22 Sides
22 Sides is a podcast that will let you get to know some fascinating people and keep up with many things that are happening in and around the Houston area.
22 Sides
Navigating the AI Landscape with Jha Allen
Artificial intelligence isn't just changing our world—it's redefining what we consider "intelligence" itself. In this fascinating conversation with AI consultant Jha Allen, we explore how the definition of artificial intelligence has constantly shifted throughout computing history. Every time technologists accomplish what was previously labeled as "AI," we move the goalposts and declare it's not "real intelligence" after all.
The true revolution of today's AI tools like ChatGPT isn't just their power but their accessibility through natural language. As Jha explains, "The biggest thing that makes this revolutionary is language. Before, only tech specialists could understand it, but now the common person can access that same technology—which also makes it a little scary." This democratization has profound implications for businesses, privacy, and how we understand intelligence itself.
Our conversation takes unexpected turns as we examine AI's impact on jobs (if AI handles half your workload, should your salary change?), data privacy concerns (why are people willing to share intimate details with ChatGPT when they wouldn't with Alexa?), and the ethical considerations of AI decision-making in critical situations. We also explore practical approaches to learning AI technology, with Jha recommending focusing deeply on mastering one tool rather than spreading yourself thin across multiple platforms.
Whether you're a business owner looking to integrate AI, a professional concerned about technological disruption, or simply curious about where this technology is heading, this episode provides both historical context and practical insights for navigating our increasingly AI-enhanced world. Join us as we explore not just what AI can do, but what it means for how we work, communicate, and understand intelligence itself.
To find more about Jha Allen see https://endless8marketing.com/
We hope you will listen often.
For more information, visit our website 22sides.com
We don't care. Well, is there anything that you want to talk about or don't want to talk about?
Alexis:There's something I want to talk about. What do? You want to talk about. That's who we are and do the introduction.
Robin:Okay, let's do the introduction.
Alexis:You know I mean we frequently end up halfway through the podcast before we think about doing the introduction.
Robin:We'll jump into it. So let's see. Thank you for joining 22 Sides podcast. This is Robin Meck, and we're with Alexis Melvin today and Jaw Allen. We're really excited to have you in. Thanks for coming in, Jaw.
Jha:Definitely I'm excited, I'm excited.
Robin:Yeah Well, you are already out there a lot with your tech and your media, so I think if people want to find you, you're youable and you actually teach people about tech and media, which I think in this day and age there's a lot of gaps to fill, so it's important to have someone like you to come in and gently assist people in whatever that gap is.
Alexis:So that sort of gets rid of my first question, because I was going to say so what do you do? I'll ask it anyway and let you explain it. No, definitely so I started out disagreeing with Robin. Go right ahead.
Robin:Yeah, I don't know anything about tech. Don't throw me under the tech bus.
Jha:No, no, no, you got it right on the head pretty much. So I started out in marketing full service marketing agency, website design, social media, things like that and then over the last three years, we've really focused on consulting, public speaking and training. Like you mentioned, training on artificial intelligence has been the number one training segment that most companies and small business owners want to learn about is how to integrate AI into their current business, whether it's their process, their systems and just kind of getting used to it.
Robin:I feel like it's coming out fast on a lot of different.
Jha:I feel like it's coming out fast on a lot of different platforms. It's built into our computers, now even on our phones or listening devices, the Google, the this, the that. And so I feel like, even if you maybe don't think about it or don't want to use it, know, just because right there they're not using it or they don't want to use it, kind of like, um, if you see it on like social media, like meta, has their meta ai when you're trying to make a post or instagram has it popped up one day and I was like I don't know you yeah, you.
Jha:So just because you have it, most people they don't. They don't want to use it or they are not interested. They might it, but they really don't understand what it is you know this podcast.
Alexis:We use AI for two things. Number one it comes up with the descriptions. After going through everything, it comes up with descriptions that we never thought of but are right on.
Robin:That's pretty good. Yeah, it's great.
Alexis:And then the transcripts. It does the transcript which is very helpful.
Robin:You know, I mean, we've had a podcast before and then you would have to outsource a person or you'd have to worry about lag time and I want jobs for everyone but at the same time, AI just does it right there if you don't have the skill set. So if you're thinking about starting a podcast and you're like, well, but I'm not that great in language or I'm not that great in typing, or you know it's an audio thing, so this would be the thing for me, but what about the components where I'm going to have to, you know, type and things like this? Co-hosts has been really great for us.
Alexis:It's very inexpensive, but Buzzsprout is the part, the one that we use. It's been really good.
Jha:Yeah, buzzsprout gets it out for you so you can attach it to any podcast. Apple Spotify.
Alexis:The only one we are not on is iHeartRadio. Iheartradio Because they have an infinite amount of forms you have to fill out, and I'm not kidding. You fill out all their forms and they're like and here's set number two.
Robin:And here's set number three. And when Buzzsprout makes it so easy, they're like and here's set number two, and here's set number three Buzzsprout makes it so easy, we're like eh, we'll just go with the ones we're on.
Alexis:Well, we're on literally everything else. So it's like yeah, and eventually I'll get around to filling out the rest of the forms. But you know, when you say, well, it's like two in the morning, I don't have anything to do, I'll go fill these out, and you and I were filling out forms and you're like this is ridiculous.
Jha:For real, especially for just eye heart. You know that's like okay.
Alexis:I mean, you know, for the seven people that ever see it.
Jha:Right, it's important, but it's hard.
Alexis:It's hard to know who your demographic is when you're like first putting it out there and you know, when I look at you, you're always reminding people like who you are so for our listeners.
Robin:how would you create yourself for them? What do you mean by that? Well, we said what you do. Good question on your part. I was wondering that too. Well, we said what you do, but you know, if it's obviously not a camera podcast like, how would you say who Ja Allen is Like when they work with Ja, when they know Ja, when they think with Ja, when they know Ja, when they think about Ja? What do you want your people who are introduced to you to be left with?
Jha:That's a good question, actually really good, I would say. I would want them to know. Well, first of all, I want them to know like integrity, that's a huge thing for me. Person is very honest, this person is very creative, this person is a forward thinker, always thinking outside the box, very systemized in their approach and their move and what they're looking to do next. So ideally, I would hope that's how I come off of my current people, what they would say about me. I think that's true, yeah.
Robin:That's good. That's good. I think it's absolutely true, and we're just talking off the cuff here. But I always think of you as somebody who's generous. You're always trying to give people tips and tricks, even if they're not your clients. You're like sign up for my free sheet and just get started where you are, because you have helped a lot of small businesses and a lot of times they may think of marketing as an afterthought, but that's the thing that will get them to the next person.
Jha:So they got to start somewhere. Most of the time, most of the time. So no, yeah, definitely. I guess I never thought about it. I never think generous when I think myself.
Robin:You don't feel generous? It's not. I don't feel, it's just not. I'm stingy.
Jha:No, no, you know how it is. I'm doing a thumbs up on that comment.
Robin:No, oh, you met, you met John and you were like not this person this right now I'm just like generous.
Jha:You know that's such a word. I guess I think we all have that, though, like words, we don't necessarily categorize ourselves, but we naturally maybe because it's more of like well, that's just who you, a vibe you're always in, so you forget that that's the vibe that you are.
