AI-powered microlearning is reshaping the way organizations engage, upskill, and empower their workforces. As the co-founder and chief innovation officer of Bites, a startup in SHRM’s 2025 Workplace Tech Accelerator cohort, Hagai Horovitz shares how personalization drives results. “When you’re able to personalize, then you're getting higher engagement. You have employees more connected to your business, leaving the company less, and you improve your employee retention. It’s a complete cycle.” Learn how AI is transforming employee learning, enabling multilingual training, and making off-the-shelf courses obsolete.
AI-powered microlearning is reshaping the way organizations engage, upskill, and empower their workforces. As the co-founder and chief innovation officer of Bites, a startup in SHRM’s 2025 Workplace Tech Accelerator cohort, Hagai Horovitz shares how personalization drives results. “When you’re able to personalize, then you're getting higher engagement. You have employees more connected to your business, leaving the company less, and you improve your employee retention. It’s a complete cycle.” Learn how AI is transforming employee learning, enabling multilingual training, and making off-the-shelf courses obsolete.
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Alex: Welcome to the IHI Project. I'm Alex Alonzo shr, m's. Chief Data and Analytics Officer. Thanks for joining us. This week we'll be exploring the transformative role of AI and workforce development and employee training. Today our focus is on how innovation and innovative technologies. Like AI powered microlearning can reshape the way [00:01:00] organizations engage, upskill, and empower their workforces.
Our guest this week is Hagai Horowitz, co-founder and chief Innovation Officer of Bytes, one of the startup organizations in shr, M's. Workplace Tech Accelerator 2025 cohort. Welcome to the AI Hi Project guy.
Hagai: Hi Alex. Happy to be here.
Alex: Thanks for being with us. To start us off, I'd love to hear a little bit about your story, what got you into tech, what got you into innovation, and then tell us a little bit about the story behind Bytes and, and I'm somebody, I've met you before. I met you when you were part of the Workplace Tech Accelerator kickoff orientation here in Alexandria, Virginia.
I got to meet you with Johnny C. Taylor, Jr. Shrm, CEO, and I loved the story the way you compared bites to the tick. Talk of employee development and I, I'd love to hear that story.
Hagai: Uh, okay. Uh, let me see where I can start. Uh, so I
Alex: Yeah.
Hagai: say that, you know, we, we started from a relatively [00:02:00] different place than most startup, uh, begin. We did not come from, uh, uh, the tech world. Um, we were doing something else. I do have my, my, you know, my education in, in technology, but I was, I was spend spending, I was enjoying 15 years of, of actually teaching.
Uh, I taught, uh, uh, GA and uh, SAT prep courses for 15 years. Uh, it was amazing. I think it's an amazing experience to actually, you know, the benefit of, of making people understanding and actually, you know, apply them for their own, uh, good. Um, and now I'm very well connected with many doctors in the hospitals 'cause I help them get there in a way.
So that's another benefit, but like. As part of that, we were always trying to, you know, to to, to incorporate new technologies and find, you know, the, the things that can assist us in, in simplifying things, in, in make things, uh, more, more effective. And, [00:03:00] and to be honest, I was, most of the time I was pretty frustrated with the existing technology as, as it was not, it was not advancing in the same pace and the same speed, like things were advancing outside of the learning and training world.
I mean, it was. You know, it was while, while outside on your day-to-day work consuming contents in, in, in YouTube shorts, in, in Instagram, and then in in TikTok came to your school or to your workplace and you were supposed to learn and train and consume information, uh, with the presentations, uh, with the reading documents and manuals. And this was the, just the beginning. And it was, it felt inappropriate. And like if I take it, I jump to today. people also already lost, lost the capability to, to consume written content. So we understood that something had to change. We dropped our, uh, me and and and t my co-founder. We dropped our, uh, day jobs teaching, and we went out to, [00:04:00] to build bytes. We started with the education world. It was a bit too early for them, as they are not the perfect. Early adopters, we'll get back to them at one point. And then we did a slight shift. We went to, moved on to, uh, businesses, uh, mostly focused on frontline employees, which are times they are of, of, you know, of younger generations.
And they actually, they were actually very thirsty for, for that
Alex: So talk, walk me through this a little bit. 'cause I, I, I've always been a, a amazed at how you highlight the, the power of, uh, bytes as a kind of a, a TikTok of, of employee learning, right? And, uh, to me that speaks to. Algorithm, but that also speaks to the, the value of a, uh, personalized learning journey.
