Why Using Your Own Voice Is More Powerful Than AI-Generated Content?

Want your podcast and videocast to be seen, heard, found and rewarded in this noisy digital world, you are not alone. Join the nonprofit community at Podcasters United and podcast industry experts Tom Hazard and Tracy Hazard as they debunk all that outdated and bad advice you've been getting from the podcast gurus and find out what actually works. Today, get ready to finish feed your brand with smart cut tactics proven to cast your original voice to the world.

All right. Hey, everyone. We are live Tom Hazard here with Tracy Hazard, and it is our weekly client coaching call. We have a fantastic topic today and I'm super excited for this episode. This is not your average coaching call.

No, this isn't really about coaching. It's picking Tom's and Tracy's brain and hear what we think about stuff. So this is a common topic that I get asked about all the time because I wrote for Inc. Magazine for four years, so innovation. So people would ask me and they've been asking me for years what I think of AI and that's what we're going to talk about today when you've.

Been really studying AI.

Yeah, I've been studying it over a decade now.

You've also been testing it?

Yeah, I absolutely have.

So we're going to talk about that. This isn't just in the abstract, right?

But I do want to quickly start our episode because it's our 200th episode today. We're recording and we're recording this live with all of you, so you get to hear that. So let's just jump right in, Tom, because this is gonna be a longer episode. I think we got a lot to cover, so let's jump right in.

Welcome back to Feed you'd Brand. I'm Tom Hazard along with my co host, Tracy Hazzard and better half. And boy, are you going to realize why she's my better half today in this episode. And before I talk about today's topic, I think we need a celebration moment. Tracy. Cause this is our 200th episode of Feed you'd Brand.

Woo.

Like I didn't even know that until.

I know I got the message from the team because we have a team who submits our episodes for us. I don't see the numbers until they publish. So we wouldn't have recorded knowing that in mind. We would. It just would have published and it would have randomly been episode. This one would be randomly be episode 200. But I got the message this morning before we recorded here and I told our daughter, our youngest daughter, that it was our 200th episode. And I said, we recommend that podcasters celebrate. What would you do to celebrate recording 200 episodes? And she says, have a party with cake, because that's like what 8 year olds think about. And I was like. And then she started going off and have confetti and let's have a funfetti cake. And then so she was just going wild with it. And I was like, this is what we all need though. That little bit of mindset shift to remembering that celebration is more than just acknowledgement of it. We also need to have a little celebration. Maybe a little margarita later. Or maybe we need to celebrate more. All of us do.

Yeah, 200 episode margaritas. You're on later. Let's do it.

The calculation though is that I personally now have tipped over recording a thousand episodes.

Personally. No, you've done much more than that.

No, I've recorded lots of interviews and all of those things, but I personally recorded and published over a thousand episodes myself.

I'm surprised it's that little, honestly, because we did 650 with WTF and you've had the binge factor. How many?

150.

We're about 100 and 200 here. I thought it was well over a thousand, but anyway, it's a lot, so that's great. All right. But aside from the celebration moment and thank you listeners for indulging us to do that. And I think all of you that achieve a milestone like that should celebrate and acknowledge it because it's significant achievement. Not your average podcaster doesn't get past 20.

Absolutely. And it's an accomplishment.

But we have a really fantastic topic today and message we want to share with you, all of our listeners. And this is meaningful. Pretty powerful stuff. Did you want to say something, Traci, before I reveal the topic for today?

I did. I wanted to say thank you to you for being my co host for 31 years. Because as we're recording this, it's not only our 200th episode, but it is our 31st wedding anniversary. And so I wanted to thank you for being my co host all along the way and the fact that you indulge my interest in some of these unusual things like what we're going to talk about in our topic today is one of the reasons I married you. Because we love to have conversations, we love to have mind share and thinking about these innovative topics. And so that's one of my favorite things about being married to you.

Well, very much I appreciate it. The feeling is completely mutual. I have to tell you, I could never have recorded 650 episodes of a podcast about 3D printing with without you doing. And honestly, for me, co hosting podcast is a lot more fun. Not that I don't get a lot out of podcasts that I record that are just me certainly do and I enjoyed providing that value to others. But no, doing this with you is the great pleasure of my life. And being married to you for 31 years, honestly, I still feel like a teenager. I don't. I can't believe it's been 31 years and we actually met when we were teenagers. Just in case y'. All.

Yes, I was still. I was 17 when I met you.

You were 17. I was 18.