Alexis:So, yeah, yeah, sometimes we just are that we don't try to be that right yeah, thanks, and you don't list that in social media, because then everyone will try to take advantage of you.
Jha:That's it now.
Robin:That's the truth now, that's the truth I only have one free sheet, right, yeah they might list to this podcast.
Alexis:Robin told us your generation. It might turn into that be careful, be careful so we now know whose fault that's going to be right well, I don't know.
Robin:You could have said a few things. You could have said well, I'm a recent dog lover, I got a dog named Louie.
Jha:Oh yeah, louie.
Robin:I got a dog named Louie. Who's got me? Wrapped around his little paw. Yeah, you didn't see that coming.
Jha:You know, and it's funny, I'm trying to get well. I wouldn't say I'm trying to get better at that. I noticed that when people ask me well, who are you? And things like that, I never associate personal facts or personal traits about myself.
Robin:Well, that's true, I don't know why, I just don't. Sometimes it's hard. Yeah, some people lead with their accolades. Some people lead with, I mean, I like fruit or I like steak or I like this. You know, like whatever they think of is what they think of, you know. But when I think of you, I think of louie, because I'm a dog lover too, and then, uh, I love how fur pals come into our life and they like it's kind of a surprise to us, they own us for sure.
Robin:But, it's a surprise to us, and Louis strikes me as that type of gentleman.
Jha:Yeah, he is. He is, yeah, louis, yeah.
Robin:And then you took on fitness and you share a lot about fitness on your social media, which I think is inspiring, because a lot of people think, well, what if I can't get started, or why should I stay working on it? And you're constantly reminding people that it's the everyday steps that add up.
Jha:It is, oh my God. You say fitness. I'm just like, even I still do.
Robin:You don't probably think of yourself as a fitness person. No, I don't, you know't probably think of yourself as a fitness person?
Jha:No, I don't. And then you know, sometimes I'm like you go in the gym now and everybody has their little camera and record and stuff and I'm just like, oh man, I just, I'm just in here to get it done.
Alexis:I don't necessarily want to see what that would look like.
Robin:And a lot of people don't want to see it either.
Alexis:Yeah, I know they don't want the person next to them to be their camera to be over.
Robin:Then for some people it's like accountability, or for some people it's like they track their progress.
Jha:Right, right right.
Robin:And I do happen to know that it was just a goal you set for yourself, and then you kind of kept going.
Jha:Yeah, yeah, yeah, exactly, exactly. So, yeah, I'm out of the recording stage. I don't, and I wish I was. I wish I felt sometimes it was like I don't and I wish I was. I wish I felt sometimes she was like I don't know, I feel self-conscious in the gym.
Jha:I'm like I don't want to be sitting here recording myself, recording myself, but I try to break out of that, you know but I'm pretty egotistical, in my opinion, to want to record yourself yeah, in the gym sometimes some people be fitness like fitness trainers and stuff like that's what I I hold, as sometimes it's like that's their job or they like you know?
Robin:Yes, it is their job.
Jha:In my view. Are they paying me? You know how it is with social media now. Oh, I know. Or like that's like, they use it for like promo to get more clients, or they want to record their clients.
Alexis:I took this person. They were so bad. Here I'll show you.
Robin:Well, it is hard when you feel like you have an audience that's watching you and you know maybe they are, maybe they're not, Maybe that becomes a persona, Maybe it's authentic to yourself. Like, there are some social media and media in general repercussions and I think some people got into that mode of social media, especially during the pandemic, and didn't even know some of those repercussions. For instance, we had bit of the isolation and loneliness factors that some people have, but for job to job and marketing and missions and connection. It can also lend itself to that too. So it's about how you use it. So I mean, where do you find that you come in for people and meet them where they're at, mostly these days with marketing?
Jha:what I found in coin being coined as consistently is just the simplicity, because I try to make everything as simple as possible and understanding people that they just don't they're not there or they don't do this every day. It's not something that's normal for them. So just finding ways to consistently bring up the simplicity of how to use it, especially with AI. So, like every Wednesday, we send out a newsletter which is updates on this is what's happening with AI. We coin chat GPT, because that is one of the bigger platforms and that's the one that's the most known. So we will do and I stick to that software, that's it. I don't. I hardly. We will do and I stick to that software, that's it. I don't hardly bring in other ones, because I've noticed that I was literally just talking to someone earlier in a meeting about this People. I think I'm great at what I'm doing, but I think people don't understand that the reason that they feel so great after this workshop is because we were focused. We weren't in here like looking at a lot of different tools.
Alexis:We were in here focused, because if you throw in like 30 other ones, yeah, you can't learn enough no right, because humans only learn at a certain speed right, dad, and they feel like you know they're.
Jha:They're not leaving feeling accomplished, or they they might feel like they learn something, but they don't feel as great as if we take a tool that they probably use every day and I just show you how to use it more effectively or more efficiently, because a lot of people use ChagVT every day, but the way I use ChagVT and the way they use ChagVT might be two total different ways.
Jha:It's because they don't know or understand certain features and certain aspects that you can do on ChagVT, whereas I study and I do understand it, so it makes it easier for me to educate you on something that you use every day, kind of like a social media manager, where it's like at one point we're like, well, why do I need a social media? Um, a manager. But it's like, well, they understand TikTok a lot more than you do when it comes to just posting a video, or Instagram, which is posting a post, ideally they're expert in what they do, so they understand the features and how to use it at a different level than just you would if you're just you know posting.
Robin:It's so important.
Alexis:Go ahead. I was going to say a lot of the other AIs that you might end up using. You know, for instance, if you're doing anything with video or anything with photos, you're going to use Adobe, yeah, and you know it's built in, but it doesn't take very long to learn it if you just generally understand how they work and you know the same thing with. You know a few of the others, right, it's like they're very specific purpose, specific use, like the one with the podcast. I mean, it's easy to use because it does a certain set of things and it does them really well. Easy to use because it does a certain set of things and it doesn't really well. But you know, the idea is, if you understand generally how it works and chat, gpt is about as generic as you get.
Jha:Right, and you just said a valid point, which is a lot of these different tools are building in AI to something that's already there, so you don't got to recreate the wheel, although it is going to be hundreds of AI tools that come out like new tools that you've never heard of. But I try to encourage everyone that what is a tool you're already using? Because nine times out of 10, they see where we're going and they've probably already integrated AI into that tool.
Alexis:And the one thing that I've noticed is you want to make sure that, if you're picking up an AI tool, that you understand what the learning base is for it, because if it's really shallow, then the AI is going to come up with really shallow answers. That too, yeah, and again, that's why you know. If it's something image-wise, adobe has a way bigger learning base than anybody else, right? No, definitely, and I think that's a big part of it.
Jha:Definitely, they call it prompt engineering. So, the way you're able to ask the different tool how to do something for you affects the response that you get, whether it's picture, video, text.
