The advance of human capabilities has been led by people who were able to imagine things that were not possible and then muster the willpower to build them. That requires a combination of seeing the world a bit differently and being willing to take risks and push the limits to create something new.

Eric Adolphe, CEO of Forward Edge-AI, Inc., is a technology-savvy executive with over thirty years of success building high-growth firms focused on mission impact, revenue, and margin attainment, primarily in the national security sector. But he isn’t interested in technology for technology’s own sake. Instead, he believes that it has the potential to generate enormous benefits for all of humanity.

In this episode, Eric joins co-hosts Scott Luton and Kevin L. Jackson to talk about his passion for innovation and willingness to go where no man has gone before:

– Eric’s opportunities to work first with NASA and now with the United States Space Force

– Why innovators must dedicate themselves to building responsible and more inclusive AI capabilities than we have today

– How AI is acting as an accelerant in manufacturing, making it possible to bring designs to market faster than ever before

Intro/Outro (00:03):

Welcome to Supply Chain Now, the voice of global supply chain. Supply Chain Now focuses on the best in the business for our worldwide audience, the people, the technologies, the best practices, and today’s critical issues, the challenges and opportunities. Stay tuned to hear from those making global business happen right here on Supply Chain Now.

Scott Luton (00:33):

Hey, good morning, good afternoon, good evening, wherever you are. Scott Luton and the one and only Kevin L. Jackson with you here on Supply Chain Now. Welcome to today’s show. Kevin, how are you doing today?

Kevin L. Jackson (00:43):

You know, it’s been a great day. Thank you very much for asking. Beginning of the week. Beginning of the fall. Hey, let’s do this.

Scott Luton (00:51):

Before long, you’re going to need a couple of clones based on everything you’ve got going on. But great to have you here. We’ve got an outstanding conversation. In fact, I’m really excited about the show that we’ve got lined up today. We’ve got a big mover and shaker joining us as we dive into, Kevin. Some of the intriguing work taking place at or near, I’ll call it, the intersection of artificial intelligence in manufacturing. Kevin, we should have sold tickets to today’s show, huh?

Kevin L. Jackson (01:17):

Yes, absolutely. I tell you, talking about moving and shaking. I mean, it’s an earthquake here with Eric, I tell you. He has some great stuff going on over at the Ford Edge-AI. I mean, I’m amazed at all the stuff they — that they’re into.

Scott Luton (01:33):

So, a good calamity. A positive calamity then what we’re going to have here today over the next hour or so. So, today’s episode, folks, is presented in partnership with our friends at Microsoft who’s doing some pretty cool things in the industry on — in their own right. Helping us all move forward. So, more on that to come. So, Kevin, I’ve got some bullet points. I’m going to introduce our speaker. You ready to go?

Kevin L. Jackson (01:54):

Oh, yes. I’m ready to go. Go.

Scott Luton (01:57):

All right. So, I’ve got our speaker today. Our dear guest has a phone book of recognition and accolades and awards. So, I’m going to give you the Reader’s Digest version here, but an award-winning business leader. Our guest today brings more than 30 years of experience in industry. He’s an honoree with the National Inventors Hall of Fame. How about that? He’s a winner of one of NASA’s highest civilian honors. He’s also the first African American Small Business Innovative Research Tibbetts Award winner. And those are, again, are just a few of his accomplishments and honors.

Scott Luton (02:28):

His company, Ford Edge-AI, as Kevin mentioned, is focused on artificial intelligence for the benefit of humanity. I love that. So, please join me in welcoming Eric Adolphe, CEO with Forward Edge-AI. Eric, how you doing?

Kevin L. Jackson (02:43):

Hi. Thank you, Scott. Thank you, Kevin. Good to see you guys.

Scott Luton (02:46):

It is so neat to rub elbow with you today. Kevin, I really appreciate you bringing some of your moving and shaking friends here today.

Kevin L. Jackson (02:54):

Oh, no. I tell you — I mean, Eric really is. He’s an inventor. He’s a serial entrepreneur. He’s smart. He taught me a lot of things, that’s for sure. And he’s a long-time friend. And I really — I appreciate him by taking some time to spend with us. Thank you, Eric.

Scott Luton (03:15):

I agree.

Eric Adolphe (03:16):

That’s a lot. I want to meet that guy.

Scott Luton (03:19):

I want to — well, Eric, you’re too humble, too. You’re very modest, given all that you’ve done in your career. So, I want to start here. This is where we want to start. So, fortunately, as much as you and Kevin know each other and have worked together and done big things together, our audience may be new to some of what you’ve done. I want to get to know you a little better first before we get into some industry talk.

Scott Luton (03:37):

So, in talking with you before we kick things off, I understand you grew up in Brooklyn, New York, in a neighborhood, Eric, that was highly diverse and it had a big impact on your worldview. Tell us more about that.

Eric Adolphe (03:49):

Yes. So, that is actually, as I said, this is my formative — these were my formative views, right? So, the one that really kind of sticks out is a neighbor, as I said, that was — she was an Auschwitz survivor. And I would sit summer days, just sit on her porch and she would just — we’d just talk. And she would tell me about her experiences. I — she showed me her tattoos. And that made a big impact on me. And the entire community was that way. We had Polish immigrants. We had immigrants from Puerto Rico. We had immigrants from Jamaica that made up the fabric of this community.

Eric Adolphe (04:25):

And, you know, the best folks borrow from each of these, right? Which is what I ended up doing, I borrowed from each of these. And what I learned, or I got out of that experience was love of history. I’m just really nuts about history. And it wasn’t something that was taught in school. It was just, I love to read. I love watching anything that’s related to history. It’s just one of those things. And that’s how, actually how I keep myself busy when I’m not working.

Scott Luton (04:51):

And, you know, Kevin, my hunch — and Eric, I’d love you to weigh in too. I’m a big history nerd as well. And you know, what’s old is always new. Again, we can learn so much no matter where or how advanced we get, how technological we get, Kevin, we can look back to all sorts of different parts of history and always find new lessons to be learned and applied. Is that right, Kevin?

