? You know, everybody's on a different path and different part of their journey. Some people are, you know, newly into their AI journey. Some people are much farther along.

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But that's why these podcasts are great because we are able to get real-world experiences and see how all these different industries are adopting AI and how they're doing it.

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So maybe how have you seen AI specifically transforming business operations at organizations? And if you can provide some examples.

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Sure. I mean, one of my favorite examples is a partner that we work with very closely, Lotus Technology. You may know them. They're the British performance car brand. What is fascinating about Lotus is they're a global manufacturer and so is Lenovo.

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Right but are our types of manufacturing are quite different lenovo is the number one pc maker on the planet right so we are manufacturing tons and tons of this material and tons and tons of these very certified user devices every single day every single hour.

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Lotus, on the other hand, they're all about handcrafted, custom built vehicles for your personal consumption. So what was fascinating is every single vehicle that comes off of their smart manufacturing line is custom built.

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And we were able to engage with them to still share a lot of the best practices that we had internally and help them apply it to their smart manufacturing line. One of the great examples is quality inspection, right?

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When every vehicle is custom built and kind of custom designed, it makes it a little bit more difficult to go do cookie cutter quality inspection. So now with AI and with something at Lenovo that we call our smart eye,

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we are able to work with them to implement this computer vision smart inspection module to really accelerate that process and identify a lot of defects that they may not have been able to identify before just with human and technology, human-assisted technology.

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That's allowed them to actually have an 80 percent reduction in their installation errors and a 50 percent increase in their manufacturing performance. So this is a great example for me.

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And I learned a lot from this because it showed me how something that we can take from our manufacturing line that we developed internally can now help one of the great automotive performance vehicle brands on the planet to craft and cater these products for their end customers.

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Yeah, that's really exciting. You know, I love to see all these videos you see out there of manufacturing lines and assembly lines and how automated everything is and how much computer vision there is in all these lines.

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And, you know, just sometimes not even a millimeter, microns of defect matter a lot, especially as we're making things more compact and more efficient and increasing scale. Hey, machines are really good at that.

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They're really good at that kind of task. It's kind of funny having humans use our eyeballs and brains. We call it mind-numbing for a reason, because it's not the best use of our creative brains. That's for sure.

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So let machines do what machines are good at, and people do what people are good at, and together we can do that. Well, so from that perspective, as we're putting AI into all these systems, we, of course, weren't into a lot of the challenges, right?

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AI isn't perfect. It's probabilistic. And we have a lot of issues with regards to the use of AI and applying it properly and responsibly, ethically, transparently, all these sorts of things.

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So maybe in your conversations and what you're looking at, maybe talk a little about some of those challenges and kind of how you're addressing them and maybe in some of your conversations that you're having,

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also with some of these CIOs and others, how you're working through these fairly significant issues.

00:10:08 Speaker_03
Absolutely. A lot of those CIOs and IT decision-makers that we spoke with during our CIO study said that they weren't ready for AI.

00:10:15 Speaker_03
Then specifically, three-quarters of them said it's because they don't have an AI-ready corporate policy about that ethical use that you mentioned, and how to operationalize AI and the promise of AI inside of their organizations.

00:10:29 Speaker_03
Another three quarters of them said that their supply chain is not AI ready. How do they know that these components are secure? How do they know that the technology will integrate well?

00:10:39 Speaker_03
And so when we look at our approach to AI adoption, the reason that we engaged with these CIOs is to really understand the pain points that customers have in adopting the potential and harnessing the potential of AI.

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We now have a methodology that is based on our own learning as well that is called security first and people centric. So we think about four pillars of security, people, technology, and processes.

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And we assess our own AI readiness along those four pillars whenever we're thinking about adopting AI or scaling an AI POC. That methodology has actually helped a lot of our customers as well.

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So when we think about, for example, security being one of the fundamental challenges that these CIOs want to overcome so that they get comfortable with AI adoption, one of the things that we offer

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is that we are able to provide a service around secure and responsible AI. It's based on our own best practices that are written into our own Lenovo corporate AI policy. And it addresses things like data privacy and data sovereignty, right?

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It also addresses things like diversity and inclusion and how we think about the guardrails we put around AI so that it can come with ethical outcomes. It even addresses things like, how do we do AI and use AI in a more sustainable manner?

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So that as we scale out these large footprints, as we adopt AI across the workforce, we're doing it in a way that is sustainable and can help us achieve our ROI most effectively.

00:12:18 Speaker_02
Yeah, you said a lot of things in that and we're shaking our heads. I know the listeners can't hear that, but we're like, yes, yes, yes.

00:12:25 Speaker_02
You know, in the past few years specifically, a lot of talk has been around the ethical, transparent and responsible use of AI. And so, you know, first organizations just said, how can I adopt AI? And you can look to see how others have done it.

