Ethics, Empathy, and AI: A Conversation with Arshad Hisham of InGen Dynamics

Arshad Hisham (00:00):

You’re kind seeing all unwind in real time as we speak. I think the bigger thing is that I feel that AI and reports are like the new computer. It’s going to increase productivity by a crazy factor. It’s not like two or three XI think we’re going to see 50 XA hundred x in recent productivity across the board. Every field, accountants, engineers, lawyers, everybody will be using it. Increased productivity

Scott Kinka (00:58):

By 2035, automation and robotics powered by AI will revolutionize industries from healthcare to education, enabling businesses to solve some of the world’s most pressing challenges from labor shortages to environmental sustainability. As the future of work becomes more dependent on intelligent technology, the race to create responsible impactful solutions is more critical now than ever. And that’s where my guest comes in. Welcome to the Bridge cast. Today I’m thrilled to sit down with Arshad Hisham. He’s a serial entrepreneur, innovator, and the founder and CEO of Ingen Dynamics. They’re a company at the forefront of AI, robotics and automation solutions. With the proven track record of building multimillion dollar businesses, Arshad has been a driving force in revolutionizing industries with products like their current modular service robots and real-time monitoring and event detection process products, I should say addressing global challenges and improving human lives. AADs work has garnered recognition across the globe from AI and robotics innovations to his role in shaping the future of ethical technology. Today he’s here to share his insights on how these new technologies are transforming industries, the ethical implications of these technologies and how leaders might think about automation and robotics in their own businesses. Arshan, welcome to the show.

Arshad Hisam (02:19):

Thank you very much for that, Scott, and really look forward. Thank you for the introduction

Scott Kinka (02:23):

I do on the description there. Okay,

Arshad Hisam (02:25):

Pretty good. Pretty good, thank you.

Scott Kinka (02:27):

Alright, well before we jump into your work, I’d love to start just hearing about maybe a defining moment in your journey that shaped the way you think about leadership and innovation. Just give me a story that’s shaped who you are today and how you think about innovation.

Arshad Hisam (02:43):

Sure. And for that Scott, I think we need to go pretty long back when I was 11 years old, I think. So that’s when I read the first book on asmo, the foundation series. So that kind of influenced what I wanted to do growing up, the intersection of science, ethics and humanity. And that’s what I wanted to build from a very early age and that’s what I ended up doing. So that’s been my philosophy ethos since age 11.

Scott Kinka (03:11):

Fantastic. So you’ve led transformative projects across multiple industries, right? Healthcare, education and your work’s very often centered around creating solutions that are people focused that help people. How has your vision evolved over the years? I mean especially with the focus on AI and robotics right now, still people centric. Is that generally the driving vision by what you’re doing?

Arshad Hisam (03:35):

Absolutely. I think it has even become more people-centric over the last five to 10 years compared to earlier because people have realized that a collaborative approach is a way forward as the next phase rather than a full on automation. So definitely there’s human in the loop coming in. So this is what I think the majority of the changes and if you see the three things that we make sure our products are affordable, intuitive, and practical. And if you see the middle one intuitive, it’s very important, especially with AI and robots, if it’s not intuitive, it is difficult to kind of implement a rollout. So definitely it is moving to more people-centric roles and positions and it’s kind of fascinating how it has evolved over the last five years and come back to the last 20 years. The last five years has been massively accelerate.

Scott Kinka (04:27):

Take me back though. So how long have you been leading? Well, when did you found Engine?

Arshad Hisam (04:33):

It was in 2015. So we’ve been around, this is the 10th year, but I started companies in 2007, eight, so that’s when I started becoming an entrepreneur. So I had four companies before Engine. I sold my, exited my last startup to a subsidy of General Motors and I had an enterprise software company before that and a vehicle analytics fleet automation company, an online games company and a hardware point of sale company right at the started engine 2015. And we’ve done fairly okay since then. We’ve got a lot of press traction, got a pretty decent revenue commitment, been working a lot with the government, including the UK government. We’re doing a lot of work with the UK government specifically around healthcare and other initiatives. So yeah, it’s been a fascinating journey the last 10 years.

Scott Kinka (05:19):

And wow, I mean that’s a varied background there. What really was driving your turn in 2015 towards AI and robotic automation?