Kevin L. Jackson (05:10):

Yes, yes. Absolutely. I find that you learn how to apply new technologies by looking at old technologies and how they were applied in the past and how they affected our society. And there’s so many lessons that you can learn, you know, from just being a student of history.

Scott Luton (05:37):

Eric, it sounds like you would agree with that perspective, Eric.

Eric Adolphe (05:40):

A hundred percent. A hundred percent. Well said.

Scott Luton (05:42):

And you know, I’m thinking, especially where I’m going next because we’re going to ask you about some of your work at NASA, some of your groundbreaking work at NASA. Whether it’s modern history or even ancient history. I was reading about the construction of the pyramids and how there’s so many scientists still today, we’re still — we’re just mind-boggled of how things actually happened and were built and constructed.

Scott Luton (06:04):

So, hey, mystery is still abound. All sorts of different parts of our global collective history. So, let’s talk about NASA, Eric. Now, as I mentioned — Kevin and I have talked about this before, we’re in such a — an exciting time when it comes to space exploration as we see the private sector get involved. Man, and what’s taking place. And who knows? Who knows? Especially with the current missions, the Lunar missions taking place, and getting ready to put our newest stamps on the moon. And who knows beyond? Tell us though, what did you do at NASA, Eric?

Eric Adolphe (06:36):

Yes, so a little bit of history there. Space has always been, sort of, in my background. I was always a dreamer. I was a huge, and still am, a “Star Trek” fan. And most of what I learned, “Star Trek”, actually. And when I was a young engineer, I worked for the FAA. And the F — the government announced this new program called Technicians in Space. And they were going to send people to the Hubble and, you know, satellite and other satellites to do repairs.

Eric Adolphe (07:06):

And I signed up and, unfortunately, the year I signed up, the Challenger accident happened. And so, the program was canceled. The reason why I bring that up is just a few years later, after I launched my company, I was sitting in an office with the lady, Charlotte Adams. I was being intubated and trying to figure out what I was going to do. I just started my own company and she came to my desk and she put this yellow book on my desk and it said, Small Business Innovation Research Program at NASA.

Eric Adolphe (07:36):

And just like everything else, I was intrigued and I started thumbing through it. And I saw this requirement. The Shuttle Challenger accident had occurred, and they were trying to solve that problem. Well, I went home and I was watching “Star Trek” and I saw Kirk was at his seat, command seat, and Nurse Chapel came with this thing that looked like a tablet computer. And it was — and gave him a battle damage assessment. And I said, wow, that’s the solution. I want to go build that. And, yes. And back then there were no tablet computers. There were — there was no wireless networking back then. And I said, I want to build that.

Eric Adolphe (08:15):

So, you see where that spark came from. That it was — it starts off with that curiosity in trying to solve a specific problem and then being passionate about the subject. Well, I won that. I wrote the proposal, won that SBIR, and that was something like $60,000, right? And we began to build that technology and it didn’t exist. And the whole time, I got to tell you, it was the — probably the best time of my career, best time of my life.

Eric Adolphe (08:45):

I could remember sitting in the back of this white van, not a creepy white van, but it’s a white van. And we had our laptops in there. We had all our gear. And we were sitting there on the side of the road writing code on a battery. And we were given a certain amount of time to prove that the technology could work. And we were driving to the Kennedy Space Center, and we were writing code as we were driving — taking turns driving. We got to the gate of the Kennedy Space Center and didn’t know if it was going to work.

Scott Luton (09:21):

Oh, gosh.

Eric Adolphe (09:21):

Yes. And we walked in and the — I’ll never forget this, the project manager said, well, this is your chance. If this works, then we’re going to move to phase two. If it doesn’t, this project ends. Man, we fired that thing up and it worked. And I got to tell you the — I still get misty about that. And that just defined, you know, my company, my career from that point forward. And that whole attitude of nothing’s impossible came from that dreaming beyond the horizon came from that. And it’s just the way we’ve kind of carried ourselves and our new company, right?

Scott Luton (09:57):

Oh, Eric —

Kevin L. Jackson (09:58):

Yes, its’ amazing how —

Scott Luton (09:59):

Yes, Kevin, go ahead.

Kevin L. Jackson (10:00):

It’s amazing how a vision and a passion combine to create reality. And that’s basically what happens over and over and over again.

Scott Luton (10:14):

Kevin, well said. And Eric, there’s so many — man, just what you shared in the last seven minutes, I wish we could spend the next four hours there, because to be able to be inspired by an idea that you find in the world of science fiction or make believer, or whatever that didn’t exist in real world. And then to go to work, rolling up your sleeves, making that happen, and the trials and tribulations that come with any kind of new technology of consequence, and then to be able to pass that big hurdle. And it just — and it not just changed your trajectory, but it changes the NASA trajectory.

Scott Luton (10:46):

And of course, as we all know, many folks know at least, all of — a lot of what has come out, all the feats and projects and successes and failures, all of it from our space program, from NASA, from the history to — up to now has benefited all the rest of us. All the rest of humanity and industry. So, Eric, we’re going to have to have you back and you’re going to have to tell us a lot more stories of you and your work. And of course, you and Kevin’s work both at NASA. And Kevin, I’ll give you the last word there.

Kevin L. Jackson (11:16):

Yes, before you leave that space work. I want to get — you know, Eric is still involved in space. And we’ve talked about history. And you — and, you know, everybody knows about all the junk that we’ve put up in space that goes around the Earth. And before long, all the satellites are going to be hitting each other because there’s going to not be enough. I mean, Starlink by itself is like thousands and thousands of satellites up there. But recently, I understand that the Forward Edge actually may be doing something about all of that junk that’s up in space. Is that right, Eric?