Robin:For somebody who does this as a profession. How much time do you use to keep learning all this stuff? Because I think that I can only imagine it's just sort of endless, you know, I mean, do you try to pull yourself in a little bit and balance your screen time, or do you get in there and geek out for a few hours? In there and geek out for a few hours, or like, what's your, what's your strategy on on how you stay? Uh, enough, not not knowing all things, but enough up to date to be able to communicate what you know and maybe to apply it for your people ideally, my goal is to listen to something every day one video a day but I only listen to a particular.
Jha:I only listen. I'm there. I've learned to be very focused with this stuff so, like on um youtube, I'll listen to ibm technology okay, that's like a training video yeah, they, they have.
Jha:Every day they come out with a new video about ai or about technology as a whole. Typically it's not a long video, um, but every day I'll listen to something with IBM or OpenAI, which is ChatGPT, has an academy that teaches you everything about ChatGPT. So I'll listen to one of their videos and then it's some like YouTube influencers that I will tune into, but I don't tune into a lot of them because it's biased information. I'd rather just learn directly from ChatGPT or I learn directly from IBM. But my idea or my goal is one video a day, even if the video is like six, seven minutes, because IBM is good for making like a seven minute video that's just packed with information.
Jha:And if I have more time I can do like a 42 minute video or one hour. I try not to do nothing over an hour. Or if it's like two hours sometimes it's like a podcast and they're going back and forth, but even something with two hours I learn I got to digest the information, so I'm big on like I'll listen to it for like 10 minutes, 15 minutes, and then I have to stop it and then I'll just sit with whatever I learned, because usually I'm working and if I'm working it's hard for me to work and listen, because I want to start implementing I get excited, I'm like, oh, I didn't know I could, so I'm going back and forth.
Jha:So, if I notice I'm learning something really new and insightful, I'll stop listening to it. If I'm doing something that I want to focus on, because I can't focus and listen at the same time.
Robin:It's good to know yourself.
Jha:Yeah, one thing every day, even if it's small, I'm on everybody's email list.
Alexis:The interesting thing is nobody can. It's just a lot of people think they can?
Jha:oh, yeah, yeah, yeah, I guess.
Alexis:So, yeah, yeah, yeah, yeah, I mean you know they've done all sorts of studies and tests. It's like no, you can't do two or three things at once.
Jha:Yeah, you know you swap in and out fast, but people aren't made to have multi-processing yeah, you know, but I noticed that and well, I I probably try to do it with other stuff, but when it comes to learning, I don't, for some reason.
Robin:I'm just like no, that's good, it's too.
Robin:Yeah, you know when to focus yeah, I'm like no, it's too good I like the fact that you just made that accessible for people even listening to this, because you know like they may not be running a business, they may not need your business, but they might want to learn something about what they've got going on. And it's like, well, what influencer do I start out with? I agree with you, I think go to the source of the makers, and so it's more streamlined. But I didn't know they were pumping out that content every day, so that's kind of cool to know yeah, ibm pumps out content every day and then um chat, gpt or open AI.
Jha:They have their own podcast now and they have it. They post they've been put. They're on their like third or fourth episode. Wow, so you, if you are using something like a chat GPT, you can hear directly from them on different things that they're doing with the technology.
Robin:But yeah, they're like their third or fourth episode um open AI podcasts my concern with chat gpt, just as somebody who's like observing this, and I'm the type of person who, uh, is late to the game, like I'm not, I'm not, I'm not putting up myself on a platform, my image like anything and and I'm a, I would.
Robin:I would say that I'm not tech savvy, but but my concern, just observing chat gpt, is you you in your information, you talk to it, things like this, and what I'm seeing humans do is they didn't want to talk to their Alexas or their Google, you know, in their house, but they're telling chat GPT everything, like they're even using it for therapy.
Robin:So I'm like, wait, how did we go from they're listening to let me tell you all this stuff and make you my personal assistant, my best advisor and now my therapist, and, and okay, if it's delivering on all and all that, like I wish everyone well and maybe it's accessible and this is the thing we've been waiting for. But when it goes into the the void of data, if you will, what's to say that? Let's say, if you're a business person and you're giving it your ideas and your business data, that somebody in you know another state, another country, isn't going like oh hey, this is the best idea that chat gpt gave me and it's like your idea, it's your stuff. We used to copyright stuff, but now we're just giving it away freely ideally is there any?
Robin:is there any talk about that? Like I'm on a right track about that because I'm like that is that's interesting. Like I mean I could literally say my idea right now and then somebody in france is hearing that idea from chat gpt and be like that's my idea and I, I don't know. Is there like a stinginess that is there for people or that's going away for people, or what's chat pg doing with all that stuff?
Jha:nah, you know they promote that they're keeping your data. You know it's private. If you pay for it, then you can like. It's a feature on there where you can say don't train the model on my data. So ideally the model is not being trained on data that you're giving it.
Robin:However, we humans believe that.
Jha:Yeah, that's, that's that's what we believe. That's what we believe. So that's their hookup on that. But when it comes to no you're, you're absolutely right. I think it was just a progression. So, yeah, at one point we we didn't want to talk to Alexa or Google Home. However, now we're open to talking to Chad GPT and I think it's because of the comfort level in the east that they've made Chad GPT into everyone's life.
Jha:So I was listening to something that Sam Altman said, which he was even shocked when they came out with um Chad GPT, because he was like they weren't thinking it was going to do this good, but he was shocked that how many people just like to talk to the model. So it's not even necessarily like it doing anything for you. It's more so of you being able to talk to it right and it can comprehend and talk right back to you. Um. So, from a from a standpoint of it, now being um able to do some of your tasks or to really answer any type of intricate questions you have just makes it 10 times better. But at one point it was just it's able to talk back. It's a chat like I'm able to converse with something.
Jha:And yeah.
Robin:And when we were in the COVID pandemic and we were isolated and loneliness was already an issue before then. Like I want that for people to some degree right.
Robin:But then I'm a little concerned where it's supposed to be something that learns you and you shape it to learn you and I've thankfully seen some therapists speak to this Like you have to sort of. They say you have to sort of ask it to ask you the hard questions too, not just what you want to hear, or have it ask you like what you're not considering. So it's not so you shaped Right and because, like are we just basically creating another?
Jha:you know, us bubble me bubble. It seemed like it was skewing towards that. Ok, however yes, to whomever you've seen this from you do have to prompt it to ask you the hard questions or to be your thought partner. And it's different. I teach these different traits you can have it adapt to. So if you go in your settings, you can change the traits and say, hey, I want you to be more thought provoking, I want you to ask me the hard questions. You can kind of train it to how you want it to respond back to you, which is a pro, but it also potentially can be a con, because, like you're saying, if somebody wanted to create their own bubble, they're going to do it.
Jha:They can.
Alexis:But they can do that with friends.
Jha:Yeah, they could, they can.
Alexis:I mean, you see that all the time you get a bunch of people together. There's some of them that they ask the hard questions and they don't lie to you, but they ask the hard questions and they don't lie to you, right? And then there's others that everything you do is perfect and it was wonderful, until they turn around.
