Hi, I'm Jeff Rea, your host for Economic Outlook.

Welcome to our program.

We hope you enjoy the show.

Please make plans each week to join us as we discuss the region's most important economic development initiatives with a panel of experts, with recent announcements by AWS in Saint Joseph County and Microsoft in LaPorte County.

People in the region are excited about the future of technology related businesses in our region.

We'll dive deeper into data centers, cloud computing, AI, and the future of tech in our region.

Coming up on economic outlook.

Major tech announcements aren't reserved for Silicon Valley anymore, as major tech companies have found the Midwest to be a great location for future expansions.

Recent announcements about some of the largest projects in Indiana's history have captured the attention of the tech world.

Today, we're diving deeper into data centers cloud computing, AI, the future of tech in our region.

Joining me for that conversation are Rich Carlton, the president of Aunalytics, and David Cieslak, the chief data scientist at Aunalytics.

Guys, thanks for being here today.

Thanks for having us.

Appreciate you both have been here before and grateful to have you back, and especially just to have kind of this high level tech conversation today.

There's a lot it's getting a lot of attention in the media.

So we thought we're going to go to the local experts and pick their brains and help us understand this little bit more at Rich maybe start, though, if folks aren't familiar with analytics, talk to us a little bit about what you do.

Sure, analytics is an IT and data services company, so we provide AI, cloud computing and IT and analytics services to large and mid-sized businesses actually throughout the United States.

Delivered from our data center that we built about ten years ago here at Ignition Park in South Bend, where we have a robust cloud infrastructure and our own software, and talented people like David that deliver that service.

And David just for our viewers purposes, you're the chief data scientist of Aunalytics and talk to us about what a data scientist is and what they do.

A data scientist really kind of came to the forefront in the tech sphere around 2010 or that that time range, basically, a data scientist kind of grew out of the software and database, professional stack.

They've infused a bit more of the scientific methodology approach in terms of building hypothesis and theory, and then matching data to try to suit, improve and come up with useful insights, for typically for businesses to work on.

A lot of attention has been given with them because they also do a lot of development, in the artificial intelligence and machine learning spaces as well.

Great.

All right.

We're going to come back to both of you.

So rich, let's back up and maybe take a bigger picture.

So Indiana, maybe years ago, wasn't on the radar screen of tech companies thinking about doing work here.

There's kind of been a concentrated effort.

You and others have helped, you know, kind of give us a feel for the tech space in Indiana and the environment here for for doing businesses like what you're doing.

Yeah, I would say you're absolutely right.

There was there was needles and haystacks, you know, ten plus years ago, kind of when we were doing some of the things in tech in the in the early stages here.

And one of the biggest challenges we saw, and you see it from, from Indiana's, you know, whether it be the regional cities or READI initiatives or anything, it was population growth was one of the challenges we had.

And when we look deeper within population growth, we were not only not keeping our, our, our, our younger people, but particularly in tech, we weren't given enough opportunities.

people that grew up in our areas like here, were leaving and going to other jobs in technology, and those students that were coming in from Notre Dame surely weren't weren't staying here.

We also didn't have the right tax structure in many cases to attract the foundation of a lot of it, which is data centers and cloud computing, the way that Indiana taxed and handled that compared to comparative states in our the Midwest region, we were losing those opportunities there.

And so, you know, over the last ten years, and to be honest with you, it was particularly the data center side was led here by Saint Joe County efforts.

It was it was Pat McMahon.

And some people, my organization, others that that went down.

And and our organization was the first one to take advantage of that change.

And the view being that if we could build that foundation of of infrastructure and cloud, we could attract the talent, we could attract people and give them a reason to stay.

And there's been some real successes in that, not just in South Bend, obviously, but in Indianapolis and other markets as well.

Yeah, going to stay with second because, the work that's happening in tech, I know here recently the Mirror Awards for example.

So your company nominated for a mirror were tell us a little bit about kind of what that is and why they were recognizing you.

Yeah, we were and we don't do a great job of, of tooting our horn, so to speak.

We just want to want to do a great job, build a great company and serve customers and grow.

But but it was a recognition of the fact that we started about ten years ago.

We were nominated for Tech Company of the Year in Indiana.

And the vision being exactly what I said we wanted to solve for our our businesses and our region are struggling or would struggle in the past is I don't have the technology talent.

It's very hard for them to get a Dave Cieslak to work at their organization.

And so we wanted to be the forward thinking ones in innovation and in it particularly, and around AI, and not only bringing the software in the technology, but bringing the people to it.