Right. I mean, I, I sadly, I waste way too much time on TikTok, learning about all sorts of things and, you know, swiping up and swiping up and learning every as much as I can. Right. I guess, uh, I'd love to hear specifically what it is [00:05:00] that Bytes does, and then at the same time, tell us how you're leveraging AI to kind of create those personalized learning paths.
Hagai: Okay. Um, that, that's a very good question. I, I, I, you know, first of all, I shouldn't apologize for spending time on TikTok. Everybody does that. That's, that's
a reality today. So we, it's, it's relevant and it's true for all of us. I, I think, like I, I'll give you an example. Uh, short, short videos and contents existed way before TikTok and way before Instagram.
They were never that
addicting. People did not spend that much time. Actually swiping on and on and on and watching 20 seconds and 15 seconds videos. I mean, if you remember, there was this platform that was called a Vine. They had these super short videos.
It did not last, it was, it never got to be that addictive as TikTok.
So, so what's the big difference? and, and the big difference is, is exactly that. It's, it's, it's personalization. I mean, if [00:06:00] I'm gonna start from a certain video and you're gonna start from the same video and we're gonna be swiping up. not gonna see the next videos next. I mean, you're gonna see the videos that you're most likely to actually want to watch.
I'm gonna see the videos that are mo the most likely, uh, you know, want to watch. It's not necessarily gonna be the same. And, you know, since we actually, we, we kind of became spoiled, you know, if we're not getting something that's super interesting for us, we're not gonna spend any time on that. when, you know, when people come to learn professional content and, and do that in their workplace, it's the same.
That's the habit. So, you know, if if we start with the same initial intro, onboarding basic skills video, not necessarily going to need or gonna want to watch the next one the same. when you're able to actually personalize. Understand the needs of your employees and what [00:07:00] is right for them to go through and, and get next.
Then you're getting higher, higher engagement. You're getting higher engagement. You have employees more connected to your uh, uh, business. You have employees leaving the company less so you improve your employee retention and, you know, it's, it's, it's a complete cycle. I mean, you don't have to rehire more employees.
It costs you less. You have people staying for longer times, they become more qualified, they become more productive. And, and this is a cycle and we're actually doing exactly that, uh, uh, with bites. I mean, we have like the basic core, uh, contents and knowledge that everyone meets in the beginning, but after that, a feed, which is very similar to the ones you see on social media.
On the feed, you would see recommendation. Based on both the business interest of what is right and what they want you to learn next, and also based on what's interesting for you. So you are more likely to [00:08:00] actually open and go through and move on to the next stage. We're doing that by analyzing all the information that we can gather, of course, legally, which means that we know and we can, we actually gather just, just like, you know, social media algorithm.
We, we gather how much time you spend on videos, whether, whether you were trying to, to skip parts of that. Did you watch a video more than once? Uh, we are also gathering information from the questions that you ask. We have an AI tool which allows you to ask, uh, questions and get direct answers. We're also gathering information from there.
This information is applied for what would be interesting for you to watch next. It's also applied for the business for the managers to understand whether there are, you know, any knowledge gaps. That they want to complete and, and use our platform to, to build stuff around that. And, and this way is how we leverage a AI and, and mostly personalization of, of content for everyone.
Alex: You know, it, I, I'm always intrigued by the way that the data is used to kind of, uh, [00:09:00] determine what is the next natural learning point or what is the n the preference that someone might have, right. That personalized per personalization engine. I. I'd love to hear a little bit about, even just in general, kind of, uh, terms, what it is that the AI is doing, what that algorithm is actually picking up on in those data points.
Right. What, what is it that you're seeing that is really meaningful in, in making that personalization come to life?
Hagai: So I, I can't really tell you all the secrets, but I can
Alex: Sure. Of course.
Hagai: tell you a few things. Uh, we know to, know, to take a video and, and actually analyze, uh, um, you know, the major drop offs where people are dropping the video and stopping not working that anymore. We can analyze where, uh, uh, you know, people are skipping.
or less, uh, analyze whether it was paused. Um, we analyzed again, like I mentioned, whether it was watched more than once. And this is information that we collect, we collect, and then we combine that with other information that we have. Like I [00:10:00] mentioned, like the questions you ask, like, you know, in general contents that were assigned to you, you know, even if you were assigned a set of, I don't know, 10 content, uh, units, would make a huge difference.