Robin:Yeah, no, true. Some people say what's the time limit to your friendship? Is the moment they tell you no or disagree, right? Or you know, some people believe in there's power in silos because it's protective and it feels comfortable and no one pushes anyone. But it's also tough, because when you climb a ladder, look out your silo, you realize the rest of the people created those two and that keeps us apart from one another. I could see that, yeah, but I could see that I had a friend of mine say well, I told my chat GPT to be the best somatic therapist and they started listing all the therapists they wanted to see but they couldn't afford. So they were like I'm going to need the somatic therapist, the psychotherapist and the this, but I'm going to need to be told very nicely, or something like this, you know, and I'm like okay, well, I like I like that for you, like, I hope it goes well.
Jha:Yeah, it was a video that became popular recently where and this is probably a con to some people that are using it as a therapist, potentially but there's no guardrails in Chad, gpt, where when you're talking to a therapist or you're talking to a lawyer, then they have guardra like your chat, gpt chats, and that is something that potentially the courts can't ask them to do and they legally, you know they have to because they don't have that same confidentiality wall that therapists, lawyers etc have.
Jha:So that's also something to think about when people are using it as a therapist.
Robin:Nice, good to know. Good to know. It's one of those things that are just going to sort of keep growing. And I had the what do you say? The gift, the time, the accessibility to join one of your workshops and I loved how, in a Q&A, one of the guests asked you know, like, where's this going? Or what happens if I put all my ideas into it, with a copyright situation and whatnot and trademarks and everything, and and I think you were just very honest in saying like this is a new tool, so no one really has those answers and use it as if that's the case.
Robin:You know, no one knew where my space was going, right, where's that now? No one knew where my space was going, right, where's that now? No one knew where facebook was going, completely even the owner didn't. You know, like no one knew where. You know what I'm saying? Like it just grows right, so you take it in stride and I like that. There's a mental health component and I like that there's a business support component, because even if we did go to academia and try our best, the technology is always changing. So it's nice that there's a way to keep learning with that and keep growing with our businesses, no matter what the business is. Do you find that there's certain businesses or nonprofits that you gravitate towards working with Me personally?
Jha:Yeah, mostly, just I leave it in a nutshell of service-based some type of organization where they're trying to serve a bigger mission.
Jha:Okay so and that bigger mission is different for a lot of different groups, but most of the time it's service-based. But going back to your point of academia and using ChagGPT, they have ChagGPT EDU, so it is inside of certain institutes already and they just came out with something called study and learn. So with this new feature, which has to be to study and learn, it's supposed to be where it's not telling you the answers anymore. It's acting almost like a tutor for you and helping you move, maneuver through complex problems or complex situations without automatically giving you the answer.
Robin:So that's kind of so. That's what they put into place.
Jha:Look out kids, look out students, yeah that just came out, maybe two or three days ago, oh wow. Yeah, it's free, it's on a free plan, but it's called Study and Learn. So if you go inside of ChatGPT and look at tools and you'll see Study and Learn and yeah, it's almost like a tutoring effect where it's moving you through how to get the answer without just giving you the answer.
Robin:That's so cool.
Alexis:Yeah, I think one of the things that's scary about all of the AI programs is that they evolve rather quickly. Oh yeah, and you know you talked about the amount of time you spend. You know trying, talked about the amount of time you spend. You know trying to keep up if you will, and I think that's what worries an awful lot of people, and businesses have been unable to evolve that fast.
Jha:Definitely.
Alexis:So the businesses are always behind, and sometimes being behind is a really bad idea.
Jha:Definitely, especially in today's day and age, is being behind is going to cost a lot of businesses and, unfortunately, it's going to cost a lot of people. I posed a question and I still don't have the answer to it, but I posed it on TikTok and I got mixed reviews where it's like, let's say, you work for a company and you had 10 bullets of tasks that they hired you to do. However, they integrate AI and now out of those 10 tasks, they only need you to do five. Does your salary stay the same or does it now change and go in half because you're doing half the task? I don't have it, but that's just a thought-promoting question that I ask people. I got mixed reviews.
Alexis:I was going to say I did a lot of management consulting. And that brings up the standard age-old question If, by getting rid of those, you know they only need you to do five of the tasks, they've now saved half a person. Well, as we all know, you can't save half a person, right? So what do they do? Most businesses are like well, I don't need you anymore because I only have half a job for you, right? Yeah, we'll figure out the other half.
Jha:Right.
Alexis:Some businesses go the other way and say we've got plenty of stuff for you to do, we'll find something Right. But most of them take the approach of I've saved half a person, so I need to take my savings, shall we say, which means you're out of a job.
Jha:Definitely and it's going to be unfortunate. But a lot of employees and you know people can say well, I was doing. You know you want Chad GPT quote unquote to handle your mundane tasks. But when you start realizing I think a part of your salary is handling those mundane tasks, so you start to kind of question do you really want to handle those mundane tasks? And then, to like to your point we said like half a person, that's very true. And then two, like to your point where you said like half a person, that's very true. But also think about OK, if Chad GPT is handling, let's say again, those five tasks out of the 10, are you honestly going to go find more work to make the company more valuable? Or do we live and I believe this part is unfortunate, we live in a day and age where some employees might take the rest of the day off?
Alexis:And it's like you can't do that Well, and the big thing, I think that you actually see when that happens. What you're talking about is that their view is it's management's job to figure out what they need me to do?
Robin:And it sort of is.
Alexis:Yeah, but that doesn't really keep your job. But that doesn't really keep your job, maybe their job, but it needs your job.
Robin:Right, catch-22 for sure, and it depends on the employer, because there are programs that will show the employer how long you're actually touching the keyboard. Oh yeah, you know what you're doing, what you're saying, things like this, and they may not be too forthcoming about that, right.
Jha:But that doesn't mean that they don't have the program going right.
Alexis:I was going to say and that, that's, you know, gotten certain people that just automatically type in their sleep. And yes, I'm making the noise on purpose. You know they go to sleep, keep typing I'm sleep typing.
Jha:No, definitely but it's it's be an interesting world. We head into a very interesting time to be alive.
Alexis:It's interesting Well and part of what worries me about all the AI is when we start getting it into government and military.
Jha:It's there, oh, I know, oh, okay.
Robin:Oh yeah, she's not just breaking it here. Okay, I know.
Alexis:Oh yeah, she's not just breaking it here, ok. And but because it doesn't have the ethics. Of course government doesn't have ethics these days anyway, but that's beside the point. But military honestly does have some ethics. It may not be the ones I like, but if you start getting rid of all their ethics, right, it will make some decisions that you may not like.
Jha:Right, kind of like our robot, and it's funny. I just recently really seen iRobot. But, kind of like the whole thing with Will Smith and his whole thing with what he called these robots was because they saved him instead of the little girl that was in the car with him, and the reason they did that was because, to their calculations, he had a higher percentage of living versus her, whereas he's saying, if it was another way around, it was a human.
Jha:Naturally, the human would have let the grown man figure it out and would have saved the little girl right so kind of to your point when it comes, it's not really on ethics necessarily, but it's on that pool where it's like you know, it's different yeah, it's like the self-driving cars.
Alexis:One of their problems is if you're in a situation where the analysis is do I hurt, do I allow someone in the car to be hurt or do I hurt somebody outside the car?
