Artificial Intelligence Podcast: ChatGPT, Claude, Midjourney and all other AI Tools

AI In Latin America with Mateus Quelhas

• Jonathan Green : Artificial Intelligence Expert and Author of ChatGPT Profits • Episode 344

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Welcome to the Artificial Intelligence Podcast with Jonathan Green! In this insightful episode, we delve into the dynamic landscape of AI in Latin America with our distinguished guest, Mateus Quelhas. Mateus provides a unique perspective on how AI is transforming various industries across the region, drawing from his extensive experience in both local and international markets.

Mateus emphasizes the importance of AI as an equalizer, particularly highlighting its potential to bridge gaps in opportunity for countries with limited resources. The episode also explores the challenges faced by traditional corporations in Latin America as they strive to integrate AI into their operations, often hindered by organizational silos and cultural nuances.

Notable Quotes:

  • "One of the things I find really interesting is that the best use case for AI is as an equalizer." - [Mateus Quelhas]
  • "If you have to wait for someone to answer a question, you might have to wait 12 hours, 18 hours, or two days if it’s their day off." - [Jonathan Green]
  • "There's so much language out there about replacing your team with AI, but it’s about making your problems go away and turbocharging your team." - [Jonathan Green]

Connect with Mateus Quelhas:

Connect with Jonathan Green

Is Latin America ready to surf the AI wave with today's special, special guest Mateus Quelhas. Today's episode is brought to you by the bestseller Chat, GPT Profits. This book is the Missing Instruction Manual to get you up and running with chat GBT in a matter of minutes as a special gift. You can get it absolutely free@artificialintelligencepod.com slash gift, or at the link right below this episode. Make sure to grab your copy before it goes back up to full price. Are you tired of dealing with your boss? Do you feel underpaid and underappreciated? If you wanna make it online, fire your boss and start living your retirement dreams now. Then you can come to the right place. Welcome to the Artificial Intelligence Podcast. You will learn how to use artificial intelligence to open new revenue streams and make money while you sleep. Presented live from a tropical island in the South Pacific by bestselling author Jonathan Green. Now here's your host. I'm so excited to have you here today, Mateos, because we're so busy thinking about AI as America and China . Like every time you see the news, it's American and China, American, China, but we forget other countries in. One of the things I find really interesting is that the best use case for AI is as an equalizer. Now, the things that are happening with translation, the things that are happening with education open up a lot of doors. We saw a few years ago when we tried to do home education without artificial intelligence, really didn't work very well. We saw a lot of people have to repeat grades. We get a step behind or have trouble socializing. So I'm really, I kind of see how it's helping countries that have a disadvantage who actually catch up. I actually think that it helps. Countries at the bottom the most because it can really cover these gaps where there's just massive differences of opportunity. And as I mentioned, I live in a small country in Asia and the island I lived on before this one, I only had internet from midnight to 6:00 AM so I only had six hours of internet a day. And like it's hard to explain. That's to people who are like talking about, should I get gigabit or 10 gigabit internet? And I'm like, well, during the day my internet's so slow. I can't open an email, so it's like a completely different world. But I'm really interested in your perspective, the Latin American perspective. A lot of things are happening with Latin America in the news, and it's like for some reason we never see good news about Latin America, even though there's lots of amazing things happening down there. So like just take it away. Tell me kind of things that are happening and where the AI wave is going. Yeah. Fantastic. So, It's a pleasure to be here and I think it's gonna be a great conversation when we think about Latin America. So, I'm Brazilian originally. And I've lived most of my life in Latin America. Made my career in Latin America. But a lot of it is also done like outside of Latin America. So I can like contrast both cultures. Where I used to live, and I do work with a lot of big corporations. So when you think about traditional corporations it, it is hard to grasp what AI can help you with. We've seen a lot of innovation for, for the, the general public. So for the consumer. We've seen people double, triple their revenue, for example, by using AI tools, by using, you know, distribution and all of that. But for corporations it's a little bit harder because most of the times those companies, they didn't start off by having data as the key point of their business. And so they're just like doing their business and basically they're trying to, you know, increase revenue. So when you think about that position, and then once you have ai, you need everything organized, for example. It's a massive difference. One other thing is. Once you are from a country where there's a lot of technology being developed in Latin America, for example, but it's not where it's the birthplace of AI or even, you know, all of that data management. So we, as you said, we think about China, we think about the US and that's it. Like North America and that's it. So we're usually importing those kind of technologies. When you're importing something one, it's more expensive, so it's harder to implement anything. But second of all is again, the business started as. How do I make more profit? Not how do I organize my data because of technology. So a lot of those things, they grew as informal, let's call it like that, the, those kind of business. And then once they grew, now they have to organize everything. So a lot of my clients