And so, you know, we've been able to, to be the first ones that went into Ignition Park, with a goal originally ten years ago was could we hire 15 people in technology at a, at a certain wage level?

of our 250 people, 170 of them are in that region.

And we've got about 40 degrees from Notre Dame and and 40 plus advanced degrees that are working on customers in our region and beyond.

And so it was a nice recognition for some of that growth that we've had.

Dave, Rich talked about talent attraction.

And so you're one of these, you went to school here.

You stayed here.

people like you were in demand all over the country.

Talk a little bit about, just that element of it, the talent attraction.

What caused you to to stay here after going to school?

Yeah, that's a really interesting existential question you're asking me there, right?

Of course.

I ended up coming here to to Notre Dame, originally as an undergrad from Naperville, Illinois.

and honestly, the region did a really great job in terms of the school itself and retaining me for graduate school to come back to, to earn a PhD.

kind of in that those five years, I got really lucky to engage in what we had to call machine learning at the time.

that was kind of the proto term that people used for artificial intelligence.

And it was I was really lucky to, to get to study with some world class faculty.

that guided my, my research efforts.

What was really amazing is the school, kind of under the leadership of Father Jenkins at the time was in John Affleck Graves especially.

We're making some real big inroads in terms of research and having a startup and innovation philosophy, around the school.

So they sprung up a number of, of facilities like, Innovation Park, right, right across the street from the school.

honestly, it was just kind of a confluence of factors that allowed for analytics to form at exactly the right time.

As I was getting out of grad school and starting to look for a job, I, my dad worked for Bell Labs, as did my mom, as programmers for a long time.

So I have a lot of that big tech blood in me, if you will.

but my dad always talked to me about how he wished he'd kind of started.

Had an opportunity to start something, throughout his life.

And I thought this would be a fantastic opportunity.

I didn't want to have to move all the way to New York or to California to look for that kind of startup, life experience.

And I was really lucky to have that opportunity here.

And then just over the years, the companies really had a good vision for, bringing technology to, mid-size and large businesses, maybe in, in more secondary markets, not necessarily in the major markets.

and really, I've found a great appeal in all the concepts that I worked on in grad school.

Kind of mapping them into the marketplace has been just something that's been a real wonderful life challenge for me.

So kind of a bunch of those factors.

And Rich alluded to building a space for smart, talented people to come and want to stay.

The region itself is has grown fantastically.

This is maybe a strange story, but you don't have to look any further than like, the Potawatomi Zoo to see how how much that thing as an entity has just grown in the last like 5 to 10 years, like all the new exhibits and everything.

all the gentrification, all the urban renewal efforts that are happening have really made this an area for professionals to, to want to live in.

It's really exciting times, not just in the tech space, but in every space and in the greater region here.

Rich, I stay with you for kind of similar question because you're a local kid, grew up here, but but again, a guy with your talent is in high demand, whether it be somewhere else in Indiana or somewhere else across the country.

You made a decision to come here and more importantly, made this decision to invest in your business and grow your business here.

Talk to us about that decision.

Well, we we were kind of at a crossroads.

We had had a previous company that, had an exit about 10 or 12 years ago, and we had built it here.

But there was a question of the challenges that we saw out there in technology.

Could you get talent?

Could you have people that were committed to you need investors in the beginning stage.

You need you need bigger vision.

You need people who are willing to say, hey, I know this AI thing is coming or this data thing is coming, why not us?

Why can't we do this?

And you started to see.

Dave said it was a lot of factors that came to back at the same time that that could all be done here and it could be done here on a significant scale.

I mean, not only do we have phenomenal talent that grows up here in great local and public schools, that if you give them the right reason to come back, they will.

But we have all this talent that comes in to Notre Dame.

And then when you look right at the county next door, when you pretty much own and dominate an industry, that there's an opportunity to bring data and AI and other things to that, it was a lot of those of factors that said, you can build a business here, and you can build a tech business here that can be incredibly successful and can serve anywhere from around the world.

And you're not going to lack for capital and you're not going to lack for talent.

You're not going to lack for ideas.

And then when, as Dave said, you put on top of that, it becomes a really nice place to live and grow up and raise your family and raise kids and connect with people.

And there's more things to do all the time.

So, we're proud to be from here.

We're proud of what, part we've played in the continued development here.

And while we're proud of where it is, we're pretty excited about where it's going.

To be honest with you as a region and a company.

It is.

And you've plowed a lot of this field to help these things happen.

So thank you guys for for that work.

So David, let's get into the technical side a little bit more.

So this is so we're hearing everywhere right about AI and how it's going to but for somebody who doesn't know what that is and who can barely spell it, talk to us a little bit more about AI and what's happening in that space right now.

