Unlocking AI Innovations in Construction with Marcus Turner

One of my most favorite quotes that a guest said was, is that, that basically construction people come together as strangers and leave as enemies. And it's a pretty strong statement. And, you know, we, I would like, I love to see less of that. And I would love to see people kind of working on processes and projects and things like that. Because, I mean, we don't want to just go to work and just know it's a frustrating experience. We kind of want to go to work and have some relief.

And I think that it would be, you know, construction is sometimes a very long process because it's going to be years being with these people. So I think having more of a collaborative environment would be beneficial. Welcome to the EBFC show, the easier, better for construction podcast. I'm your host, Felipe Engineer Manriquez. this show is all about the business of construction. Today's show is also sponsored by the Lean Construction Institute.

LCI is working to lead the building industry and transforming its practices and culture. Its vision is to create a healthy and thriving industry that delivers outstanding project outcomes every time for everyone. Check the show notes for more information. Now, to the show. Welcome to the show, Marcus Turner.

Marcus, I am so excited to have you on the show that I even woke up early to make sure that I didn't miss you and thank you so much for coming on the show, ladies and gentlemen, this is going to be a treat. Marcus Turner is the one person that you need to be following on LinkedIn and social media. He is my secret weapon as to how I've become so able to use AI to enhance my workflows, my lifestyle, and all the things that I want to get done to make my life easier, better, and faster.

Marcus, please introduce yourself so people can know why you're such a gangster when it comes to AI, artificial intelligence, and all things tech. Thank you for that, Felipe. You definitely have taken some things that I've showed you and definitely ran with it in ways that I never imagined. And I am so proud of all the things that you've accomplished where I'm learning stuff from you at this point. And we're sharing information back and forth.

It's really cool because we can text each other like, look what I found, look what I found in the sky. Awesome. My name is Marcus Turner. I am part of the second half of Constructor. If anybody here who follows the show remembers Brittany Campbell Turner. She is my wife and we're on the journey, working together, trying to figure out how to make the construction industry more interesting.

How I stumbled upon AI and working with it was actually around 2020, yeah, 2020 when we were working on marketing efforts, as far as trying to get our communication out there. And we were messing with what I didn't know at the time, but I actually got to learn through Clubhouse. Everybody remembers being on Clubhouse in 2020? Yeah, I remember. So, but what I learned was, is that I was using it through this one platform that was trying to help us work on our marketing messages.

And I was really frustrated during the time of trying to figure out like, Like, what do I need to say to get it to look the way that I wanted to do? I don't understand how to get AI to do that. And then I was like, so what is this system using? I don't understand why the software is even needed in the first place. And I started learning about GPT-3. And I started learning about prompt engineering. And so I realized I didn't really need that software product anymore.

So I kind of like dished that product off to the side. And I was like, oh, okay, this GPT-3 thing seems to be kind of more worth it, trying to mess around with that. I had some results and actually I walked away from it. And then, like a lot of people, Chet GPT came around. And I got excited. And I was like, how factual is this information? Trying to figure stuff out. So during that time, it came out during the same time college finals were happening. And I had some friends who were professors.

So, I had some friends who were professors who were very kind to me to actually give me some of their finals and some papers and gave me some ideas to come up with. And I was just like, I can see you totally. If I was a college student, I can use this to cheat. Get that edge. Cool, transparent. And so, I asked my college friends because I really wanted to dive into how accurate was the information and what is the acceptable level. problem.

And they were like, this is actually not that bad. This is actually pretty good. And then they showed me some answers that they came up with and the way that the AI solved the problem. I got to the right solution. The steps that I did was not necessarily something that they would teach, but I still got to the same solution. And then so we had some conversations back and forth. How are you going to prepare for the next semester? Stuff like that.

Do you think this is going to replace students, teachers? Do you think it's going to help teachers? And a lot of them actually came with it with them from a very positive mindset. One of the teachers, one of the professors I was talking to was a communication professor. So there's a lot of written papers and things like that. And he was like, you know, I'll just probably do a lot more like speaking.

So how do you present yourself and things like that? So more real world type of stuff instead of just like looking at papers every single time. Because a lot of, I mean, you can have as much AI detection software out there in the world. It doesn't mean that all someone has to do is just running through two different AI programs or something like that. And then all of a sudden, Hey, I got a paper. So for all the listeners, you just heard how to hack through.

It's that easy to beat the AI detection. Yeah. And it's always going to be a, like a forever game, you know, going back and for it so and i think so that was a i think that was part of it and then another part was talking to one that was a math teacher i actually learned that it's not as good with an engineering professor friend of mine it wasn't as good with math and as i thought it was so we tried some stuff and i was like okay so ai is not fully ready to be kind of this all-encompassing thing

where we can just ask a question to it and then give us a jarvis-like answer and everybody can be tony stark iron man you know so it's got some limitations i mean i'll i've even asked it like basic finance equations and it's good at telling you like what's the definition of the equation and it it'll lie to you and tell you that it's calculating correctly and then if you run the the math yourself on the side you're like hey math doesn't math and you call it math.

It doesn't math math doesn't math and then it it'll apologize to you and then run it again and like magically on the second time it usually gets it right usually not always yeah check check ai's math people if you're relying on ai math you're gonna be disappointed yeah i i think one of the things that i find i don't use it as much for math anymore but what i one of the things i I actually use a lot for it is telling it, asking it code, especially with chat GPT.

Sometimes you can get it to solve a math problem by showing code. It's actually a lot more reliable. I think they have some, they have some Python scripts that they can kind of run in the background, at least for a chat, for chat GPT. We're getting to the AIs after that, but that is something that they actually do a really good job with. So. Yeah, I absolutely do. I agree. And there's even some with the GPT store.

Now you can create your own GPT and force it into those environments where you're calling up like Python to do some things.

Things and if you're if you're running software that's like good for math like python super good.

Your odds for correct answers are going to be very high but the large language model in itself is like you're asking it to do something that it was not intended to do even though there have been emergent things happening with open ai which i want to get into on the show but before we get into all that marcus thank you for introducing yourself and i think the other thing you forgot to mention i'm just going to remind you marcus and i are both nerds

so just in case you didn't know and it didn't come across like you heard him he's like talking to teachers he's not in school anymore he's been out of school for a long time and he still talks to teachers so just go to show like that's uh things we have in common like we're both you know electrically uh focused and we both are not in school but still learning every single day which is why i love getting those text messages from you at 11 o'clock at night because it's going

to be something good it's going to be good so i wanted to ask you like just starting off what is something that surprised you recently with ai i haven't gotten into this one yet. So this is a lot i think the thing that actually caught my interest was this thing called ai AI scientist. And... There's a version of it that I could talk about a little bit earlier, but I think going into this one was pretty deep.

