Life Unscripted with Kevin Shook
Welcome to 'Life Unscripted with Kevin Shook', a heartening podcast where embracing vulnerability is the key to success. Join your host, Kevin, as he dives into the stories of remarkable individuals who have transformed their lives by opening up, facing challenges, and finding strength in their most vulnerable moments. Each episode features inspiring conversations with guests from various walks of life. Kevin's journey of embracing vulnerability has led him to meet amazing people, and now he brings their wisdom, laughter, and insights to you. Tune in and discover how embracing your vulnerabilities can lead to your greatest victories in life, both personally & professionally.
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Life Unscripted with Kevin Shook
AI’s Next Frontier: Transforming Business Through Automation with Wokkah – On Life Unscripted with Kevin Shook
The AI revolution isn’t coming—it’s already here. And businesses that fail to adapt are at risk of falling dangerously behind.
In this compelling conversation with Dr. Iyanu Odebode (CEO of Wokkah) and Jason Wright (COO of Wokkah), we explore how artificial intelligence has evolved from niche academic ideas like “pattern recognition” and “data mining” into real-world business tools that are transforming industries.
Ever wondered what an API actually is or how it works?
Iyanu and Jason break it down in simple terms—showing how APIs, the “digital connectors” of our time, enable powerful automation and productivity across platforms. As Jason puts it:
“The businesses that get it, the businesses that embrace this, are going to have such a competitive edge over the businesses that don’t. It’s not even going to be fair.”
From producing 900+ educational videos in just three days to streamlining content creation and social media workflows, this episode showcases the incredible efficiency AI brings to marketing and operations.
Concerned about data privacy?
Dr. Odebode also discusses how AI can be used responsibly in sensitive industries like healthcare—through proper governance and secure, isolated environments.
And if you think AI is here to take your job—think again.
This discussion redefines AI not as a replacement for people, but as a force multiplier that frees up humans to become strategic orchestrators.
Want to see Iyanu’s passion for technology and leadership in AI? Watch his TEDx Talk: https://www.youtube.com/watch?v=8TzSs9ejxdY
Learn more about Wokkah at: www.wokkah.com
Ready to do this? Yeah, let's do it we don't smoke anything in here like Joe Rogan, that's good.
Speaker 3:Life Unscripted with Kevin Shipp.
Speaker 1:Welcome to Life. Unscripted. Thanks, kevin. So this is like a podcast that sometimes goes off the rails. It's not scripted, it's nothing, I don't plan anything, but I'm really fortunate to have you guys here today. Iannu Odibodi, you got it right. Yes.
Speaker 2:Jason.
Speaker 1:Jason Wright From Walker. Yeah, and tell me a little bit about Walker.
Speaker 3:So we saw a gap in the market and we realized that, as AI begins to become a thing, that as AI begins to become a thing, that there will be displacement of jobs for many people, and that gave us a lot of concern, and that's one of the reasons why we chose to create a company that would be really focused on equipping talents to fill this gap and then positioning them to get opportunities with companies all around the country.
Speaker 3:So our passion is driven by that. But the core of what we're able to accomplish is, you know, think about building AI agents, vertical AI agents, think about automation and where automation is going. I mean, you own a marketing company, so you can imagine how automation can just help accelerate the work that you currently do. So these are the issues that we saw and we realized hey, look, if we can train multiple or more people to be able to address this problem, then the world would be a better place and we'd be able to see acceleration in growth in business growth from a small business perspective, and even from a mid-sized to large-sized companies also can benefit from it.
Speaker 1:So backing up a little bit too. First of all, a lot of people they're still scared of AI and I think there's a lot of unknown because they're not familiar with it. Yes, ai coming out is very comparable to when electricity came out right, and it's so profound and it's made such a large impact at scale to this date that people are still scared because there's a lot of unknown. So that's kind of why I wanted you guys to hang out with me right this episode. Um, because I'm down here and uh, but I'm like the everyday consumer. Like you said, I have a marketing business and I have clients in multiple industries. So I'm trying to come up here and knock on your door in the cloud and say, hey, how can I use what you're doing in my everyday processes? So the way you've explained what WACA does is the way you explained it to me is you just take a lot of the AI tools and then you develop APIs and pull them all together. So my first question is what the hell is API?