Let's get on to providing some value to our listeners today. We'll celebrate more later, but this topic is really exciting. I've been looking forward to recording this episode. Today we want to talk about why using your own voice is more powerful than AI generated content. And why are we talking about this today and AI generated content in general? Because it's really happening all around us. A lot of you may not realize it, but Tracy's been studying and researching AI for a number of years and testing it. And then we've been doing some more testing recently with the emergence of ChatGPT, but I'm getting a little ahead of myself. Tracy, I want to throw it to you to lead us in this discussion because you truly are our resident expert.

In it, and I wouldn't consider myself. This is new territory. And so one of my favorite things to do, and this is something that Tom and I, and the reason why we brought up our anniversary and our milestones, is whenever we hit an anniversary or milestone, we really start looking at what's next. This is our opportunity to talk about the future. And so I've been considering for some while what is the future of podcasting. And there are lots of people who say the future of everything is AI, artificial intelligence. And I've been looking at that, saying I'm not so sure. And I like to look at everything with this sort of slightly skeptical view. I think it helps me be a little bit more objective about figuring out the best way to use something when I approach it from this skepticism standpoint without sticking my head in the sand and saying, oh, AI is never going to happen, or this is never like those people I don't believe in at all either. So, like, we look at innovation from the standpoint of it's highly unlikely for it to take over the world like people believe, because that just doesn't happen. Very often in innovation in general. And it's a whole lot slower usually than everybody imagines it will be. And look at it today. What we were just talking about, our 3D print podcast, which kicked off everything that we do here. That 3D print podcast, they predicted that everyone would have a 3D printer in their kitchen, in their house, in there somewhere. How many of you have one?

They predicted it would be like by now. Yeah, by now everybody would have. Which it's not.

It's not the way it goes. And so we know that because we've worked on so much of this disruptive technology over time. So having skeptical view of things helps us understand of where the roadblocks are. When we get to like, big proponent of something and we just jump on the bandwagon and we just go on it, we have a harder time understanding how we're going to bring everybody along with.

I think that skepticism can be healthy, but at the same time, I want our listeners to understand we have really dived into this technology and we're not just talking about it and being armchair quarterbacks here. We've been testing you in particular, have been testing AI with your podcast for a couple of years because others have come out with AI that was supposed to help with generating highlight clips automatically and things like that. Tracy, you've been testing stuff for a couple of years and really found unimpressive results in the past.

And I'm going to just gloss over that a little bit and I will. We're going to do a future episode. Not probably until a couple months from now, but we're going to do a future episode because I want more time testing out ChatGPT specifically because it's only only been testing it. It's only been available really to most people for about a month, and it's had hit and miss access. For some of you, you make a login and it's too busy, you can't access now. So it's been like that for me as well. So I haven't gotten as much time on it as I would like, but I have spent a lot of time on other AIs and testing them out. And I'm going to provide some future guidelines as well as discussions of some of those different types of AIs in a future episode. But for right now, we're really going to be focused on why ChatGPT is changing the game a little bit. And that requires a slight history lesson. So if everybody will indulge me for a moment, and hopefully it's going to be really understandable. So the next time someone asks you, like, what about this AI stuff in podcasting, you have this, oh, I know all about this. And you can recite what I'm saying here or summarize it, right? But most of the other AIs have been based on a couple of different technologies. One of them is DeepMind, which is Google's version of things that you maybe have heard about, you may have seen tests about. ChatGPT is the third version of something that's come out from this whole group called OpenAI that I'm going to talk about and give you a little historical context. So we've been seeing some things that are building off it. And there's a bunch of other smaller AIs and other AIs that have been created in time. And so they are to truly be the artificial intelligence that ChatGPT is, it needs to learn. So it doesn't just need to automate something. Let's be really clear on here. There are artificial intelligences. Intelligence psi. I don't know. I don't think that's. How about.

I would say there is artificial intelligence that does this. Okay, so maybe that's the way it's plural.

As is. I don't know. Anyway, there is artificial intelligence that automates things, right? We consider every time we see a chatbot, we think it's artificial intelligence. But the reality is it's all programming pre programmed to follow a path. So that's really automation. I want you to understand the difference here. That's automation and not that it's not smart and it's fantastic and it saves us all time and energy and that's great, but it is not learning. So true. Artificial intelligence in this model learns in some way, shape or form.

And this is the big distinction, Tracy, that I definitely need to share with our listeners the way you did with me as we were talking about it, I think yesterday in preparation here about what that difference is, because it really. You can understand what the leap is.