So AI scientists is created by a lot of some people that are scholar researchers and things like that. And basically, they just wanted to do they're like, well, you know, there's this process that we do to write these academic research articles and things like that. But what we also want to do is take the research articles and start adding them together and trying to see if AI can find some ideas and help us find some solutions from it.

So that's the big, carry audacious goal of theirs is that now we could use AI to do all this research and this research thing can now be executed by AI. And now we can find some other things that we didn't find before because we just didn't necessarily think about it in the way that an AI would. I mean, I wouldn't say a way that AI would, but like we can't iterate as fast and basically using AI to be able to be the assistant to help us be able to do that.

Now we can be able to do some things a lot better than we normally could before. for. So that has caught my interest as of late. And I think the other thing that has caught my interest just recently is seeing AI as far as being able to kind of create your own small apps on the side. And it could be like a calculator. It can be like, hey, I can actually be, hey, I just want to create an interactive lesson plan, stuff like that.

Little small stuff that you'd ever really think of. Oh, I don't have a PDF highlighter. Oh, I got to buy a PDF highlighter. Well, why can't I just ask AI to help me build a PDF highlighter? So now I can highlight the PDF and send it back to the person that I was talking to. and i spent no dollars on that kind of awesome.

That's so cool and we had a i've done a couple ai talks and you've done a couple ai talks as well in the construction space and the last one i did one i had a researcher from the university of austin texas in the audience and we had a there's a section at the end of the presentation where i I just open up a prompt window and I ask the audiences anything they want to see so they could practice prompting with me because I've got years of experience now prompting thanks to you.

And so we asked it about research. And the interesting thing is I found out a couple of things like construction research right now is almost nothing on AI. And the reason for that is because it takes researchers with peer review and the process they have to go through about two years on the fast side and more than two years on the typical side. So we're about to see a wave starting next year and the year after on lots of research published about AI in the design and construction space.

It's coming, but it's not, there's almost nothing there yet because all the papers are in review and going through the process. And so the researcher asked like, I've got this topic I'm thinking about. And through prompting, we took that topic and then had, we used GPT and CLAUD, create iterations of things that they can study that would be interesting based on what their objectives were, the research. And they were just amazed at how fast it did it.

And she said, her comment was like, what you just did on the screen could sometimes take us like three months or four months to get to the same end result. And you just did it in like 20 seconds. And it's only because I'm a slow typer.

Yeah yeah if i would have voice to texted it it would have been like 10 seconds yeah and i actually obviously i really can't wait for the the 40 voice to text feature to come out so i can kind of dialogue with the ai a little bit more but i use it now and i absolutely love it and i think you know i think that's gonna probably be the way that a lot of people start interacting with it a little bit because even today it was weird for me like a little while ago

but i have friends who sent me voice memos instead of actual text passages which is pretty dope but i didn't even think that was like when i first got it i was like i used to be a voice about it was like.

I know i have a i have a couple friends that consistently send me voice memos, and i'm still not used to it like you know you're you just get we're just creatures of habit marcus you get used to seeing characters in your little box in the message and that's what you want to you you expect and you get weird stuff. Like I have a friend that sends me videos through WhatsApp, which I really love. Like those are so cool to get short videos and WhatsApp.

So there's, I mean, there's different things that people use and, Just, I like, of all my friends that message me, I like it that you spice it up. Keep it spicy. I'll start sending them some more voice memos to everyone. Yeah. Yeah. Let's see. Let's start a trend. Voice memos. So I want to get into unpacking a couple of things. Everyone, this is going to be a great episode.

You're going to want to listen to the show two times, unpacking a little bit about AI and some of the current trends in design and construction. All right. All right. So Marcus, as an observer in the construction industry, you've had a lot of experience in your prior career. What has surprised you about how buildings get built? I think to me, it depends on the organization. And I think that part bothers me. How much upfront work an organization wants to do.

And I think the other thing that bothers me a lot is when you don't do the upfront work and some companies use this term, not all do, but value engineering. And it really is, we, I'm not going to say the word because, you know, it's a podcast, we effed up. And we are now going to figure out what can we cut from the process that we think it's not as, wouldn't impact the project as much. And sometimes just having the upfront conversation would be it.

So I think those two spaces or those two things are. Because my background for was working at a nuclear power plant. And one of the things that we did consistently is we brought all the parties together. We're going to be working on the project or the process or whatever the maintenance activity was. And they were pretty extreme with it. So this will go down to even changing of a light bulb. So who are the people you need to call, sit down, have a work package put together,

have a plan scheduled around the plan. and you execute the changing of the light bulb. But there is some consistency within that. So you kind of know what to expect and you kind of set a pattern and you set a standard. You know, those who are sports fans, you know, some people like their teams to play hard. And even though somebody, let's say, I'm a basketball fan, so I'm just going to say, contesting a shot after the whistle has been blown, stuff like that.

Like there's a standard to play and you try to set the standard of play so you can be consistent so when those times when you are You know, you're tired you're fatigued and things like that. Everyone has that routine kind of built in So when something actually happens that needs to happen, you just kind of do it instinctively as a team or as a group.

So I think I think that was really good and I think that when I I looked into construction, had conversations with construction professionals and things like that. That was the one thing that I saw that was kind of lacking was the lack of camaraderie and teamwork.

On Brittany's podcast, one of the, I think one of my most favorite quotes that a guest said was, is that, that basically construction people come together as strangers and leave as enemies. And it's a pretty strong statement. And you know, we, I would like, I love to see less of that. And I would love to see people kind of working on processes and projects and things like that, because, I mean, we don't want to just go to work and just know it's a frustrating experience.

We kind of want to go to work and have some relief. And I think that it would be, you know, construction is sometimes a very long process because it's going to be years being with these people. So I think having more of a collaborative environment would be beneficial. That is so, so good. Good. That's such a good quote. I was on a job one time, and I also like to remember the things people say, and I even will write down. So I put it to commit it to memory.

And one of the things that popped into mind as you were saying that is that there was a contractor. It's a mixed job. It's like, it's like a complicated job design build. And one of the general contractors in charge said something to the effect of, we've decided what we're going to do. We're no longer asking for your permission. And they said, tough shit, we're doing it. And that was like their quote. That was in response to, I remember, a trade contractor was asking a question.

It's related to design. And that, that response was like, as if the designer, you know, was, was present, which they weren't at the time, but this is the type of the environment is such that. People get pitted against each other, even though they're trying to build something together. Yeah. And that's even, that's a design build. I mean, so like people are taking hard lines, even in design build, which is supposed to be like the solution to the hard bid.

It's supposed to solve all the problems of the hard bid, just like construction management was supposed to solve all the problems of the hard bid, you know, before that. And we keep iterating. Now we've got to fast forward to today. We have integrated project delivery. It's supposed to solve all those problems. But we can unpack that and talk about that on another show.