Eric Adolphe (11:54):

Yes, and I am so happy to be back in space, quite honest. Yes. So, we recently received notification that we were selected for a joint Space Force, air force SBIR to develop basically a device that will lead the way to the future space internet security. And what we’re doing — and there’s AI involved in that. What we’re doing is we’re going to be securing the data links that’s going to be used for low Earth orbit satellites and orbital robots that are going to be basically in orbit cleaning, grabbing space junk, and doing reclamation and warehousing it and that kind of stuff.

Eric Adolphe (12:32):

So, we’re going to be providing the technology that’s going to secure the data links so those robots can act autonomously without, you know, having to have human intervention. So, yes, it’s — we’re back in space and this is — man, I got to tell you, it’s a blessing for us.

Scott Luton (12:47):

Wow. All right. So, before you ask —

Kevin L. Jackson (12:49):

Yes, sustainable — sustainable space flight.

Scott Luton (12:52):

Sustainable space flights, we need a lot more of that because all that space junk up there. But I would just add one more thing. And Kevin, and I’ll pass the baton to you. I am so glad of all the things that you could have been inspired by from watching “Star Trek.” I’m so glad the Tribbles were not one of those things. So — sorry, “Star Trek,” dad joke maybe. But — all right. So, Kevin, where are we going next with Eric here?

Kevin L. Jackson (13:17):

Well, you know, the name of his company Ford Edge-AI, I mean, they’re doing a lot of work in artificial intelligence. And I recall a story that Eric told me about. He was on travel — you may not remember this Eric, but you were on travel and got off a plane and wanted to go wash your hands. Went into the restroom and they had these automatic faucets. And he put his hand down to the automatic faucet and it didn’t come on. He moved his hand back and put it back and it didn’t come on. And somebody came after him and it was a white gentleman and put his hands and it worked just fine. And it was like, it sparked your interest in artificial intelligence, as I understood. Is that true, Eric?

Eric Adolphe (14:09):

Yes, and you’re telling the Cliff Notes version of that because somebody called the police and they thought I was being a creep. So, what happened was —

Scott Luton (14:18):

Wow.

Eric Adolphe (14:20):

When it didn’t work, I observed. And that’s another thing about ingenuity, you observe things that others don’t, right? And I observed that other folks were using the sink no problem. And each one that I went to had that problem. So, I went underneath the sink and I started taking pictures of the part numbers and the manufacturing part numbers with the intent that I was going to, you know, contact the manufacturers and let them know their — that they have a problem. Well, somebody saw me taking pictures onto the sink. It’s like — so when the cops showed up at the airport and they said, well, what are you doing? And I said, your sinks are racist.

Scott Luton (15:06):

Oh, gosh. Man. All right. So, Eric — man, all the stories, we’re just going to get — be able to scratch the surface here today. But Kevin, AI, a lot of folks may still — although fewer and fewer may still be rolling their eyes here, right?

Kevin L. Jackson (15:21):

So — I mean, artificial intelligence, it’s a — you know, maybe I see it as a buzz word, but I don’t think a lot of people really understand what it is. And they oversubscribe to Hollywood when it comes to artificial intelligence. I mean, at its basic, AI is the ability of a computer or a robot to perform task that are typically associated with human intelligence, such as learning and problem solving.

Kevin L. Jackson (15:54):

But the goal of AI is to be able to do things like recognize patterns and make decisions and make judgments like a human. But let’s be clear that AI is not the “Terminator”. “Terminator” is a hypothetical type of like intelligent agent referred to as artificial general intelligence or AGI. If realized, an AGI could learn to accomplish any intellectual task that human beings or animals can perform. AGI has been defined as an autonomous system that surpasses human capabilities in the majority of economically valuable tasks.

Kevin L. Jackson (16:45):

So, the — so, let’s — don’t get these terms twisted. We’re not there yet. The timeline of AGI is a subject of a lot of debate among researchers and experts. Some argue that it may be possible in years or a couple of decades, and others say it may take a century or more. And a minority of these believe that it may never be achieved. So, don’t be afraid of AI. AI is just a tool. It’s not the “Terminator” coming to knock on your door.

Scott Luton (17:25):

Well — so, Eric, speak to that. You — you’re undoubtedly, there’s folks, we probably all know them in our networks that when they hear the word AI, they may roll their eyes a bit and it’s just — they may perceive it as just the latest, you know, tech flavor of the month. What must they know, Eric, about artificial intelligence?

Eric Adolphe (17:43):

Yes, I think I agree with Kevin, and I would — just want to distill what his thoughts to one kind of point. What’s different about AI, true AI is that it has the ability to learn, right? Absent that is just code, right? And I want to give you an example. When — so ChatGPT is the thing that everybody’s excited about and people think it’s going to take my job, it’s coming for me, that kind of thing. I went on to ChatGPT and I entered a prompt. I said, are Canadians, Americans? And it replied, no, they are not. And I said, what continent is Canada on? And it replied, the North American Continent.

Eric Adolphe (18:28):

So, then I did another prompt. I said, so are Canadians, Americans? And it responded, no. And then I prompt — said — and I kept down — kept going with this saying — I did Mexico. I did Haiti. Every — all the countries in North America. And it kept coming back, was polite. I said, I’m sorry, I —

Kevin L. Jackson (18:50):

It was polite in its ignorance, right?

Eric Adolphe (18:52):

But the point is — the point is that demonstrated fairly clearly that it wasn’t learning, right? So, it’s a large language model, right? Difference is, humans have the ability to take in raw data and learn, right? That’s something, as Kevin said, AGI or the singularity maybe in 2060 we might get there.

Eric Adolphe (19:15):

And the last thing — I’m going to go back to history for a second because there’s a lot of — I see the Hollywood strikes and that kind of thing. People are like freaking out about it. So, Thomas Edison and his team developed the light bulb, right? The Candlemakers Union went to Congress to try to stop him, right? Because they said he would take away all their jobs. And that’s a case where there was some actual fear there, right? So, Congress enacted a law that limited the deployment of can of light bulbs to hotels and not into people’s homes. So, the first deployment of the light bulbs were in hotels, not in homes, because they wanted to protect that market, right? So —

Kevin L. Jackson (19:55):

Protectionism, that’s the best.