Uh, in, in, in the order where you would watch them, mean, there's a good chance that if I'm gonna force you to watch the second content, which probably is less interesting for you now, or that for, to be the, I dunno, the, the 10th content, you would have a much better, you know, chance of actually completing your entire training and everything that I want you to, to consume.
So these, these are some of the things that we do. We do, we do, when we also do, uh, uh, sentiment analysis, since we also have, uh, um, a social collaborative interface where employees and in general users can actually add their comments, ask uh, questions, interact with each other. That's part of the learning experience in, in the way that we see that.
Uh, and [00:11:00] we also analyze a, a sentiment from there. So we, we have a lot to work with. we actually, you know, at one point. We actually built, um, a success prediction mechanism for videos. you would, you know, add a video and I would be able to tell you this video has a high success rate of actually people completing watching that or not.
Uh, this is based, I can tell you on a few things, but like, for example, we were, uh, measuring how many smiles people were smiling during, uh,
the video. We would measure the speed. In which you speak and we could tell you that there's a certain speed that would make better engaging videos. We did some of these fixes automatically.
We also do that today. So it's like, you know, it's, it's a science. Eventually it's like, you know, we, we, we feel like, uh, people are gonna watch something. 'cause we have a gut feeling that's in that, that, that, it's interesting, but it, it's not a gut feeling. It's like [00:12:00] it's based on things that you can actually find.
And it is based on, on patterns.
Alex: So, you know, one of the things that also struck me about bytes and, and some of the, the work that you've been working on is how AI enabled algorithm is one thing, but you also have an AI enabled studio to help people adapt the learning content that comes through, help it actually change, shift and do so in a dynamic fashion.
Tell me a little bit about that. What led to that, but then also how does it work in reality?
Hagai: Um, you know. Psychologists define one of the biggest, uh, fears as, as the fear of change. And, and that's, that's true for everyone. And, and you know, when you come to a business and, and they, they're doing something in a certain way and they know that it's not working for them. I mean, it's, it's not a secrets, not something that they have to, to understand.
They understand that, but then want them to change what they're doing you cannot assist them [00:13:00] in, you know, making this change. They're probably gonna, you know, cave into their fears and, and just avoid that. So understanding that we understood that, I mean, it, it's not enough that we come and say, Hey, we have an amazing tool.
You can create amazing content with that. Just start shooting videos like you do on, on, on TikTok and Instagram and it's gonna be amazing. And, and we will assist you with that. And it's gonna be, super engaging and it's gonna work, it's gonna be benefit you and bring you amazing ROI That is completely true.
like, if I cannot help you leverage the things that you already have and do the transformation for you almost automatically within, you know, a matter of of minutes without you having to like, break everything and starting from scratch, then, then we have a problem. So, you know, when AI Today enable us to build a tool, just that, that takes, takes a static traditional, uh, legacy content.
Like PDFs, [00:14:00] like PowerPoints, they can just, they upload it to our platform. Then we do a process of a complete, very deep analysis of that. And based on that, we start, you know, offering, uh, uh, scripts for the, the, the videos. We allow them to actually select the, the topics that they want to cover. Then they do the script.
The script is actually, you know, it's, it's a script. Like for a movie, for a short video. they read the script, they go through that, they approve that. Then we do many other processes in the background. I. Where we, you know, we extract visuals. If you have in the document, we take everything together and we actually build and create a video of that.
And then we let you watch that video and, uh, meet that video and have the ability to edit and change and customers with our dedicated, uh, video editor that's part of this, you know, entire solution. But then, you know, you start at one point. With a PDF with some nice pictures and nice visualizations, and you end it with a, a live video.
And it's not a video [00:15:00] of, you know, just like flipping through the pages of the PDF. It's a completely new thing. It, you know, it concentrates on, on, on specific subjects. And then we also, you know, we leverage our videos into a complete micro learning unit with, uh, the additional layers of other translations and voiceovers and, and, and, and voiceover translations.