Yeah.

And it's interesting that way back when, you know, I hate to say this, but I can say things now, like 20 years ago in my career, I feel way too young to say things like that.

But I can now say things like that right.

But when I was starting out in grad school, we couldn't even really call it AI.

We had to call it machine learning.

There's something that's kind of come and gone called the AI Winter, where there have been this this perpetual hype cycle.

You could look back in the 80s and the 70s, in the 90s, and kind of some of the disappointments that AI has had that's led to you know, people kind of cashing out on that as a concept.

So it's funny that now it's, you know, we're kind of at that peak cycle again for what artificial intelligence is, is really capable of doing, and a lot of what's changed over the last several years is that you would see a company like Nvidia, which has really grown massively.

I think they're the largest publicly held company now.

And as recently as 2001, they were not a part of the S&P 500.

They actually took Enron's place in the S&P 500, which is kind of interesting.

So you're seeing a lot of the chipset, being really customized for artificial intelligence, which means it's everywhere now.

which is which is really exciting.

And what's really happened is that what I can do is able to interact more with people's data as is, rather than having to transform it.

So an example I would give would be maybe 15 years ago.

Let's say we had the roster of people at your company and a picture and, and their salary, and you wanted to create a model that predicted, based on their picture what their salary was.

And so 15, 20 years ago, I would have to look at that picture and write down, like in a column about that person, maybe their gender, my guesses, their age, my guess at their role.

And then I'd be running that through like, a model that that handcrafted data through a model, plus their salary.

And then I'd be able to make predictions in the future.

Now, what's happening is that, the models have have gone up a step and they are actually able to look directly at those images.

And now they could look at that image and your salary and render that prediction directly without having to make that intermediate kind of, encoding step of it.

So there's been a lot of, changes in that, and it's just so much more prevalent now.

people have gotten a lot more used to the idea of AI like technologies in the form of, like Google search.

And now all of a sudden we see things like ChatGPT come to the forefront.

And in a lot of ways, it's really just kind of the next generation of search technology and, and ways for people to interact with a large knowledge base of information and getting answers.

So it's it's really exciting times to be, living in the AI space, I would say.

Yeah.

You know, it's interesting Rich is we're hearing more about AI.

We're also hearing more about the need to store data.

And obviously, you've been in the data center business for a few years.

But, but around the country, like these are exploding in, in, in Indiana, thanks to the, some of the ground you plowed years ago.

Meta, Google AWS, Microsoft have all made announcements about, you know, coming to Indiana.

talk to us first about, you know, why the need for so much storage and then why a place like Indiana is attractive for those kind of users?

Well, first off, the need for so much data as Dave said, as AI is becoming more prevalent and one of the big things that have driven a lot of it is the ability to interact with very, very large data sets and large take data models.

And Nvidia, who does the chips and others, allows that to be possible because you can process a whole lot more.

So instead of having to look at at three factors of data, there are ten factors.

I can look at hundreds or thousands.

And so data creates data.

Quite often it's I'm going to combine these three existing data points.

I've created a new algorithm that I'll put a data.

And so it's kind of self-perpetuating in some of those ways.

And so the need to be able to process and store that kind of data relies on cloud computing and data centers.

You have to have very large compute environments, very memory intensive, and they have to exist in data centers.

Well, what a data centers need to be successful.

Data centers need a very robust power infrastructure.

Not only does it have to be, a stable power infrastructure that preferably is at a lower cost, but it can scale up or down and it have some redundancy within it.

we've always been very beneficial to have that kind of in our region.

That was one of the things that we considered when we were selecting.

The other thing you need is you need the ability to be able to move data back and forth, you know, from different places.

So, you know, South Dakota has really low power cost, but there's not as much fiber that comes through different locations to be able to move it through.

Well, you're transcontinental fiber.

When it was going New York, Chicago, LA utilized a lot of the right of way through 8090 an our in our interstate, train track systems.

And when we were considering locations in the same way, many of these people are as well, it's like, oh my gosh, Indiana in some of these locations has really good, fiber capabilities, has good low cost, stable power.

This makes sense for us to be able to build their the thing that you're seeing right now is a lot of it is betting on the on the future is that as David said, we're starting this okay.

AI is starting to become prevalent.

But right now, if you really look at the the people that have made money on AI is really Nvidia and the people there, everybody's betting on the opportunity to get into a business, to have it be have it be business impacting, have it be able to change people's lives in some different ways.

But the very, very largest of the tech companies are the ones who've benefited the most.

And Nvidia, even at the end of last year, was saying, hey, we're only going to ship chips because we only have so many to places who have capacity to do that.