at this point we are seeing them spending years and so much money trying to organize, I don't know how many systems they have, like internally because the data, they don't talk to each other. Now once you're talking about ai, it's very easy to go onto a conversational ai and then you, you know, you can chat with it. But if you don't have a good data set, , that means you cannot necessarily trust whatever the AI is telling you. And then that goes on even deeper because if you do use some, some more tools that are available for the, for the general consumer, you're probably not having that safety of the data that you need. So it's a lot of like, it's. It, it's complicated , but it's very different from what we would expect from companies that are technology based. And I find that one of the biggest challenges is this is the way, this is the way we've always done it, that the larger company is the slower it moves. And as a company gets bigger and bigger, they lose agility in exchange for momentum and it's really hard to, even if you build something amazing to see it actually get implemented. Mm-hmm. I find that with the clients I work with, that even if I build something and I demonstrate it and it can say that it gets actually . Implemented across the company. And there's this thing that happens with company cultures, and I wonder if it's the same with South American and Latin American companies, which is that departments get siloed, which is, I'm not, marketing doesn't wanna share its data with sales. Sales doesn't wanna share its data with tech. And that because each department starts to hoard their data because it becomes their value, which is that with all of our . If the other department knows all of our secrets, then we won't be needed anymore. And that's one of the, I always try to explain to my other, my friends and people I'm teaching that I spend most of my time waiting for someone to gimme the data, someone to gimme the login, someone to answer the question, and I. Sometimes I'll ask person A, they'll say, oh, it's actually person B. Person B goes, it's not me, it's person C. And person C goes, no, it's person A and person A goes, oh yeah, it is me, but I need permission from person B. And you go in these circles, and it's because we develop these habits and there really is, I try to explain this that I can accelerate a process, but if you don't have a process, then you have a different problem. And most companies, they don't have a really good way of, like, if you wanna know something, you walk over to someone's desk and you ask them. So they already have poor organized data. Like, let's be honest, most of us have disorganized hard drives on our laptops. I've just started, actually I,'cause I teach this, I've started implementing where I have like folders for different categories instead of just, everything goes in the downloads folder, which is what most people do. It's like, well this is for PDFs and this is for documents, this is for spreadsheets, and just that level. I've just started implementing myself in the past two weeks. Like to be completely honest, I just have never taken action on it. So if we're disorganized with our own data, how much more do we have these issues with larger companies? So I'm really interested in if. If the culture is kind of the same or if there's higher levels of collaboration or if people are even more defensive of their data in their different departments? Yeah, that's a great question and I think there are a couple things that come to play. One of the things is exactly what you said is my data is my. My gold. So basically I won't give it to you just like that. When you have companies a lot of the companies that have like ditched the silo game but still it's more personal. So even though like supply chain and sales, they don't have a problem, maybe I have a problem with you. And we don't. You know, we don't necessarily like each other. So why am I gonna help you? Or why am I gonna give you the data from a project that I'm working with? And maybe I don't know that, and, and it's not ready. Maybe I'm just insecure about it. I'm, it's not ready. So I don't want to give you that piece of information. All of this comes in play, of course, because again, it's human beings. We're all. Know what to do with that. It doesn't work. The second thing, and I think this is probably where I've seen the most difference between companies that can work like together and companies that are very siloed with between departments. It's actually leadership, and this is a hard word. It's a very, it's very used like leadership is the problem and all that. But honestly, two things happen. One, if I grew within the company, and it's been, I don't know, 20 years, 25 years that I'm here I've learned to do the process and I've learned to find the little things that will make our process perfect the way that they were created because I worked on it. So when I get the experience on it, that means I can actually improve that process or help you understand the process as it's. But the thing is, the way technology is being developed at this point, what I learned and what I did two years ago, it's not the same anymore and it could be even better. So one thing is about inspiring people. So I'm like inspiring you to be innovative, to be creative, to think outside the box and do whatever you can do for the company. And the other thing is actually pivoting. My point of view and my mindset as leadership to, you know, be, make sure that we are using the right tools and we're using the best there is in the market. So there are two things here that play in culture people, and leadership in general. And I think when we look at the perspective of the, the region Latin America if you think about it, it's very relational. So all everything is relationship. I was talking to a friend of mine here in the US and, and it's, it's crazy 'cause for me, one of the cultural shocks that I had when I got here was you don't just go on to people and say, hi, how are you? What'd you do? And then you start a conversation like, you network here is with purpose. So I want something