Speaker 3:So great, great question. So API is sort of an interface between whatsoever you're trying to do and a database system. What's a database system? A database system is a system that helps store records. So let's say you wanted to enter information about your company, your customers and things of that nature. You put it in a form. It sends it to a SQL database. Now we have like Google Sheets, where people can actually visually see some of the things that they're updating via Google Forms right, but a database stores all this information.
Speaker 3:Now, for us to have access to that information, then we have to go through an API system. If we would have to access someone else's you know data or someone else's information. So companies that are providing these services right now, typically you go in and then you can use whatever services they provide you. But if you wanted to develop it at scale or if you wanted to solve problems at scale, you would have to drag and drop all of these things within the context of the software. So now you don't have to drag and drop all of these things you know within the context of the software. So now you don't have to do that, since you can, you know, interact with the exact same service via an API. So you make an API request and essentially, the request then produces a response that helps you to solve that exact problem.
Speaker 2:I kind of think of it as like a backdoor into, kind of behind, the software, so that way you don't have to go and type it in from the front of it, you can all access it from the backend through code. And so a lot of it, a lot of it is it's it's speeding up the process, it's you know cause. Right now, say you wanted to use a piece of software like, for instance, even chat GPT. You got to go into a, you got to go to chatgbtcom, you got to log in, you got to type in what you want. An API would allow you to access it from the back end of it. So you didn't actually have to go to the website. So you have another tool, another piece of software. You can engage with chatgbt without ever going to the website through that one tool. And so imagine if you could hook into all these other different pieces of software through one tool. That's what APIs unlock the power of.
Speaker 1:So what are some current tools? You mentioned ChatGVT, and then I was showing you some of the video applications I've used. I think Reveal was one of them, where we insert a static image and it turns it into a little video. So I still are using all these tools. So can you give me some examples of what tools currently exist that you could pull together by doing the code and creating the APIs?
Speaker 3:So I mean one is GPT. It's an easy one to explain and, by the way, API means application programming interface, just for some people.
Speaker 1:I'm gonna need that and I'm gonna put it on the screen when I edit this.
Speaker 3:Okay okay, awesome. So. So, for example, gpt is one right. Typically, when you want to ask a question, you put in your information into a chat and then you you add your data and you say, hey, tell me about number of sales that I had this month from the data that I imputed into you and it just does it right.
Speaker 3:But now, rather than having to do that, you could actually interface through APIs where you actually write a code or write code in Python, and then it hits that API and would ask multiple data sets, the same exact question and give you responses that could be actually visually displayed and things of that nature. So typically you would always still need someone with some type of coding experience to interface with it. But what it unlocks for a small business is it unlocks opportunities to do things at scale and to do things pretty quickly. So the things that you used to have to do and would take you five hours to do, now you can do it in five minutes because you have access to one GPT to do the prompting, the data, but also the API that requests that information directly from GPT, so that you can get the response without having to interface with GPT all the time.
Speaker 1:Very cool and I know we talked the other night about, you know, where does AI come into place with human operations, and you said it kind of at scale. So that's where this seems to be really valuable is being able to create, yes, 900 videos in two days, versus the human, yes, and there is a lot of. You know, the people want that human talking to them, oh, yes, but sometimes we can't make that in that time, so like, especially when it comes to video editing. Well, you know, I was telling you all my little processes the other night that I was doing to create 90 short videos and that took me like four or five hours. Yes, and um, ai could have, you know, I could have used, like opus was as a tool, but I still have to go to opus and still have to feed it that video, which is, I'm not complaining because, by the way, has its api system too. Yeah, yeah, so that, because that's light years ahead of you know what we used to have to do to make all of these clips.
Speaker 2:That's correct, that's correct.
Speaker 1:Um so, but what you're doing, and by connecting all the dots, you're speeding up faster and faster and faster and making that a more efficient process.
Speaker 2:Yeah, and I just wanted to throw in a comment. There you talk about what are the different tools. There's probably what? Over 1,000 different tools out there available right now, and my own experience is I came from a, a manufacturing company, and I ran our marketing department, and you know, one of the challenges that I had was I didn't have time to learn all these new tools.
