How AI Can Humanize Health Care: Meet "IC" Chiranjeevi Praveen Ikkurthy, CHCIO, Stanford Health Care

Host Yolanda Fintschenko, executive director of Daybreak Labs and i-GATE Innovation Hub,  and guest co-host Hazel Wetherford, Deputy City Manager for the City of Dublin, talk with  Chiranjeevi Praveen Ikkurthy, CHCIO,  Interim IT Administrative Director for Stanford Health Care - Valley Health Care. IC was a panelist in our 2024 Tri-Valley AI Summit, and we are thrilled to welcome him to the pod! 

Chiranjeevi Ikkurthy (“IC”) is a seasoned IT leader with a proven track record of driving digital transformation in healthcare settings. He is part of Stanford Health Care’s Technology and Digital Solutions team, and currently serves as the IT Director supporting Stanford Health Care Tri-Valley. Even though he has been part of SHC for over 17 years, his journey with SHC Tri-Valley began in late 2016 when he spearheaded a $100 million IT program to overhaul the hospital’s digital infrastructure. This included deploying Epic electronic medical record (EMR) system and over 150 integrated applications, as well as 3,800 end-user devices, and training the entire staff and clinical teams. He is passionate about advancing the organization’s digital capabilities and establishing SHC Tri-Valley as a hub for healthcare innovation in the East Bay. 

Currently, he is focused on establishing an AI Workgroup to generate excitement, engagement, and education around AI within the hospital. This initiative directly supports the Advance Digital Innovation section SHC Tri-Valley’s 2030 strategic plan. He is a key contributor for this section, which emphasizes leveraging and optimizing core technology platforms while also leveraging AI to optimize clinical and business operations for improved patient care and access to care. This work highlights his commitment to expanding patient care options and establishing SHC Tri-Valley as a frontrunner in healthcare innovation. Watch on YouTube! 

Transcript

Startup Tri-Valley Podcast - Chiranjeevi Ikkurthy

[00:00:00] Yolanda: This is the Startup Tri-Valley Podcast featuring in-depth conversations with leaders who are making the Tri-Valley the go-to ecosystem for science-based startups. I'm Yolanda Fintschenko from Startup Tri-Valley.

[00:00:14] Hazel: I'm Hazel Wetherford, Economic Development Director for The City of Dublin.

[00:00:20] Yolanda: I'd like to welcome to the podcast, Chiranjeevi "IC" Ikkurthy, CHCIO, and CPHIMS, which is a Certified Healthcare CIO, and Certified Professional and Healthcare Information and Management Systems at Stanford Healthcare and School of Medicine.

IC, welcome to the pod.

[00:00:43] IC: Thank you. Thank you, Yolanda and Hazel. Um, it's a privilege to be here. I'm, uh, looking forward to our conversation and thank you for the opportunity last year to be at the panel, so I'm glad to continue that conversation.

[00:00:55] Yolanda: Absolutely. I'm glad you mentioned IC because one of the strengths I think of the Tri-Valley is how we work together to try and get everyone together within certain areas that we think are critical to the economic success of the region. And one of them is artificial intelligence. And obviously the city of Dublin has been a huge partner with Startup Tri-Valley to really establish thought leadership as well as an AI ecosystem here in the Tri-Valley.

And, in the city of Dublin as a hub, we were so fortunate to get to know you as a panelist for last year's Tri-Valley AI Summit. And it's, I think maybe the best place to start is to tell us a little bit about yourself, your organization, and maybe a little bit about the role of AI and what you're doing.

Okay.

[00:02:00] IC: Yes. I go by IC. I've been with Stanford Healthcare for about 18 years, and my career has mainly been in healthcare. I started off at Epic Systems as a developer and worked at Kaiser for a little bit and then progressed through my career at Stanford Healthcare. Recently, I have, the program that I kind of brought forward for Stanford Healthcare was Technology, infrastructure, implementation and overhaul for Stanford Healthcare Tri-Valley back in 2018. So, as of yesterday, it's been seven years that we have been on that journey. And I'm excited to be part of the conversation and where we are on our journey with AI. I think we are learning as an organization. We are trying to build that infrastructure where we are a learning organization with the people and how we go about things. At the same time, we are also trying to do a lot of thought leadership and making sure that we are intentional and responsible in how we bring forward AI solutions. Even whether they're built in-house or if we were to buy.