from you. You want something from me? And then we're networking. If we don't have that kind of transactional relationship, we're not networking. And that's crazy because Latin America in general, people are just like, hi, you wanna grab a coffee? You know, it's very different. And that also comes into play in the business environment. So a lot of the companies that I work with, they have the subsidiaries in Brazil, but they have the headquarters, I dunno, in German or even the us and then they think completely different. U usually headquarters think, well this is the process. One plus one equals two, and that's it. You know, just roll it out and it will work everywhere. And it doesn't then again,'cause people don't adopt it. Once they don't they're not using whatever process you're creating or whatever technology you're giving them. It just becomes obsolete and it's not used, and then you don't get the information that you need. So the culture is very tricky. I think if I'm recapping here, you have people interaction with them, like between them you have leadership and how not only I inspire, but I pivot from what I think. And a third is if it's a relationship based culture, you need to foster relationship with the technology or whatever means you can. But if you don't foster that, you're probably not gonna get through with anything. One of the big challenges that I discover a lot when I talk to potential clients and work on projects is that some of the technology, they've been using things the same way for 30 years or 20 years. So one of the big mistakes people that are super keen on AI make is forgetting that there's a transition period. How long will it take someone to switch to this platform and get used to this new way of doing things? And that's a really important factor. And it's like sometimes when I'm designing an automation, like it will take me five hours, but it'll save me 10 minutes. Maybe I shouldn't do it. But you get caught in these loops.'cause we love building and love technology and sometimes we spend so much time being efficient that we don't get anything done. And that's one of the kind of challenges being super excited about ai. Sometimes people say to me, everyone's, we using ai, why aren't they so excited? Why are some companies not using it? And I'm like, well. There's plenty of, they usually have a good reason, right? Has a lot of times it has to do with the security policy, it has to do with their particular industry. There's a lot of unique things about each industry, and that's one of the really interesting areas is that you have to shift at a pace that the company can handle, right? So if you say good news, we're placing all of your technology. Everyone's like, that's not good news. That's the worst thing I've ever heard.'cause now everything I know doesn't work anymore. I have, and now they spend so much time learning instead of doing, so you'll actually have like a, a big dip in productivity before you see the benefit. So when you're kind of assessing with a company or looking at a project, how do you factor in that dip? Or how do you limit the negative before the positive kind of comes into play? Yeah, great question. This is a hard one because again, I'll talk about behavior and people relationship all day if you want.'cause usually for, for example, for you, for me, it's natural that something that takes me 10 minutes today, if I spend five hours automating this, it. I won't be, you know, using those 10 minutes in I don't know how many years. So when am I getting the ROI of that? So if I need, if I have those five hours, when are those five hours going to be used? And this is usually the question, I'm talking about five hours here. But then think about in a bigger scale if I'm thinking about this, it's natural for us to not want to teach. A machine or teach a technology on how we think. And we know AI has its limitations. Microsoft now they're doing the copilot labs, for example. They're trying more conversational with ai. That gets a lot more from the, the perspective of what you're talking and not necessarily just whatever you're telling the ai. So that's good. But still testing. And if I'm not, if I'm gonna teach, you know, the machine, I'm gonna spend five hours here. You know, I. This is the thing that has happened since forever. Again, if, if you think about how a person climbs in their career, like traditionally they're very good on what they do on their work. And then because they're very good and they're very efficient and they meet deadlines and they do like process optimization and all of that, and they deliver, you know, something that was five business days is now one business day. And I do that because of my expertise, my, my own expertise. I get promoted and then I get promoted, and then I have people to lead. And then usually that doesn't work because I'm a very good, you know, individual collaborator. I'm not necessarily a very good leader. So that has happened everywhere. People, you know. Teaching other people or technology to do their work for them. Because again, essential. That means I can still be here if I'm not essential anymore. So I'm not gonna be here. And if I have more stuff to do, then I, I will not be there, you know filling in a piece of data or a spreadsheet for the, the technology to understand whatever I'm saying. And that will happen like absolutely everywhere. Specific case, I can relate to this. If you think about Walmart for example, they are investing a lot in data analytics. They're investing a lot in, in technology and automation. They have a really hard time integrating everything. And then if you ask me why, I can tell you it's. They are a retailer. So what I have is very small margins over products that were produced by other people. So I have a very efficient way of buying, I have a very efficient way of displacing or placing things into the store. And then I have a very good way of getting people to buy that. And then I have the discount and all of that. So imagine a physical store and then once you migrate everything for technology and then you want to integrate your digital