Speaker 2:I was too busy doing my job, and so every day I would come in and like, ok, how do I get this stuff done using the knowledge that I have?
Speaker 2:And I was using stuff like chat, gpt, but aside from that, I wasn't really using a whole lot, but aside from that, I wasn't really using a whole lot.
Speaker 2:And so one of the I think that the things that's coming, that it's already happening right now, is really more of an automation to where you come in and I no longer have to go do the things. We actually use AI to do the things and I just kind of conduct the orchestra so we can create like automated workflows that actually, you know, instead of me going in and creating the social media posts, I actually have an AI agent that oversees that, and so how does it know what to do. Well, I train it, I give it all of my data, I dump everything in there about my brand and about what I'm doing as a company and say here's your instructions. And then I have another AI agent that acts as more of a it summarizes and it brings everything into a usable format and then it passes along. So we create workflows that actually step-by-step. You've got different AI, so imagine chat GBT as just one of your workers and it has a specific task, and then you have.
Speaker 2:You can actually line these things up and create workflows that get all of your work done faster and then so really what your job is at the end of the day is more of like a manager or an overseer that says, okay, is the quality good or do I need to? And you can even train it to go back and edit its own work and figure out what it you know might do better, and then at the end of the day, you basically say, okay, what I want from you is I want you to create all these social media posts and add them as drafts in my Facebook account.
Speaker 2:And then I can go in and manually approve them to make sure that they're on point. So that's really. You know, a lot of people think of chat, gbt, as you know, ai, but really it's it's kind of the tip of the iceberg, it's it's.
Speaker 2:It goes so much deeper than that, especially when you talk about automation and real world applications, because for me, ai was always this mysterious box and, like you're, trying to understand what's in it. But I think this year it's already happening. But this year we're going to see more of it where it becomes practical, where businesses can say, oh, you mean, this could save me 10 hours per week. Yes, I'll take that.
Speaker 1:I'm starting to see it creep into I shouldn't say creep when it comes to AI, because then people but I've heard of grant writers starting to use it a little bit to apply for grants and people are starting to see, oh, this is actually a wonderful tool when used properly.
Speaker 1:Oh, yes, um, I've seen it in health care. So a client, uh, hospital up north, um, they went to a little speech, little little deal, and where they were talking about ai and health care and management. And I walked in on this conversation the other day and I had to go up there to do some stuff. But I heard her talking about that and just from talking to you and you guys, I was like, oh yeah, that's so possible. I said, hey, I work with this company. You know we meet every Monday and they just explained that whole process to me and I she was like that was like that's exactly everything. I shouldn't have went to that thing.
Speaker 3:Right, right, I mean right now you could use AI for training. You could access tons of data via API from multiple databases. Train AI to be able to explain educational materials, company materials, company documentation, fact sheets and things of that nature where employees can actually start to gain real-time access to how to do their jobs more effectively. So this is really powerful.
Speaker 1:With that educational aspect. A lot of companies don't want their information out there, so can you explain how you protect that?
Speaker 3:Yes, I like what you said earlier when you talked about responsible use of AI. Not so many people think about this and how to responsibly use it. There's a lot of work around responsible and ethical AI lot of work around responsible and ethical AI and lots of the government put out a sort of a policy, a NIST policy, around how to responsibly use AI for all the different, I would say, cycles of machine learning development, from data extraction to data training to developing the models to inference. All of that might sound like crazy for some people listening, but we'll definitely get into some of that conversation as we move along, um, and discuss some of this and definitely open to sharing more of that, you know, on your your podcast and getting people up to speed with that, but around responsible use.
Speaker 3:Now companies are moving towards using more open source models, so the idea behind that is you can actually bring in a model like Olamer into your environment and train on Olamer, and Olamer is completely blocked from the outside, so restricted within your organization, used specifically for your own data, has no interference with the outside world at all, and you're still using this information to help your staff to do, to create training courses, to build systems and things of that nature, and so the open source route is becoming a good option for companies that are thinking about the security of their data and being able to have that helps you know a lot, so we're working together on a proposal pretty soon for those educational videos, so that would be using open source and then private network.
Speaker 1:Yes, that's correct and you've mentioned before, basically you're putting a wall between that cloud and that cloud.