Right. And so I'm going to touch back on this in a minute. But ChatGPT and GPT, I just wanted. So all of the GPT stands for something generative. Pre trained, Transformer, Generative, meaning it's going generations. It's learning, it's moving to the next generation. It's growing older, it's growing smarter. Right? Pre trained. So it has training wheels, guardrails, like some of those things on it, and they pre program some of this into it. Pre program where it gets its information from. It's pre programmed to do some of these things. It's pre trained and it's transformer, meaning it should take what it learns and where it is and transform that into something else for you. It should generate a result for you. Right. That's the idea of what it means. Okay. And it is what they call a reinforcement learning platform, meaning that it learns, but it requires someone to reinforce its learning, to give it feedback. And there are lots of AI out there that don't have reinforcement learning. They don't have a feedback loop. We call them AI, but there's no feedback loop in it. The transcription systems famous no feedback loop.

That's right. In fact, there are many different transcription systems out there that people use to transcribe their podcast audio for one reason or another. And they're often called AI. Or Rev.com has one called Rev AI and there are others also that do. And.

It'S a one way.

Flow of information right, from the audio to the transcript. And there is not a feedback loop which inherently limits its ability to learn.

Right. So just want to keep that in mind. That's this type, the ChatGPT. What makes it so interesting is how it's learning. It's reinforcement learning and that's a real significant part of it. Now there are many other, I mentioned before that DeepMind, the Google version, right. It's out there and it is a reinforcement learning process as well, but it has much tighter guardrails because Google owns it. Right. So it's privately owned. OpenAI, the company and the nonprofit. So it's a really weird structure. OpenAI is technically a nonprofit and the revenue generating platform that they're building is the for profit side, but it has one shareholder, the nonprofit. So it's an interesting structure. Now that the criticism that has come from who's invested in the nonprofit or who's. And they don't call it invested, they call it pledged because they've pledged the funds into the nonprofit. So as the nonprofit needs it, they use it. Right. The money goes in, it doesn't flow and sit in that like an investment does. Okay. Elon Musk, Reid Hoffman, Jessica Livingston, Peter Thiel, AWS, InfoSystem, Y Research and Microsoft. And then you have Sam Altman, who's the CEO and the, I'm going to say the Kickoff founder of it. It happened with a group of people, but he's a Kickoff founder and he's from Y Combinator fame as well, and Microsoft. And so all of those individuals, not Microsoft, but all Those individuals, including AWS, InfoSystem and Y Combinator Research, they came in with a billion dollar pledge. So they all pledged a billion dollars at the beginning of this. And then Microsoft came in and matched the billion dollars, which is an interesting change. And that happened. OpenAI is built on the Azure platform, which is Microsoft's cloud computing. It's like AWS or their version of it, but Azure platform, their cloud computing platform. And so it's really critically important that it's built on this hefty right now like they're gating this the amount of people on it for a reason because they don't want it to overwhelm the servers. They don't want it to overwhelm the space. Right. They want it to run and it requires a lot of computing power and heavy lifting to run AI. So that's part of why this is a real good test for Microsoft in the future. And so it's a good investment. And I think it's. I personally, my view of it is this was one of the smartest investments they could make make in the last decade. So a billion dollars seems like a lot of money. I think it's a drop in the bucket and I think they're going to need 10 times that in the near future in order to get where they're going. Their plan is to create. They call it the API. Not API or an API or multiple APIs. They call it the. And I'm putting air quotes here for those of you who are just listening. The API for all to use. And that is OpenAI's mission that the idea that this is open for all is what is going to keep AI from going terribly wrong. This is their idea to prevent the Terminator Cyberdyne systems. Cyberdyne system future. Yeah, exactly right. Like their idea is that OpenAI AI is based on the premise that in order to reduce the risk of a Terminator future, everyone should have access to the AI and it shouldn't be in the hands of corporations like Google. That's really, that's how they're going up against Google on this and but other criticizes that it's going to really go wrong anyway. The Internet still has the deep web. There's still the.

There's a dark side.