Arshad Hisam (05:31):

I thought the 2015 was an interesting pivotal year because I kind of saw what is coming in five to six years, the lowering cost of a lot of sensors and robotic parts, the exploration of ai. So I saw a lot of opportunities and we were lucky to be very early on in the field. And I think in the specific sectors I think around healthcare, elderly care, the medicine, special needs surveillance, and then there’s hospitality including surplus delivery. So I think there are some very, very burning near term use cases, but now you can see humanoid every days. It’s hard not to see robots nowadays, but that does not the case five years back. And I still feel that the next five years we’re going to see a lot of this reputation on the neo used spaces, which I think would be very, very interesting.

Scott Kinka (06:23):

Got it. So we’re sort of at this, you’ve been at since 2015, and I think a lot of people are listening to this right now are like, we’re right at the edge of the robotic era. We’re just starting to see these technologies come to market. Did you guys spend most of your time getting to market now in the time since 2015? When did you’re out there delivering solutions to customers today, but tell us about that research and development, I mean all the time that went into delivering the products that you have today.

Arshad Hisam (06:54):

Sure. I think robotics as an industry and to do a startup is pretty brutal because it’s a hardware product. Selling to business, it’s a kind of very tough thing to pull off. So we had our own journey. I think every startup has its own journey. So we kind of navigated along the way. We invented a lot of things that didn’t exist because I think we figure, I’m not just talking from a technical perspective in terms of business models as all right, we were kind of figuring out what is the right way to price it, what’s the right way to lease it, and what are the ancillary revenues we created? And in fact, our education stream started out in 2019 because we saw a lot of need for people to be trained and skilled in this. So that’s an main offshoot of a company now. So I think we evolved along the way and I think it’s been fascinating to see all this develop and breakneck speed and it’s a very exciting future. I think there are some scary parts to what’s coming, but I’m an entrepreneur, I’m an optimist and I want to be in a role that will make a difference, but I’m fairly sure that it’ll come to mostly good for everybody in the long run.

Scott Kinka (08:10):

Let’s just get right at it because we’ve said the word robot a couple times and we’re not talking about ag agentic AI right now, right? We’re talking about actual robots in your business, that’s number one. And two, you said the word scary, and I think a lot of people, certainly those outside of it are equating those two things together. Our listeners may be like, well, the robots are coming. So let me just ask this. As AI moves forward, I mean we know where we’re getting to. Artificial general intelligence is on the horizon. So as you think about it in your business, but also as an IT leader, how we should be thinking about it, where do you see that line between technology’s role as helper? You’ve been building human-centric technology for some time. Where’s that line between the technology’s role as helper and really as sort of autonomous decision maker? How do we think about that in the coming years?

Arshad Hisam (09:04):

Yeah, I think it’s a very tough question to answer because we kind of seeing all unwind in real time as we speak. But I think the bigger thing is that I feel that AI and reports are the new computer. It’s going to increase productivity by a crazy factor. It’s not like two or three x, I think we’re going to see 50 x, a hundred x increasing productivity across the board. So it’s going to be like the new computer. So every field, accountants, engineers, civil engineers, chartered accountants, lawyers, everybody wouldn’t be using it. Increased productivity, there would be some pain in the shutdown term because I think a lot of this, I think there’s an interesting study by the McKinsey and OECD that by around 20, 30, 70% of all task definition in every job will contain a fairly high amount of automation. So we are kind of looking at redefine every single job that is out there and that’s happening in a much faster pace compared to previous generation like our parents, our grandparents, great, great paths, they had a whole lifetime to adjust, but this is going to hit us in five to 10 years.

Arshad Hisam (10:15):

So that’s a massive opportunity, but that’s also a problem if you’re not ready to rescale.

Scott Kinka (10:20):

Well, so that brings up an interesting point, two questions. The first one, while we, I’m walking right into the landmines this point, but what does that, and you’ve spoken quite a bit about the moral and ethical obligations around the development of this technology, so we’re going to get hit with it. You said it could be problematic for those like unable to rescale. I mean, how do you think about what truly are the moral and ethical dilemmas facing us over the next five years as we’re adopting to this rapid rate of change?

Arshad Hisam (10:58):

Sure, and I think you pointed out a very significant one right at the beginning is autonomy. What degree of autonomy do we give the systems and is there any legal, this is happening all over the us. Is that one of the reason a lot of the autonomists not given to agents and robots is that it becomes very complicated legally if there is an incident. So we need to overhaul the legal system making the decision. Is it the programmer who wrote the robotics algorithm or the agent who will be responsible for a mishap because the machine cannot be held accountable, so who’s going to take the pipe? So this is a bigger problem. This is one of the reason that this’s a lot of delay and approval including for drones by the fa. So this is kind of a classic problem. So autonomy, the legal side, how is it going to handled is one and second is a more of a philosophical slash interesting point is that a lot of the tasks for humans gives us purpose.