And we add, uh, you know, the, the assessment, the engagement of the questions and key takeaways, and we wrap everything into our unique, uh, microlearning unit. And, and boom, you had, started with, with a piece of paper and you end up with a video. So that was something that we understood that we have to do that, and, you know, in the pace that AI is advancing today, it's like the, the, the sky's the limit to what we, we can do next with that.
Alex: You know, I'm, I'm not surprised by that. And you seem to be hitting upon the, uh. The golden rule that I think of whenever engaging with someone and, and, and you've got their attention, right, which is keeping their attention and making sure that you're doing so [00:16:00] through convenience and access. Right. I I think that's a, that's a, that's how you drive value.
I, I, you know, obviously you, you're playing to my, my heart because, you know, I'm a psychologist, but, uh. I, uh, I, I appreciate it when people actually understand the psychology of that consumer paradigm there. Uh, one of the things that it makes me think about too is frontline workers, right? I've, I've, I myself, have come from, uh, two different industries.
I came from the financial services industry, and I've come from, uh, the, uh, the, uh. Transportation and logistics industry. And, uh, we don't have frontline workers the same way that other industries ha uh, do. But I've worked quite a bit with healthcare. I've worked with retail and I've worked with a couple different service giants out there.
And I, I think to myself specifically about how. Finding that time and that ability to train those frontline workers can be really difficult, and especially maintaining the relevancy of what you're teaching them can be really difficult. Talk to me about [00:17:00] what advantages you're seeing with AI in helping frontline workers get training much more quickly, getting more relevant and current training much more quickly.
Hagai: Yeah, definitely. Well, you know, first of all, all the industries you mentioned are, are, are, you know, they have a very, uh, large, uh, audience of of front end employees. In general, uh, many people don't know that, but like frontend employees are 80% of the global workforce. So wherever you look, that's you, you are, you're very likely to meet, uh, frontend employees.
Um, I think AI is, is actually, you know, it's, it's shortening processes. It's just making things quicker, and it's not only making things happen quicker, it's making things happen. In a way that allows you to actually, you know, personalize, but like, not just personalize for the person, but also personalize the content in terms of what is the [00:18:00] content that they need to get.
I mean, we are using AI to, you know, to do the initial research. We're using AI to do the kind of psychological profile of, of the person we want to, to communicate with. Then we're using AI to build the content based on these two initial researches. So when we're doing that, the person who's receiving the content is more likely to actually benefit from that. I mean, the, the way we see that, and it's a, I think it's very specific, mostly specific with front end employees, is that you're delivering content to someone, it has to have a benefit for them. Not for you, I mean for you of course as a byproduct, but like first, first it has to benefit them. So if they're getting stuff that doesn't benefit them and they don't see any use to that, you can, you know, you can try to force them as much as you want to watch these [00:19:00] contents, but it's not gonna happen eventually.
They're not gonna just, they're not gonna spend time watching that. So the first thing you need to think to do, and again, profiling with AI really helps us. Is to see what will benefit the, you know, the end user, the, the receiver of the content. And, and this is where it kind of gets in.
Alex: So, you know, I, I'm thinking specifically about some of that, and I'm thinking also about the challenge of, I worked for a, uh, uh, Latin American airline as an example in my, in my logistics and transportation days. It was the seventh largest airline in the world. What became latam now? Uh, uh, before that it was Tam and and l.
Uh, and I, I think a little bit about what it is that, um, we experienced, which was having to operate in.
multilingual environments and operating specifically in what learning meant, especially in different regions, different regulations, but also file, file. Uh. Supporting or, or sticking to and being compliant with I a A [00:20:00] requirements.
And, and I think specifically about how helpful it would've been to have had AI in maintaining that multicultural and multilingual, uh, uh, kind of content and making sure that it's relevant, current and, and true to what we needed to ensure. Uh, how are you seeing that play a role with the different learning and development of your clients and, and more importantly, the learning and development that you see across multiple nations?
Multiple. Societies, what? What are you seeing there?
Hagai: Uh, I, I think it relates to what, what we were talking about before, because when, when I say shortening things, I mean before when things weren't short enough, I. They were just not done, like, you know, before ai, if I had now to recreate 10 different contents, each one in the same, in a different, in a different language and like, and have an expert for each one of these languages, and it's, it's a huge lift.
It's something that, [00:21:00] because it's such a huge, nobody does that and then, you know, you would focus on 1, 2, 3 different languages now. You just create the content in one language and boom, you have it in 150 different languages and it's super accurate. I mean, it's like, it's something that can actually be applied like instantly.