There's a dark side Cryptocurrency. Right. Like crime. Like there's a dark side to all of these things. There's always going to be. But if the majority of what it's being used at for good, maybe they're right. This is my view on this. I'm going to share with you in a minute but I just want to give you finish giving you the like broad brush history lesson on how this works. So DeepMind is their direct competitor. DeepMind is a London based company that Google bought in 2014 and DeepMind's actually a lot more mature than people think it is because it was already pretty mature in 2014 when they bought into. There's a lot of applications that they've already been testing using it, but there's been a lot of reports that Google actually scaled back because they felt it was too good. And so I can't confirm that this came straight from Google or not, but I'd be happy to link you to the article for what I read on this one that I think is probably a good indicator of what seems likely for them to find whether or not this is true and that is that. Imagine if your search on Google was so efficient and so quickly and got you to the perfect answer for you. Not just the perfect answer, not just a listing of answers. Are you going to spend as much time on Google as you do now? Are you going to get served up enough ads? So if the AI works right, then they lose money because majority of Google's money comes from advertisement.

And this reminds me, Tracy, I spent or you and I both did actually spent about two hours a couple days ago on the phone with someone who we regard as an expert in so many things, tech. He's an ethical hacker I think is a good way to talk about him or describe him. And he thinks that within a couple years this AI, whatever ChatGPT becomes will fundamentally change Google, if not kill Google. At least the way they're doing business.

Today, yeah, it's going to harm their business model. So rumor is that they already have it. They already know how theirs works. It's so good that it would harm their business and so they're trying to figure out what to do with it. So bringing out ChatGPT is really smart because it pushes them to have to figure this out faster. So I don't think you should count out Google. That's just my view of the world. Like I don't think you should count a company out like that has that much to lose who already knows what this can do. It's not like they're seeing someone else do this for the first time and they're like oh my goodness. Now there's a lot of benefits that ChatGPT is amazing. But we don't actually know how DeepMind works because it's not actively in use so you can't play with it to.

Know or it's not publicly available.

Not publicly available. So like it could be great. It could be just as good. Like we don't know. But rumor has it that Microsoft is prepared to put this into Bing as soon as March of 2023. So depending on when you're listening to this, it could be after and you could already be seeing its effect on Bing. And I think it's really smart Tom. And this is what I want to really say is like Microsoft's business model is extremely different from Google's. They don't need advertising dollars, they have arrangements with Apple. That's the Bing is the search that Apple is based on for some of the searches that they do. Really Alexa, what do you mean?

Bing is search is based on Bing.

Some of the searches that they use underneath things to give you answers like.

Weather and like in Safari stuff. Because I knew that was true of Bing is the search engine underneath Alexa, aws, Amazon.

Right. So some of the searches are what I'm going to call more enterprise level searches. So in order to get you an answer on this, your phone is actually tapping into a Bing search to get the current results. So it's a more at this API enterprise level. It's not on a. I'm getting served up an ad because I'm using the Bing search engine like Safari or Chrome or like something like that. Right. Different. So Bing's model of business is a little bit more enterprise focused otherwise they would have killed it long time ago. Like why would you keep using it?

Yeah, because Bing is like a, I think 1% of Internet searches if that.

But that's using Bing as your search engine solely not running underneath it the searches. So now if you speed that up, you improve it, you're efficient with it. Can you imagine how much more money you'll make in enterprise solutions because you.

Already have your hooks into all these other devices and systems that use it. Pretty smart.

It's pretty smart. Second thing is that it's also a lot more. It's very efficient and has a lot more mobile basis. Right. So when I search on my phone I am less likely to spend more time going down a rabbit hole than I do on my computer. I'm not going to go through everything on the first page of Chrome or which is Google based product for those of you who don't remember. But I'm not going to go Google something and then spend hours going through the first couple of pages of it. I'm going to click on the first thing that's there, I need an answer quickly if I'm on my mobile device. And when you're wrong, I'm annoyed. So Google gets the brunt of me being pissed off that they gave me a bad answer. So I want a more accurate answer. And this is where AI can be much more useful in the search process. And if Bing is delivering those on a mobile device, then now we have a much better shot of being a better answer. And if I ask my Alexa device for an answer and she gives me the best answer for me, because she's learning me, she knows me, our whole household will trust that faster, and we'll continue to reinforce and use that in a better way than we would any other device to get an answer. Okay, I just did it today. I was checking Greenwich Mean Time against our local time, and I asked her, but what she didn't do was give me the time zone in Pacific time. She didn't give me the specific time I asked for. She gave me if it's noon in.

Greenwich Mean, it's four in the morning in California. Yeah. She didn't tell you what time it is now, but I think maybe the way you asked the question was different. But. Okay, this gives us some great background on ChatGPT and this AI. Let's get this to where our listeners can really understand why this is so next level.