Arshad Hisam (12:04):

We don’t need to automate everything. It doesn’t make sense to automate everything. So what does the end goal, just because everything needs to be automated, it need not be made automated. I think the end goal is to improve quality of life for humans. It is not about increasing productivity. Can we lead a better life? Can we build a life that is more meaning, more purpose? And that’s where I think we need to design a world where all this technologies and tools work for our better rather than just blindly increasing productivity and efficiency because that’s what being a human means.

Scott Kinka (12:40):

Yeah. I’m confronted with this thought of the kind of legal and ethical dilemmas around this technology being planet wide, right? Like existential, do you see concern that we’ve got broad based cultural differences, we’ve got broad based ideological differences and a couple different camps around the world and yet we’re all going to have to, if this is going to work, we’re going to largely have to subscribe to the same set of rules around, I don’t know if controlling or containing is the right word, but I think you know what I mean, controlling that level of autonomy. What’s our risk that we don’t all agree and how does that affect ultimately the trajectory of autonomous systems?

Arshad Hisam (13:32):

Right. This is a great question and I would love to point out an analogy. Historically, if you see every new technology that has come in, let’s look at the automobile which came in. There is a period of early adoption where there are a lot of events or accidents that comes in and it causes some damage. But usually we can kind of get around this period because the boundary conditions are not outlier event that can cause an extinction level threat. But the challenge here now is that with a lot of the new AI robotics and automation coming out, the first five years in adoption could create some boundary conditions that can be very SC extinction level threats. So that’s very different this time around. So do we have mechanisms to control and that’s more of a threat than yours. Some AI turning Cynthia and turning, I think they’re rubbish.

Arshad Hisam (14:30):

I think that’s not going to happen in the next five to 10 years. I think the bigger thing is that the first threat is more about what are the boundary conditions in early adoption that will lead to a catastrophe? And we need to be very, very carefully prepared for this. And we need to look at this problem as a global problem. As you rightly, this is not a local problem, it’s a global problem. We need to have a framework that will help us address this and move in the right direction. So I think that’s the way to look at it. And that’s significantly different this time because if you have an AI controlling, let’s say an nuclear power plant, that’s actually happening by the way, I’m sure you’re reading the news. And then I think if there is a boundary condition that triggers something, it’s a sign switch movie come true, it is for the horror signs and that’s actually happening. So can we have checks and balances in place to filter out all the boundary condition of all the AI technologies coming out in the next decade? This is a big thing that we need to happen.

Scott Kinka (15:37):

So the hot take there if I read that back from your perspective is you’re not worried about the singularity conscious robots deciding it’s time to kill the humans. You are more concerned about irresponsible use or lack of appropriate boundary conditions around our creations today in terms of not less them deciding on their own and less us being really bad prompt engineers. I’m oversimplifying. Well, you know what I mean?

Arshad Hisam (16:09):

I think that’s a bigger threat. I think the second one only appears a bit later on. So we need to pass the first phase and there are dangers there, so we need to handle that first and make sure that we’ll be good. And then we can look at the singularity.

Scott Kinka (16:23):

You just said it’s not five to 10 years you want to hot. Take me how many years, when do you think we start thinking about it and what do we know is really the issue?

Arshad Hisam (16:33):

And again, I mean what cells are happening? My worry is just like once AI gets redefined, once AI gets adopted to mainstream, it becomes common tech. It’s not ai. So AI has been constantly redefined since nineties, like the character or technician phase, these are all now just tech. You don’t call it ai. So maybe the singularity will also be similar. Maybe there are levels of singularity will get adopted and it may a moving target potentially. And what do you define? I mean there is no common consensus on how do you define singularity. So that’s also another problem. How do you define it? I mean Microsoft, it has something that generates a hundred billion or some in revenue, they have a revenue flag in their agreement, open ai. But is that the definition of singularity? Is that the hammer

Scott Kinka (17:26):

Or is it the touring test at the end of the day on some autonomous system? Yeah, I hear you. And then that’s kind of my point about maybe we wouldn’t know. I think it just becomes, I like your point about it ultimately becoming accepted technology. We think this is going to be this heralded moment where AI wakes up like frosty the snowman and says happy birthday. That’s not how this is going to go. Right. No, I totally understand. Let’s jump back to innovation for a moment because you’re doing some super cool things around robotics in particular. I mean you have a product that is effectively a service robot today, and I think I read used cases are all over the place there. It’s in hospitality, it’s in healthcare, which in and of itself maybe has its own ethical dilemmas. Just tell me about a couple of things. One, where you’re really at in the growth and the development of that product, number one, and then maybe just what’s been the thing that’s occurred that surprised you in that process that maybe you weren’t expecting to occur as you were working through the process of building effectively a service robot product?