Speaker 3:We need to do that, gotcha. We need to do that to be able to build responsibly. Otherwise, you give your data back to the know, the world, to train and right.
Speaker 1:That's. That was the big thing. That's what we kind of talked about up there. Um that hospital was you know, um they, you know they were like well, how can they not get our data, how can they not get our hip?
Speaker 3:this is the reason why you need people that have expertise in this specific area.
Speaker 1:So they could do that, so they could do that. You know anybody?
Speaker 3:we do. I mean, we, we have that expertise. Um, we have that expertise, um we've we've done a lot of work in this. In this space, I particularly have also done quite a number of work um in this space. I have a phd in artificial intelligence myself, so the ability to know where things start to get iffy is really really critical Also outside of just the AI expertise.
Speaker 3:I think it's also critical to have all the stakeholders involved in the conversation, so from the business executives to the subject matter experts involved in that conversation as well, because policy doesn't lie only in the hand of the AI expert. You have to sort of think of it as a more collective effort to get there so the business manager might see some, you know, sides that you wouldn't see. And this is where people like Jason come in and start saying, hey, how do we think about this? How do we look at this?
Speaker 2:And you know.
Speaker 3:So that's my thought process around. It is yes, have your AI infrastructure in place, but also have subject matter experts that can tell you hey, this is what data governance looks like in this space. This is what we want to expose. This is what we don't want to expose. What does our RBAC? Rbac meaning, you know, our role-based access control. What does that look like? You know, who are we giving access to? Who are we not giving?
Speaker 1:access to.
Speaker 3:Right.
Speaker 1:So that's what that's kind of. What that marketing manager up there was talking about is they're allowed to use ChatsBT for a lot of their stuff, but they are restrictive on what they can tell it. Oh, yeah, so that's why they need you guys to kind of come in and be able to make sure they are protected.
Speaker 3:Yes, yes, yes, you could be completely blocked out. And also another thing companies do is they might just choose to use pre-trained models to fine-tune what they already have inside. So you use your regular open source models, you train on your data, but then it's not talking to anything outside, but also it's restricted to what's inside. You get what I mean, and so all the questions you ask are focused on what's inside and not necessarily what's outside.
Speaker 1:So you got a PhD in artificial intelligence? Yes, sir. So how long did that take? Seven years. So you knew about AI seven years ago, Because I never heard of it until three years ago maybe so I got into the information systems program at UMBC Before that.
Speaker 3:While I was doing my master's, I was working on protein sequences, and so at the time, I was using AI neural networks to be specific as a matter of fact it wasn't called AI.
Speaker 1:You used AI to get your PhD. Got it, got it. I get one of those. I get one of those too. I'll get it today. Let's do it. I'm on chat, gpt right now.
Speaker 3:Yeah, I mean chat. Gpt was taking tests, you know PhD legal tests and this thing was doing like was acing the test. So you can imagine.
Speaker 1:You don't need to go for a PhD anymore now.
Speaker 3:All 10 viewers are going to get this confession from you. Yeah, but like I got into my master's program and we were already, it wasn't even called AI. It was called pattern recognition and pattern mining, data mining.
Speaker 1:Really yes.
Speaker 3:Yes, okay, so the name has actually largely evolved from data mining. We started calling it machine learning and then we started calling deep learning and all of a sudden you had this whole generative AI thing come out. And then everybody starts calling it AI, which is perfectly fine. I can spell that. But if you read some of those old books, you know artificial intelligence would be compared to like expert systems and things of that nature.
Speaker 2:Now how did you get involved? So we, you know it was interesting, because it's probably been about a little over two years ago that, um, I met jan it was actually through our church and, um, you know, we, we, you know he knew that I was in business and we started talking and it was like, you know, I wonder if there's something here. And at the time he was trying to get me as a client to you know, and it was interesting this is just a barter.
Speaker 3:Yeah, it was interesting.
Speaker 2:This is just a barter, yeah.
Speaker 3:It was interesting Six months back and forth.
Speaker 2:Yeah, we were having meetings and you know, I'll admit, you know, my struggle at the time was because he was talking, you know, and, and Yano's world is like this big, and I was living in a world that was this big and I couldn't get there, I couldn't get what he was talking about, cause I'm like I don't even know what's possible. And you're, you know, when I ask you, you know, what can we do? His answer was anything.