[00:03:22] Hazel: That's wonderful. So, help us define some of those terms for our audience: like artificial intelligence and machine learning, transparency, bias. Help us define some of those terms.

[00:03:34] IC: Let me start with neural networks. Our human brain is made of thousands and millions of neurons, and they kind of drive how we operate as human beings and apply the same phenomenon with computers and applying those algorithms that can mimic the thinking and building of solutions using that framework where we are not dictating what the systems should do. We are giving them some framework and data and it's able to think and do things by itself. Either it's a prediction or it's giving discreet inputs for guidance. We are definitely using AI in so many different facets within Stanford Healthcare. And be it predictive modeling or be it starting to think about leveraging the generative AI capabilities that are coming down the pipe. 

[00:04:39] Yolanda: Great. So, you mentioned, how you're implementing.  Artificial intelligence basically relies on these neural networks and algorithms to allow an output. That is, maybe it, that was arrived at independent of the input, right? So, of course, you are doing this in a healthcare setting. So how do you, in your role and as a healthcare system, think about transparency, guardrails, bias, and privacy so that you can reap the benefits? And still address all the obvious concerns, whether it's security, privacy, bias, or any of those things that have been raised, particularly not just with AI, but with healthcare itself?

[00:05:31] IC: Yes. I think I missed that part of the question that you had. I think you touched on some of those. We are very methodical, especially with our inaugural chief data scientist, Dr. Neha, who's been with our organization. And he's kind of defined, built a framework that we are all leveraging, we call it FURM, Fair, Usable, Reliable, and Monetary (returns). So, for any AI solution that we are trying to bring forward we want to make sure that we have that go through the FURM process. Is it fair? Is the solution equitable? Are there biases that we are probably missing that we need to make sure we do a thorough assessment about? Is it usable, right? Is it just a tool that is coming in? Are there tangible, measurable results and outcomes that we can foresee? And is it reliable?

As the systems change, as the workflows evolve, is this going to be something that we can reliably see that this is not going to hallucinate? That we have a good understanding of how strong this can really serve its purpose. And at the end of the day, we want to be fiducially responsible in how we invest our time and money in ai. And so, the last one is measurable, monetary returns. So, what we invest versus what we can see, as an ROI is an important component. And, that's the general framework in how we think about building solutions in-house that are AI solutions, but also the solutions that are coming from our strategic partners Epic. Who's the EMR vendor? ServiceNow, who's our platform for service delivery and WorkDay for our Human Capital and Finance and HR. So, we definitely keep a very close eye on the solutions that are coming in. Even when the AI models are being rolled out by these vendors before we turn them on, we make sure to have them go through our FURM assessment so that we are very clear what we can see as pros and cons and benefits of some of these capabilities. And, we have, on the equity front we have a framework called Heal AI, which is, I forget the phrase, focused on the equity component around AI. And the team that is defining and helping create the frameworks for our internal solutions. We have something called Guide AI that is externally first-focusing where if others are looking at leveraging the FURM assessment, how can they think about the equity components. So, These are some of the things that we keep in mind as we evaluate, implement, and monitor our AI solutions.

[00:09:03] Hazel: Thank you for walking us through. The processes that you have in place. So, let's translate that into the Healthcare environment. Tell us a little bit about how AI is transforming healthcare and how healthcare practitioners are using that in the workplace.

[00:09:22] IC: AI is definitely going to be transformational in so many different ways. We are already seeing several great use cases for ai. Some of the things that we have recently done, we have piloted a partnership with the Nuance Dax, with leveraging Copilot Nuance is the platform for transcribing the conversations. And so we've connected the Nuance Dax copilot with our Epic EMR, where we did the cope, where the AI solution can actually listen to the provider and patient conversation in the clinic setting. So the provider can actually keep their attention on the patient and not the computer to document. Then it will provide draft notes that the provider can look at and make sure that it is aligned with what they're thinking. It's fascinating how better it is getting as we have more and more folks try it, that's one-use case. We also have, you may have heard our draft email responses when patients are messaging their providers. Now with the copilot connection within Epic, the AI solution can give a draft response, which is a lot more compassionate it helps that human element for the providers as well. And so it's great. While that's for the provider's side of the house, there are so many other use cases that we have on the operations side as well. There are so many different use cases that are coming forward. Things such as coding, right? When providers or care team members are taking care of patients, they're supposed to document things in a certain way so that the reimbursement goes through and patients are billed appropriately for the services they're rendered. And the coding team is in the back end, the CDI clinical documentation. That team is really double-checking that work and making sure there is nothing missed, or if things are not quoted appropriately. So there's the augmented component that can actually be, the current workflow is the CDI folks would then, after the fact, come back to the clinical team saying “Hey, can you please fix these so that it's appropriately billed to the patient or sent to the insurance?”. Now, these screens come ahead as the providers are placing the order saying, “Hey, Are you sure? Do you want to make sure that you are placing the right order?” “Are you missing some diagnosis based on?” Because it is also looking at the entire patient's chart.