And the employees, the, you know, the ones who are receiving the contents, they can actually select what's their preferred language and it's gonna be right there ready for them. So, you know, removing that friction of having to create content actually makes people create the content, which they would not have done before.
then it makes, you know, different crowds, uh, in your workforce first, first of all, feel more connected because, you know, the, the company respects them and respects their language and respects how, how they want and, and need to get the, the content. Uh, and, and, you know, it's, it's, it's a, it's a change.
It's, it's a huge, it's a huge difference.
Alex: So, you know, I'm, I, [00:22:00] I'm, it makes me think specifically, 'cause now I'm gonna ask even more generally, what are some innovations that you're seeing in the world of AI that are gonna change what it is that you are, the way that. People learn that they develop, that they think about things.
Hagai: I think it's, it's, it's gonna be, it, it's an earthquake. It's not less than that. And, and, and it's not around the corner. We're already around the corner. I mean, I
would give, just give you one, one example, which which I can think of. Um, you know, how how many and, and some people are not gonna like what I'm gonna, uh, what I'm about to say, but like, you know how the, there are these companies who, you know, you can buy, uh, a subscription and get like courses in how to operate
the forklift and, and you know, how to safety instruction on, on how to climb the ladder and, and stuff like that.
gonna become irrelevant. Because I can, I can today. I, it's not like tomorrow, today I can [00:23:00] actually write on some tools, some or other tools. I can just write, okay, I have an employee. Um, I'm, I have a company, um, you know, we work in a warehouse and I wanna train them on, you know, the best practices for safety when climbing a ladder.
first of all, I, I wanna create and understand and create the, the, the framework for that. After that, after, you know, I gather all the necessary information. I wanna create a, a, a complete training with the videos, with the, you know, AI generated images and AI generated videos, and so that I can send it to them and, and that's it.
Boom, I have it, it's going to be a matter of minutes. And now, you know, if I have an employee who's working not in a warehouse, I mean, you know, there's a, an assembly line of, of something, so I can just, you know, change it. You know, slightly change that and, and get dedicated training. And if I wanna [00:24:00] create something that's like with compliance, with the specific compliance rules of, you know, the state of California, can just say, okay, first I wanna understand the, the basic and specific compliance rules of the state of California.
And I'm gonna have two more clicks and a few more words. And I'm gonna have a training, a complete training. So, you know, the, the off the shelf courses. They're becoming irrelevant. 'cause you know, we, we discussed a lot. Everything that has to do with personalization and customization, it's, it's, it's a prompt way.
And, and you're gonna get a much better, uh, result. You're gonna get a much more engaging result. And, uh, you know, I, I think, I think, I mean, to me it's very, very clear and, you know, this is where we're actually heading. This, this is exactly what we're building. like, you know, an an L and D expert, all they have to do is just define what they wanna teach to whom they want to teach that.
And if they have like, specific, I don't know, attire of the workers in the, [00:25:00] in the company that they also want to include in that, uh, training. it. A few, a few words. A few sentences. And, and in a matter of minutes we have something that's perfect and can be sent. you know, all the off the shelf courses.
kind of becoming irrelevant anymore.
Alex: So, you know, it makes me think, are you seeing that this is actually making HR more efficient? Uh, obviously I'm always gonna apply the lens of, of what does it do for HR operations, HR processes. In my mind, it should be making it more efficient, right? And more effective in delivering that tailored personalized learning that's needed.
Are you seeing that?
Hagai: That's, That's, a hundred percent. I mean, you know, if you look at what was happening before the AI revolution, which we're just starting to feel, HR departments would create contents. They would, first of all, they would pay tons of money for that. 'cause they would use, most of the time they would use the external professionals for that.
take them months to [00:26:00] create that. will be super invested in that, because of that, they're probably not gonna update or change anything with that content for like, I don't know. Five years. that's, that's good. When, when it has become so easy and so quick and so agile and it's so, so effortless.
People are creating more content. So contents are more relevant, they're more updated, they're more engaging, and, and, you know, the information is being delivered in, in a way more effective way with people not having to spend that much time in these super large and and costly projects.