Jha:right, and that's a hard question yeah, yeah, and we're leaving those hard questions up. I wrote in a waymo in san San Francisco and self-driving cars. I did one. It was cool, but to your point that's the same thing where you're leaving. But OK, let me play this one Is anything wrong with having these tools or machines make those hard decisions versus people? You know, potentially make a decision that we don't always agree with as well? So what's the biggest difference between the two?
Alexis:In my mind, you'll get more consistency with the tools, right, but you have to give it a heck of a lot more thought than some other type decisions you have them make. I mean whether to make a cookie a little sweeter or not quite as sweet, I could care less. But if it's who dies, once it's determined that somebody's going to die here, you know, at a high probability, deciding who dies is a really difficult decision that requires a whole lot of training, thought, and so I think you know that that's the difference, and I worry that we don't do enough of the ethics training up front.
Jha:Right, no, definitely Definitely.
Alexis:Yeah, and these are the ones that have no real answer.
Jha:And that's the scary part, because you won't have an answer until something happens. But even after something happens, it's still not.
Alexis:And you know, the moment something happens it's bad, congress is going to get involved. And you know, the moment something happens, that's bad, congress is going to get involved. And you know, the biggest way to know that something's a bad bill is when Congress tells you how to do it, not what to do. And they'll be telling you how to do it Right and it'll just get worse.
Jha:Yeah, what a time to be alive. I was watching something on Instagram and that's probably another way I keep up. You know these algorithms. That's one thing they are doing well for me right now. They know what I want to see, so I keep up, too from just scrolling on social media. I don't see a lot of stuff that's not AI technology related nowadays, but I was watching. You know, elon has his Optimus robots he's seeking to create, but they already have other companies that are doing it and one of them is called Humane Robot, so they've been building that for a few years, and I might be saying the name a bit wrong, but I was watching the founder. He has one of them at home and they're training the one that he has at home, and this one was putting laundry inside of the washer.
Jha:He said it took it a month for them to train how to do it and things like that Different garments yeah. He trained them over a month, but now other of the same systems know how to do that. So, that's one thing about certain technology when one of them learns it, it deploys it to all of them. So now all of them kind of have that nuance of knowing how to do laundry?
Robin:Yeah, and humans don't work that way?
Jha:No, and that's the scary part about it. I was on a podcast. I said that we don't work that way and we learn at like step, step, step. I forgot how many words, even in a sentence, we can make, whereas, like these, robots can do very fast.
Alexis:Well, yeah, I keep thinking as we go through.
Robin:And I'm just like oh.
Alexis:As we're going through this, I think about something that I think in fact I first heard in the 50s. I've done computer consulting for a long, long, long time, Since 1964. Wow, and that sort of stuff. But you know, the standard thing of the air is human. It takes a computer to really screw it up. Well, it's the same thing with this. You know, the air is human, but AI can really screw it up. Yeah, Because you get one little piece of wrong training in there and it propagates to everything in the world.
Jha:It's like the movies, the Iroba's, all the other ones that everybody keep references. That's what it turns into.
Alexis:And it can't. I mean, the thing about it is that's possible, yeah, and that's the thing.
Jha:It's very possible. One of the they call him the godfather of AI, henry. He's been going, he's work for Google, but he no longer works for Google, so he created like the whole algorithms and how AI is essentially able to work and Google bought the technology. So Google actually has been sitting on this for a while, but Chad GPT is the one that released it and just exploited it to the world. But Google's been having it for a while but they didn't release it for whatever reason I'm not sure, didn't release what Didn't release the AI technology, like the chats and different things.
Alexis:It wasn't really mature and they wanted it mature.
Jha:That too, and.
Alexis:ChatGPT wasn't mature when it first was released.
Jha:It wasn't you remember. It used to stop or it used to have all these different things happening, but it's steady growing. But, however, he worked for Google for I think 10 years or something, but he's no longer working with them, so now he does podcasts to warn people about this technology, about what he created. Oh my gosh, yeah, and he's a very. I believe him because he's like a straight shooter.
Alexis:He seems like he's like a straight shooter.
Jha:He seems like he's like a Canadian guy, just a straight shooter, doesn't try to like go over and make anything elaborate, he's just very straightforward in like hey, we created something. And I think he said it's like a 20 or 30 percent chance that he feels like they'll take moment. He didn't realize the cons of what he was creating. I guess kind of any determined person, so many people are telling you that it can't be done. He was more so showing like hey, I'm going to get it done. And once he got it done, he said that's when, after he started to really realize like whoa, what do we just do here?
Alexis:realize like whoa, what do we just do here? Yeah, when we came up with the atomic bomb, there were a couple of people that did that. That their whole thing was, oh my Lord, what did we just do?
Robin:And I mean they were dead serious about it Right Some things are created, but there's major consequences for them.
Alexis:Because the big thing was, when they were doing it, they were just concentrating on doing it and not thinking about any of the negatives. Right, and the same thing with, I think, ai yeah, I've got a question. So you know, ai, artificial intelligence. Do we think this really qualifies as artificial intelligence, or is there one piece that separates it from human intelligence?
Jha:To be honest, that's a good question. It's a saying that say if it's artificial intelligence, then how is it intelligent if it's artificial? I've heard that before, which is when this comes from.
Alexis:I've been around artificial intelligence for a long time and every time we were able to accomplish what the definition of artificial intelligence was, we decided the definition was wrong. Yeah, I mean, at one point what we came to know as heuristic systems were considered artificial intelligence. But then, when we got heuristic systems all over the place that's a system that can program itself a little bit when we got those, everyone's like, well, that's not really artificial intelligence, it's not really thinking. Then we went with rule-based systems and everyone's like if we ever make that work, it'll be artificial intelligence. Well, then the rule-based system started working and suddenly everyone's like, well, that's not really artificial intelligence, it doesn't really think for itself. Then we went with some advanced rule-based systems, which they put another name on it, but that's all it was was just making better rules. And it's like well, when we get this working, it'll be artificial intelligence. And as soon as it was working, it was like well, this isn't really artificial intelligence. The current AI? That's my question Is this really artificial intelligence? Does it think for itself?
Jha:Supposedly it doesn't, but supposedly it doesn't.
Alexis:And I'm saying this, I'm asking you what do I think?
Jha:I just I don't know. I honestly don't know, and it's funny you mentioned that. I'm glad you gave that that timeline, because that's how that's what they're doing now with what they call like the AI agents that can work autonomously. Now it's like OK. When they got to Chad GPT they said they thought that was like OK, that's autonomous. And then now it's going even further, now that some of these agents can actually do the task for you. But now they're pushing it even further. Well, is that really AI agents? So, kind of to your point, it's just going further and further and further. Into when do you get to the point of where you accomplish?
Alexis:And honestly, my opinion is that with chat, GPT and all the other AIs, they're just very fast and creative rule-based systems, I mean and they're finding their own rules. That's okay. We did that when we did some of the stuff that we did. One of the groups that worked for me was Schlumberger got the first actual patent that went to an artificial intelligence system, and that's because we had no idea how to do what it did. It just followed rules and it came up with a rule that nobody even knew was in the rule base until it showed up and used it and it created something that no one had ever seen the likes of, that worked really well and was patented by Schlumberger.