Speaker 3:And I'm like I need more specifics.
Speaker 1:I'll take two yeah.
Speaker 2:You know, and so my challenges at the time were in the realm of marketing and I had all these manual processes that I was going through every day. You know, ad managing, adword campaigns, like doing all of this stuff. That was very labor intensive, you know from or you know it was.
Speaker 1:I wasn't actually, it wasn't hard labor, but let's get it straight, man, cause I do some of that. It wasn't that hard, but it's commitment though.
Speaker 2:Well, I was starting to. It started to get me thinking about, you know, maybe maybe I'm not doing things in the most efficient way, maybe there's a better way. Long story short, you know, I ended up leaving my job last last summer and then we started talking about like hey, maybe we should do something, like maybe we should actually start, start start something, and so that's kind of how I got involved. But you know, since then, you know and this is why I say this because when I was working I knew that this, that some of this stuff was coming, but I did not have time, I didn't have time to learn it. And so since I left, I've started to understand a lot more, because I have a lot more time to really dig in and kind of go down rabbit holes and figure out, like, okay, what is he talking about?
Speaker 1:Is he on the phone at night with you for an hour and a half?
Speaker 2:Yeah, so after you know five months or six months now, I'm just now starting to like get the gravity of what we're dealing with here, and some of this stuff is happening faster than anyone realizes, like I think most businesses would be shocked to understand how fast this is. It's like a freight train coming at them and they don't see it coming. And, in my mind, what this really means is the businesses that get it, the businesses that embrace this, are going to have such a competitive edge over the businesses that don't. It's not even going to be fair. I mean, they're going to. A lot of businesses are going to go under, not because AI is replacing their jobs, but because they don't embrace it, because what it empowers you to do is to do things better, faster and cheaper, and your competitors are going to do it, and so it's going to be. It's going to depend on how willing you are. Are you to embrace this new technology and and to accept that it's part of it's part of the way forward?
Speaker 1:before. Before um ai, I had no idea like what the dental industry is like, what the car automotive industry is like or the automotive collision repair and all this stuff. So I could create content. I could still do videos and stuff, but I couldn't post shit on their social media pages because I didn't know anything about it. But then AI comes along. I start sitting there and having conversations with ChatGPT and then it gets to know me and how I talk. Ai comes along, I start sitting there and having conversations with chat GPT and then it gets to know me and how I talk so it can understand me, and then I can start developing content based on that Brand packages, everything On AI. Now it's a full-scale marketing business, right, and it's just me and a contractor.
Speaker 2:I think the next level is really in the realm of automation because, you've got the tools, now you're able to do stuff better and maybe faster. But where automation comes in is it almost takes a lot of what you're doing out of the loop and so now it does all the stuff that you were doing and now you just kind of oversee it.
Speaker 1:Yeah, so we spoke off camera about this before a couple, last week or whatnot. But I want to talk on camera about this because I kind of want to explain to these people how this would be very efficient. Just in my world, there the other day, I had scripts that I got off of chat gbt 30 scripts for 30 videos, 20 second long, and I had them on a teleprompter. So I went up there and I miked them, lights, everything, filmed it, all of that. None of that would really change and then so then I had my a roll, which was all that voice, and then I got b roll footage of the golf carts and drone footage and everything else. So my current process is to come back and put it on my server, my little nasa home, and then of course, it's already set up to where it backs up to google, a google file. But then I still got to pull those videos and that's where I sat there for four or five hours at night and edited 90 videos. I had three um duplicated, three people, but um, that still took. That took a lot of time, because then I have to a roll b roll call, a grade adjustment, layer, captions, then I have to export, do it in and out in adobe Premiere and export each one to that file. Okay, so then I got my videos.
Speaker 1:But now I still have to go to chat jbt and say create a caption based on this video, and I could slide my video in and they can analyze it, or I could just say what that video is about. You know the title. Basically I'll just take that title. Anytime it's a short clip, it'll get what it needs create my caption. And then I have to open up a software like Metricool to create my post and schedule it or post it. But you could make something that pulls from the Google file. Yes, literally. So as soon as it backs up to the Google file, I'm hands off.