Arshad Hisam (18:39):

Sure, and I think, let me start with the definition of a robot. I think there are two schools of thoughts in robotics. One is that you have a general purpose robot that does a lot of tasks like Rosie from the Jetsons, right? That’s one school of thought. The second school of thought is that every physical object down the line in a decade would become a robot. Like your mirror, your dressing room table, your chair, the sofa. This could have intelligence and that’s what Jensen Hong calls physical intelligence. So I think that’s a classic thing. There are two schools of thought. So I think we don’t know what’s right and a lot of development, probably some part of both are right? And I think when we developed some of the products, what we really found fascinating is that there are a lot of non-technical paths like the social robotics aspect because there’s a lot of psychology.

Arshad Hisam (19:34):

Is the robot as the same height? Is it mirroring your behavior? Is it looking back? Does it look empathetic? These are the soft things that matter. It is less about efficiency and then the willingness of people to adopt it as part of a workflow is very important. Do they really understand, is it going to really add value? Have you buy in and especially in healthcare like telemedicine, elderly care, special needs. I think this becomes a very, very important part. So I would say a lot of things around robotics and I think around AI is around the soft stuff of social robotics and pretty much mirroring conversation. Uncanny valley, don’t be too creepy, don’t preempt. So just have the right balance. And also again, there is a classic saying with reports, you buy a report, it’s very interesting, then it gets boring and then it becomes very irritating in very short time. So this is a classic trajectory of other robots. So all that part is what I found in my journey really surprising. It’s not a technical problem, this is more of a psychology versus social robotics problem.

Scott Kinka (20:53):

It’s a design ethos more or less into what it is that you’re doing. So it’s like engineering, I was going to say engineering humanity, but that would be the wrong thing because that it’s anything but you engineering it to feel more human to create acceptance by the human party in the transaction with the robot. So I saw some of the prototypes that had the screen on the top and it’s got a face and it smiles. Or maybe that’s why we often picture robots with legs or hands or a face or the kinds of things that so they feel like they’re interacting with something that feels human, but it’s really an adoption challenge, less a technology challenge.

Arshad Hisam (21:38):

Sure, sure. And also it’s like how much, I mean, and the bigger challenge also Scott, is that you kind of know how to interact with the phone with a tablet or a TV or a vacuum cleaner because you know how it works. If you put a new robot in, you don’t know how to interact with it. And I’m talking about very smart people. I’m not talking about just even very smart people. You don’t have a frame of reference if you do X, y, z, this is how to reciprocate. This is a UX ui. If it blinks, you need to be standing. And so there is a whole language around how you need to work with this, which is undefined.

Scott Kinka (22:16):

Yeah, it’s so interesting. I thought of this story that I read last week about the amount of computing power that’s being leveraged in spoken model LLM access around the AI infrastructure, needing to respond to things like please and thank you, which are totally unnecessary to the interaction. But you’ve gotten your answer and you tell Siri, please thank you. It has to process your thank you and come up with a reaction. When you drive that all the way down to power, sustainability, energy, it’s really crazy that we’re generating so much computing around effectively a false two-way humanistic interaction. Like saying please or thank you or how’s your day to the AI that doesn’t really care at this point. Maybe one day, to your point, we don’t know it’s sent, it feels badly, but right now we’re relatively sure it’s not occurring. But it is an interesting parallel as you think about getting people comfortable with the use cases. Let me hit you with a different one on this. What was the biggest challenge that you’ve had to overcome in the creation of your service robot solutions and how did you overcome?

Arshad Hisam (23:45):

I think it’s an adoption of the products. And I’m not talking about the user adoption. I’m talking with from the business perspective, how do business make sense of how to pay for this units? And that needs to be daily orchestrated because a lot of the businesses has what they call the gimmicky robot budget. So you can buy 10 robots as a gimmick, put it out there. It’s nice, but is that solving a real problem? Why not really? It’s just good. They can release in the newsletter, they bought some robots sitting on the thing. It’s great, but it starts so that’s not scalable. So the trick is in everywhere you’re doing, you need to find out what is a use case it’s solving, is it scalable? Are they willing to pay that money for it? And is there something there? And this is not us, this is the robotics as an industry has struggled with it over the last 30 years.