Alexis:And so it was like, OK, it's a rule based system. It's sort of thought for itself, but not really, because it went and found a rule that worked there, Right, and I just I don't see, you know, like the chat, GBT etc. Being much different than that. You know it looks up its own rules and creates its own rules and you know it does lots of combining of rules and to make it really efficient, but I think it still goes, which makes me more comfortable than if it was actually thinking.
Jha:Right, no, that's a good point. Supposedly, with these AI agents, that's where it's going to take off, to where they're able to now, like you can tell what they call an AI agent, it'll work autonomously. So you can say, hey, can you update my website? And then, after you update my website, make sure that you send an email out to my subscribers, and then the AI agent will go in and it'll update your website and also send that email. But supposedly it will be able to realize and think and maybe see where, hey, we can send this email about a deal that you have next week, but what about what we have going on tomorrow? So, instead of sending that email that you maybe suggested, it can come back and tell you well, hey, what about if we do this? Or it should be able to think and be able to reason on what would be a better approach to certain situations. Or, let's say, you are coming up with a hiccup, with a task that you ask it to do, instead of coming back to you telling you it cannot do the task.
Jha:It should be able to process how to get around to get it done, which when you, when I talk about it out loud, it could potentially still be like a rule where it just knows.
Alexis:So I mean again, and you, know, and it's like there's another layer of rule processing that creates the more complicated rules. But you know it could all be done with rules if you will.
Jha:Right. Right now we're hoping that's all. It's going to keep being Right, Because when I explain it out loud, then I look at what you explain yeah, it's just consistent and more advanced rules and hopefully it stays that way.
Alexis:Yeah, because if it starts making up the rules, yeah, then we have an issue.
Alexis:But I mean, one of the systems that we did was basically a computer-aided engineering system and it designed things and that's the one that got the patent. Plus, there was a landing gear for aircraft that had brakes and it could not be designed, I mean, with the standard traditional design. It couldn't be. So the idea was to throw it into the AI system and just let it crunch on it for a while and the first pass of designing something took it almost two months on two crates. It was a lot of crunching and it came up with a design that worked and no one had built it like that before, because some of the components of this landing year system and braking were sort of inverted. But you know, the idea was okay, it's going to cost this much to build one and we're like we'll pay, we have to see it. But then the interesting thing was everyone's like well, we can't spend that much time. But the second one that it did took about an hour so I learned oh yeah it created a whole lot of sub rules, etc.
Alexis:And every time this happened we had to spend you know hours. I say we, the people that work for me, had to spend hours going back through to make sure they understand how it did what it did, to make sure it wasn't screwed up and it was like you said there could be an error.
Alexis:Yeah there could be an error. That could be a really bad error because I mean, literally this was being built by Bendix for airplanes, so it's sort of important to not be the people that are mentioned in the crash, right for sure, and that sort of stuff. And, like Ford was using the stuff that we had done. And then, like Ford was using the stuff that we had done, there was a car that it was designed completely electronically and we ran the AI simulations on it to say what will happen. And they had looked at all of the standard engineering stuff, but the AI simulation, instead of just pushing buttons, it would tap buttons hard, simulate it, it would push them slow, and it would push them slow and then release them. And the first time it did that, with the speedometer reset, the button comes out of the dashboard, turns around and ends up in the seat and everybody's like, oh, that's just messed up.
Alexis:And so they went and looked at their mock-up that they'd been working on. They'd forgotten a little tiny thing that's called, you know, a nut that keeps it in place. It had nothing on the back and if you actually did that, that's exactly what happened and they wouldn't have seen that. And all of a sudden they wanted to buy the system Right, of course you know, and the whole bit. So system right, you know the whole bit. So yeah I, I look at it and I don't see these at advance advances. What I see them as doing is going into language.
Alexis:More than just engineering, I mean engineering is pretty straightforward, right, because the initial program on the system were the rules of physics. I mean, there's a certain number of them, but they're pretty hard and fast, right, and so that that was the start and it could develop anything it wanted from those. And then you did other rules for special things. But with language you start having to go in and now it's more complicated. But again it's just more complicated. It's not impossible.
Jha:Right and to your point. I was listening to something and I forgot who it was, but that's exactly what they said. The biggest thing, and what's making what makes this so revolutionary, is its language. So before people like yourself you understood everything. I could write rules for it. Yeah, you guys were in a set group of people and it was only a certain amount of people that could and understand that. Only a certain amount of people that could and understand that, but now it, because it's language, natural language.
Jha:Yep, the common person can get that similar or same technology, which also makes it a little scary. Yeah, exactly no, exactly to your point. But yeah, I was. I forgot what I was listening to, but yes, that's exactly what they mentioned where it's it's now that it's language. Is what makes it like hold like whoa? Well, and it doesn't, is what makes it like hold Like whoa.
Alexis:Well, and it doesn't care what language it is.
Jha:That too. English Spanish, whatever, you know, that's another thing. Russian Chinese yeah, you can change it to whatever and it'll talk back to you in that language too.
Robin:Yep Talk back and forth.
Jha:So no, yeah, yeah, yeah. But that's really that's man. We can have you on the podcast Watch that. That was that took me on a wild ride.
Alexis:I was excited we can start in the 60s.
Jha:That was a wild ride. I was excited.
Robin:Well, you're always welcome back and all I can say is.
Alexis:It seems like people are surprised sometimes at what I've done or haven't.
Jha:Not surprised more. So I think because I'm so interested in the industry.
Alexis:That's what I'm made by, and see one of the things I've done my entire life and you know because I've been around computers for a really, really long time is I look at what's the same as opposed to what's different, right, and usually there's a little tiny sliver that's different. That's all you have to really learn. If you're like, okay, this is the same as this, this is the same as this, and you know like when object-oriented programming came out, they were trying to say, oh, this is a revolutionary thing. No, it's just subroutines and functions. If you really were looking at programs and you know they called it something that's sexier and nicer and all like that, I get that and it's sort of like okay, so now I fully understand it. That took about seven minutes and people are like, well, but it does. And I'm like, yeah, I know there's different names that were attached to those. It's neither the way you do it, I'll learn the language and the whole bit. And it's like I shoot pictures and all like that.
Alexis:I used to consider myself a casual photographer, and by casual I meant I didn't do a whole lot of let's set up the entire, you know set and do all that and a whole bit. I like to be out and just sort of take pictures of what's going on in life. Well then, a bunch of people from probably the West Coast but it could be now is New York came up with the term street shooters Well, that was sexier, so I started becoming a street shooter. I didn't change what I did. Shooters Well, that was sexier, so I started becoming a street shooter. I didn't change what I did.
Alexis:But in teaching classes, people like to be trained to do street shooting much more than casual photography and it's like hey, I'm adjustable, I can change the name with no problem and it's a different style photography, but the same as the casual photography, right, right, right, because you aren't adjusting the environment to fit the photography, you're adjusting the photography to fit the environment, which is what I prefer.
Robin:Right, and you've been having a lot of fun with the newer programs for AI, with photography also. Oh yeah, I mean the fact that they think for you, they're faster, they can alter the image in the way you're thinking is just really new.