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Now you say, okay, how do I do it in a trustworthy way, in a responsible way, in an ethical way?

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Because we say you don't want to spend all of this money, time, and resources to be adopting these technologies only for people to not trust them and then not use them. Because at that point, why do it, right?

00:12:56 Speaker_02
And you talk about ROI too, that return on investment. Our listeners know we talk about that all the time because it can be a money return on investment, but it can also be a time return on investment or a, you know, equipment return on investment.

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What are you doing here and how are you measuring that? And so we always say, you need to start with the business understanding. Our listeners know we are big advocates of best practices methodologies.

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We're big advocates of CPMAI, the Cognitive Project Management for AI methodology, which is a step-by-step approach for running and managing AI projects. We start with business understanding. We say, what problem are you trying to solve?

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Seems like a simple question. Too many people skip that and they just move forward. Then we say, what's that return going to look like?

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We also talk a lot about the seven patterns of AI, which, you know, break it down one level deeper and say, OK, I know I want to do an AI project, but do I want to do a recognition project?

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Or am I doing a conversational project or am I doing a hyper personalization project that's going to matter when it comes to what that return looks like the length of time for your project, maybe the algorithms that you select if you're you know building this from scratch also the data that you have so.

00:14:09 Speaker_02
It's really nice to hear other organizations are kind of looking at this from the same perspective as well. And so, you know, maybe on that note too, because I know that, you know, you are looking at this and that is really great.

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Maybe what are some of the most important things that you think folks should look at as they are going about adopting AI and trying to do it in that ethical and responsible way?

00:14:33 Speaker_03
Oh, that's a really big question. And, you know, I think what you said really resonated around the CPM AI strategy.

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Because what I like about that strategy is that it really takes you a chance, gives you a chance to step back and assess why are you doing AI? Where are you implementing the AI? And who's going to be able to receive it and benefit from it, right?

00:14:55 Speaker_03
That is the same approach that we take. When we use our methodology of security first and people-centric, we do think a lot about that people element.

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Because at the end of the day, a lot of AI is still going to be used by people, augmenting people, and having humans in the loop. I really like something that an HBS professor, right?

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Professor Lakhani at Harvard Business School says that AI is not going to replace humans, but humans who know how to wield AI, they might be in a better position than humans who cannot.

00:15:29 Speaker_03
And so whenever we think about AI adoption and AI implementation, we do it in a people-centric way. Now, a part of that is that we have a people practice inside of our AI Center of Excellence.

00:15:42 Speaker_03
And this is all about, again, to your point about CPM AI, understanding the objective for why we're implementing AI. Is it for productivity gains? Is it for efficiency savings? Is it for rapid innovation?

00:15:56 Speaker_03
Once we know that, we can actually identify the groups that are more likely to embrace this AI adoption, the people who are more likely to be able to skill up, train up, and adapt their tasks to use the AI most effectively.

00:16:11 Speaker_03
And then when we've identified that, we can create the change management plans, the communication templates, the curated training paths.

00:16:19 Speaker_03
And that I think is something very important for organizations to understand upfront if they want to achieve their ROI. And there are other ways to achieve ROI, right? Sometimes you want AI to augment your employees.

00:16:33 Speaker_03
Other times you actually want AI to replace tasks that humans don't want to do so that we can free up our time to go do something that's more value added. And sometimes you actually want to use AI to create something new.

00:16:46 Speaker_03
right, to make headways in innovation, to be able to simulate a lot of new products and new testing ideas that you never otherwise would have had the bandwidth to do with, you know, a labor force of humans.

00:16:59 Speaker_03
One good example is in our partnership with Lotus Technology, right, we definitely started in terms of quality inspection and how to improve the efficiency of the manufacturing line and the quality process.

00:17:12 Speaker_03
But through this, we identified use cases for generative AI on the product development side, right? So we are now able to use AI to help them rapidly innovate what they call kind of the smart kind of driver enterprise AI twin.

00:17:30 Speaker_03
So the idea behind this is that the fleet of their vehicles can become a twin for their drivers and their customers.

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The individual vehicle which is custom built custom tailored to that particular driver can now also understand that drivers behavior right load in that driver schedule understand where that driver likes to go what they like to do at what time of day.

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and really integrated with other data that the driver is willing to provide, can then become a personal assistant for that driver.

00:18:04 Speaker_03
So this idea of enterprise AI twins and personal AI twins is another one of those great ambitions that AI and Gen AI have now been able to unlock for us.

00:18:17 Speaker_02
Yeah, we love to have these discussions because we always get to, you know, learn how people are thinking about this.