store and your, your physical store, it doesn't work because probably the way that I buy, I buy in boxes. And then some of the articles that I buy in boxes, I don't know how many of those articles are within the box. So if you sell clothes, for example, one thing is to buy a S size white t-shirt. But most of the times I don't buy a s size y t-shirt. I buy a bulk of two M size one s, size three x L size, and then two double L size. And so I'm buying a pack. And then if I sell in store and I don't have that piece of information, because again, it's related to that stock, it's not related to the item. I, I cannot work. I don't know how many of the pieces that I have. So how am I gonna sell online something that I might not have the size that fits Jonathan, for example. And so it's, it's. It, it, it's a very difficult game to play. Again, they're spending years and tons of money just trying to organize everything at this point. One of the the clients that I have and, and this one is a technology based company. They are from Brazil and exactly, and they are an open stock. The strategy that they use is buying other companies. So they buy companies that are mature enough and they don't necessarily integrate the business within the, the, the main business, but they do have it orbiting the main business. And then those business, they are in the same client journey. So, you know, great idea. We're buying other little companies that can actually, you know. Scale our operations. Yeah. But the way that Jonathan's company did their data management and the way my company did, data management is completely different. So you sell, for example, the distribution and I sell the product. So how am I gonna integrate this with this? So a lot of the work that we did with them was where your, is your data governance gonna be? Is it gonna be into a technology department or is it gonna be within the companies? How are you gonna move data pieces from one company to the other and then have that integrated because the client at the end of the day is the same one. So for, for the client, I need everything integrated 'cause I don't wanna. I don't care about how you manage all of that internally. I want my data secured. I want my experience to be great, and I want to be able to do something with that information. So if I'm using your system to sell, for example, say on an e-commerce that means I want that e-commerce to work. I don't want something to crash. And then I, you know, send a message or call you or talk to someone and they're like, well, this is not within this company is that company. And then, you know, I don't. So this brings up a topic that I think is really important, which is you need to choose where the central truth is. Where is, where can I find what customer, how many customers we have, what each customers bought, the status of their orders. And even, I've worked at some large tech companies where you have to open six or seven different tabs. One of the most interesting things, no matter the size of the company, the first kind of phase I go through is just trying to find out what their tech stack is, and very rarely does anyone know. I've worked with companies where three different departments using three different CRMs, different project management software, and. I'll just ask sometimes, well, why are we using both? And then it creates a whole thing. Like it creates a scenario where someone's like, Hey, whoa, that's what we love to use. Don't ask this to change. I'm like, no, I'm not asking to change it. I just wanna understand.'cause if I understand why you're using it, then I can figure out how to connect these two things together. Because we have to have one place that we know is the right information. Then it can flow down to everywhere else. And it, it's surprisingly difficult to create that, even in my own company. It's always a challenge for us as. We bring on a new employee of workflow changes, then the process changes and we'll move an automation around or how we edit the podcast episodes. That changes everything and every little change means that sometimes the way the tools we use change, we actually just change our entire process for tracking podcast reduction. So we have a CRM that tracks as people come in before the podcast. I have another source that's an AI to help me remember who everyone is. It's just a database. And then I had a project manager for when I was editing the episodes myself, because with AI I can edit episode at two hours, so it's not that long. But now I have someone else doing it and I was like, well, I don't need to track it in the project manager.'cause they, they're an outsourcers, so they use a different project manager. I was like, so if we can go from three to two things, that's way better. Then the problem is right before this episode, I had to remember to look in the new place. So even someone who's as technology forward as I am, it still comes up all the time and it does this thing of what's the central piece of truth and what is going to be this? It has to start from there. And then you're exactly right. Data governance is so tricky right now because you get really excited and then there are certain tools that will scan. Your entire Google Drive, your entire Dropbox Drive, and it's like there is a lot of stuff in there that you might've forgotten that, whether it's business stuff or not stuff or proprietary stuff. And then once it starts getting transmitted, you increase vulnerability. Even if you have a secure from me to you, there's still a possibility as soon as things are going in and outta the internet. So it is very tricky to kind of get people excited, but not so worried about security that they completely pull back and it is this. Kind of narrow line to walk because a lot of what can be done is really internal and understanding that, understanding kind of this approach, like I'm more security conscious than a lot of the clients that I work with. They're like, they don't really worry about that. I'm like, well, I worry about it because I don't want it to be my fault. Right? I don't wanna kind of create a vulnerability and it is . A very interesting time because it's a very exciting time. But it also means that like it requires a lot more fastidiousness from people like us to really give good guidance and kind of pay attention to these different elements.'cause I've seen companies who just go to their IT department and say, set up our ai. Or they go to their cybersecurity department and say, set up our ai. And they have completely different perspectives and you kind of have to. Explain why. What we do is what we do and what I really find is that so little such a small percentage of the things I work on has anything to do with ai. It's almost always data management, data organization. The AI might be one step in automation that's doing filtering, but mostly it's creating, and this is what I try to explain my, when our recent said, I want it to be that when anyone is looking for a piece of information, they don't have to ask someone else. They can just find it. If we can have that. Because I what's really interesting, and I wanna know about this as well for Latin America, but in America, nobody wants to work in an office anymore. Now that people have gotten a taste of work from home, suddenly it's become so popular. I just, as someone who's been working from home for, gosh, 15 years now, it's like I. I see it differently 'cause sometimes I see people like these offices that have like five star chefs and hammocks. I've never had anything like that. Right? Like that seems really nice. And if they don't wanna work there, they don't wanna work in any building. So you really have, then once you do that, I. You have people working different hours, which means that if you have to wait for someone to answer a question, you might have to wait 12 hours, 18 hours or two days of their day off. So it becomes more and more important to have this central piece of truth or this way to get all the information in one place so that if I pick up the phone and the customer has a problem, even if I'm not in customer support, I can at least look up their file and give them some bit of an answer. That really becomes kind of the central thesis that I have as I work with more and more projects. It's that I want everything that people are frustrated by to go away and that I just want everyone to be able to find what they're looking for. And that seems like such a small goal, but it's actually such a game changer. So. Really, are you people still willing to work in offices in Latin America, south America, or is it the same kind of shift where everyone wants to work online? Everyone wants to work remote, and so you're seeing people working at different times more and more. Rule of thumb people generally want to work from home. After the pandemics, like we've seen it's possible to do that or even work from anywhere. However we are seeing more and more companies bringing everyone back to the office because again, as I said, it is a relationship based culture. So if it's relationship based, we need to grab that coffee. I need to be able to come to Jonathan and say, Hey how is that project going? Or, you know, how is this happening? Or, I need that information. Can you help me with this? So those small little conversations, they matter. So we're seeing a lot of companies saying, you're, you're gonna be here at least three times a week. But some of them are actually going. Full right back to the office, not other people like it. So we are also seeing some people being able to balance their lives and their home and whatever they have to do during the day. Work. Work. And once you are in a city, let me take for example the city of Mexico, or for example Sao Paulo, like gigantic cities that get 40, 50, 1 hour and a half long to get from one place to another place, like from your house to the office when you need that much time you, and then you go back and then you see how much you lose time. How much you are missing out. So a lot of people don't want that, but most of the companies and a lot of the companies are bringing people back into the office at least three times a week or two times a week. So this is something that is happening. And you were saying something very interesting at this point because it's where, how, how can I make everything easier once everything is, I'm, I'm not necessarily talking to you all the time. I'll give you my example. So I live far from the office. I live in another country, . Basically everything that I do, I'm waiting for an answer, as you said, . If I don't, if I am at the office, like some of the times I am, it's easier. Honestly, it's easier. I'll just, you know, poke you a little bit and I say like, Hey do you have a minute? And, and, and that makes things, every, everything, you know, completely easy. If you go online on your platform I use Slack a lot. So if you go onto the platform and say, hi, how are you? People do not answer and I don't answer. If you just say, hi, how are you? If you don't give me the, the rest of the information, like, hi, how are you? I need this. I, I probably won't answer you. So it, it will be, I'll be jammed in a lot of messages to, to answer. So this kind of thing like behavior we're seeing. However you talked about how the data is connected and I have the information on that file or that client, for example, and I do think that there's a functional side to it. So I can solve a problem or I can use that information for something and to get something out of it. But it's more, it's even more crucial. Diminish the losses that you can have or even the, the problems that you can find when implementing technology and ai just by letting people understand why. So if you make them understand why that is important, why putting that information on your drive or putting that information on this type of format, that's completely necessary, they will understand. The problem is how you scale that to a company that has, I. So it's, it's how you scale things. So you, if you get those you asked me before, what do I use or what do I do to make sure that everything that we need to implement is implemented? One thing is you cannot mess up the functional. So again, one plus