So I want to go back into AI. And this is a true story. But the audience, you don't know that in order to make this podcast happen today. Marcus and I both had to use AI in different ways just to get all of our tech to work. And we were, I was commenting to him as we were getting set up that, oh, Zoom has all these new features in place. Like we could share our screens at the same time. It's like I didn't get the memo on the release notes Zoom for that happening.

We are recording this in Zoom because it's just easy. And I've experimented. If you're a fan of the show, we're in season five. I've used four different platforms throughout the years to make these shows possible. And I started with Zoom and I'm back on Zoom after five years. But I still experiment and I try stuff. And I'm super glad that Marcus also does the same. We learn to keep, we keep sharp when we come to like a black screen or like stuff that doesn't

work. It doesn't, nothing can stop the show. Yeah. Yeah, definitely. It's crazy. Like sometimes when you run into problems and this was actually a quote, I think one of the things that a friend said to me recently, and I think this, this is actually something I actually use in my talks. now. We get so used to doing something a certain way that we forget that we can just ask AI.

Or the solution to whatever our problem is, because we've been so trained to do it a certain way, just based off of our habits. That is so true. That is so true. I was roped into something recently, Marcus, where somebody had gotten an assignment and this person does not use AI. They're aware that AI exists, but they haven't played with it at all. And the company they work for does not encourage them to play with it.

And I could tell because of how you've helped me retrain my brain with prompt engineering, that my ability to use all of my lean thinking to turn my thinking around to what's possible and to focus on the outcome that I want changes how I talk to people. So when I was talking to this individual, I said, because they asked me, like, can you help me? Oh, I need some lean help is what they said. And so for me, I confirmed that they actually wanted coaching and that everything's possible.

It's a wide open because sometimes as a coach, you could be asked a question and they don't really want your help. They just want you to listen to their process. This was a case where they actually wanted coaching. So I said, this is what you said, this is your state, this is what's going to happen if you go down your path, and then here's an alternative, if you change two things, you can now do this, what you thought was going to take two years, and what had taken two years.

You now can get done in less than four weeks. Weeks and at first they were like no can't be done and i just walked them through like it's just thinking and like the way that you prompt give some context this is what you want i have to do a little algebra to calculate the time and my algebra was pretty good because they had the they already had the answer their their process as is takes two years the revised process us four weeks. It was awesome.

And now it's happening. And I asked the question just to close the loop. I said, what's your first step? And I made them like, tell me what the first step was. And I was like, nope, that's not it. They went right back into the process that they used for two years. And I was like, nope, I'm going to sit here and I'm going to wait until you execute step one to make sure that it starts. And then I said, I'm going to see you in a couple of days.

And the first thing I'm going to say is, are you on to step two yet? And I'm just going to be on you like until we get done and we close it out in four weeks. In reality, they got six weeks to get it done. So we got a two-week buffer. So I give it two weeks for them to go back and make some mistakes. It's okay. It's okay. So I want to pack.

Let's go back to, let's stay on AI, Marcus. And what are some of the current trends in design and construction that, you know, people like me that I'm out there nerding out with it all the time, but most of the audiences I've polled people and you've had talks with construction folks, and it's a mix. If you're going to an AI talk, you're going to get more than average people. When I talk to the everyday construction partner, they're not using AI at all. What's your take?

I would say it's still very early days. It still feels very early days. Most people, they've heard of AI. Even some companies have even implemented AI solutions where they're using, you can access GPT-4.0 or Claude or Gemini, which is Google's product. So, but the thing is, is that a lot of people still use it or there's different levels of it is what one is, I've used it and I didn't like it. And typically those are the people who are kind of using it as a search engine.

And it's not a search engine. I think one of the consistent themes that I do in my talks is, you know, you got to think of it as you're talking to an assistant or an intern. What are the steps that you're going to guide an intern with? How are you going to walk through the process with them? What's the end goal? What are some of the pitfalls? What are some of the constraints that you have on your question?

So, and then the layer two of that is I would always say that from another thing I would tell people is that give it a role. You are a construction engineer or you are a commercial licensed architect. Licensed architect would probably get you some, they'll probably say, I'm not a licensed architect, blah, blah, blah, blah. But if you get it to role play in that realm, it can get you start thinking about what an architect would think about.

Maybe if you just, even if you have like a document and maybe you have a perspective that you have on the document, but you want to understand another partner's perspective, right? Right. So those who do personas and companies, they understand they have a list of what those personas are. Well, based off a list of these personas, what would you think if I said this and you posted the document? Give me a debate back.

You can get a list of things and now you can find out some of the objections or some of the concerns that somebody would have based off of a document or a plan or something like that. Scott. So I think just playing those two things help a lot. And then the third one is what I would always say is in most of your prompts, explaining in a step by step way or think step less things step by step.

If you could do those things where it can kind of give you a breakdown of the process of what it's showing. It's still a prediction model but it's a prediction model based off the world what i mean by that is if it basically predicts the next token so the cow jumps over the moon you know, i'll play along okay so you know it's it's stuff like that so it you know romeo and juliet perfect Perfect. Julieta. Yes. But, you know, so it's playing off of that.

And what you want to do is build it context. And if you build more context and you build in constraints and you build in role playing and you tell it to think step by step, you will get better results out of what your answers are.

Instead of saying okay tell me the top five blah blah blah blah blah just like how you would use google give me the latest blah blah blah blah blah blah and that's just not what a large language model using just chat gpt or using just google gemini by itself that's not what they're capable of. They don't have access to the search engines and they don't have access to those type of things. Now, if I said you can give an A, now you can give it a tool to use, then it would use that tool.

Then it would synthesize some of that stuff. And that's what you're seeing. I know, I'm assuming most people still use Chrome today. That's what you're, or that's what you're seeing within Chrome now that you're seeing AI generated stuff at the top for a little bit. And it's giving you a summary or synopsis, and now you're seeing the links that are followed behind it. Bing does the same thing now, and their Bing chat feature, those who are using, and they're using, Bing chat is using GPT 4.0.

So if you prefer 4.0, I'm not saying that you should go to Bing, but if you prefer 4.0, you can use Bing chat to be able to do so. Yeah, and even Amazon is using Rufus to synthesize all the reviews.