These folks are all very cash flush right now, and so they're looking at regions and locations that they can they can take advantage of those opportunities that that we saw ten years ago, that this was a good place to be able to build your data center and housing store data.

Right.

I'm going to stick with you for a second because because it's part of just even knowing you through the years.

And as analytics was growing that, you know, I feel like if we were in conversation years ago about, people have a lot of data, but they don't know what to do with it.

And so, so, so maybe the difference in kind of what you guys were doing, I thought was sort of helping me as a company understand how to do that.

Just talked about Aunalytics role in terms of helping your customers.

Sure.

Better utilize their data.

Sure.

that was something that we had historically been in the business of storing and protecting, and we're still in that business where we manage enterprise data and information for organizations throughout our region and beyond every single day.

But where we kind of saw the future coming was, I have all this data, information, and what can I do with it and what we're going to be the barriers to that ability to do it, that there was twofold.

Number one is, David, I'm going to do it in the simplest terms.

But to build a data pipeline, so to speak, when you're talking about here's the business problem I want to solve, I want to reduce churn of my best customers, okay?

I want to get to them before they leave me.

And they're probably leaving me signals every day, every week, every month that they might be heading down that path.

Okay, so to solve that business problem, I might have data that tells me some of those things in four or 5 or 6 different systems that aren't designed to talk to each other, that are in different places, in different locations.

Once I bring them in to a single location, I've got to clean them.

I've got to organize them.

I've got to get them into a data model that somebody can interact on, and I have to write algorithms and predictions and other things that we call smart features to be able to augment that data.

Then even once I do that, I've got to get it to what we call the edge, where it's got to get to where somebody can take action on it.

Now, sometimes that actions that a report, sometimes it's sending it to another system.

Sometimes it's automating the connection, what we call automated engagement, right to taking that action.

And then the humans going to take action on it.

And as Dave said, all that data is going to be pumped back then and the machine is going to learn.

And oh, by the way, you need to do that every day at real time and at scale.

And so what we ended up investing in was building a software, an end to end platform to be able to to do that and process, we process billions of transactions of data out of this facility in South Bend and our others in the Midwest.

But on top of that, it goes back to that core problem we solved.

Even if we gave away our software for free, many of our companies would not be able to utilize it in the most effective way.

And so what we do is we provide not just the technology and the software, but the talent, the data engineers, the software engineers, the business analysts and the people that are going to help really dive in with the regional companies like we have here.

So.

So where you people have asked, well, these new data centers coming in does that.

Those data centers have always been here for some in some, some regard does for us, it's very reaffirming that they're saying, hey, this is a good area to be.

And the difference that we have is that we provide the people side of it that you need as well, to actually get the business value from it and David come your way, maybe to build on what Richard's saying.

So talk about your role in kind of the what's the data scientists and the role it plays in kind of helping to, have your customers better utilize the data they have?

Yeah, that's really interesting.

A lot of our customers, to Rich's point, really rely on us to provide almost like a data strategy or understanding applications within where data may be applicable, and helping them out quite a bit.

we've been able really lucky to build a team of data scientists that have pretty deep expertise.

So that side of the equation is usually solved when we're working with them.

But, you know, for example, a team that we might work with at a bank may have ideas about how predictive modeling may be may be helpful.

and what our team what's great about our team is we've solved the predictive modeling part of the solution.

and, and now it's bridging the gap to their specific problems in meaningful ways.

So can we leverage, some, some sort of model that might predict the future about which accounts are likely to have a precipitous drop in their balances?

And then based on that, we can also align that with historical actions or interventions at the bank or financial institute might have taken, and using that in order to kind of drive, actionable insights out of, out of their data directly, into, into making that something that that can really improve or help their business out.

So a lot of it is really about finding the areas of business value.

typically and then and then translating that into something that's a technical problem.

and delivering value, every day.

To Rich's point, on billions of transactions daily from, from some of our institutes that we work with.

Great.

Rich let me come back your way.

So you mentioned as you were, citing your location initially, power was was critical.

And I think of like downtown, for example, the Studebaker also needed power.

And, so, so a great power system already there.

you mentioned fiber.

The railroad goes right through there.

And so, so, so as data centers are happening everywhere, there's a little bit of, pushback from some communities.

Sometimes it's, you know, can the power grid handle all of these that are popping up everywhere?

Can our water system handle these data centers?

Need water talks a little bit about just some of those kind of things.

even the water, like I hear, I don't understand what you do is water.

Are those are fair questions and great and great concerns.

And the community should look at that because there are things that you can do from a design standpoint.

Now, the the first thing I would say is, is the computer systems themselves.

