Steve Carlin Podcast Transcript
Steve Carlin joins host Brian Thomas on The Digital Executive Podcast.
Welcome to Coruzant Technologies, home of the Digital Executive Podcast.
Brian Thomas: Welcome to The Digital Executive. Today’s guest is Steve Carlin. As CEO of AiFi, Steve Carlin leads a company at the forefront of spatial intelligence with over 280 locations deployed worldwide. He has built a steady career in commercializing and scaling brands and businesses, and is an advisor to more than half a dozen startups.
He has held leadership positions at companies such as P& G, Ubisoft, and Facebook. Most recently, he was president and chief strategy officer at SoftBank Robotics, for which he led the go to market strategy for its retail facing autonomous solutions.
Well, good afternoon, Steve. Welcome to the show!
Steve Carlin: Thanks, Brian. I’m excited to be here.
Brian Thomas: Awesome. I appreciate you jumping on, making the time, hailing out of the great city of San Francisco. I’m in Kansas City, so a little bit of a time traverse here across the continent, but appreciate the time, like I said, and I’m just going to jump right into your first question.
We want to get your story out to our audience. So, Steve, your career spans leadership roles at industry giants like P& G, Ubisoft, Facebook, and SoftBank Robotics. . What inspired you to pivot into leading AIFI and what excites you the most about the company’s vision for spatial intelligence?
Steve Carlin: Well, you know, usually you start by working with bar soap and cosmetics and then go to batteries and then go to video games and then go to robotics and social media in between.
So it’s a pretty normal career path. Obviously, the funny thing is, there is actually a method to the madness there. I was given. Advice years ago, and I give this advice now that nobody’s going to own your career path, but you so to the extent you can, you should try to figure out what it is that you are interested in doing for a career and try to build a career path towards that.
And in my case, I’ve always been drawn towards leadership roles. And so I built my career to be in leadership roles. Positions to, to run companies, to be the leader of these businesses. And so I felt the best way to do that was to try to get as many different kinds of roles and experiences as I could. So the throughput there is just continuing to add on different experiences.
So that now that I’m sitting in this role, I understand how it all fits together, whether it’s marketing or sales or the back office, accounting, legal, you name it, to have a sense of how to put it all together, to be most effective and efficient in this role. So that was the thinking. This is just a natural progression.
Into that, it’s not that I was necessarily looking to run an AI company or spatial intelligence company. Uh, it was just the opportunity that presented itself to me, given the experience I’ve had.
Brian Thomas: Amazing career, spanned a lot of different, not only industries, but different roles and different companies, very large, obviously.
But I appreciate the share and that certainly has contributed to your success in your current role. So I appreciate telling us your backstory and Steve as a leader with deep expertise in go to market strategy, what do you see as the biggest challenges and opportunities in commercializing AI powered autonomous retail solutions?
Steve Carlin: Sure, you know, the first thing I would say is, uh, educating the buyer of this kind of technology. The reality is, this is new to the world kind of stuff, and I’ll explain why in just a second, but the issue tends to be whether we’re working with a retailer or whether we’re working with other industrial players or quick service restaurants or Airports, what name you, they tend to think immediately because of all the noise that’s out there with other technologies that they fully grasp what this technology does and the reality is they don’t because it didn’t exist until this point.
And so let me be a little more clear on why that is. The way that our system works is as a spatial intelligence platform is we seek first to understand the people, the objects, And then the places that we’re in. And so that differs a little bit from say, typical computer vision companies in that we are trying to understand the 3 dimensional space in real time.
And that isn’t typically how computer vision companies approach, say, a CV problem. They tend to look at a 2D screen. And try to match the pixels. And if the pixels seem to match what a, say a hard hat looks like, then they can rightly say there’s a hard hat in this picture. Whereas what we’re trying to understand is, how is Brian moving through space?