[00:12:22] Hazel: I love that. It's like a checks and balances system and making sure. Right.

[00:12:27] IC: There are also the best practice alerts as well is another example where when a provider is placing an order, for example, there's usually a best practice alert saying, “Hey, have you thought about this drug-drug interaction or drug-food interaction that the patient may have?” That's a built-in sort of capability, but with the AI augmentation, it also goes a little bit further, saying you're placing an order for a warfarin 500. “Should we think about a slightly different dosage for this patient because of this reason?” So, there are citations that support the patient context.

[00:13:10] Yolanda: That's fascinating. I think I heard you say two things that seem counterintuitive, but with AI they are both true. One is you're using AI to essentially humanize responses when people are super busy and trying to respond to a patient and create a draft email that provides the information but also provides the feeling of being heard compassionately by another person,  Which is, I think, counterintuitive a little bit to have AI humanize communication. And then at the same time to do something that is more associated with how computers operate, which is to prevent mistakes.

Yes. because it is the ability to not only provide a flag, “have you considered this?” But just as you said, to pull in the context. Because Of X, Y, and Z. That was also in the patient's chart, which still ultimately allows the care provider to make an informed decision. So, it's pulling up information and putting it into context in such a way that it's helping to augment someone's decision making process.

[00:14:26] IC: It is. The one thing that I completely missed is the cognitive overload that generally goes onto a physician to have to respond and to make sure that everything is accurate, is a lot of, if you think about the physician's time, you know they're spending the time in the clinic back to back with patients or providing care, and they're spending time at home capturing these notes, responding to these emails. And there's a term “pajama time” where you're acting in your pajamas and doing this work. So even though the amount of work the physicians must do has not gone down with these tools like the copilot, or you have the email response tool, It does reduce the cognitive overload that they can spend, and they can still spend quality time with the family. Which is amazing.

[00:15:20] Hazel: And it would be interesting to see, I'm sure there's a decrease in errors.

[00:15:24] IC: Yes. We are in a very early stage, but definitely we are trending in that direction where less cognitive overload should allow people to provide better, more compassionate care.

[00:15:40] Yolanda:  That's wonderful. So, you have a very interesting background. You come from a technical background and you are working in healthcare. So, tell us a little bit about yourself and how you came into something that is healthcare related. I tend to think of this as just being very compassionate. This is something that is a very human-facing role, even if you are behind the scenes.

[00:16:13] IC: Yes. I go back to my high school days where you know, I did my high school in India and my undergrad as well. When I was deeply interested in medicine, and I had a choice to go between medicine and engineering. And while my heart was in healthcare, I felt like I was more wired to be an engineer. That's where I went. But, then somehow when my path came back to as a healthcare opportunity at Epic, I loved it because I'm able to make an impact through some of the work that we do within our team and see that with our patients and providers and colleagues that provide care.

So that's amazing. I landed in this space, I would say.

[00:17:08] Hazel: That's nice. When the two worlds collide. Tell us something that has surprised you over in your current role. I'm sure with cutting-edge technology, there are many surprises: Anything you'd share with our audience?

[00:17:26] IC: What's surprising is that the pace at which the innovations and the solutions that are coming out in. So, we must stay grounded with. Some of the core fundamentals, especially with ai. In all honesty, I've started my strong AI journey with the launch of Chat GPT, and I wanted to make sure that I stay relevant in this time and age. So, I've spent a lot of time in the AI space trying to learn. So, that's the surprising piece. So, one advice I would give is definitely: Pay attention, and play with these tools. They may seem daunting. They may seem like they are going to take away jobs, but we have no way back.

[00:18:28] Yolanda: The genies out of the bottle.