The hardware continues to get better all the time in the amount of I mean, we can process so much more using so much less power just in that, just in the systems themselves.

But you're continuing to need more of them.

So there's still that that self perpetuation.

Now they generate a lot of heat.

So you say, well why why is water need a why is any of this.

So when you look at you've got a couple factors of electricity usage.

Number one, you've got electricity usage to power the compute.

Because when it's processing it's churning.

Now when it's churning in the same way, your laptop sitting on your lap, sometimes you hear that little fan kick on, you feel hear it's generating heat to where cooling the facility and displacing that heat and getting that out of there is one of the biggest drivers of electricity usage, too, and it's the biggest driver of the water usage because of how you do cooling.

Now, I don't know how the others are being designed to come in, but what, you know, some of the things that we looked at was, was, number one, we use a closed loop system for our, for our water.

So any of our water that comes in through our condensers, it cycles through five times before I ever goes back into a treatment cycle.

So that's one of the areas that that lowers the power usage considerably.

The other area is, and I know it's strange to say on a day like today when it's 90 plus degrees, but we also have some alternative days to this kind of weather to where when it is cooler outside, the design that we utilized actually drains all the water out of the system.

So over 50% of the year we're not using any of the water, we're actually using the the weather that we have that can occasionally be below 40 degrees to be able to displace our heat and be able to do it with almost no electricity use, to be able to do that in very little electricity use and no water usage whatsoever.

So there is environmental design things that you can definitely do into your consideration of your design and, and the power grids themselves that, you know, they're continuing to look to and adapt on it.

And, and we do have a very robust infrastructure in this region.

as you mentioned, we actually get fed at our location at Ignition Park.

it was where so much Studebaker manufacturer done.

We've got two substations that feed.

It's very redundant.

You've got Indy Turbo that's in there now that is doing some really high end research things.

And so, you know, the grid is is handling that very well.

And hopefully it will continue to do so for everyone else.

We're starting to get to our last 3 or 4 minutes here.

So let's let's switch to the workforce real quick because I think of your work like I want to think of two things that you need.

And I'll let you either one, that sort of I would call it the the Davids of the world, the like the data scientist and the software developer and that kind of stuff.

But then it's sort of the, the infrastructure side, right?

Somebody's got to build this.

Somebody's got to wire, someone's got to make sure the machines go.

Somebody's got to splice the the fiber together.

Those kind of things.

Yeah.

Talk to us just a little bit about just the jobs.

and maybe some of the skills that are helpful to, you know, I'll kick to Dave to specifically handle some of the data engineering and software I but but you know, I mentioned a little bit about our, our team earlier.

one of the things that we've been really proud of is, as I mentioned, we've been able to keep Notre Dame talent.

A lot of those degrees here.

We've had folks from we've got folks who grew up here, went to IU, Michigan, Michigan State, Purdue, any of those that have that have come back and even some that didn't have any connection here.

We have people from Stanford and MIT and Caltech and those.

But beyond that, our software team is full of people from IUSB that have done a phenomenal job in training people.

The other thing is, we have lots of folks from Ivy tech who have come through with our with our service desk and our help desk in our infrastructure, that Ivy tech has been a big producer of talent for us.

And another area, everything that we do has to handle has to be around security.

I mean, it's it is, it is.

You've got to be secure.

The level of things that we do because of our, our customer relationship with, with AM General and people in banking and health care and others is is at a national scale.

And so much of our security team came from the US military.

The military does a phenomenal job in training people.

I mean, when we interview somebody and they talk about setting up a network in Fallujah, we get great comfort that they could probably set one up for for a security level for our customers in South Bend.

So, David, maybe in hour, last minute or so is just advice to folks who are want to get in this tech space, who maybe want to be data scientist, maybe want to work on the infrastructure side, you know?

Right.

There's nothing stopping anybody right now from doing that.

There's plentiful amount of online resources, whether it's online courses, cloud computing platforms, whatever.

start today, create a project.

There's something called GitHub where you can put your code, put put stuff in GitHub, find something you're passionate about, just start writing code.

And that's that's the first step.

and you, you know, if you want to get better at something, get 1% better at something every day, you're going to you're going to be an expert in a couple of years if you just practice on your, coding muscle, as it were.

Yeah.

No, this is great, guys.

Appreciate the conversation today.

This is we're really excited about the area, but really appreciative of the good work you've done in the community to kind of plow this ground, to sort of help set the stage for a, for technology and really to help develop all the programs to train and all that.

So thanks for sharing some of that with us today.

Community's been good to us.

Thank you.

That's it for our show today.

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