What is the context with which he is interacting with these products or objects in that space? And that context is the major difference. And so, and we can explain a little more if you want a follow up question or two. But basically, the way to think about us is, if a computer vision company is, say, Spellcheck.
Then we’re a large language model, or if a computer vision company is a widget on a website, we’re Google analytics. That’s the way to kind of think about us.
Brian Thomas: I appreciate the analogies there kind of differentiate you versus some of the other companies out there. And I think it’s amazing how we’re seeing just in the last 18 months, a lot of leapfrogging here.
And I’ve learned so much from guests like you about some of the great things you’re doing in this space. So I appreciate that. And Steve, AIFI’s technology aims to enhance the customer shopping experience. What feedback have you received from retail partners and consumers, and how does AiFi Insurance Solutions address real world pain points?
Steve Carlin: Yeah, and again, we’re a spatial intelligence company using computer vision, and so one of the applications is in retail, so To your specAiFic question. Yeah, look the retailers themselves are very appreciative of the technology. The first is roughly 10 percent of shopping baskets are abandoned because people walk into the store and they see a line and in a stadium.
It’s something like 45 percent of people will say, like, when they’re going to the chiefs game that they choose not to go wait in the concession stand line because the lines too long. Right and furthermore, they’d spend say, 20 more if you could just reduce that line by half. So there’s a massive opportunity there just from the feedback of nobody wants to wait in line.
But beyond that, that means that the throughput for the retailer in this case, whether it’s the concessionaire or a convenience store or a grocery store, the throughput is quite a bit better. And then. Concession stand scenarios, we see a three to even as high as an eight X throughput advantage that these kinds of stores have over a traditional concession stand.
What we call a belly up concession stand. And then the other key piece for these retailers is they see a reduction and shrink. And that isn’t like people necessarily grabbing everything off the shelf and throwing into a bag. We’re talking like the average person just skipping something in a self checkout, for example.
And so we’ve had a big partner of ours say that they’ve seen like a 30 percent reduction and shrink. So not only are the people happier to do the shopping, and the labor gets to focus on higher value added activity other than a cashier. Checking people out, which is a fairly mundane job, but you get bigger baskets and better throughput.
So it’s sort of a win across the board is how I would, uh, characterize this. And so it’s been really good feedback and shoppers. There’s plenty of, uh, of, uh, videos on our website of shoppers coming out in the premier league in particular, coming out of the store going, I can’t believe it only took me 15 seconds to get through there to get a beer and chips and maybe a pie and get back out and get back to the game.
And, uh, the last piece I’d say is, you know, we’ve had a great partnership with the Induit Dome, with the Los Angeles Clippers. As Steve Ballmer would tell you himself, his, his, uh, vision is that you’re spending most of your time cheering the team on. Because a home team gets something like a two and a half point advantage the louder the, uh, the stadium is cheering for them.
So, his vision was that you should be able to get up out of your seat, go to the concession stand, and never break stride. Almost like you’re going to your refrigerator at your house and be able to get what you want and get back to your seat really fast. And we’re, we’ve been so pleased to be able to be a partner of the, the Clippers and of Steve Ballmer’s vision and being able to execute on that dream.
And it’s a, it’s a phenomenal experience that you can have with this kind of technology. So that’s a very long way of saying the feedback’s been very, very good.
Brian Thomas: That’s awesome. And just having that opportunity to partner with Steve Ballmer. He’s very excitable person, as you know, but, uh, very excited about the Clippers and where they’re going and, and he has a vision.
And I, I watched a little documentary with him or interview rather, and that’s awesome, but you are hitting some of those pain points. And again, the long lines turn everybody off and I’m glad that we’re addressing that. That’s been always been a huge pain point for everybody. So, Steve, last question of the day, looking ahead, what are your priorities for AiFi in the next few years and what role will innovation play in staying competitive in the autonomous retail and spatial intelligence sectors?