So if you go to, and I learned about this recently, I was on Amazon looking at cameras of all things, of course, because podcasters what my next purchase is going to be another camera and it would take like some of these cameras have you know thousands of reviews thousands because products people love the products they talk about it so rufus for amazon is now giving you a like a one paragraph, here's what most of the reviews say helpful not

helpful like not like and it's like a very consistent but people look at in the reviews that it's synthesizing for you so you don't have to look at 10 000 reviews you can and it's a pretty good summary i've used it a few times with some different types of products that i didn't have a lot of experience with and i found it to be very helpful and when it first turned on it was terrible because uh you know like all things ai like it starts really bad but they've got to expose

it to humans to help it train and learn and then it gets better very fast like the iterations and the speed of improvements like I've been experimenting with GPT on an app on my phone, talking to it. And we talked about this, Marcus. I had a consulting call about Scrum, probably about... You know, almost a year ago. And the voice to text was already a thing. And so I took the call, I was on the road and it was like a one hour call. I didn't record the call. I didn't have the client's permission.

I didn't ask. I'm in California. So we have to always ask if you're going to record somebody, you got to ask their permission to be legal and compliant. So I just said, let me just do this live. I'm not going to record. And then after the call was over, I turned on GPT. And at that time, I think it was three, five voice to text, the audio version, the earlier version, not the version that's out now. And I just had a conversation with it. I said, I just had a consulting call.

I want you to act as a coach to me, to coach me, the consultant, to make me a better consultant. I'm going to tell you what I talked about from memory. I want you to ask me questions for things that are not clear as I'm sharing you this narrative of what happened and then coach me to do better to help the person the next time we talk.

I want definitive things. So we had this conversation, I'm driving and I'm just talking and I talked to it for 45 minutes, but coaching call was an hour, but I would talk to AI for 45 minutes while I was driving and, you know, hands-free. So it's like this going through my car. And at the end of all that, I got a transcript. So I could go back and see like, Oh, do this better. Listen here. Like I gave me suggestions, like you did.

And it even gave me good things too. So it's, you know, a lot of the things, Marcus, when you're working with people and you ask for, for help or feedback, everybody always wants to give you constructive criticism, like right away. And so I appreciated the large language model, reinforcing the good coaching things that I was doing, like, you know, listening first, asking clarifying questions. It's that I did a really good job of doing that.

And I was just super impressed. And since then, I've continued to refer back to that occasionally and continue enhancing and improving my ability to be more effective coaching. I think now today, if you're listening to the show and you haven't practiced with AI, just think about people like Marcus and I that have been doing this for almost half a decade now. And if you're not, you can catch up. You can still start to learn.

There's really no reason why you can't learn something. And Marcus, you've got stuff that you want to share. So I don't know if you've got more trends that you want to unpack or if you want to start sharing. I can actually follow up with another story that's in line with all of this, right? So working with, so Brittany is a part of the Respect for People Committee. So those who were at the LCI last event know that it was recorded.

So, one of the things that we wanted to do was get a comprehensive definition of what respect for people actually means. So, we recorded the event. People spoke. And one of the things that we wanted to do was, one, anonymize everything that's there. And then, two, figure out what their stories were.

So, we wanted to summarize each person's story. So we, well, this is what I did, was summarize each one's story and then from there, we looked at everyone's story and said, okay, based off of these stories, this is what our current working definition is. Okay, now, based off of these stories that you now have, that are now summaries, take these stories and now add that to the, what do you think the new definition

should be based off of the stories that were provided? it. So, and then what I usually do during those type of processes is I don't never ask for just one based off of those. I ask for multiple because I want different, different things, different perspectives and different things to be able to be shown to, to kind of go through that process. So I asked for five, just simply five. And so as a base off of these, give us, do five definitions. And it gave us, it gave us five different definitions.

Now I'm not a part of the committee but i do of the odd assist things such as that and. So that's what, that's what I ended up doing for the, for that time. And then another thing that I did off of that was based off of each of one of the stories, because everyone had to, the reception of it was pretty high. It got ranked as far as the LCI scores, as far as meeting participations and things like that. So that was pretty good.

And one of the things that I, feedback was, is we want more programming, and we wish the section was longer and so i said based off of the stories that were shared and people seem to enjoy those let's come up with curriculum based off these stories and so i what i did was is i categorized.

Asked it to categorize a few of the stories to say what's similar to each other and then build a program off of that now what the respect for people committee does after that with the information and things like that. That's up to them as far as what they want to do with it. But I did try to start doing the lesson planning process of this. And going back to my professor friend, he actually now uses AI for both of them actually do.

They both use AI for lesson planning, which is a big time suck for teachers. Those who are educators definitely try to see how, what ways you can be able to do that. And that was definitely something that they ended up doing throughout their process is being able to use AI as a subsistence to build out a lesson plan. So it's a lot easier for themselves.

Yeah, that's a great story. And even the AI talk that I was giving where I talked about the researcher asking questions at the end, I tell people in the beginning, like, this entire presentation was started with me having a conversation with GPT-3, 5 in the beginning. And then we later, 4-0 came out, GPT-4 came out later.

And so it started a year ago and built it in three five including the slides the flow the timing it's a two-hour interactive presentation and then we updated it with four gpt4 and we had feedback we had sessions we did a repeat so we had in our community in california the community said we want this ai presentation again like they wanted a replay live and so we did it two more times so So four times total, Sacramento, San Francisco, and then Sacramento Bay, and then Peninsula Bay Area.

And in the second, the version, the second and third, second and fourth time, I'm sorry, third and fourth time, got to get my math right, third and fourth time, one of the feedback comments we got from the audience, this is one of the owners that builds over a billion dollars a year in hospitals here in California, said, you know, the presentation was very positive. And I'm not surprised, because you asked AI to help you make it. It gave a very positive spin. What about the pitfalls?

And so in version, the third and fourth version, we've now balanced the, the down, the scary parts. I'm just going to call it the scary parts of AI. And one of the people, we had a electrical contractor, JP, shout out to JP was in the, he went to all the sessions. So every time it was there, he he's, he's seen all of it. And he commented to us like number one, shockingly how informative it is and like how we present it.

And then the second thing was he's like and he mentions it every time now because i've seen him like at two more events since then he says every time he thinks about the updated version that shows the dark side of ai he said it gives him nightmares like while he's awake every time it's it's scary because the the dark side it can go to the worst parts of humanity the things that it can do and people always they will assign the dark sides of ai like to the ai itself and they forget that there's

people prompting it engaging with it getting it to do these things and so there are some like scary stuff about it but it was interesting to see like how we took the same thing and we iterated with a a new version of it and made it totally balanced. For people, but it took like, I'm, you know, I call it human in the loop.

I didn't, I didn't make that up, but that's a, in the space people talk about, don't forget the person inside, like you and you said, you did all this stuff with the respect for people task force. And then you kicked it back to the humans in the loop that are responsible for implementing, you know, where they go with that content. Yeah. That's going to be up to them. So it's not, it just, it's not automatically like doing something on its own.