So here's the thing about ChatGPT is like the third version of things that has come out from OpenAI. So they've generated other ones that didn't work as well as this one does. There was lots of criticisms about them. There was lots of issues with giving, like, stupid results. I call it the Amelia Bedelia Results. Like, so for those of you who don't know Amelia Bedelia's children's book, but it was Mike. I hated that book as a child. Absolutely hated it. I didn't understand why people would read that she's dust. Why would you be so literal about something like it? Never understood that. And that kind of indignant attitude is how we get to these AIs. We think they're stupid because they take our questions so literally. They don't get us.

It's interesting the way your mind works. My mind works. It's very different because I thought those books were very funny as a child. They were read to me as a child because it deals with nuance, plays on words, really, and puns, if you will. And I always thought those things were.

Very funny, but I was like, she should be smarter than that. She should get us. This is how we approach our AI. We look at it and we think, if they don't get us, then it's not right, then it's not gonna work, it's never gonna make it, it's never gonna happen. And that's what happens. So there's like, things like, it's like, what would happen if Christopher Columbus discovered America in 2014 or discovered the Americas, and he didn't discover the Americas in 2014. So the AI has to be smart enough to know, say, hypothetically, if this happened. And that's what they don't do. Instead, they go through and they give you this historical. Exactly like what happened, but it doesn't make sense in 2014. This is how those previous AIs had been tested by others. So then what people would cite about it is the criticism of it is that it's not smart enough to know that you shouldn't answer these questions in that way. You should approach them from a different way. And you end up with sometimes very controversial results, very racist results, very sexist results, because they're based. Taking something historical and stuffing it into.

Current day as an answer, which isn't really very helpful.

No. I think there's a lot of criticism about ChatGPT and about OpenAI being. Having too much guardrails, having. Being filtering out sexist and racist results, being too leftist in its viewpoint on the world, too politically correct, if that's the way you want to say it. And here's the thing. I think my view of it, it is just my perspective on it. I think that they had to do that. They have to do that, because otherwise the conversation is about the racist results that it puts out and not about what it potentially can do and what you do in the process of talking only about the controversy of it, because that's what people are going to go in and they're going to test things out. What do we do when we get the Internet? We look for sex. What is that song from Avenue Q?

Oh, like something about the Internet is for porn? Something like that.

Exactly. So that's what people go to try and do. So if we did that with this, then that's all we're ever going to talk about. And it hurts the future investment dollars. And ChatGPT is nothing if not a shot across the bow to the entire industry saying, we're where you should be investing your dollars. You should be joining our network. You should be joining OpenAI's nonprofit. You should be a part of the future. That's what this is about. It's about bringing in more dollars into it, because if more dollars happen, it's going to proliferate everywhere and it's actually going to be a better AI at the end of the day. But if we leave it in this conversation about the controversy, we never get to its potential. And so that's why I believe they did it. They didn't do it to be leftist about this. They didn't do it to be. To be politically correct. They did it because you have to remove this from the conversation, because for a decade now, that's the conversation around where AI has gone terribly wrong in. So let's remove it from the conversation. So that's what they did. So that's one of the criticisms that you're going to hear lobbed against it. So I think this was necessary in order to prove where they're going with it and its mission on what it can do. So you can see it's really great business potential for yourself. So, ChatGPT, the reason it's so brilliant is that it is based on this reinforcement learning.

What does that mean? Tracy, can you give us an example?

Of course. It means that I ask an AI to generate a transcript or I generate a headline. Let's do it with headlines. Because I do this all the time. I use the AI to generate headlines for articles. So we. It generates a headline for me based on my copy, based on what I give it, based on it. And I don't like it, I just don't use it. That's what happens a lot of times. I just don't use it.

And so that isn't what I was.

Hoping it would be.

Right.

Sometimes I might like refresh. So at least I'm telling it. You didn't give me the result the first time, but it doesn't know. And if I take the copy and paste that headline out and then go use it in my blog or go use it on my podcast title, they don't know I used it, they just know I stopped. So all the headline tools I've ever used have no feedback loop because it's not happening within the system.

So how is ChatGPT different? What did you do differently when you were testing it?

So ChatGPT built this in for it. So not only do I say I wanna regenerate a new response, I type in a chat, telling it what's wrong and regenerate it. So I say the headline's not emotional enough, I would like it to have a better tone, or I would like it to Be more excited. And I would tell it those things and then say, regenerate. So now it's learning what I didn't like about it naturally in conversation with me.