[00:18:31] IC: Play with the tools, and you will be amazed at how many things you can build yourself, and it's just your creativity that's going to empower you to build things. The word handicap is sort of taken away because your knowledge, your constraints can be come, with some support, successful.

[00:18:56] Hazel: I love that. I want to take it a step further. So, for those. Audience members are listening and have not had any experience in ai. What would you recommend? Where would you have them start? Just to get some exposure.

[00:19:10] IC: Yes. I'll start with what we have done within our organization because that's a question that we had, and because we are in a healthcare space, it's important that we are doing that in a safe, secure manner so that the patient's information is not out. So, we've built our own secure platform called Secure, GPT, which is where we've hosted an OpenAI, GPT models. We've hosted the Deepseek latest model and a few other Lambda. It's just available for folks. You can use it for what you see as appropriate. People are leveraging it for things like drafting email responses and how to handle a conversation. And so just play with it, play with these tools and create an open AI account, a perplexity account. There are so many of these. It can be just overwhelming. But try to understand how these things work and how you can leverage them. For example, I struggle with how to communicate certain things, but I have a rough framework so I can put a quick brain dump of what I'm thinking and saying, how do I articulate this?

I want to make sure that the message is concise, and it is at the seventh-grade level. So that people can digest the information. I'm not getting too technical. So, you can be as verbose as you want and have that conversational request in. That's just for helping with conversations, but there are so many other things you could do. So, just start. Create an account.

[00:20:57] Yolanda: Exciting. So, I just want a quick follow up question to replicate the secure environment that you guys actually built. The average user would just make sure not to use personally identifiable information in an open-source platform like a chat GPT, and that would essentially give them the same protection.

[00:21:17] IC: Yes, that's a very important point to keep in mind because even all of these tools are free and nothing is free. You're giving your information rights for them to play with. So, keep in mind what information you are sharing, because that information is going to be leveraged by the platform to make itself better, but also create a personal image of who you are. For example, my wife is a super user of Chad GPT and she worked on communications and now Chat GPT has understood how she communicates. So, when she's asking for some sort of feedback, it's so personalized that she doesn't have to be so verbose. But she's definitely very mindful about the level of detail. But at least the style element is there, that synchrony. If you're talking to a best friend, they know you don't have to share a lot of information. Right? But they get what you're saying.

[00:22:24] Yolanda: That's a good point. That's helpful guidance. So, what has been in this role that you have right now? what has been the most helpful thing to you and for your company's growth, particularly with this AI utilization and even development in mind?

[00:22:53] IC: Sorry, could you repeat the question?

[00:22:54] Yolanda: What have you found the most helpful in your role? I think especially as related to artificial intelligence.

[00:23:07] IC: I think, what I've found most helpful is: our teams have spent a good amount of time thinking about how to make the concepts of AI easily digestible. We've created a couple of inbuilt tutorials on ai. How should an IT person think about AI and what considerations do you have in mind? And that's such an important step. And We played with it within our IT. Now we made that available for the entire organization.

While we have kind of made the secure GPT available, we are also augmenting that with training saying, “okay, it's overwhelming” but “Walk through this with us and let's learn this together”.  And our CIO has done an amazing job. He's said even though we support hundreds of systems in a healthcare organization within it, our focus is going to continue to increase in the AI space. This is important for us. So, we will continue to go around this path.

[00:24:21] Yolanda: That's amazing. There's something you said I just wanted to pull a little bit more on. You've essentially identified training as being the most helpful. And if I understood you correctly, when you were first talking about your SecureGPT, I had just assumed that this was a tool that you were making available to people within Stanford Healthcare, to anyone within Stanford Healthcare. So, you are educating everyone to be able to play with AI in a safe environment so that they can come up with innovative ways to apply it and to help them get their work done. That's amazing.

[00:25:07] IC: And I'm excited to think about bringing some of that locally to Tri-Valley Hospital and our colleagues here as well. We have a five-year strategic plan. We are on the second iteration, 2026 to 2030. One of the strategic priorities is to advance digital innovation, application and adoption wherein we want to think about bringing our people along, bringing the best of the technologies in a way that we are leveraging our core platforms, working towards making Tri-Valley, our East Bay innovation hub. So, I'm excited about that journey where we are exciting, bring our people along, and we lean on them to bring forward transformations.

[00:25:53] Yolanda: That's amazing.