Steve Carlin: Yeah. So, you know, going back to kind of where we started the conversation, the thing that differentiates AiFi versus some of the other technologies that you might think are similar, for example, let’s just use Amazon. Everyone’s heard of Amazon. You probably are familiar with their Just Walk Out technology.
The two companies, AiFi and Amazon, approached the same problem, cashierless checkout, in very different ways. We approached it by understanding the people, the objects, and the space, and then said, well, once you’ve understood that, it’s pretty easy to generate a receipt. Whereas, Amazon chose first to Solve the problem of how do you generate a receipt?
And so they have extra sensing modalities. For example, weight sensors. They have purpose built cameras. They have to affect the lighting. They have to affect how the space is set up because that’s the way they approach solving the problem. So. Back to your question, how do we see things evolving? Well, we’re pretty proud of the fact that we’re sort of stand alone and how we have approached the problem.
Therefore, what our platform and technology really is. And so what we can see doing is expanding into spaces well, beyond where we are right now into. Problem sets like, how do we keep Brian safe in a industrial setting? How do we help, say, the nursing staff focus on the patients and not worry about what’s in the back room and how to keep inventory?
How do we help quick service restaurants focus their employees such that, The throughput for the line at a lunch rush is, uh, maximized, and all the people that are coming in for lunch get what they want faster. These are the, uh, the really interesting problems that we can start to focus on, because we understand how people and objects move through space.
One last piece to that, which I think will, your listeners will find interesting, Everybody is familiar with AI in the form of reasoning and planning. That’s when you use Google Maps or when you have a Spotify playlist or a Netflix playlist. We now understand understanding large language models. That’s what our friends at OpenAI have done for us and Anthropic and Gemini.
We now understand that you can understand language in a way that hadn’t been before. But the way that they did that was by taking individual words within a sentence and understanding it. How those words were important within the context of that sentence, and therefore how important it was, and therefore what word should follow that word, and when they put that all together, they created what we call language.
And so the way to think about our technology is we do something similar. We understand when Brian picks up an object, whether it’s in a retail setting or anywhere else, what’s the context of that? It isn’t just that we. Understand objects. And it isn’t just that we understand, say human poses, like typical computer vision companies, we understand all that.
Plus what does it mean really to pick something up? What’s the context of that? If it’s picked up, that means it’s not on the shelf anymore. It means it’s moving around. We understand where you came from and how long you’ve been there. All of that context means that we can go deploy in a lot of different spaces and really evolve what this technology is because it all trains the model even more.
So you’ll see first that we’ll expand where we are, which is in retail, and that helps train the model to a big degree. And then you’ll see that we go out and we do safety and we do track and trace in airports and we do efficiency and we do effectiveness. These are all what’s really exciting about where we sit, because we are going to help define that fourth pillar of artAiFicial intelligence, which is understanding the physical world.
And so once all four of those pillars, reasoning, planning, understanding language, and understanding physical places are put together. Then you can start to understand the dream of some of these big visionaries that you read about every day, Sam Altman, for example, when he talks about artAiFicial general intelligence and what that means, you can’t have AGI until you understand physical spaces, and we sit right there.
So it’s really fun. We’re really excited about what AIFI has to offer the world. We have a front row view to the technology landscape and its growth. And so we’re really looking forward to the next several years.
Brian Thomas: That’s amazing. I appreciate you. You’ve really broken a lot out for me and the audience this evening, but more importantly to me, I, what I extrapolated out of your last answer was your vision and you clearly have that lined up, ready to go.
And that’s what I like to hear is because a lot of times people are nosed down into a problem and they’re not seeing the next big truck maybe coming down the road. So that’s great. I really do appreciate that. It means a lot to me. And Steve, it was such a pleasure having you on today and I look forward to speaking with you real soon.
Steve Carlin: Great, Brian. Thanks so much for having us. I really appreciate it.
Brian Thomas: Bye for now.
Steve Carlin Podcast Transcript. Listen to the audio on the guest’s Podcast Page.