Alexis:And you know some of them are okay, Some of them are really great, like Adobe's. I've used a bunch of stuff with Adobe Lightroom and what they will do, if you want them to, is they'll look at every picture you have. They will go through the entire Adobe library of pictures and they will come out with photos that they think are the same same, that have been professionally adjusted with everything you want to do, and they start displaying yours with those set of adjustments and it's like pick the one you like, Wow, and you know, and you get the adjustments and everything else and you can make changes if you want.
Robin:So next thing, you know you're like whoa, I shot that picture.
Alexis:It's like not really, but Well, yes, really, I mean, I'm sorry, anything you know. Well, the other thing about it is, with photos, almost anything that you change to do post-processing, you could have changed in the camera if you wanted to take the time.
Jha:Right, right, right, and you know, that's the big thing.
Alexis:I mean like I don't edit anything that I couldn't have changed in the camera, right, that's just my ethic, right, and you know. But that means you know I can change all the lighting, I can change a whole lot of stuff, just not the actual image.
Jha:That's a good ethic to go by.
Robin:I think I've heard that one and you know the one add, but I will remove. Okay, that's good.
Alexis:That's just art. No, I'm just kidding, that's just standards. That's good. That's good.
Robin:Unless it's a good photo bomb, you don't want it.
Alexis:Right, and sometimes those are okay.
Robin:Sometimes they work out.
Alexis:Yeah, but you know, and I guess, like I said, my biggest thing is I try to see the sameness, if you will, or the fact you know the commonality between the previous versions and the new version, and all like that, because you know there's just too much to learn if you start from scratch, and there's a lot of times people are like how do you know all this? I'm like, well, I started with a little tiny piece. You know, it was like we didn't even have Fortran. We had to write everything in binary computer code, wow. And then when we got Fortran, it was amazing and I can do pretty much anything you ever wanted to do in Fortran. But there's better languages and better, you know, right, it's like, but you know as it goes along, you decide which ones are worth it, et cetera.
Robin:Right. And now you just got a new computer that you're installing that has the preference of choosing do I want this computer to come with AI programs or do I not?
Alexis:Well, I need a new computer. You know, 15 years is about as long as it'll last, even if you buy one and configure it, so it'll last as long as it can. Plus, windows 10 is going away and I sort of need this stuff in Windows 11. So I got a new computer and the real question was do I want to get an ultraprocessor or not? And the ultraprocessor, in addition to having a graphics processing unit, has an AI processing unit.
Robin:Boy does it do.
Alexis:AI fast. Yeah, you know the things where you're getting the stuff, where it's coming up slowly on a regular computer. It just goes boom all there. And I started watching the AI processor and it's being used quite a bit, wow. And I'm not exactly sure what they do or how they do it, but it certainly seems to work well, wow, wow. And looking at it I was like, okay, it's a little more money. And then I'm like, okay, in the next 10 years, ai is going to be really important. It would be really nice to have its own processor in there and it runs at the same speed as the main processor, In fact, a little faster than the main processor. So it's all good, wow.
Robin:But so who knows? I mean, we have a lot of interesting things going on. As you said, what are you looking forward to next in your life from your viewpoint y'all Just in life.
Jha:Yeah, yeah, man, to be honest, all I think about is my business and growing my business.
Alexis:Okay, so where do you want your business to?
Jha:go, that's literally by the end of the year or just in general, this year, next year, either way what would you want here in 2025, and if you?
Alexis:six month, 12 or 18 month and five year plan there 18 month and five year plan.
Jha:That's three years or two years five years.
Alexis:18 months is a year and a half yeah, yeah, and you, yeah, and you said I said you know, in three months.
Jha:Okay, okay, okay.
Alexis:Or end of the year.
Jha:Okay, end of the year, that's easy. End of the year is easy. Let's at least aim for three more corporate clients. Because, I'm moving into the private sector, I help a lot of small business, still want to help small business, but I want them to be a bit bigger. But still they can be small business because, as you know, small business can mean they're making 10, 15, 20 million dollars in revenue if you go by the SBA revenue a small, so I would say at least three more corporate accounts by the end of the year.
Alexis:Nick, yes, you know, I was just say when I was doing consulting. I quit consulting with small businesses because they just didn't have the money to pay.
Jha:Yeah, I don't want to be that. Yeah, they don't have the money to pay.
Alexis:And so you know, basically, if I stayed with small businesses because somebody who can't pay, I'm not going to ding them on it, right, you know? And so what that meant was I was going to be broke, yeah, no. And so I decided, after doing a couple of big corporation type things, I'm like they have the money to pay and they also recognize the value they can get out of something.
Jha:That too, that too, and so.
Alexis:I sort of switched to Fortune 10 companies and governments.
Jha:Yeah, I sort of switched to Fortune 10 companies and government. Yeah, the government, I play around in that space here and there. By play around I mean I actually bid and do different things. It's just like you probably know, a longer relationship building game with them, which is fine, but moving more in the private sector where, kind of how you mentioned, they have the money, they know they need it, they're willing to just go ahead and pay. And I always wonder, are they willing to just go ahead and pay? Because it's not their money technically and it's the. You know they don't have real emotional attachment to it, but I don't know why small businesses I found out the owners and people running them usually had emotional attachment yeah, yeah.
Jha:That's why I feel like they're like yeah, there's a certain size.
Alexis:When suddenly they don't, when they have a board of directors that actually does things and they start having shareholder meetings, right. No, they could care less, right.
Jha:But yeah, I figured the corporates. I'm like, oh, they'll pay. So that's where the sector that I'm really looking to probe and get more into.
Alexis:So how are you getting the information to them about what you do?
Jha:Right now I do a lot on LinkedIn. So that's a big one for me. I do, believe it or not. I do a lot of networking. So in the networking groups that I'm now becoming a part of in, they aren't with really mostly small businesses, so they're more like the core, like they might have a membership to the organization because their corporation is a member. So they might have a membership to the organization because their corporation is a member, so you might have different banks and law firms and things like that.
Alexis:But they know the small businesses that have money and banks are really good because if there's something you can do to produce revenue, the banks will frequently point you toward a small business that's having trouble, that the bank wants to have survive.
Jha:Right, right, right. The banks. I haven't did much with banking. I need to get better banking associates because I found the ones that I deal with most of the time they're always just well. I can't say that because one guy just introduced me to someone via email earlier and I haven't followed up with him yet. He's a banker, so he introduced me to someone recently. But, to answer your question, most of the time I'm doing a lot on LinkedIn and then events, so I do a lot of speaking. So if I'm speaking at an event, then I may get the reference from that too.
Alexis:Yep, that's always good.
Robin:Long-term. What about long-term? I'm not sure. Okay, it's open.
Jha:Long term over the year I'm building so aside, I'm really good at I'm an educator. I can educate you. I can make topics simple. I'm more of the person where you're going to go out. You're probably front and center of the face. However, I'm building a back end tech arm because, from an implementation standpoint, while that's something that I'm privy to, I don't want to learn full-blown because why?
Jha:Right, it's hard to do both. It's hard to do both, but also I can build partnerships with that one. So I'm now at a stage in my business where I don't want to be everything. I know what I'm strong at and I'm learning that most developers are not strong at the same things that I'm strong at. So they've actually been coming to me.