So you're actually communicating in ChatGPT with ChatGPT, providing it feedback, asking another level of depth of question or asking it refinement. I remember you told me at one point you said, hey, I want it to have more energy. Or you also used it in a way where you said, I want this to read like it was said by a Hollywood announcer or something like that. You give it some context. Context.

I gave it context of what I was looking for, and then it generated a new one and it gets better every time. That's fascinating. So they've built into the process a way to encourage us to do the feedback loop because humans are inherently lazy. So when we don't get the results we want, we just don't tell anyone. We just move on. Very often, unless it was so offensive, we complain about it. So when something's right, it doesn't learn that it's right and it needs to learn the reward that this was correct, that I liked the results. So they also have an upvote and a down vote. So encouraging us to say this was good and I'm moving on, right? And I'm taking this and I'm going on to the next thing. It wasn't. This was bad, and I'm giving up. I downvote it. So it's giving you that thing that happens in Reddit. That's a Reddit thing. If you guys are users of that, that they upvote and downvote things. But by naturally encouraging the conversation, I'm telling it where I want it to go, why it wasn't good. I'm getting it to refine it and really quickly so that the next time. So this is what happened to me. So I tell that. I tell it. The headline's not energetic enough. It interprets what I meant by energy. I tried not to give it a specific direction. So then it's. It gave me some energy. And then I said, okay, I want it to have positive energy. I added that word because I thought it sounded a little like it was energetic, but it was a little harsh. And so I wanted to have positive energy. It reworded it and it was perfect. So I clicked the upvote and I took and I moved on. The next time I typed in and asked it to do a title, it automatically gave me positive energy because it know it learned what I wanted and it starts from that place and continues on.

So you have a chat that is ongoing within.

Right. So we're going to talk about how to use these things in a good way in a future episode because it's a whole conversation about how I use this and what I do. But essentially I'm doing all my headlines in one place because I know it's going to continually learn. It's something I learned because I recommend to all of you the CO Schedule headline tool, which I really like. And it has these terminologies emotion more energetic. It talks about them in how it keywords them and how it uses it. I bet you anything OpenAI knows about the cogital heads line tool and is learning it. So one of the things that I just want you to be aware of is that the OpenAI platform and ChatGPT doesn't have anything after 2021.

So that's one of these guardrails they put on it because they had to limit the data set, is that right, that it used.

I think it's not because of that. I think they don't want it to inadvertently have an influence on current politics or something currently in the news, the war. Like it doesn't want to inadvertently do something that's so current in information it could have an influence on what's happening right now. I think it's a guardrail from that standpoint because they don't know what people are getting. The whole point of putting this out is to see what people are going to use it for so that they can develop an API that makes sense. The API that makes sense, that's what they're trying to figure out, is their business model for it. So that's what they need for this. So that's one of the things that I discovered in this process of using it, is that it's brilliant and it's conversational because the other AIs can't get you to tell you that you disliked it, you didn't use it. It doesn't learn enough when you don't have that training built in. And in this conversational way, because I was confused, why do you want another chat? I didn't understand that before I got in to use it, but I understand because of this reinforcement learning process that it's really actually for us because we won't do what they need it to do, our share of the feedback loop. We won't do it because we're too lazy. And by creating this conversation, it makes us do it in a way that was very comfortable and easy for us. So that's how it's going to get better and better. And it's why it's so impressive, because it also does interpret what I'm saying. It doesn't do this thing where it's not interpreting what I mean by energy. It makes an interpretation. It doesn't give up. It might get it wrong. So then I tell it what type of energy I'm looking for and I refine it. And now next time it does it right from that standpoint. So it's going to be really interesting to see how it keeps playing out the more I play with it, how much smarter it is. And this is what I found with almost all AIs that I played with before. They actually get worse over time.

Let's explore that because I think it's important. And this is where I think there ends up being some good news for creative types like podcast that we want to end on that positive note when we get there. We're not there yet. But why? Let's talk about why other AIs have that problem.

So a lot of AIs are based on pulling the most common pieces of information that are out there. So think about it as like Google's taking the more is more model. So if more people are saying this out in the world, then it must be right. The AI is not making a judgment call. The search isn't making a judgment call on that. Google eventually had to put in authority value. Just because people are saying it doesn't make it the right answer. So how do we weigh expert resources heavier than just the general public? So we get real health information or we get real weather information from the weather bureau and not from the guy with the binoculars next door. It just where are we getting real weather? So like weighing your sources of information, right? Become it. The problem is when something's brand new. And this happened to us in our 3D printing world. Things were moving so quickly in 3D printing that Google couldn't keep up with it. One out of every five searches in Google has no results that it could do because it's so brand new. 20% of search is something Google's never seen before.