Eric Adolphe (19:59):

Take a look at today, right? Candlemakers are not out of business, not by a long stretch. And what happened was candles now are used. The candle making industry is huge. And what they’re using it for, like, intimate settings. That — it’s changed what candles are used for. We don’t use it for lights unless, you know, we lose power, right? Birthdays, anniversaries, the things that are important to us. We don’t sit there with a light bulb to wish somebody happy birthday. Candles.

Eric Adolphe (20:32):

So, like — so my point is, you know, like art, poetry, literature, the things that make us human, right, we’re going to still want them to come from humans. So, I would just tell people just — take a chill.

Scott Luton (20:47):

And, you know, I love that perspective. And two thoughts there — and Kevin, I’ll get yours. One, is that candle example. It allows candles to be used for the — their best possible purpose, right? Where they add so much value, because to your point, you don’t want to celebrate happy birthday with a bunch of light bulbs, perhaps. And then secondly, folks, we’re going to get more into some powerful outcomes, especially in the manufacturing industry where we’re going to talk more about some big-time outcomes that AI is driving.

Scott Luton (21:17):

Kevin, before we move on, and we’re going to be talking about responsible and inclusive AI here momentarily, what else comes to your mind with what Eric just shared?

Kevin L. Jackson (21:26):

Well, the thing that jumped to my mind was the MoMA exhibit of AI where they have created a whole new art form, dynamic art form that is never the same twice, forever. And is a — and it’s amazing what’s possible when you are not limited by the human brain. I mean, AI can really expand the possibilities in art, the possibilities in technology, and the possibilities in the human experience. And I think that’s one thing we have to recognize.

Kevin L. Jackson (22:14):

Also, we have to recognize that AI only does what a human tells it to do. It’s not sentient, right? It can’t create itself, not yet. So, it’s all about humans. How are we going to use and leverage AI? Humans can do bad things but, you know, hopefully most humans that use AI will be — do it in a socially acceptable and empowering way.

Scott Luton (22:49):

And Eric, give you the final word here before we move on. What would you say, Eric, for folks that, you know, that aren’t enlightened like you and Kevin are about just how AI and Generative AI, or maybe even the AGI that Kevin was talking about earlier, whenever it comes along. How it truly is going to revolutionize industry and automate the things, the redundant things that humans really get tired of while accentuating, at least in my perspective, the creative side and enabling and empowering humans to really achieve new heights and do new things and create new value in industry? Eric, for folks that may be taking a pessimistic view there, and this is just the latest trend, what would you say to those folks, Eric?

Eric Adolphe (23:30):

Yes, I love that question. And to go back to the candle example, back then when Edison was doing the light bulb, there was one flavor of candle, it rolled [phonetic], right? And —

Scott Luton (23:43):

One scent, I guess. One scent, Eric.

Eric Adolphe (23:45):

One scent. One scent, that was it. One scent, one color. Now, you can get in every possible scent and color you can imagine that —

Kevin L. Jackson (23:53):

And shape.

Eric Adolphe (23:54):

Yes. And it further human creativity, right? And so, I’m in favor of anything that reduces cognitive overload. I’m in favor of. And a good example of that, right? Right now, AI has gotten pretty good. Computer vision has gotten pretty good. Machine learning’s gotten pretty good at analyzing CAT scans, MRIs, X-rays, et cetera. Finding potential cancer, broken bones, that kind of thing, right? AI can do that quicker and as accurate as the human physician or radiologist can.

Eric Adolphe (24:27):

It’s important, right? A lot quicker and as accurate, perhaps, a little bit more accurate, right? So, what does that do? Fewer mistakes. I’m going to miss my doctor, physician, radiologist is going to miss fewer things, and it’s going to reduce the load on the hospital staff, right?

Eric Adolphe (24:47):

Now, imagine if I took a sonogram, right? A portable sonogram doesn’t give off radiation, and I augment that with artificial intelligence and I sell that to the consumers. Now, I can sit at home, I get injured, scan my arm and see if — and it’ll tell me if my bone is broken. So, I either need Advil or I need to get to a doctor. Scan my breast, and — OK, there’s a lump here. You need to go get this looked at, this looks like cancer. Could you imagine that?

Eric Adolphe (25:20):

Now, if you could do that, you offload all of that stuff, the misdiagnosis, the stuff that’s missed because people don’t have access to a doctor or healthcare, you offload all that stuff. Now, you could prevent diseases. You could prevent problems in the future.

Eric Adolphe (25:35):

Now, here’s the dark side of that, and this is where we talk about, you know, inclusive and responsible AI, right? So, black females have denser breast tissue, right? So, if you train your magical sonogram, augmented sonogram on one dataset, and then you try to apply it to others in the population, what’s going to happen? You’re going to get a lot of faulty data, right? So, as an entrepreneur, why would I go out and invent something that’s going to exclude a big part of the market? It makes no sense. But yet we do that every day because everybody around us in our lab looks like us. So, fill in the blank or whatever your company is, right?

Scott Luton (26:30):

Yes. So — yes. So, Kevin, I love Eric’s example there because he’s reading my mind. I was going to ask him about why building responsible and inclusive AI? What that means and why it’s important. And I think that example really speaks to both of those. What else would you add, Kevin?

Kevin L. Jackson (26:45):

Well, first of all, being responsible with technology is just good business to start off with, right? But with respect to AI, everybody thinks about AI as in the future. It’s not in the future. It’s — we’re there and we are accelerating. AI is used — like Eric was talking about, AI is used for virtual assistance and chat bots. It’s used in agriculture and farming, autonomous flying and security, surveillance, sports analytics. And a lot of different sports activities, manufacturing and production. We’ll talk more about that. And even in livestock and inventory management.

Kevin L. Jackson (27:32):

And today, what’s used to provide personalized recommendations, ChatGPT accepted to process thousands of transactions in a second. It can actually recognize problematic activities and protect you. It — well, it verifies applications for loans. It’s another use case for having a much broader database. And it can match clinical trials with patients. It drives robotic surgeons. And like Eric mentioned before, reads radiological findings much better than humans, OK. It augments humans, OK?