Jha:Like in my last engagement it was a developer in there. He has a small team and he came to me. He was like hey, I really like what you're doing and yeah, you presented really well. And he brought me the idea that I was already thinking where I want to build stronger relationships with developers on the back end, because I can go in and I can upscale a department. I can teach them everything they need to know about anything with ChatGPT or Microsoft Copilot. So from the simple bottleneck admin tasks I can show you how to do that. Admin tasks I can show you how to do that. But from a technical standpoint, if you want to create something custom or have different AI agents integrated, I would need a technical arm or I would like a technical arm to go ahead and handle that part.
Robin:Yeah, you could be a bridge to that business. Yeah.
Jha:Well, that would. We would be a partnership. Hey, you're not kicking me out the deal.
Robin:So it would be a partnership between us three, because they still would. And I'm like, hey, you're not kicking me out the deal.
Jha:So it would be a partnership between us three, because they still would and I feel like still strongly they still would need me too.
Robin:The interaction.
Jha:Yeah, I'm the one that the company trusts and knows. And then two again they're good at building things, but when it comes to really like emphasizing, emphasizing well, what is this going to help with? Why do I need it? That whole sales process, they're most of them the best at talking about it no, and they don't want to.
Alexis:Yeah, they don't want to yeah, this is sort of like what happened in general it and in general it if you look at it. One of the things that businesses and what I would call I would call them coders, just because and that's not a positive term, it's just what they know how to do is they decided they didn't need business analyst and the systems don't work well and it's because you need somebody who understands the business as well as the technology to decide how you apply the technology to the business. Right, and you know, they sort of got together and decided, oh, we don't need those anymore. And I did a lot of consulting and the results panned out for you I'm like well, you know your problem is, you need all that fix.
Alexis:You need to go back and redo the analysis because it's obviously not done.
Jha:well, right, and they're like oh, we didn't do any, and I'm like that could explain it. Yeah, that works out, but no, that's what I'm doing. So, over a year, build stronger relationships. So I can confidently know that I have a strong tech arm arm because I feel the way I'm doing things, the networking I'm doing, the speaking engagements I'm doing, I'm now encountering corporates that would be beneficial for, so I want to build it early. So I'm like let's build it now, be ready.
Alexis:Don't forget about the training, especially with big companies, especially oil companies, because they like to do lots of technology updates and if you go into the technology updates for all of their non-technical people, that whole group of people who, by the way, frequently are the people running the company, suddenly consider you the expert.
Jha:Right right, right right.
Alexis:No, and that's very strong, shall we say.
Jha:Right, right, right, no, no, you're definitely right. One of my mentors says that all the time. He's like you'll be surprised how many people yeah corporate, they're running a company and they have no idea what's happening.
Alexis:And what they really want to know is watching your training, that you know what's happening Right right right, they don't need to know, they just need to know someone who does know.
Jha:Right exactly right. They don't need to know, they just need to know someone who does know Right, exactly, exactly exactly. So yeah, that's my goal is more corporate and a stronger technical arm so we can actually do the next step, training. But after we train, we want to build something custom or, if we want to do it that nature Exactly if they need it. So just having it just in case.
Robin:That's wonderful. Well, how do people find you?
Jha:They can find me on websites, social media. So social media is J-A-L-L-E-N and that's on Instagram, TikTok and LinkedIn, and then my website is endless.
Alexis:No.
Jha:Facebook. I got Facebook too. You left it off.
Robin:I just thought I'd ask she's got to have something for herself.
Jha:I got Facebook, so if you want to follow me on Facebook, you can use the same handle. You can follow me on Facebook. It's funny you say that.
Robin:Wait a minute. Where can they find your website?
Jha:Oh, endless8marketingcom, endless 8. So E-N-D-L-E-S-S, the number 8, marketingcom Wonderful.
Robin:And in your training, what were you going to say?
Jha:No, I was going to say in one of my trainings somebody followed me on Facebook and it's not listed, but she followed me on Facebook. So you know, at the end of the training you have, let's stay connected. And I had, you know, my LinkedIn, my TikTok, that's probably what she's on, but I get, yeah, she was on Facebook and she just went ahead and followed me on Facebook.
Alexis:I was going to say I only do LinkedIn and Facebook out of that list.
Jha:personally, she asked me. She said did you add me on Facebook? I said you have my Facebook and, sure enough, I went to my friends and friend requests and I accepted, because I post similar. I'm the same person on all of them. So I said, well, yeah, that's good.
Alexis:So you're a nice person on one and a mean person on the other Come on.
Robin:Playing all the different algorithms.
Jha:No, I got to be the same Even for my Instagram. I just have to be the same person. I'm starting to have all kinds of different people follow me now too, so I'm trying to find that balance of how much do I really want to share and how much do I just really want to keep it, you know.
Robin:Next is your book. You're going to co-write a book with Chad GPT. You're going to put that out there. That's one of my goals. That's what I should have told no, I feel this.
Jha:They're going to contact me to be a trainer for them because they need help. Again, they're the people on the back end where they're a decent job now of doing podcasts. They do have someone running their Instagram so they've gotten better at that. But I noticed from the Open AI Academy they partner with certain cities so I'm like I feel like they're going to contact me about, hey, we need to get consistent trainings going in Houston.
Robin:I could see you doing it with them.
Alexis:We need to do training, yeah hit them up, don't wait for them, just be like. You know you need me and don't forget, you can always contact them saying the same thing.
Robin:Yeah, you know you need me let's go, let's probably wait. Houston is the city to go.
Jha:I don't talk about this a lot, not out, but I'm on their um, on their Instagram and their highlights. I did a video one time and they contacted me. They're like hey, they found it on TikTok. They're like hey, this is a really great video, do you mind if we repost it? And they did. And they're like oh, we're gonna post it on instagram too. And I said, okay, so if you go to like chad gpt's main instagram and their highlights, I'm one of the videos, nice, on the main instagram.
Robin:So yes, it's in the works. Yeah exactly. We're courting one another.
Alexis:Yeah exactly it's fine well that explains the 10-year question uh well, she can't. She can't disclose all the plans when they want to be in 10 years is filthy rich and retired to someplace that they really like and basically just sort of every now and then doing something.
Robin:Pop it out every now and then. Hey, what's wrong with that? Nothing. Pop it out every now and then, Sort of like Bezos was doing and now is doing yeah, pretty much Well come back, let us know how you're doing, let us know what we can do with you, and thank you for coming in today. And I want to say, if you're listening to this, check out Jaws Work, check out any of our other podcasts that you might like. And thank you to our subscribers. Keep taking care.
Alexis:And all of these links that were mentioned overly fast.
Robin:So fast.
Alexis:Will be in our comments.
Robin:Yeah, you know why? Because AI does the work, yep.
Alexis:Because we don't do it. Bye, bye. You going to say goodbye, oh, bye.
Jha:I know it was a team effort. You don't?
Alexis:have to say goodbye, but that'll just leave you on the podcast Everybody will be wondering where you are.
Robin:No no, she's in the ether. She left. She was like poof Wherever their data goes. She just evaporated. Disappear with it. Oh my gosh, I think that was a pretty good vibe, no, it.