Speaker 3:Yes, and you could tag your videos. You could make the AI analyze the video and tag the videos for you based on certain words or certain voice commands that you put in there. You can see A-roll, shot one, shot two, and it would recognize that and use that to actually even build the entire sequence for you. Now you could also take AI and use it to edit the video and say, hey, take out second 0.001 to 0.10. So the idea is you need to have a workflow for what it is that you're doing and for each of those steps, there are systems in place that we built that would also help you to do it.
Speaker 1:So you could take it from. As soon as it backs up to google, pulls it, edits it, it creates the copy for the social media post and then it actually schedules the post as a draft. Yes, to where? Later on in the day? Absolutely, I'm gonna get more sleep yes, take my credit card.
Speaker 2:Now, let's do this let's do it so we had a, we had a customer that, uh, it was a couple of weeks ago that they approached us and they said we want, we want to build a um, a nano learning platform which is just small videos, very like 30 second minute long videos, that that their customers would pay for subscription and they would, they would be able to consume kind of like different content videos over like leadership and motivation and all these different topics.
Speaker 2:And they said so we want you guys to create the platform. We also want you to create all of the content. So develop all the content and also create the videos. So basically they had nothing at the time. They said can you guys develop all of this for us? We created 900 plus videos in three days.
Speaker 2:three days and developed the app. The entire thing was done in three days that's crazy. Yeah, yes, that's the power of automation, and it wasn't just like, hey, there's a tool that you can go out there and do this with, because there wasn't.
Speaker 1:We had to hook like using apis, we had to hook like 10 different tools together so apis are just like little chain links that you can just clip together in all the different ways.
Speaker 3:You can imagine to have that and then have an AI-powered system in front of it.
Speaker 1:Mm-hmm.
Speaker 3:Game-changing.
Speaker 1:That's interesting. So is there anything, as we kind of wrap this up, that you can tell, you can kind of pass along to the everyday consumer, because I feel like every day somebody should be playing with some type of ai tool just to get familiar with capabilities? Yes, you know, and we've seen open ai pretty much dominate. Um, google can't keep up. And here's a. Here's something I like to ask people. Do you think, as I start to use chat gpt more and more and more, I don't use google for anything as a search engine?
Speaker 1:I use chat gpt as a search engine and uh, do you think this is just off the cuff, casual that one day open ai will take out google, or because I know they keep trying to catch up with jim and I. Yeah, but jim and I keeps putting out some awkward um, giving you about some awkward answers and stuff, so so I have a very interesting take on this.
Speaker 3:I think Google is going to continue to stay ahead of the curve here. Yes, because Google. It was a paper that was written out of Google. Attention is all you need. That's how GPT got created. So a lot of the things that we see on GPT the foundational knowledge was learned from Google. Now I don't know what Google's search engine optimization or how they run their ads would look like in the future, but that's not to say they wouldn't find new opportunities.
Speaker 1:They got to step it up because their Gemini. They'll run their Gemini for a while and then they'll take it back down because they can't get it to perform like chat gpt does. Yeah, but here lately I've noticed they've kept it up, so I don't know if it's doing better chat.
Speaker 3:Gpt2 does have its own challenges, though, because, um, like, there's no ai tool that really has that reasoning capability all figured out. Because it's all text, so it's natural language processing, right. So it's all text. It learns by sentence completion, right? So you know, two plus two goes into the database you know, and then it tries to see, okay, what might be the answer to that.
Speaker 2:The other thing is OpenAI. They don't actually own any of their own data. Like google has youtube, gmail, all of the you know, google has their own set of data that they can utilize. Um versus chat, gbt is using other people's data oh yeah, it scrapes the entire internet.
Speaker 1:Right, that's it. I mean right. That's why I use it as a search engine instead of google, because this thing's gonna scrape the entire internet now. Will it eventually catch up to where there'll be copyright issues with, uh, with like chat, gbt and other tools? I think?
Speaker 3:the uh. Data is now gold, like data is the new gold. Literally, data is a new currency. So I think every company should keep their data really proprietary to them because that information would be so gold in in the new age of ai. And so yes, but I think that copyright issues is going to be a problem because now, with access to books and access, to all that information.
Speaker 3:You can just feed that into an LLM. There's a lot of issues there. I think there would need to be more laws around how people's books get used. There will be some ethical stuff that would come out of that.