Arshad Hisam (24:51):

And the most successful robot still is a Roomba, which by the way went bankrupt and going through their incentive problems. But the most successful robotics company is Aruba the last 30 years. So what that does tell you, so I think robotics still is missing clear cut killer use cases like the spreadsheet was for the PCs in the eighties, that was a killer use case. So robotics still needs its killer use cases in each of the spaces. And that was a big learning for us to fit in what we can identify per customer per use case, what are the problems we can solve with robots taking away the gimmicky factor.

Scott Kinka (25:32):

Yeah, well and then how do you drive that into the balance sheet of the business, right? I think you can say that just about any technology, but we’re seeing it a lot in just general use AI right now, which is our customers are saying, well I’m not going to replace people. That would be an easy mathematics equation. Remove this expense, add this one. But I don’t know that we necessarily have the measures in place as employers and in business today to measure, truly measure productivity. You say we’re going to get better productivity, but we’ve always paid people for an eight hour day regardless of how much wood they chopped over the course of the day. We don’t pay by the piece of wood, we pay by the hours worked. So it’s hard. You don’t know really how to do that, right? Or it’s a significantly lagging indicator later on of widgets sold production.

Scott Kinka (26:26):

But there’s not a sort of a direct line of I’m removing this expense and adding this one in, which makes it hard. I think that’s a good parallel to maybe my next question and then we’ll have a little bit of fun because we’re running up on time. Our listeners of this show are CIOs and their IT leaders and they’re directors of IT and inside of businesses and they’re hearing all this stuff and they’re like, yeah, that’s way off for me. Or maybe they’re just thinking about their adoption around AI right now and it’s exciting and daunting at the same time. We’re all tech people. We want to play with toys and we want to make stuff happen. To the point of your 11-year-old story, if you’re that IT heater and you’re looking at all this and saying, not from me yet, what’s the first step they should take? If you’re thinking about their AI journey or their automation journey and they’re just concerned about getting overwhelmed or falling into or overindexing, whatever that is, what would you do first if you’re in it that are thinking about all of this?

Arshad Hisam (27:32):

Yeah, I would love to answer this with an example. I actually met a CIO of a hospital chain very recently and he said, we are not planning to adopt ai maybe in the next one or two years, we don’t want to use that. And you know what? I was actually speaking to their workers on the ground, the receptionist, what they were using on the ground. They were using chat jpp, they were using Gemini, so they were already using ai. So that’s a big eye opener because it’s not that you can have a strategy that you’re not going to adopt this, but people are already using it in this productivity. They’re already doing it. So you need to have policies around how this will be done, this will be implemented. And that’s kind of not an option. Unfortunately anymore everybody would need to take up on agents and robots are nothing but physical agents.

Arshad Hisam (28:25):

So the robots are also kind of the same track. So I think this is a required paradigm shift. And even if the leaders decide not to take it, the organization is already using it at some level. So this is not optional would be, and this is something I’ve seen speaking to a lot of leaders in different sectors around the world. It’s the same thing that’s happening with this wave. So there’s a lot of an option and if you don’t have policy structures and plan around it, you’re putting yourself at risk with the organization set on all those items.

Scott Kinka (28:56):

So step one is accepting that it’s happening, building governance really around it and protecting yourself. But then you can start to uncover use cases, why are my employees using it, et cetera. Listen, it’s going to happen to you regardless. So I get it. We’ve been making a lot of predictions. Let’s have some fun as we’re wrapping up, if you wouldn’t mind, I need a bold prediction from you if you would just give me something next 12 to 18 months that we can look back on together and see how right you were. And it doesn’t need to be about tech, it can be about sports, it can be, it doesn’t matter, whatever you feel it.

Arshad Hisam (29:32):

Maybe I’ll stick with tech. Let me see if I can, I think we’ve going to see a slightly going to see a lot of adoption of humanoids in the next 12 to 18 months. A lot of places, and not all of them may be successful, but we’re going to see a lot of humanoids coming to the market and I think it’s going to become a common site for the next 12 to 18 months.

Scott Kinka (29:59):

I like that. Alright. Two, give me some kind of hot take on AI or robotics either or where you have a strong opinion that you feel like others in the industry would push back on. Give me something controversial, an opinion that you hold.