Even though with, even though there are now auto AIs and, you know, that type of stuff where we could talk about if you want to, you know, some of the scarier things that can happen. I mean, there's some, I mean, I've messed around with auto GPT, which was supposed to complete tasks for you based off of the questions that you ask.

And what I realized was it ran up my API credits and it never completed the task it's so you know it's a good yeah for me it let me know that it's a long way to go from there some people try to so you know i looked on twitter and saw some use cases and i was like okay let me try that you can use case i tried it didn't work and i'm just like you know this is a great experiment i think it's a great thought experiment you can probably take bits and pieces

from this and be able to do some stuff but you know for those who are super super deep into ai and agents and doing these things, there's some things I can definitely tell you to look into. I'm not going to go into detail about all of them, but Crew.ai, Autogen, and Llama Index, and Langchain all have agent frameworks that you can build upon that you can make these agents string into each other.

Why is this important? Well, if I was giving an agent, if I was giving one AI one thing to be able to do the task, now the AI can critique itself using another AI. And now another agent, whereas we were talking about role-playing and why role-playing was very important, now it's role-playing different perspectives to be able to create some of these things. Now, I can actually transition this into what I was going to show Felipe.

And one of the reasons why this show came about is I was excited about some AI features, and I wanted to show Felipe some of the things and some of the variables that I went down. And one of these things is showing how an AI agent can actually work for people to be able to do that. And so that's a great, good transition into what's, what I'm going to share my screen upon.

Yeah, let's do it. Now, Marcus shares a screen just for all you know, while he's finagling the share button, just the big green button on the bottom. I tried to get him on the show for a while. And now that this topic finally unlocked the key. So now we're here. So, and you all get to learn with me at the same time. Like I have not seen what he's going to share. I'm seeing this for the first time myself. We hear all the time that building enclosure is the number one problem in construction.

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the needs of your company. Yeah. Everyone's seen a preview about how me and Felipe will talk back and forth now. So Felipe, is there like, okay, so I'm going to ask you a question and then we can kind of go with it and I'll just type it in. Right. Okay. So this is kind of using, Storm is made by Stanford, which is what they ended up doing with creating a research assistant, which is a whole bunch of AI agents that were playing a role, chained together using a tool. And the tool is the internet.

And it's a few things. One is called Archives. One's actually called, they actually use GitHub as well to gather a lot of information and and be able to create Wikisite argument articles based for research. So Felipe, is there anything that you would, they asking me to, there's a limitation to how long the topic could be, but can you send me a topic of something that you may be interested in? And then we can just kind of go from there.

Yeah, I'm interested in a Scrum. So let's ask it about how industries are using Scrum in their management practices. And for those of you watching the show, you should know that I love Scrum. And I have a dedicated playlist just to all the Scrum episodes that happen. So I think I just forced this one to the playlist. Okay. So do you want me to elaborate or should I just kind of ask that question and kind of go with it?

Yeah, I think let's just go with it without too much elaboration, see what we got. Okay. Oh, I'm just going to say you have to elaborate. I'm just going to do the same thing. Just type right here. Okay. And I'll change that. I want to understand. There you go. So he's taking that prompt in for those of you just listening. I want to understand how industries are using scrum management practices is the elaboration.

So definitely check this out on YouTube. If you're only listening to the audio version of the podcast, love you people. And while you're there, it's not going to hurt you to hit the like button and leave us a comment. Marcus and I will definitely be watching the comments on the show and answering your questions. So if you've got something and you want a deeper dive on, hit us up in the comments either on YouTube or wherever you're listening to this podcast.

You know, it takes about three minutes to be able to generate the article. While I do that, I can just sit here and wait for that. I'm not sure. Yeah. I guess your editor will probably edit, cut this part out until I get to the actual answer. Unless we talk about, unless we talk about something interesting. Okay. And then otherwise, yeah. So like shout out to editor Geronimo. Thank you for making the show so beautiful. Super appreciate what you're doing.

And if you're listening, this is how we'll know if Geronimo actually listens to the show. If not, people are going to just get free banter. It's all right. Yeah. This is a free banter. So, yeah, like as fast as AI is, I could tell this the first time I'm seeing Storm. It's got the prompt says it's generating article may take up to three minutes. And then it says start identifying different perspectives for the researching of the topic steps one of four.

So it looks like it's doing a multi-step thing. So if I was to guess what's happening behind the scenes, I would sense that it's, you know, searching what it's been trained on. Like you said, it's, it's trained in a couple of different areas. What is, what are the limitations of where it's trained? Can it go to, does this go to the active internet now or is it going to?

Yes, this is going to the active internet now. So one of the things I can do is actually show some articles that I actually did using the downloaded version. So this is completely open sourced. The one I was showing before is a web UI. So one of the things I can do is just kind of click one of these things. Since we talk about IPD for a little bit of this show, I have to click one based off of that. So I'm just going to go ahead and click this real quick and kind of scroll through it.

Um pretty quickly and so as you can see there's like a table of contents there's links so these actually i don't know if you can see the bottom left let's see it cited sources got references. So you know which is really good references that's impressive yeah it's uh 19 19 references hot dog yeah and you can kind of take this and then kind of read the read over this and then and dive back in to go deeper into your research to be able to figure out some more things, right?

Because this is creating an article, it's creating information. From there, you can actually see what questions were being asked. Oh my God. Like, hold on. As you were scrolling, I did, I did read one sentence about the challenges right there. Challenges implementing AI within IPD frameworks. It's, it's saying that it's going to be hard because an obstacle is traditional methods and manual repetitive tasks that affect.

Effect and it was like as i was reading it i thought that was pretty spot on where it's talking about the significant challenges you know people are so triggered and traumatized marcus in construction like there is no shortage of trauma written about how design and construction projects come together and even in this you know 19 reference article thing on ai with ipd it's it's warning the the reader which is us now that it's going to be hard because of these

traditional methods that are really difficult and a lot of the tasks are really manual there's not a lot of automation and process improvement in the construction space and i had uh you know our mutual friend sean graystone on the show a couple seasons ago and he talked about the way that we build today is based on methods from before the civil war and if you go if you some if a construction historian went back in time to the civil war to see

how projects get done and they they came back to 2024 it would look exactly the same like the same processes some of the the companies change and the names change but the the roles and the functions and the processes are still there intact the same. And it's, it creates like that environment, like you said earlier about how from that quote, people, strangers come together and they, after working together for a couple of years, they leave as enemies.

Like it creates a system that just turns people against each other sometimes. And you know, there's crazy people like myself and you and other people, Brittany, for sure, that we think we don't have to fight with each other to get stuff done. We can actually work together. There is another way. There's very few stories of dysfunctional sports teams that somehow won a championship in the end. I don't know of any.