Yeah, searches. People are searching on so many different things all the time, every day. About 20% of what people type into Google. Google's never seen that exact search query before.

I think it's astounding that it's that high. But what it shows you is that things are changing so quickly and we're looking for answers and we're looking for Customized answers to us. So that's why it's not the same. What I type in isn't the same as what Tom types in. So our queries are all also diversely different. And that's cool. That's a really cool, amazing thing about human beings. And so if our technology can't keep up with that, can't develop to that, where are they going to rely on their resources? Right. So remember that ChatGPT and OpenAI is pre trained, so it's got its sources for some things, but other things it has no source for it at all. Where is it going to find thought leadership in this case? Like on 3D printing that we were talking about thought leadership on 3D printing, Google was looking for this. The OpenAI ChatGPT is be looking for something like that, of course, and probably another topic because 3D printing is a little old at the recording of this, it's a little bit older. But what we found when we were doing our podcast was that our podcast was so much faster and more current than articles and anything else that was coming out in the market. And because we were blogging them, they were in a written, searchable format for Google. And so when some new question was asked of it, Google would send us the traffic automatically, assuming we had the.

Answer or because we were the most relevant thing that existed. Even if they couldn't find exactly what someone was searching for, Google really rarely provides you no results. They'll provide you the closest thing it knows of. Right.

And it will provide you the most credible resource for getting the answer if they don't see it readily apparent. So they are saying these people have a podcast they publish every week. They're likely to cover this topic in the next week and we don't know it yet. So let's give them the traffic. So that's where you get authority value and you're getting authority on the idea that Google sees you as a thought leader that they're looking to for answers. And they're going to be expecting you to give that to people. So now you're in a thought leadership position. But very often most websites are built to pull that information from other resources. The news feeds pull in information from other places from other and from their chosen sources from those chosen places. So almost every article's written, citing resources. Right. Or citing a quote from somebody so they're not coming up with the original thought in almost every other place. Videocasts, podcasts are uniquely suited for that thought leadership position because what happens when they're pulling information from the same old places. And everyone has those same. They're just using the same old places. What happens, Tom?

Oh, so this is what happened. Right. With earlier versions of AI is without that feedback loop, whatever people are typing into it, it's basically thinking. Like you said, more is better. Whatever there's more of is what we'll give back to people. And it wasn't capable. And AI is still not capable of original thought. Right. It's only capable of providing you things that it knows of and that exist.

And so it might be original to you. Let me be very clear. It might be something that's outside your perspective, something you don't have the resources to see, but that doesn't make it still group think at the end of.

The day, which is the opposite of thought leadership to me. Yeah, when we were talking about this, I was saying, really, it sounds like.

Thought followership, which is 90% of like TikTok and Instagram out there. They're. They find a tip somewhere and then they reiterate it in their own way. And they might be doing it in a creative and fun way and they've got their followers, but they aren't the thought leaders. They didn't originate those ideas. Thought leaders are very rare because they require a different mode of thinking, and it cannot happen in AI. Someone has to lead that thought. So now the thought leaders are going to become the future value for that AI to tap into, to find out what's new, what's happening, what the thoughts are on this process, and then start to group those thought leaders together and say, is this a good path? Does this make sense? Is this going to happen? So we're going to see a lot of that occurring. So your thought leadership and the fact that you're putting it out in podcast and videocast consistently and constantly is the way to play with AI in a really great way and make sure that you are a part of that conversation in the future. That's the power of that original voice is going to have. The other side of that is in an AI generated world where I don't know whether or not a bot generated this or a human did, while there are deep fakes of videos and deep fakes of voices, almost all good technology can detect that. We can see when it's a fake. We can see it's in the audio pattern. You can see when it was faked with. So there are ways for even AI to tell if something's a fake or not. And there are ways for Google to tell if something's A fake or not. But when you're showing up on camera and you're showing up with your voice, and it really is truly your voice and your face, that in and of itself is where more reward is going to happen than using AI generated stuff. So that means that there's going to be a downgrade in copy in blogs, in other things that don't come from voice generation.