Kevin L. Jackson (28:17):

The question is, where is AI not being used? OK. You just don’t know how much it’s already affecting your life. So, I think AI with responsibility is key. And that’s why Forward Edge is going to be huge company because that’s the key to good business.

Scott Luton (28:42):

Well said, Kevin. And going back to Eric’s example about the inclusive part, making sure all parties, all users can benefit. And you know, one of the thing is as Eric and Kevin, as both of you all were talking about the healthcare applications, there’s so many transfers between the healthcare industry and the manufacturing industry.

Scott Luton (29:00):

I mean, just kind of sitting back and listening to you both, you know, capacity, quality, value, waste reduction, just to name a few. And so then — so, with that said and — before we move on, Eric, anything else that you want to add? We’re going to — we’re about to get into Semantic votes [phonetic] about the manufacturing industry and where you’re seeing real value, AI driven value. But anything else you want to share that we didn’t touch on when it comes to that, how passionate you are about the need for greater responsibility and inclusivity when it comes to AI.

Eric Adolphe (29:28):

Right. Yes, so, great, great lead in. So, as I mentioned, data is king. It was a project that happened about four or five years ago. Social Security administration, very laudable goal was to reduce fraud in Social Security and also in Medicare, right? And so, they began developing an AI tool to sniff out, find fraud in the filings, right? Which is everybody wants that. You as a taxpayer, you’d want that, right?

Scott Luton (29:58):

Right?

Eric Adolphe (29:58):

So, what they did is it got data of known proven fraud cases and they used that to train the artificial intelligence, right? That’s the data. So, it got quite good at recognizing these patterns. And then what they discovered is that it kept picking on senior citizens and kept picking on veterans. As it turns out, veterans who are suffering from post-traumatic stress and senior citizens were being overmedicated for reasons, you know, that are kind of beyond me.

Eric Adolphe (30:34):

So, when you train the artificial intelligence to look for people who are consuming these drugs, and it’s this large population, the AI learns that all senior citizens and all veterans are criminals, which is not what you want, right? So, now you have a data set, a raw data set of the entire population, it’s going to keep picking out the veterans and the senior citizens, right?

Eric Adolphe (31:01):

So, this is another example. So, every — when we say inclusive AI, people always think it has to do with ethnicity or something like that. This is a perfect example of what I’m talking about, right? So — and one more point before I know I’m going on here, on my first company, I had a consultant who came in to look at the company and tell me what was wrong. And he came to me, he says, you’re the problem. And I was like, shocked. I was like, me. And he said, yes, you’re the problem. And he says — and I said, why? He says, because you’re biased.

Eric Adolphe (31:31):

Now, I looked. I had black, white, Asian, I mean, you name it in my company. I said, no freaking way. He said, yes, yes, you’re biased. And he says, come step outside. And we — I stepped outside. I had all the — I had a bunch of employees there. He says, look around. He says, don’t you see this? I said, no. All of my employees were between 5’4″ and 5’6″.

Scott Luton (31:53):

Really?

Eric Adolphe (31:54):

Yes. And I — it was like, wow. And I was instinctively hiring people who reminded me of myself. And even though I was sort of “Enlightened,” everybody was 5’4″ to 5’5″. I’m 5’5″.

Kevin L. Jackson (32:13):

Unconscious —

Eric Adolphe (32:16):

So, I got out of the hiring process. We’re human. We’re all susceptible to these things. And if you sit there and you think it can’t happen to me, well, look again, the moral of that.

Scott Luton (32:28):

I love that. And Kevin, I’ll get your word here before we get into some other anecdotes related to manufacturing and we do need to take. When we talk about the word inclusivity, we need to be highly inclusive and universal and very broad and holistic in terms of how we even define the word inclusivity, to Eric’s point. Your final word there, Kevin.

Kevin L. Jackson (32:48):

There are an indefinite number of domains within which you can apply inclusivity, right, and diversity. So, let’s not be just stuck on one domain. It’s — have an open mind for a lot of reasons.

Scott Luton (33:06):

And it’s really important for AIs they learn and learn and learn to have really big open minds. All right. So, shifting — we’ve been teasing, we’re getting there about examples of manufacturing of real practical AI applications and outcomes. So, Eric, let’s get into that. What’s a couple of stories that you can share that you’ve seen AI really powerfully be applied in the manufacturing environment?

Eric Adolphe (33:30):

Yes. One — so, there’s one that I’m pretty excited about now. Som when I was, a younger guy, I was designing ASICs, or these are application specific circuits, right? So, very, very complex. And now, designing these things to — for the performance we’re looking for is just humanly not possible. And I was just shocked to see how AI has come and turned that around. And so, you have — humans are still involved, obviously, but now using AI, you can get to market a lot faster with designing these chips because a lot of this now could be done by AI.

Eric Adolphe (34:09):

And I am — I was just shocked by what can be done and what can be produced. And basically, what I’ve been seeing in manufacturing, a lot of what AI can do is get me to the 80% solution and the 20% that remains is where my human inspired creativity comes and takes in, right. But I can offload the — just the monotony of designing a circuit, a print circuit board or a chip to AI, and then bring in the human, you know, intellectual property and inspiration to make it something unique in the marketplace.

Kevin L. Jackson (34:46):

Yes.

Scott Luton (34:48):

Kevin, your thoughts on that?

Kevin L. Jackson (34:50):

Well, when it comes to manufacturing, one of the most visible areas is in connected field service. Where technicians can deliver proactive and predictive service by connecting a manufacturer’s smart product with the empowered technicians through, like in Microsoft’s case, the Azure Cloud, really. This is — this drives innovation with connected products by reimagining manufacturing. OK.