Speaker 1:I wonder, because there's a few podcasts that I listen to that talk about some of this and you know they talk about will Google keep up with open AI, that kind of stuff? They talk about the lawsuits All of them get sued all the time there was deep seek or something like that. That's an interesting one. They've been brought up before.
Speaker 3:Yeah, yeah, an interesting one.
Speaker 1:I don't know if you want to share. Not, I don't get a whole lot of viewers, so don't worry about that. Well, so, so don't worry about that.
Speaker 3:Well, so DeepSeq and there's been a lot of concern around this DeepSeq and around where it's trained, how it is trained, what data they're using for training and things of that nature. But it goes back to what I was saying earlier is, if you're using DeepSeq within your contained environment, then run as much security tests around it before you use it. Otherwise, ensure that, whatever platform you're using, you're not feeding it private information or data that is sensitive, because all of that whether they say they train it or not, we don't know right.
Speaker 3:We still have to be careful, and so it's really critical that that's done. And running these models are not really hard to do right now. In a day or two we could take care of that kind of thing for any system.
Speaker 1:So I think we're getting it to where I'm going to understand all of this. So I think we're getting it to where I'm going to understand all of this. So they're basically like. Chatgpt is just like a big box of millions of APIs all talking to each other.
Speaker 3:No, GIPT is using a bunch of people's data training it, using AI to generate this model that we all go in and ask it questions how?
Speaker 1:do they get that data, though? What was that? That's going to be my ringtone for you from now on, oh man. So they script the internet.
Speaker 3:So they script the internet, you know.
Speaker 1:Are they using APIs to script the internet, though?
Speaker 3:No, not necessarily. They might be getting some data from internal systems, you know, via API. So ChatGPT might have reached out to this company that does. There's this company that has lots of images. They might have reached out to them and say hey, would you give us access to your API so that we can get all your images, so that we can use that to train our model to do.
Speaker 2:X and Z. They collect data for training.
Speaker 3:Yeah, they collect data through APIs for training.
Speaker 1:But what you can do is come in in a more secured fashion and create the AIs and code it to get more secured product end product.
Speaker 3:So what we could do is isolate that model, put it within your environment, use an open source version and not necessarily an open AI system. Open AI has its own so it's just totally up to any customer once you use that.
Speaker 1:Open AI has good application, but not in every single industry, Like healthcare when we were talking about healthcare and everything else that is correct. That's where that would really come into play is you can come in and build a more secure system that they can still use.
Speaker 3:Also, some of these models have their limitation in terms of their responses.
Speaker 3:So all of them run between, I think, 4,000-something tokens. So even if you put in inputs in terms of questions, there's a limit to which the number of answers they can produce, which definitely also limits the way that the responses come out, and things of that nature, because some of it might appear somewhat summarized and things of that nature. There are ways around it, you know, and chunking and things of that nature, but I think ultimately the core of it is, you know, being able to isolate it, bring it into your environment. The core of it is being able to isolate it, bring it into your environment, use your data to fine-tune what already exists and supercharge your operations. That's crazy.
Speaker 1:Yeah, I'm ready to start seeing it. Let's do it, let's do it. I don't even know where we start, See Caffeine.
Speaker 3:Well, see, I always say, like, try to look at your process and see which of your processes brings you a lot of pain, and then ask how can AI help to do that? And the best place for people to start is to use ChartGPT to be honest with you. Just to get it, just to get it just to get familiar yes, and don't think of gpt as just a question and answer platform. Think of gpt as your companion, who is there to give you some guidance, wow yeah well, the other night.
Speaker 1:So, randolph county, they wanted that marketing proposal, yeah, so I kind of knew the nuts and bolts of what I wanted to pitch, but I needed help. So for it was about two and a half hours I sat there and talked to ChatGBT, put it on, talk to text. That way I'm not just getting arthritis. But so I had that long drawn-out conversation, conversation with chat gbt, and it got me thinking about certain points and then I would be like, okay, so what if we change this a little bit? Or you know, um, how can we connect the employers more? How and it literally helped me write that entire proposal um, I've done a lot of that where clients have wanted proposals.