So what's this down here at the bottom now? So if you wanted to kind of understand the thought process of what was the type of questions that are being asked. Right. So you can see what the answers are based off of what the and this is kind of using the A.I.'s common knowledge.

And it's asking it basically playing a role being able to do that and then they even it'll even show like where it says hey i don't have enough information to answer this question right so you're going through this so you're seeing what the thought process is there right and then, construction manager there's different questions that are being asked as well so i think and then what's the other role ai specialist so they created the ai so it created it three roles an ipd expert a basic

effect writer construction manager and an ai specialist so those are the roles that the ai generated from itself based off the question that i asked based off of one sentence so that's impressive yeah but it's chained together a lot of different prompts to be able to do that so you're chaining together a whole bunch of different prompts within ai and, so it's being able to understand what the question is to be able to create the

prompts to be able to generate the personas that are being needed so this is kind of like an auto persona generator as well.

And let's try to see if we can go back to okay that is still going okay i'm glad we showed this so and this is real time so so people can understand that like hey you know things don't always show up how they're supposed to i'm still going to let it run in the background to try to because i'm curious to see what the answer is but you're going through all those roles and so it's got four personas in the article about ipd that you did previously yeah

and the as marcus is scrolling if you're if you're not watching this video live like the questions and answers are significant like this could be you know any one of these questions and answers in these personas could have been your session that you've done and in an ai interface like a online version of gpt or claude anthropics claude or gemini or pick your favorite and but then it keeps going so it gets a question it gets an answer and then the that persona that agent

asks another question so there's a follow-up so it keeps having that dialogue and then the output that we saw when marcus first scrolled was like the the ready-built article and the article is a synthesis of all these four personas and in this example asking questions how many questions roughly do we see in this persona like four five i think it's about one two three.

So three yeah three big questions and answers on the specialist and then you know it does it's doing the same thing for the other agents i think that's that's that's a lot like to do and keep it all together with memory so this is one of the things that in the early days of ai it didn't have memory who to really have like consistent dialogues with, and now, you.

Here's an example where it's created an environment and it's using, you know, it's having four different conversations, probably almost at the same time. And then it's reading all those conversations simultaneously and creates this synthesized output based on these four different conversations. All started with one prompt, one input from a human. Yeah. And I think that's the nice thing.

And if those were down the rabbit hole of AI agents and working with different AI personas to get it to collaborate and come up with, you know, document generation, that's a whole other use case. Probably the use case that people are going to mainly feature is it's going to be some type of AI to document generation or AI to research assistant at this point.

Yeah, we talked about this in the LCI AI talk that we give here in California, that for content creation, this is a definite use case that if you don't know how to talk to it to do this type of stuff, then welcome. Now, you know, it can be done. This is one of the early cases, like a lot of people are using even Copilot in Word, in email.

So some people, their companies have turned it on to help them, you know, write letters or to, you know, create content, you know, based on something you want to communicate because it is so good at writing. And it's, you know, typically grammatically correct. It's logical. And then there's a, we did this in the updated version.

Version there's a test that they they run with not the not the turing test to see if like you can trick a person into thinking you're not talking to a robot or a computer but there's another test where they show like just average intelligence of an adult and gpt 40 has surpassed average intelligence of adult so you'll see as you talk to it and i i found this you know talking to it for years now like i've grown up with gpt like it's a you know like a member of my family like

Like it started off as like a toddler, maybe a little. It started off when it got released a little bit beyond a toddler. And now it's like talking to like a 30-year-old. And in some instances, like with programming, in programming, it's like talking to a 20-year veteran software programmer. So the experience in some of the domains is very high. Very high. Trying to see. Okay. Okay, so actually, it's actually still going.

It's on step four. Yeah, but it's on step four now, so it's right in the article. Yeah, we're almost there. The next thing I want to be able to show you, I don't want to go over it for this one yet, but I can show a different one where I can go to my articles. And I love how this article, if you ever talk to a researcher at the bottom of every research, at the bottom of every good research paper, it always ends with some nonsense about more research is necessary.

So, like, I think it's so funny. I'm just calling out all the researchers. And I've had a few academics on the program. I'm calling you all out that you're planting seeds in every one of your works to get more works. So, yeah, you're baiting everybody. everybody, like research is needed. I mean, some implementation and then some research on the implementation would be needed. I think that would be actually a really good thing.

One of the things, so there's this one that we're, for those who don't know, one of the interests of ours is exploring and we built a company around it was exploring blockchain and construction and builder pay is one of the solutions or build a chain is one of the solutions to be able to do that but and britney's written one paper that actually went to parliament parliament in the uk as far as their thoughts and ideas of blockchain within the use of supply

chain so they talk about the legal aspects and information handling aspects and stuff like that one of the things that i did was i just kind of asked a a little bit more like kind of a vague overall question. And I just wanted to see what research and what research was out there. And I was actually surprised of how much stuff and what they were looking for and things like that. And it pulled different spaces. And I was like, oh, okay.

So it's still like, you know, they're still talking about like, yes, this stuff is being talked about, but some of the same problems that are still there after, I think, You know six years later of being able to write that article that went to Parliament. You know government takes a while to implement things just right say, That's a matter where the government is takes multiple election cycles to get something done Exactly, and then you know and another party still may block it for you. So yeah.

So I thought this was a really good one. Yeah, let's check back. Okay, step four. But that Scrum article is just exhausting. The storm. Well, I'm using somebody else's UI, using somebody else's API keys. So it's going to take a while for that one. But at the same time, I was at least smart enough to prepare this before the call and show it from a local standpoint. And this is kind of how those who are watching are seeing the Storm one on the Stanford website.

It's very pretty, nice, and looks really, really awesome. But the one that you use for yourself doesn't necessarily look as well. I did have some problems at first trying to install this, but if someone wanted to install this and wanted to go through the process or anything like that, feel free to hit me up on LinkedIn.

And i'll kind of walk you through the process it is going to cost an api two api keys one of them eventually will be a hundred dollars a hundred dollars a month so you may not want to use it for you may want to get your uses in early but it has a free trial for 60 days and then the other one it does cost a gpt4 but there is a way you can do it for free i didn't do it for free but so So, but it does cost a GPT-4 API key.

So it is, I am hitting my API credits by using this. However, the other one I'm using is somebody else's API key. Yeah, that's what we're going to appreciate, the API key sharing. And yeah, thank you, Marcus, for spending some API dollars with me on one of my favorite topics in the world.

We'll make sure that the output of this article gets turned into a blog post and we'll attach it to this interview so that in the show notes, So you'll see a link to that blog post and the output of that article. We'll put the version. I'll figure out a way to get it in so that people can see what it generated and some of the thought process. We'll expand it out a little bit. So what are we looking at now, Marcus?