Kevin L. Jackson (35:29):

Just like Eric is saying, you make it better with improved insights that a human can bring. And you get efficiencies through the use of things like digital twins, right? An electronic version of the product that you can leverage to improve the product and improve the customer service. This also comes down to building an intelligent supply chain. By using intelligent business applications to optimize digital operations. This really helps manufacturers achieve the right balance of customer service and supply chain cost. And much of this is really empowered and enabled, made possible even by artificial intelligence using broad diverse data sets.

Scott Luton (36:36):

Yes. Well said, Kevin. One quick thought on both of what you just shared there. Eric, going back to what you have seen is, in your example, getting to markets faster, hey, that’s speeding up the monetization of new products. Even by extension, we’re seeing AI driven gains in limiting that order to cash flow. Shortening that cycle, right?

Eric Adolphe (36:56):

Yes, yes.

Scott Luton (36:57):

And then, Kevin, to your point, you know, one of the things I heard there, kind of, going back to the healthcare example where you’ve got finite supply of medical expertise, right?

Kevin L. Jackson (37:07):

Yes.

Scott Luton (37:07):

But you also have, as I’ve seen for 20 years now, finite supply, seemingly of maintenance talent, right? It’s tough to get the newer generations excited about going in and fixing stuff. We’re making some gains, but still there’s a massive opportunity. So, naturally we’re seeing AI applied and addressing these gaps where there’s not enough maintenance know-how, valuable maintenance talent to go around. So, naturally industries are going to apply and make gains there.

Scott Luton (37:35):

So, I love these opening examples. I’ll go back one quick question, Eric, before perhaps you share another anecdote. You mentioned ASICs. I am not a programmer or a technologist. My brain went straight and maybe I were illustrating some of the different mindsets to the sneaker. The shoes. Asics, right? That’s not what you’re talking about, right? You’re talking about —

Eric Adolphe (37:53):

No, no, no. No, no, no. Not at all. I’m talking about a computer chip.

Scott Luton (38:00):

See? So, we’re illustrating see between two humans, much less the leap between all the different AI mindsets. OK. Let’s — any other anecdote, Eric, that you might want to share from how you’re seeing AI very powerfully being applied in the manufacturing industry and driving big outcomes and opportunities?

Eric Adolphe (38:19):

Yes. Like I said, even, Kevin provided an example, there’s lots and lots of examples like making manufacturing’s line — lines more efficient. This has been something that has been going on since manufacturing lines were invented right before, right? Trying to make it more efficient. The reason why we were so successful in World War II is because we took a lot of the principles that Henry Ford developed in automating the manufacturing line, right? And we were at — we got to the point where we’re able to manufacture bomber aircraft, like — it was like one every hour was coming off the assembly line, right?

Eric Adolphe (38:55):

So, now could you imagine AI in the mix now? How quickly we can get to market? How quickly — how the efficiencies we can get from manufacturing. And this is — and by the way, we are looking to take the factories that — and those jobs that we outsourced over the last 30, 40 years and onshoring it. How are we going to compete against a country that the labor costs are like a 10th of the cost of American labor costs? Well, the way you do that is more efficiency, right? More efficiency. And that’s what’s going to really propel this country forward.

Scott Luton (39:35):

And, you know, it is not — no longer, maybe 10 years ago, perhaps, Kevin and Eric, or whatever the right timeframe is. No longer is it a nice to have, but it’s going to be requisite to protect and grow that competitive advantage to what I’ve just heard Eric speak to. Kevin, your final word here before we start talking about the future.

Kevin L. Jackson (39:54):

So, the future is now. I saw a story over the weekend on CNN for — with Fareed Zakaria on “GPS”. And he was interviewing the minister of digital transformation. He used to be a minister of digital transformation for Ukraine. And he is credited with really inventing the ace centrum — ace symmetry — asymmetric warfare that Ukraine is conducting against Russia with drones.

Kevin L. Jackson (40:35):

And one of the aspects of that is how the electromagnetic spectrum is changing on a minute-by-minute basis. How you can control the drones and conversely how the Russians are trying to prevent the control of these drones. And artificial intelligence is one way that they are able to bring in data, modify their software, and then get the drones out there to complete the mission.

Kevin L. Jackson (41:09):

So, in this case, artificial intelligence is actually saving the country. It’s not the scary “Terminator”, but it is a very difficult situation to be in. And artificial intelligence is doing a good thing, from my point of view. Personal.

Scott Luton (41:31):

Eric, any thoughts there?

Eric Adolphe (41:34):

Yes, that quite a bit. And I saw that interview as well. What struck me — or — and I think that that was mentioned during that interview. So, the way we view artificial intelligence is different than the way other countries view artificial intelligence. And I’ll give you — for example, not picking on anybody. But the way China views artificial intelligence and the purpose is completely different than what Americans do. And this is why I’m glad to be an American. I’m glad to be here and in this day, this age of artificial intelligence.

Eric Adolphe (42:04):

They’re using artificial intelligence to — for — in large part, to control their population, right? We value our freedom, right? So, if you look at the training data, if you look at the data that Chinese government uses or regulates to train artificial intelligence, you will not see the word Tenement Square anywhere, right, in the dataset, right? Not allowed. Think about that for one second, right?

Eric Adolphe (42:32):

So now you’re trained — you’re excluding a set of data, and that — that’s just one example, you’re excluding a set of data and then you’re training the AI. The AI is only as good as the training data, right? And you compare that against what the American philosophy is, right? We want as much data as possible, as much diverse data as possible, whether it’s — it helps our argument or works against our argument. Because then you’re getting closer to true generative or, you know, artificial general intelligence where it can then start to make decisions at some point in the future.

Eric Adolphe (43:10):

So today, if you think about this, if you have a product coming out of China, product coming out of the U.S., both are augmented with artificial intelligence, based on what I just said, which product do you want?

Scott Luton (43:22):

Kevin? I’ll let you answer that. Which —

Kevin L. Jackson (43:28):

No, it’s — when you look at the value of openness and truthfulness, it always, always outshines against constraint and restrictiveness.