Alex: You know, it's, the other thing it makes me think of is there's obviously this wor this sort of balance between trusting AI and not trusting ai, right. Workers, uh, and, and leaders all experience that, that sort of thing. I think. This to me is an example or an entree into how organizations and people actually trust AI more because it's about learning.
It's about, IM improving the knowledge of individuals. It's [00:27:00] about doing that and doing it in a more effective and convenient way. Do you see that this also helps build the trust that people have in their HR departments, in their, in their organizations and, and e even in ai, in, in and of itself.
Hagai: I, I might surprise you, but like I, I, I think you shouldn't trust ai. I mean,
you always have to monitor what AI is doing, so AI is there to help you. It's your super efficient assistant. It's like the best assistant you could ever ask for. It can do everything, but you shouldn't trust it completely.
I mean, it should be, moderated, it should be monitored. You should look at it, but if you compare the time that you have to spend in actually making sure that AI was doing a, good job or doing the entire job yourself. That's a huge difference. So I think AI is definitely improving tons of things and we should trust AI to a point [00:28:00] that we know that, it's there to assist us and not, to replace us.
I mean, it's, it's definitely there
for us to use that and, and, you know, get amazing results and do things that of them we were not able to do before.
Alex: So I like to throw a curve ball to my, uh, my, uh, panelists or people who join me on these on, on, on the podcast. I'd love to hear from you what guidance you would give A-C-H-R-O when it comes to consuming AI and AI enabled tools around workforce development. And more importantly, where do you see this being five years from now and six years from now, or 10 years from now?
Hagai: Wow, that, that's, that's a tough curve ball.
Alex: I apologize.
Hagai: Uh, I, I, I, I wouldn't dare, uh, you know, guess where we're gonna be like five or six years from now. 'cause you know, the pace of the change that we're experiencing with AI is, it's something that's, that's unprecedented. It's like, it, it never happened. I [00:29:00] think it's like we're living in, in very exciting times, but times that we can't really know what's gonna happen.
Uh, so it would be hard for me, but I would say like in the near future. I think that the first thing we need to understand, and I would, you know, if, if I would get the chance to, to speak to, to anyone, not just Theros. I would say that we, we shouldn't fear ai. We shouldn't trust ai, but we need to understand that this could probably, and is probably the best assistant and employee we can ever hope for, and just get the most of that.
and not, no, because, because of fear. Just, just say, okay. So I'm, I'm completely ignoring that and, and not starting to implement that. that, do it wisely. Learn how to leverage that and, and, you know, it's, gonna gain so much from that. It's, it's, it's an amazing, we're living in a revolution. It's like, you can imagine, you know, how there's this like, [00:30:00] famous saying about, uh, uh, Henry Ford that he said that I was, uh, gonna ask people.
If they want a, a faster horses or a car, they would say faster horses. I think it's there, but it's like, it's not faster horses or a car, it's faster horses or a spaceship. Uh, this is the difference. So I would go for the spaceship, but again, you need to learn how to drive the spaceship. You need to learn how to trust it, where to be careful and how to use that wisely.
Alex: Yeah, I, I mean, I, I hear you completely. I always think about what I tell my, uh, uh, my experience with ai, especially generative ai, started with my 17-year-old daughter and my 75-year-old mother asking me in the same week how they could leverage it. And I'm sitting there going, what I. What do you mean? And the thing I learned right off the bat more than anything else is it is an accelerator beyond accelerator, right?
It's that spaceship that you're describing. And the other thing is that spaceship, like any good spaceship, is going to change your perspective on things that you've accepted forever, right? [00:31:00] Time, how well you perform, what it is, the performance means, all these different things. And so I, I. I look at it as the vehicle to achieving a whole new concept of what it means to be effective and productive.
Right? And so that to me is, is where I think we land. Uh, but let's turn to skyrockets in flight as my, uh, my good friends used to say back in the night in the seventies. Uh, okay, that's gonna do it for us this week, and I really appreciate the, uh, your, your time with us here. A big thank you to a guy for sharing his expertise and deep insights with us here.
Before we say goodbye, I encourage you to follow the AI Hi project, wherever you enjoy your podcasts. If you enjoyed today's episode. Please, please, please take a moment to comment, to leave a review to like it, et cetera. Finally, you can go find all of our podcasts, all our episodes on our website, SHR [00:32:00] m.org/i ai. thanks.
for joining the conversation and we'll catch you next time.
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