So this is for somebody who maybe is struggling with prompting or anything like that. Claude has created this platform called, they created their own prompt generator. So Claude is made by Anthropic. Anthropic is a company that split off from OpenAI and they wanted to pursue AI a certain way and OpenAI wanted to pursue it in a different way. So they're, I would say they're cousins, but, and, and in a way that's still, you know, they're competitors.

So Claude has done a thing where they, they've generated an idea. They said, hey, you know, since prompt generating, prompting is really hard for people, let's figure out a way to make, you know, prompting a lot easier for people. So I'm going to take that same question that was asked from Felipe and... How are industries using Scrum and management practices? I'm just want to go to this, create a prompt, or should I take something else in Felipe and just make a prompt from that?

I think we can, the task will be, cause this is the question I get asked a billion times.

I'm new to Scrum. how can i as a as a novice start using it in my management work that's the prompt so for i mean if those you're listening like i'm i'm beyond a decade of scrum use so this is not my question but it's a question i get asked all the time i just want to see like how good are we going to get from this yeah so this is just a basic question right so in like three seconds marcus Marcus now has like a fully generated prompt. So what I'm going to do nicely is post this in the chat.

So not flip it. You can definitely read it out if you want to. Oops. Not sharing. That's the share my screen. Yeah. I'm going to check, uh, see what's coming up in the chat here. Marcus is going to share what got prompted. I'll read some of it. Yeah. What, uh, what came out of her? If you're watching this. Oh, it's actually too long. That's crazy. It's too long for Zoom chat. Yeah. I'm going to access my Google Drive. I should just ask my Google Drive not this way.

What I can just try to do is this. I'm going to open up my notepad and then bring the screen over. Yeah. That'll work. Let me not share my screen when I'm accessing my Google Drive. I'll be right back, guys. We'll just cut that out of the show so that we don't show all your, yeah let's not make it easy for people to hack you get a little harder let's think about this for a second all right so i'm gonna go here,

Go back to the share screen. Share. Okay, cool. Yeah, it's more than a page. Yeah. So. Yeah, probably. There we go. All right. So basically, hey, we're talking about the role, right? We're talking about that again, right? You're an AI-assisted task for helping a novice understand how to implement Scrum in their practices. You provide basic information about Scrum and a specific question to the user.

Your goal is to provide clear structured and practical advice to help the user get started with scrum right that's great yeah first it gives some scrum basics next present them with the user's question and then it goes into analyzing and then some of those are code snippets so people looking at you know what that is that's code that the ai is going to understand and i'm sure that this prompt would work in any of the large language models so it

doesn't have to go back to cloud necessarily but for those listening i do like the friendliness of claude i feel like between claude and gpt the personality that claude has is a little friendlier yeah and and i think that's one of the great things about being able to go back and forth with the large language models, and there's a really cool hack that i would love to talk about towards, felipe to kind of share with you so if you have some personal you can have some

personal only imagination about this nice hack that I kind of found was with the for a workflow. Yeah. Okay, so we have the prompt generator that's here, right? You still want to generate the prompt, and that's definitely good. But what you can do before this is we can go to Google Gemini. First, what we want to do is we can screen record and talk through a process or something like that. So talk through a process, walk through some steps, use a screen recording to be able to do that.

Use Google to record your screen that you're going to show whatever your flow, whatever your process is and things like that. Then what you do is you post that into Google Gemini, you go to cloud and cloud and you take the cloud generator prompt based off of kind of what you what your task is, what you wanted to do afterwards. So now Google Gemini has access to the video because it's the only platform so far out there as is recording this at August 22nd.

Let's let's make sure that's clear as of august there's the only platform that takes video, so you could take that and then take this prompt put it into google and it can generate and create things for you based off the information that you have now provided it because they can now see understand what you're trying to say sure and then it can take this prompt that that was generated from clot to produce an output and or produce some dialogue based off of what you're asking so it's

a nice little cool hack of taking three different or two different well three different things which is screen record but using two different llms in a way to generate what you wanted to do for your result for for your output so um it's a really cool cool thing that you can be able to do from that. And then whatever you do with the output, you can even chain it together to go to another LLM to do some other task for you or something like that.

Yeah, that's super cool. That is, I have not played with that video feature on Gemini yet. No? No, not yet. I've done a lot of voice to text, a lot of talking. I've done transcriptions. I use another program as part of my editing occasionally to generate really rapid transcripts. So then I'll take that to one of these LLMs and say, here's a transcript of a show. And I've actually found that in the early days, it couldn't handle like a GPT-3-5 couldn't handle more than an hour of a show.

And now when they've did these enhancements with GPT-4, it can handle like, I think like half an encyclopedia now of stuff. And some people don't know you want encyclopedias. It's like, just think of many Wikipedia pages strung together. Yeah. Yeah. Yeah. I think one of the things that I've, I'm going to stop sharing my screen now.

But one of the things that I found very interesting about putting a lot of this stuff together and going through this exploratory process is that AI has shown me that there's almost a limited different ways to kind of go about this, to be able to kind of solve a problem or use a task. And you don't even need to be a programmer to be able to hack together a solution for yourself. You know, there's two things I didn't even go over.

If somebody wants to research them and look at them later, please go ahead and do so. One is Claude's artifacts, which kind of gives you a UI that you can kind of create and mess with yourself. And then the other one is called Facebook Sam, which is segmented anything, which I think is going to be very useful for those who are in construction and they're probably going to be one of the more useful tools that are out there.

Basically, what it allows you to do is be able to click anything in an image or in a video and.

Cuts out whatever that image is wow so some crazy use cases around that for as far as reading diagrams construction safety i was thinking another one which was another one's like workplace if you want to track flows within places and things like that i think those are going to be really huge but i think for now i think the the the low hanging fruit in my opinion And it's going to be the diagrams and then looking at it from a safety perspective,

you know, be able to click and identify certain things and things like that, at least off the top of my head. And when I think about, like, being able to segment and point and click and I can cut out, you know, you know, for a podcaster standpoint, it's like, oh, I want to cut myself out and put myself on a background. This is the super low hanging fruit for podcasting.

That's true. That's good. I've talked to some architects, Marcus, too, that have been using AI to critique their fire life safety plans to be code compliant so that they can pass reviews with authorities having jurisdiction in the first round. This is something that some architects have struggled with. Some of it's just don't have the right experience. And then building codes, they don't change every year. But depending on what city you're in and what country you're in,

they do change. change occasionally and people got to learn. So you can feed, you can feed an instance of it, the information, and then you can have it review the drawing for compliance and give you recommendations and pointers of things to look at that you might've missed. So you can have it act as the authority having jurisdiction, uh, grading your, your plan to the code, and then it can make suggestions to you. And then of course you're the human in the loop.