[00:25:54] Hazel: You answered my next question because it was really going to be about bringing it local. This was planned to our Tri Valley region and our ecosystem here and how that would support your businesses, so that's fantastic.

[00:26:06] Yolanda: I'm so excited to hear that too. Having and positioning Stanford Healthcare Tri-Valley as your East Bay Innovation Center for our startup. So, you've met some of our startup founders at the AI summit. How would they intersect with this innovation hub and at what stage in their company? who would their point of contact be? What would you hope to see from some of our innovators? And how would you want to be approached?

[00:26:42] IC: There are definitely a few channels to kind of come through within Stanford Healthcare. We have industry relations and digital health team that is out there looking for these partnerships and opportunities. When I think for someone who's building a startup in the AI space in healthcare, which is so heavily regulated with a lot of security guardrails and legislatives, it's important to find your niche, make sure that you are, you're not casting your net so wide. Because, keep in mind that health systems like Stanford and others have core platforms that we leverage, like Epic. Who's already building tons of AI models into their system. So, try to find a space where you have a unique differentiating solution, right? I think, in a healthcare setting, you have a hospital and clinics, for example, right? If you try to think about a solution that spans both, that's too wide of a net. If you think about all types of clinics, that could be a wider net too, if there are specialties that you could focus on. Right? Just some ways to think about it.

[00:28:23] Hazel: That's wonderful. You talked about opportunities. Let's talk about some of the challenges. What do you see as some of the challenges in the next few years that could impact your industry or impact the work you're doing?

[00:28:37] IC: We have our Chief operating officer, who was the COO of Stanford Healthcare Tri Valley, Rick Shumway. He’s articulated that we have in a healthcare industry, we are up for heavy headwinds for ourselves. If you look at some of the recent legislation that's been passed in California where there's going to be a healthcare cap for expense and with the target of capping at 3% year over year increase by 2029, I believe. That's going to be hard for health systems if you think about it. We are a service delivery function. At the end of the day we are taking care of patients, we are providing services, but we are a consumer of products too.

Technologies that we buy, supplies the medicines. Everything that we use to run our operations and everyone increases their prices. If you looked at some of the inflammation for conflicts that happened during products and the international tariffs that increase the price of some products that we buy. But we are constrained with that 3%. That's a very hard thing to work against. So that's one of the things that's definitely we have to be very intentional about our intent investments and how we spend our time and be strategic about our partnerships. That’s a big one for us.

[00:30:23] Yolanda: So, I know this seems to be something ubiquitous that comes up in healthcare, but in terms of staffing, I know there's a deep need for medical professionals and patient facing professionals.

But, what about in the work that you do? Are you hiring and what kinds of people are you looking for?

[00:30:46] IC: People are more than welcome to look for opportunities with Stanford Healthcare. We have our jobs posting site. We are always looking for, for people who have some healthcare experience, and can be leveraged for technology implementations and support. We have several people that are nurses, pharmacists, some of them are doctors.  They chose to come into the IT as medical informaticists or physician builders. And that's for folks who are looking for getting into the clinical side.

But then you also have core PLA platforms that we use like ServiceNow and Workday. Those are strong products out there in the market that the number of people with those skills are limited. So, if you are building those skills, that will be something that will have a good market to look at.

And if you are high school students and if you are looking for internships, we, we partner with Year Up. We have a rotating group of interns coming into our organization, but also through other parts of the organization as well.

[00:32:01] Yolanda: So, what is the partnership that you partner with?

[00:32:04] IC: It is for high school students or people who are looking for internships. We have a cohort that's starting now, and there's another one that starts in summer. So, we have a fantastic group of anywhere between 20 and 40 interns who are plugged into our teams.

[00:32:23] Yolanda: That's amazing.

[00:32:24] IC: We understand that we'll have to handhold you through your experience, but we'll help you understand what we do and leverage you as someone who can help us with some of the things we do.

[00:32:40] Hazel: And is that strictly like healthcare and engineering? Or is that available to all disciplines?

[00:32:50] IC: Yes, it is an organization that partners with organizations like Stanford.

[00:32:59] IC: We are within Tri-Valley. There are internships opportunities as well for nurses and a few other specialties. I could dig that information afterwards. People are looking for that as well.

[00:33:13] Yolanda: That's amazing. We will add it to the show notes. I'm sure students here will be very interested. It's great to have a local place where you can explore your professional career.