Arshad Hisam (30:17):

I think AI is going to create more jobs. So that’s something that I think it doesn’t write well with a lot of opinion. I think AI is going to create more jobs because it’s going to create a lot of ancillary task definition and especially in the first five to 10 years. I also feel that AI will introduce a lot of problems and bugs in the system. You may need more people to fix it. So there are two sides to it and plus it’s going to increase so much productivity that we are going to look at a different paradigm. So AI will create more

Scott Kinka (30:50):

Jobs. I like that. We could probably do an entire episode on that one, so maybe we’ll come back and we’ll do that. Alright. We mentioned a couple times existential risks to the human race. You can’t have an AI conversation without going there someplace. Whatever that future looks like or whatever sci-fi you said that you have your sci-fi moment, whatever sci-fi you choose to watch, whatever that dystopian future is has occurred. And you have only one app that continues to work on your phone, you get to choose which one, which is it?

Arshad Hisam (31:25):

I think it’ll be my Kindle app for reading.

Scott Kinka (31:29):

So you’re like, I’m just shutting it down. I’m finding myself a cave and I’m entertaining myself with myself.

Arshad Hisam (31:34):

Absolutely.

Scott Kinka (31:35):

I like that. And then I think last one, before we get in there, I always love to ask this question because I think people are learning about you, they’re learning your personality, they want to learn a little bit more. What are you reading or listening to today? Where are you? What’s got your interest?

Arshad Hisam (31:50):

I’m actually reading a book on Buddism You and it’s kind of interesting and it’s a nice book. It says Why Buddhism is true. It’s a very, very nice book and it speaks about how int intelligence, there are two books I’m reading. One is called Intelligence Brief, history of Intelligence’s, a very fascinating book and that speaks about how intelligence evolved from a single cell organization and why we have the brains that we up. And the second one is, which is Connected is why Buddhism is true. So these are two books I’m reading at the moment.

Scott Kinka (32:28):

I love it. And then so lastly, I’ll just ask you, this was great by the way. We had a lot of fun. Where can our listeners find that a little bit more about your work?

Arshad Hisam (32:36):

So you can always have a look at a website, company website@enginedynamics.com. You can have a look at my personal website@usherthehan.com and there is a lot of information. I try to be responsive if anybody reaches out on my personal email or on the company, I’ll try to respond within a week or so. So this is something that I try to do, but happy to assist and happy to answer anything that comes my way.

Scott Kinka (33:02):

Amazing and a great conversation. This ended ended up being really fun. I appreciate your time. And where are we speaking from? Where are you today?

Arshad Hisam (33:10):

I’m here Singapore. So I do have a lot of travel, but I’m back in Dallas next week. I’m actually speaking at the T headquarters in Dallas next week. So I think

Scott Kinka (33:20):

We’re just trying to schedule them. They’re in pretty frequent participants on the pod and a big partner of ours, so I’m super excited. I want to hear more about that after that’s over and we’ll be happy to have you back in the country. Enjoy Singapore and thank you for being on the pod. It’s been a lot of fun.

Arshad Hisam (33:37):

Sure. Thank you very much, Scott. Thank you.

Scott Kinka (33:39):

You got it. And that’s a wrap on this episode of the Bridge Cast. If today’s conversation gave you something to think about, hit subscribe, believe us a review, share it with your team, smash that like button, whatever that is, and we’ll be super happy to see you on a future episode of the Bridge Cast. Thanks so much. Listen, if you made it this far, there must have been some good content or you’re just a fan or a relative of mine. In either case, we appreciate you spending your most valuable asset with us, your time. We don’t take that lightly. We’d also like to say one more time that we’re appreciative of Bridgepoint Technologies and their belief and sponsorship of this show. We hope that if you or someone you know is thinking about your company’s digital transformation or simply the next IT project that you may not have the resources budget or time to get to, I’m sure that bridgepoint one of the country’s fastest growing technology advisory and procurement firms can help. Check out bridgepoint technologies.com. Don’t forget the E on bridgepoint or simply reach out to me at kinka, S-K-I-N-K a@bptthree.net. Also, take a minute please if you would, to give us a five star review on your favorite platform. It helps give us the visibility to reach other people like you. Thanks for listening to this episode of The Bridge. I’m Scott Kinka, and until next time, there’s a lot of noise out there in business and in life. Do what you can to be the signal. Thanks.