one equals two, it cannot be something else. But the other part is how do I understand how the culture of the company works? How the, the actual power relationships, they work. So it's not necessarily hierarchical, but how the power works and who influences who. And if I know that and, and I know what type of routines the company has for influencing or the type of the way that people actually in inter integrate with each other, then I can not only do the one plus one equal equal two, but then again, hey. Richard one plus one equals, and then you go say two, and then I'm like, great. Fantastic. So you understood why, and then you can be an advocate for this. So once you get those many advocates for it, and then you're good on establishing the process. Again, we talk a lot about technology, but you cannot only do the one plus one equal two. It's not just a result. If you don't have a good change management in practice, if you don't have a good strategy, if it's not linked to the company strategy, if it's not, if you don't have a buy-in from everyone, or at least the, the decision makers and the influencers. So DecisionMaker is something, influencers something completely different. So if you don't have the buy-in and you don't have, the people, don't have people using, using those things that. And then for you, for me, people that are outside the company and telling them what to do and how to do it you're 100% correct on being worried about data safety because again, if something happens, that's our fault. I don't want it to be my fault. I also want things to work . So yeah, this is, this is how things are going, and then this perspective changes a little bit of everything. It may be very similar to what we've seen before, this boom of ai. But again, nobody is able to fix the relationships. You know, you have to be able to tackle all of that and then making sure you're integrating everything. Everything. And then you're applying everything. Think, yeah. I think it really is the crucial integration between human and technology because. There's so much language out there about replace your team with ai. You can fire everyone, you can replace your customer support. We've fired all these people and now we're making more money. And it's like, well, you sound like a monster. Like that's not good language. That's the kind of language that leads to AI sabotage. So employees think an AI pilot project's gonna replace them. Of course they're gonna sabotage it. I would too. So one of the big things that's really important I think for people that are actually in our field is to say that I'm not here to replace you. I'm here to make your problems go away, to kind of turn you into a super employee, to turbocharge you. Because if you already have a team that works well together, like why not just accelerate everyone, put them all on Ironman suit instead of replacing with robots. And I find that there's this period of time when I start working on a project where I talk to everyone, I let 'em know. I want to make your life easier, not replace you, not automate you out of a job, because let's say I replaced your job with automation, well then I just want you managing that, right? You could just do 10 times more. Like you're already a good employee. I don't wanna get rid of you because you're already working. So it's very, as anyone who's hired, no, it's hard to find. Once you find a great team, you don't wanna lose them. So I think that this is an important message to kind of express that. These tools can really enhance you, whether you're at the bottom or the top of a business or an industry, small company of two employees, or a big company of hundreds of thousands employees that it's also a very interesting time where smaller companies have this huge advantage because they can adopt and develop new practices and they have this agility. It's really hard to adopt 10,000 people 'cause you, you can only train 50 and then they train the next 50, so it might take seven months. Whereas if you're just training a team of 10, you can teach 'em in a week. So I think I love your perspective. I think it's really been interesting for me and I appreciate you being on today's episode. For people that are interested in more about your perspective and kind of seeing how things are working south of the United States, that there is more America out there, where can they find out what you're doing, where they connect with you, and maybe even find out if you can really help them accelerate their company. Absolutely. I think LinkedIn would be potentially the best place to connect. I am still Brazilian even though I live in the us so I'm relationship based and I accept people and I talk to them. So everyone can feel free to go there and then connect and then talk and discuss. I think LinkedIn is one is a good option. Otherwise I do have, a business Instagram where I talk about business transformation, and that is Hack Your Business, we call. So it's Hack Your Business and then it's Instagram and TikTok. So I use those channels as well to, you know, be able to talk to people and then figure out whatever I can do to help them. That's great. I'll make sure to put those links below video on YouTube and in the show notes. Thank you so much for being here today for another amazing episode of the Artificial Intelligence Podcast. Thanks for listening to today's episode. Starting with AI Can Be Scary. Chat GP Profits is not only a bestseller, but also the Missing Instruction Manual to make Mastering Chat GBTA Breeze bypass the hard stuff and get straight to success with chat g profits. As always, I would love for you to support the show by paying full price on Amazon. We can get it absolutely free for a limited time@artificialintelligencepod.com slash gift. Thank you for listening to this week's episode of the Artificial Intelligence Podcast. Make sure to subscribe so you never miss another episode. We'll be back next Monday with more tips and tactics on how to leverage AI to escape that rat race. Head over to artificial intelligence pod.com now to see past episodes. Leave a review and check out all of our socials.