[00:33:26] IC: We are also looking for volunteers. People who are helping people navigate patients. That could be your leg in to understand how the health systems work.

[00:33:39] Yolanda: That's amazing.

[00:33:41] Hazel: What about for those preparing for a career in AI similar to what you're doing?

What would you tell them? What would you tell your younger self now that you've had this career? That's a great way to phrase it. Some of the things that you would have done differently or looked into.

[00:34:01] IC: I always like that reflection back.

That is the thing that I constantly think about for my 13-year-old son.

I'm amazed at the things that he's learning and the applicability of what the kids are learning now to what they may leverage. So definitely keep playing with the AI tools. Like I said, learn how to play with them. Look at what others are leveraging these tools for: bettering themselves and building tools and products.

I don't know how to write programming or Python programming, but I just played with this tool where I was wondering if I can take a table in Excel spreadsheet and create a PowerPoint slide. I asked the chat GPT tool to say, write a program for me in R to do this, right?

And then I play it, and there'll be an error, and I just paste the error back in. It'll kind of give me an idea, okay, now try this code. I kept going and all I did was I kept asking, sharing what issues I've seen, and it would correct the issue. And finally, I got a solution that was a PowerPoint slide with the graph.

That felt good. So think about the things that you could do by yourself, right? You could use multiple sources and create your own tools, just as an example.

[00:35:34] Yolanda: So, it sounds like, if I understand you correctly, what you're encouraging people who want to work in this area to do is: you don't have to wait for someone to teach you. No. You can just do it.

And try, that will be the first steps to investigating if you like it. And second of all getting some kind of demonstrable expertise. I think that's one of the remarkable things. Very different for your 13-year-old son than for our 13-year-old son.

[00:36:12] IC: right. So if, let's say I have an idea of I'm making these cupcakes, they're amazing. My friends like them. I want to figure out how to sell them, right?

You start brainstorming with this saying: What are the steps I need to take? Where do I go? What are my easy wins where I can increase my footprint and people can even take it further. Saying: help me write a business strategy for what I want to do. This is what I'm trying to accomplish.

And the things like at least from my recent knowledge, you can write a document that is like 64,000 characters as question.

[00:36:52] IC: And say, this is my business plan. And you can even attach your documents. So that doesn't even count against the 64,000 characters. So you can have a very comprehensive brainstorming session to kind of help yourself advance build your own business

[00:37:11] Yolanda: That's amazing.

[00:37:12] IC: Right?

[00:37:13] Yolanda: Yeah, that's great advice. I don't know about our audience, but I feel like we should all be rushing off to write something right now. I question too why am I doing right? Wait, so hold that thought. We covered a lot of ground. Is there anything we didn't ask that you'd like to talk about that you think is important?

[00:37:48] IC I think just, no idea is a bad idea, so if you have an idea, if you have a question, Keep at it. I think that the tools that we have at our hand can really help us elevate ourselves in so many different directions that, you know, to my point about handicap earlier. Imagine yourself being someone with no handicap and your perceived handicaps, and think about how you can grow yourself, and think about AI as that.

A friend that's out there nurturing and taking care of you, not something that is going to take away your job or could make your life harder, but something that's going to make your life easier. Obviously, there are going to be intentioned AI use cases, but I would rather focus on what is in my control and what I can grow.

How can I grow? And so, I think. That's how I look at AI myself, and hopefully that makes sense to others too.

[00:38:55] Yolanda: That's amazing. AI is a tool for self-growth. Fantastic. Anything else, Hazel?

[00:39:05] Hazel: No, I think, you've given me a lot to think about and ways that we can continue to improve, learn and grow.

I know, I tend to ask what the gaps are. What am I missing? What are the arguments against something I may be proposing? And I find it very valuable. And it's helped me learn and structure my thoughts a little differently. But there's so much more we could be doing with the technology. I know others are.

[00:39:33] IC: Thank you to both for what you're doing. With how you're helping build the brain power and the energy within Tri-Valley with the support from Dublin and your company. I get that's out there. Thank you. Really supporting the startups finding their path forward.

[00:39:54] Yolanda: We thank you. Thank you. I think we're all a great team.

[00:39:59] IC I agree.

[00:40:01] Yolanda: So, with that, thank you so much IC for being on the podcast, for everything you've already done to help us try and nurture this AI community. Thank you so much

[00:40:11] Hazel: Thank you.