Speaker 1:Well, they don't want them in a month, they want them as soon as they text you, as soon as they call you. They want that proposal for those videos or marketing. I literally plug that in and get a proposal. And then I will talk to ChatGVT and sit there and say, okay, but let's change to these terms net 30, net 90, something like that, and put a cover letter to it. And there's my proposal for marketing services, send it off, they like it. I literally just take that document and put it back in ChatGPT and I say now, make this a purchase agreement, gives me a purchase agreement. Throw that in Adobe and get it signed.
Speaker 3:So, Kevin, imagine if you now had the opportunity to basically have a form right in front of your website. The customer puts what they want and the proposal gets created.
Speaker 1:That would be crazy. That would be crazy.
Speaker 3:Yeah, and so you have the proposal right there. You just review the proposal, like Jason would do, check for all the issues that exist in the context of the proposal. Update it, feed it right back, generate your PDF, send it right off While I'm driving down the road on my phone.
Speaker 2:You know what I'm saying Automation, automation, right. So you brought up an interesting point. I wanted to touch on that for a second, because, you know, a lot of people are concerned about ai replacing jobs, and while, while that may be true to some degree, I think it's going to be more of a shift where it's it's it's going to change the nature of work, and so you actually brought up a really good example, because what I think there's the most power is really going to come in the form of AI combined with subject matter experts. So you already knew what you wanted, you already knew what you were doing, you knew how to do it, you understood, you know almost you know you're functioning as like a CEO or a manager. You know the work that needs to be done. Now you just need to get it done, and that's where AI comes in and helps, but it still needs you to guide it, because if you've got somebody who doesn't have a clue what they're doing, then they're just going to have to hope that AI got it right, and it doesn't always.
Speaker 2:That's where it gets its bad reputation. Yeah, it doesn't always. It makes mistakes, and so it needs it needs a human in the loop, human in the loop to be able to oversee it, to make sure it's doing the correct things. So I think you know, you know the. The buzz is, you know, oh, ai is going to replace people. It's actually not. It's going to give I think it's actually going to give people the more important jobs, which is really acting almost as like an orchestra, like an orchestrator or a conductor, somebody who's looking at the whole picture and saying, okay, you know, making sure all the jobs are getting done correct, they're, they're providing oversight to the AI, which AI is just doing you know the, the grunt work a little bit, where the stuff that we're really not even that good at in the first place.
Speaker 2:But I think there is value in having still people with very specific skill sets. I mean you can look at like developers. You know and I'll just use myself as an example I'm not a developer, I'm a marketing guy. So I don't know how to write code.
Speaker 3:I mean, I know a little bit of.
Speaker 2:HTML. But other than that, you know, I've been using AI to help me build things just because I've been practicing with it and I get stuck a lot. It can't, it can't quite do it, and so. But where the real value is is actually having training a developer who already knows how to do all of it to use the AI to help him do his job better and faster, because he knows when it gets stuck. Oh, you're doing this wrong, or I see, I see what the issue is versus a guy like me, like I have to, I have to go to Yano's like help, I'm stuck. I don't know enough about code and development work to be able to figure out what the problem is. I'm just practicing, but it may get to that point at some point. But right now I think there is a. You know I always tell people a lot of times it's like, you know, ai isn't quite as scary as you think it is. It's actually going to assist us and help us be better and do more important work.
Speaker 1:Like I said, it's the new electricity, it's the new cell phone. Everyone was scared of both of those when they came out. So I think grasping it as soon as you can, learning it as soon as you can, that's the biggest takeaway, absolutely. Well, I appreciate you guys hopping on here with me. Thanks, kevin, this is an honor.
Speaker 3:Thanks, especially, you've done a TED Talk when did you do that TEDx Many years with that, like maybe four or five years ago.
Speaker 2:So you just keep going down because now you're on this.
Speaker 1:You started a TEDx Now. That'd be cool.
Speaker 3:Yeah, I'm watching. It's good it's. I'm really excited to be here. Thanks for having us.
Speaker 1:Oh, I appreciate you guys hanging out with me, cause, um, I'm just kind of like a mediocre marketer and whatnot, but or whatnot. But I'm real fascinated with what you're doing. I look forward to working with you guys and growing together and scaling together. Yeah, I look forward to the same as well.
Speaker 3:No-transcript.