You got to incorporate the change or ignore the change and they found and this one individual saying like it's made their first pass on review go up to 100 so now they always pass first pass so like if you think about that from a an architect all the architects listening like depending on how big your job is like you know most of the projects i'm involved in are they're north of 100 million dollars so for design of that i mean you

can just use the percentages that you know the effort to respond on to comments on a project that large can be more than two weeks. So if you think about a design team with their disciplines, I mean, you easily can be on a project of that size, more than 20 people for a month. So you can take 20 designers for a month and just save yourself by using AI, just looking at, I know we're just picking fire, life, safety.

I mean, you could go, there are more use cases beyond what I'm saying, but these are things that can shut you down, especially if you're doing like healthcare construction. So you can save. So like, think about this designers, you can save a month of cost that you're just eating your profit because the what the owner contracted you to do is to create a set of documents.

That makes it through permitting they don't pay for multiple rounds of permitting they don't pay for multiple rounds of comments because if you get comments and you don't pass you know by all definitions and conventions like you generate your work product is subpar and it failed to pass and And now all that extra work to get it on round two. And Marcus, some things have failed four times and have gone back into permitting four times.

Projects out there in the big wide world. So that's all money lost that designers cannot recoup from the client because the client bought a bill of goods, which is a permittable set. So how they get there after that first round is all eating their profit.

So this is one way. and i'm sorry to the experienced designers that are that qc person that checks this like this is this is an example of how you better start scaling up with ai because it can it can and does eliminate jobs by making things faster like this is one of the darker sides of you know some of these use cases like the things marcus and i were showing today these are conversations in the past you'd have with other

people and now we're just talking to a prompt on our computer And we're getting the capabilities of thousands and thousands, if not millions of people. And we're getting it in seconds. Yeah. No friction. Yeah. You know, one of the best use cases, I think, of AI is or pro use cases is, is that you don't start off with a blank sheet of paper anymore. Right. You're starting with something. And now you can create and you can iterate off of those type of things.

But at the same time, there's a cost. There's a human capital cost of being able to create those things. Yes, it's paying instruction and we don't like doing those things and all that kind of stuff. But I think, you know, that it will, you know, as, you know, the war for talent and qualified.

Within the construction space, within a lot of other different industries and things like that. But more in construction is that, you know, we're struggling to find qualified talent and we're struggling to find people that we wanna train. And sometimes we don't have the time to train those people. So being able to offset those costs or being able to be able to pursue more projects, sometimes that's the bottleneck is that we don't have enough people to be able to do that.

And we only have one person that's doing the, you know, the compliance work and making sure that the quality is supposed to be where it is. Well, now you have a chance to implement and put, you know, now they're able to do three or four, then they don't have to, they don't have to do it as much. So it gives you some opportunities to be able to get some more work. And I think it gives them a potential for smaller firms to be able to compete.

But at the same time for those larger companies, those larger firms, do we need as much staff as we need to have? Right. And I think that's where the displacement is going to start happening and you start questioning those type of things. But for the smaller firms and things like that, yes, this is going to be amazing for you. You could be able to get more work, you'd be able to be able to do more efficiently. But for those larger firms and things like that, it's going to be difficult.

I think there's going to be some departments that were as large as they used to be, won't be there anymore. You know, before we used to have departments about being able to do a lot of copy paper. You know, now everything's on iPads and screens, and you just pass it off on a tablet. Here's the document that is sold. Yeah, Marcus, some people are too young. They don't even remember that there were RepoGraphics offices. I remember in my high school, there was an office. It was like stenography.

I think it had a name. The Steno Pool. i think they call it i remember walking past the door and i was like what's this and you open up the door it's like these machines that are like drums where they just roll paper and copy with like mechanical pressure it has they used to make photocopies before photocopy machines came out and it used to be like you know it could be teams of like five ten people making copies like using this very manual process and now with

the printers and laser printers like those departments are gone gone. Those jobs are gone. Nobody talks about the poor Stenal pool. And what happened to all those people? Gone. Yeah. I mean, you can even talk about like my wife, one of her uncles worked for the UN and that was the type of department that he worked in. So imagine doing a UN call and you have to translate this papers and all these different papers and all these different languages, right?

That's a lot of paper that you're going through to, to, for, for a piece of document. And so you're making sure that it's in everybody's native language. Now, he said, you know, there were whole floors that are dedicated. I'm not talking small, small, small places, you know, you know, straight on printing stands of being able to be able to generate all that stuff. But now, you know, those departments are no longer needed or a lot smaller than what they used to be.

If there's still some paper copies out there, right. Right. But, you know, and that's translating into multiple hundreds, different languages over the same document, just so people can understand what it what that document meant. Right. So, you know, it's, you know, it's technology is always create some type of displacement. But at the same time, you know, I think as society, it's human humans. We've always found different things to do. We've always found different ways to complain.

And that's just true he's not lying people like in the ancient sumerian tablets they found when they found these things like people back in the day complaining about stuff that they bought in the market you know that they hated it so much they took the time to etch it into clay fire the tablet and then share it with people so like we'd love to complain. And I think the, you know, the use cases that we come up with is that they also give birth to new industries.

You know, somebody has to maintain that, things like that. But I think the sometimes the biggest pain for some people is the reskilling. But I do think with AI, a lot of that also can be alleviated with being able to reskill and use an AI as a tutor or coach to be able to learn how to be able to do stuff. You know, tell me like I'm five, right? Right. That's a that's a great prompt for people. And then after you tell me like I'm five, OK, now I'm a novice.

You know, you saw the prompt that was created from Cloud Generate and that was from a novice perspective. But you can go another level and say, tell me like I'm five. I don't understand. And then they explain it from there and then you can build up from there.

And I think that's one of the cool things about AI is that if you need to be explained a certain way, It can take a document or take some ideas and break it down and explain it to you in many different ways that you could ever once or imagine. You can even have it talk like a pirate if you want it to. Yeah. With the new GPTs, they've even had it. It can sing now. Yeah.

You're going to have it sing all the answers to you. So, Marcus, thank you so much for coming on the show and sharing all your knowledge and wisdom. And we're going to keep talking for sure, as we always do, and pushing the envelope. Is there anything you want to leave the audience as they go off into their day? Just if you have any questions or anything like that, feel free to hit me up on LinkedIn or any social media. I am Marcus Turner. I am Marcus Turner on everything that I could think of.

So you can use your preferred social media platform and please feel free to message me or ask me a question please let me know that you're listening to flip based podcasts so i can at least have some context around it but i am marcus turner everywhere and i think that would be the best way to be able to get in touch with me awesome thank you so much marcus all right, very special thanks to my guest i'm felipe engineer manriquez. Music.

The ebfc show is created by felipe and produced by a passion to build easier and better, thanks for listening stay safe everybody let's go build, Thank you.