Scott Luton (43:43):

Well said, Kevin. What — very well said. And Eric, great example. I appreciate what you’re sharing here today. I just want to ask a question. I know Kevin said, the future is now. And I think all of us agree with that in many different ways. But in terms of thinking about what’s next, where is AI going next? Kevin touched on — a little bit on that on the front end. Eric, in your thoughts, where is AI going next, and how fast are we going to get there?

Eric Adolphe (44:09):

Yes. So, this is why the company was founded, and this is — it’s in the name of the company, Forward Edge Artificial Intelligence which is AI at the edge, right? So, right now, artificial general intelligence, which is this kind of stuff that Elon Musk and these guys are talking about is kind of the ability to solve complex problems like a human can do, right? Humans are not, you know, plugged into — well, most of us are not plugged into a wall.

Kevin L. Jackson (44:38):

Yes, you know.

Eric Adolphe (44:41):

We’re not plugged into some wall, right? We’re at the edge. We’re always at the edge, right? And for you to be able to solve those problems at the edge, you need lots and lots of data, lots and lots of bandwidth, right? So, that’s not their end. You don’t have that kind of data and bandwidth available to you at home. So, this is the next frontier. This is why we’re there. Wayne Gretzky said this, and others have said this before as well.

Eric Adolphe (45:08):

So, there’s a book that called “The Second Bounce,” I think it’s by Ron Cohen, I think, the guy’s name is.

Scott Luton (45:14):

Yes.

Eric Adolphe (45:14):

Most people can predict, most entrepreneurs can predict where the — when you throw a ball, they can predict where the first bounce will be. It takes an exceptional person to predict where the second bounce will be. And Wayne Gretzky said it even better. He said, I’m successful. I was successful because I went where the puck is going, not where the puck is. And in my view, my humble view, where the puck is heading, the problem we have to solve is AI at the edge. Great that we can have a supercomputer and figure this stuff out on the factory or whatever. But when you could solve this at the edge, my God, that’s when things are going to really open up.

Scott Luton (45:56):

Exciting. Eric, appreciate you sharing that. Kevin, your quick thoughts. And then we’re going to touch on some of what Microsoft’s do, and of course we’re going to make sure folks know what Forward Edge-AI is up to along those lines that Eric just shared. But Kevin, your thoughts there?

Kevin L. Jackson (46:09):

Well, I really believe the power is in AI is at the edge, and how the different devices at the edge communicate with each other and create new knowledge at the edge that can be applied immediately. So, that’s where we’re going. That’s what edge computing is all about. That’s what advanced communication is all about. This is really where the protection of data is all about. And you see hints of it when it comes to the power of social media. It’s scary, but it’s powerful. We just have to learn how to —

Scott Luton (46:52):

Scary and exciting.

Kevin L. Jackson (46:54):

— how to control it. How to manage it.

Scott Luton (46:56):

Yes, scary and exciting all at the same time. It’s like going a hundred miles an hour in a convertible down the interstate or something. It’s fun, but it’s scary.

Kevin L. Jackson (47:05):

Right, right.

Scott Luton (47:06):

All right. So much more to cover and limited time here, but I want to touch on this. And Eric, we’re going to circle back with you in just a second. But I want to touch on, Kevin, some of the cool things that Microsoft is doing out industry, again, especially as it when it comes to leveraging AI and technology to power manufacturing forward.

Scott Luton (47:24):

I got to touch — before I throw it to you, Kevin. I got to tell you, Microsoft — I read a story the other day about how Microsoft’s working with PepsiCo, in particular Cheetos. So, my middle daughter, Grayson [phonetic] — I’ll tell you, Microsoft’s going to be a hero in her book. She’s the biggest Cheetos fan, I think in our extended family. And anything that keeps Cheetos supply chain coming and protecting the quality of said Cheetos, Grace is going to want some engineering autographs maybe. But Kevin, kidding aside, what’s some of the cool things that Microsoft’s up to out there?

Kevin L. Jackson (47:53):

Well, artificial intelligence is built on top of a cloud computing platform. So, Azure is really driving the use of AI responsibly in manufacturing. They’re really using it to transform businesses and reshaping the organization across every industry by integrating AI into the factory of the future. This really requires the business leaders to really do what humans do best. Look at big picture thinking, and not just consider what AI can do but what it should do.

Kevin L. Jackson (48:40):

So, Microsoft is really collaborating with these leaders and customers and partners to create a collective approach to engaging AI in a responsible manner. So, they’re really working with society to navigate what the shift — what this shift really means. And to gain the insights and perspectives that we all need to share to make AI deliver good things for the world.

Scott Luton (49:17):

Man, Kevin, you’ve got some challenge — some Shakespeare today. Some supply chain Shakespeare, I love that.

Scott Luton (49:24):

But you know, Eric, kidding aside, it’s not every day — I mean, I know I get to collaborate with Kevin regularly, but it’s not every day you get to sit down and rub elbows with an inventor, a visionary that has done big things with our national space program, and now doing big things with current and next generation technology. I mean, I know that there’s a lot more stories and we’re going to have to have you back. I’ll look forward to maybe connecting with you in San Antonio at some point soon. But I want to make sure folks know in a nutshell what Forward Edge-AI does. So, Eric, tell us about that before we wrap here.

Eric Adolphe (49:56):

Sure. So, before I do that, I wanted to make sure everybody was aware, we are a Microsoft for Startups company.

Scott Luton (50:03):

OK.

Eric Adolphe (50:05):

Microsoft was our first — was one of our first investors. We’re Microsoft startups, and we’re what’s called a Microsoft for Startups Pegasus Company, which is at the tippy top of the Microsoft Startup ecosystem. So, I wanted to make sure everybody heard that.

Scott Luton (50:20):

And tippy top is a highly technical quantification of that.

Eric Adolphe (50:26):

No. So, Microsoft has been very good to us. So, yes, so Ford Edge, there’s three things when you think about Ford Edge, I want everybody to think about. What we do is we focus on, again, leveraging artificial intelligence to solve complex problems related to national security, public safety and defense. Those are the three things we do. We don’t do anything else.