00:18:23 Speaker_02
And it really is such an exciting time, you know, especially with everything that's going on and just the transformative nature that AI has to impact, we always say, you know, personal and professional lives.

00:18:34 Speaker_02
And so what's been different about this latest wave of AI, because Ron had alluded to the AI winters in the past, so the term was coined in 1956, and then we've been through two previous AI winters that

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We have had podcasts on, and I'll link to that in the show notes if listeners want to dig deeper into that topic.

00:18:50 Speaker_02
But what's really been transformative about this wave, many different things have been transformative, but one thing in particular is that it's now being used in our everyday lives, where before it was just governments and then maybe organizations that were using it, but now it really is in the hands of each individual.

00:19:06 Speaker_02
And that's what makes it so wonderful because everybody can see the benefits that AI is bringing.

00:19:12 Speaker_02
So as a final note, we always ask our guests the same question because no matter how many times we ask it, we're always getting different varied responses because you're able to bring in your own unique experiences and insights and desires.

00:19:26 Speaker_02
Some people get very philosophical and other people are very practical with their answers. So we always love to hear how you approach this.

00:19:34 Speaker_02
As a final note, what do you believe the future of AI is in general and its application to organizations and beyond?

00:19:41 Speaker_03
Oh, what a thought provoking question, Kathleen. Yeah, when I think about the future of AI, one of the things where I already see we're on the path to achieve is multimodal generative AI, right?

00:19:54 Speaker_03
Really understanding not just large language models, but also on the road to large action models. I think about AI augmenting the human experience and the human experience isn't just about text.

00:20:07 Speaker_03
Right it's not even just about images or just about language i saw a leaf from stanford has started her new venture and this organization this startup is going to look at tackling how to.

00:20:21 Speaker_03
allow AI to be able to process the world around us in the way that we humans can with our eyeballs and our vision. And that I think would be extraordinary.

00:20:30 Speaker_03
Earlier, what Elon Musk was even doing with Neuralink years ago, it's kind of the same vision, which is all about how can we now use AI, make it even more intelligent, and find the right ways for it to complement us as humans and augment our own abilities.

00:20:46 Speaker_03
That is something that I think is going to help us with this next transition of using AI and Gen AI as more than just an assistant.

00:20:56 Speaker_03
Now, more and more, even in the enterprise today, I see some use cases where AI is going beyond an assistant and becoming more of a deputy. A deputy that we can deploy and send out to actually accomplish tasks on our behalf.

00:21:12 Speaker_03
versus just assist us on what we're doing at hand. And that, I think, is really going to unlock a lot of the productivity and creativity that we all carry with us.

00:21:23 Speaker_00
Yeah, absolutely. We actually spend a good bit of time on this whole idea of agentic AI and these smart agents that are not only able to tell you things and generate some things, but go ahead and accomplish things, right?

00:21:36 Speaker_00
You know, there's always, you know, guardrails that need to be put into place and all the things we do, like when you have things done with or without the human in the loop. But the power there is tremendous.

00:21:46 Speaker_00
And for those of you that are interested, I would go back and listen to our numerous podcasts on this as we've been talking about the evolution of what

00:21:53 Speaker_00
was previously called the robotic process automation space, which is more about, I would say, programmatic approaches to recorded approaches to repeating desktop and automation activities.

00:22:04 Speaker_00
Now, with the power of AI, we can sort of bring intelligence and automation together. and achieve that next level. And it's really very interesting. And I love everything you're saying is so consistent with everything that we're hearing.

00:22:16 Speaker_00
It is so right now in the moment and looking ahead because I think that's where people want to be. People want to hear from folks like you. This is truly thought leadership, right? Thinking ahead and helping lead the industry.

00:22:28 Speaker_00
And all the examples you provided were fantastic. So I just want to extend a big thank you for sharing your insights. As mentioned, we're going to provide all sorts of links to our show notes here.

00:22:37 Speaker_00
As mentioned, our Lenovo folks are our great supporters, sponsors of this podcast as well, and will provide some great insights to what they're doing and connecting all the great things.

00:22:46 Speaker_00
But I wanted to thank you again so much for being here, for sharing your insights with our audience.

00:22:51 Speaker_00
And we're going to encourage our folks to connect with you, to learn more and with your team and with all the great things you guys are doing there at Lenovo.

00:22:58 Speaker_03
Awesome. So much. Thank you so much, Ron and Kathleen.

00:23:01 Speaker_02
Yeah, thank you. This was such a wonderful discussion. And as Ron mentioned, we will link to additional podcasts, topics, and links around Lenovo in the show notes. So please make sure to check that out.

00:23:13 Speaker_02
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00:23:23 Speaker_02
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00:23:31 Speaker_02
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00:23:39 Speaker_02
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00:24:04 Speaker_02
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