We see there are a lot of AI tools being advertised, being talked about that will generate a blog post for you in no time. Why write it the hard way when this tool can generate a better blog for you very quickly? And it certainly can. There are lots of them out there doing that. But again, they're only able to create these things from data that it knows already exists. So how original can that be? And there's a danger in all sorts of potential issues around copyright and other things that. But also more importantly, in the eyes of the Internet, just not being original, not being a leader. And so I agree with you, Tracy. I think this is actually very exciting and good news for podcasters, right?

I think right now we've been seeing a lot of reports and there's a lot of regurgitation off of the reports saying that there are a poor economic outlook. And Tom and I just did an episode a couple of weeks ago about the, our view of that and we think they're wrong. We think that they're only looking at the podcasting market for what's less than 2% of the market, and that's the ad based market. They're not looking at the ecosystem altogether. All of you, especially our followers, the ones who are using podcasting for business and thought leadership and those types of nurturing of community and those things cannot happen by a machine. Those things happen from humans. And that in and of itself are why I think the economic outlook and in an AI driven world is completely underestimated for podcasting and videocasting. And long form, not short form. Let me be really clear on that one. I really think that there is. We're being sorely underestimated there. And we're going to find that those of us, it's like all along, over the years, Tom and I, we've had websites with blogs for a long time, for over a decade. And every time there's what they call a Google slap, where Google changes its algorithm, our website, more traffic. And we kept getting that. And there we were, astounding, some of this search engine optimized experts who were like, you're not doing any of these backlink purchases and you're not doing any of these things. How is it that you are like outdoing every single one of these algorithm shifts? Because every single time the algorithm shifts have been happening everywhere, they reward the original void more and more. And that isn't going to change. I think it's only going to happen faster in this AI driven world when they find someone with an original thought, with an original voice, with original ideas, making those connections in our head that only humans can, are really great at taking all these pieces of information, synthesizing that and coming up with an original view on the world, on what you should do in your business, on how you can help people. This is how you sell your books, your courses, this is how you do all of what you do. Our lovely business podcasters who I adore out there in what you're bringing, your messages and your views on the world that you're bringing cheap doing it. All these other things are tools. They might make the technical parts easier for you, but do not lose your original voice in this process, no matter what that matters. That curation, that viewpoint, that perspective cannot be done by a machine, will never be able to be done by a machine in the way that you can do it now.

At the same time, Tracy, just to add a little bit to that, we're not negative or down on AI or ChatGPT at all. We're just saying, hey podcasters, you guys have something special. It's your message you're bringing to the world that is going to be recognized and valued. But we're really bullish on this AI and opportunities to save time doing certain things and allow more creative energy to be put in other.

That's my excitement about the AI market for artificial intelligence, to take away the mundane stuff that I don't want to do and be right about it so I don't have to overthink it either. That's amazing. Like I want that. Because what it does is it gives me more time to reflect, to come up with better answers for you, to research things and think about where the future is going to advise you in a better way. I have more time for all of you when I don't have to do those things. That's the beauty of that future world. That's what I'm excited about. And how can I harness AI to make every one of your lives better with my view and perspective on how to truly harness innovation to make everything that you do shine. That's my job here and what I will be concentrating on for the next year and a half on our use of AI within the company. And we are, we're implementing it. We already use it in various ways. And how will we continue to use it more? Only if and how we use and how we train it and what we do with it is only going to make sure that your original voice shines through, that your uniqueness shines through in that process. Because the big danger of AI is that everything sounds the same. And that's what I've seen in every other AI I've used is it gets. The more you use it, the more you realize they're giving you the exact same answer every single time, the exact same results. The headline's exactly the same with a couple of words shifted. It's the format for the description is exactly the same every single time. Right. We can't have that. That destroys the originality that you bring to the world. And we don't want that here. We want your original voice to shine through on top of the tools.

Wow, Tracy. All right. This has been a much longer episode than our typical, but I think it's a topic that really required that and certainly hope all of our listeners have gotten some wonderful stuff out of it. I happen to think this episode probably is going to be one of the most replayed episodes to go back and say, wait, what did she say about that? And what was the history part of ChatGPT? And so that's great. Please do that. We will take some deeper dives in niche aspects of this in the future as we have more to share. So, you know, if you haven't subscribed already, please do. And stay tuned for future episodes on that. You can see that.

Yeah, definitely. We'll be bringing you more, so definitely.

And you can find the blog post for this episode with some links to things that. That we've talked about. There's a lot of references here in this episode. They'll all be for you on the blog post@potatOise.com There's a feed you'd brand page there. Check it out. All right, thanks so much, everybody. We'll be back next time with another great episode. Until then, this has been Tom and Tracy on feed.

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