Eric Adolphe (50:47):

So, everything we do is related to that. I want to be the one that’s getting the — helping the firefighter get his or her job done. I want to be the one helping our guys and gals on the ground, boots on the ground trying to protect our freedoms. That’s what we want to be doing, right? So, a couple of examples real quick. We — I mentioned earlier, we recently won a SBIR with space force, air force to develop this space internet security thing. The reason why I bring that up is because, man, that is at the edge of the edge, right? So, we always said we want to be at the edge. We — you can’t get more edge than that.

Eric Adolphe (51:26):

So, think of it this way. We’re using data provided by Microsoft. They have eight trillion security signals that they’ve collected, cyber related security signals. We’re using that to train our artificial intelligence to be able to detect a cyber-attack that’s attacking a CubeSat or an orbital robot, right, so that it could then detect these attacks, learn the patterns of life, detect these attacks, and then initiate an immune system, kind of, a response. You are not going to get into your car and drive to that satellite to make a repair. It’s got to be able to detect it, react, protect, right? It’s got to be able to do it instantly. Not waiting for a technician to show up, right? This is the kind of stuff I’m talking about. This is what we’re doing.

Scott Luton (52:15):

As inspiring and invigorating. And Eric, I really appreciate what you do and the opportunity to chat with you here today. We’re going to have — definitely have you back. Eric, really quick, how can folks connect with you?

Eric Adolphe (52:26):

All right. So, two ways. One is LinkedIn, and the other is telepathy.

Scott Luton (52:35):

Oh, man. Your sense of humor is boundless as brilliant as everything else you do. I love it.

Scott Luton (52:41):

All right. So, Kevin, first off, your quick thoughts — well, hang on a sec. Kevin, because something — as you mentioned “Terminator” — Eric, he’s mentioned “Terminator” like 12 times a day. And I just — that keep — brings up Arnold Schwarzenegger’s really intimidating face. First off, whenever we get to that point, let’s make sure we teach those bots to smile a little better. A little easier to engage, right? And then secondly, when you all —

Eric Adolphe (53:04):

Probably better without the Sunglasses too.

Scott Luton (53:07):

Right, without — and the shotgun perhaps. And perhaps not the shotgun, too. One other thing. One of you all mentioned about plugging in as humans and stuff, there was a great — since both you all may be Sci-fi fans too. There was a great amazing stories episode way back in the day, and it was a robot grandmother that was sent out to a family that didn’t have. They — I think they had just lost their grandparents or something. And there’s a — an incredible scene there as part of that Steven Spielberg series, I believe, where at the end of the day, after the grandmother had finished her nurturing duties, she was sitting and knitting in a rocking chair, being plugged into the wall, recharging for the next day.

Scott Luton (53:43):

And it was just a set — it really stuck with me as a kid. And who knows where we’re headed next, right? So, Kevin, your quick thoughts of all the brilliance that Eric has shared here today. And I want to make sure folks know how to connect with you and all the cool things you’re up to, especially with Digital Transformers.

Kevin L. Jackson (54:01):

Well, this is an amazing show. Thank you, Eric, for sharing all the things that your company is doing to make — develop and deploy AI in a responsible manner. So, thank you for all those stories. And it’s really about Digital Transformation, and that’s what I do, Digital transformation. So, you can always catch me on Digital Transformers. We release our show the fourth Monday of every month. And I will also have a — the Buzz series, a Digital Transformers edition on the second Monday of every month. And you can catch me on LinkedIn or X, that’s kevin_jackson. And I’m going to go check with Eric on how to get that telepathy thing done.

Scott Luton (54:56):

Hey, I’m confident two of you all will figure it out by next Tuesday and then maybe you’ll let some of the rest of us know. And hey, if that’s not good enough, you can find “The Rolling Stones” opening for Kevin L. Jackson’s act every once in a while. So, we’ll find out where that world tour is there. Kevin, big thanks.

Scott Luton (55:12):

Going back to Eric Adolphe with Ford Edge-AI. Eric, really appreciate your time here today and the mission you’re on — what you’ve done, right? But you know what, the best people I know, the most brilliant people I know are the folks that they don’t sit on their laurels. I mean, they appreciate the big things they’ve done, but it’s about the mission today. And today what I heard is how you are determined to find a way to help humanity and — on so many different levels. And, Eric, really appreciate your time here today.

Eric Adolphe (55:40):

Thank you. Thank you, Scott.

Scott Luton (55:42):

Kevin, always a pleasure. I appreciate you helping to facilitate today’s conversation. I learned a ton.

Kevin L. Jackson (55:46):

Thank you. That was fun.

Scott Luton

It — a blast — really, it was fun. It was practical. It was inspiring. A little scary at times, but because, you know, all of this comes with threats and obstacles and burdens, right? But it is exciting.

Kevin L. Jackson (55:58):

I’d say, going in with eyes wide open, right?

Scott Luton (56:01):

That’s right. You got a really shine a light or a very expensive candle because the candle markets still doing pretty well these days in that blind spot, right? Big thanks again to Kevin L. Jackson, of course, Digital Transformers. Make sure you find that wherever you get your podcasts from. Big thanks to our collaborative partners over at Microsoft as well, appreciate what they’re doing, the power industry forward.

Scott Luton (56:21):

And to our listeners, hey, thanks for joining us on this journey. I hope you enjoyed this episode as much as Kevin, Eric and I have. We’re all working on that telepathy thing. But hey, whatever you do, be sure to find Supply Chain Now, Digital Transformers, wherever you get your podcasts. And on behalf of our entire team here, Scott Luton challenging you do good, give forward and be the change that’s needed. And we’ll see you next time right back here at Supply Chain Now. Thanks everybody.

Intro/Outro (56:47):

Thanks for being a part of our Supply Chain Now community. Check out all of our programming at supplychainnow.com and make sure you subscribe to Supply Chain Now anywhere you listen to podcasts. And follow us on Facebook, LinkedIn, Twitter, and Instagram. See you next time on Supply Chain Now.