EP 124: 5 Ways Generative AI Shows Up in 2024

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Generative AI has taken 2023 by storm. But what about 2024? Right? As we enter the fourth quarter of this year, we're actually going to not reflect back in today's episode of what's happened so far, but we're actually going to look forward into what might be coming when we talk about generative AI in the year 2024. I'm extremely excited for today's episode of Everyday AI and welcome. If it's your first time here, thanks for joining us. So Everyday AI is a daily live stream podcast and free daily newsletter helping everyday people like me and you keep up with Generative AI but how we can not just keep up, but how we can put it to use for us. So if you are joining us live, thank you. Get your comment in what are you seeing in the generative AI landscape in 2024? If you're listening on the podcast, make sure to check out the show notes. We always leave links back to sign up for the free daily newsletter and to even join the conversation on LinkedIn. So before we get to that, and yes, please, please get in your takes right now, what are your questions? But before we get into it, let's take a look at what's going on in the world of AI news. So first, China's Beidou is coming for Chat GPT publicly, right? So China's new release to its earning Bot 4.0 from Badu, which is obviously kind of the China's equivalent of Google, they dominate the search market, but they are just releasing some new details on their Ernie bottom 4.0, again, kind of its competitor to GPT4 from OpenAI. So it should be interesting to keep an eye on what's happening with Beidou and earning bot 4.0, you know, pretty, pretty much they're saying out loud, yeah, we are competing with the GPT4 technology. All right, so New York City is trying to take the lead in responsible AI use. So New York City Mayor Eric Adams released his plan for the New York City Artificial Intelligence Action Plan, which is I believe, the first of its kind for a major US city. So with this they will also launch the My City business site, which features a pilot for New York City's first citywide AI chatbot. Interesting, right? Also in this plan, the New York City Artificial Intelligence Action Plan. That's a mouthful. It'll develop a framework for City agencies to carefully evaluate AI tools and associated risks, help city government employees build AI knowledge and skills, and also support the responsible implementation of these technologies. So pretty interesting to see. You know, New York was also kind of ahead of a curve, ahead of the curve in terms of applying, you know, different AI laws into hiring for the city. So also it's, it's going to be interesting to watch what happens with this NYC AI action plan. Last piece of news, AI is powering the economy. I talked about it yesterday, but here we go. We got another study to back us up here. So AI is powering the economy to the tune of $2.4 trillion. So a new report from venture capital firm Excel showed how much AI powered companies are actually leading the charge for the US economy. It showed that US Tech leaders, including Apple, Microsoft, Alphabet, Amazon, all the big players including Nvidia, saw their market caps grow by $2.4 trillion in a year marked by the rise of generative AI and obviously Nvidia's chips. So the economy I think right now is largely being powered by generative AI and what that means for our future. And speaking of what that means for our future, that's what today's show is all about. You know, talking about where we're going with Gen AI in 2024. So to help talk about that, I'm excited to have on the show today. And please help me welcome Josh Cavalier, the founder of JoshCavalier AI. Josh, thank you for joining us.

Hey, good morning, Jordan. Good to be here.

All right, so hey Josh, tell, tell everyone a little bit about what you do with JoshCavalier AI.

Yeah, so currently I'm offering online courses, workshops, coaching in around gen AI, specifically in the L&D area under the HR umbrella. So that's my flywheel. But I have been doing coaching with individuals outside of those boundaries, which has been extremely interesting because it's given me some ideas as far as what's happening in the industry. So that's where I'm currently at.

Yeah, love this. And, and again, I'm so, so excited for today's episode because it seems like every day on everyday AI, we're talking about things that have already happened and this is one of those episodes where, you know, talking, talking with Josh and I saw this and I'm like, oh, this is going to be good. But let's, let's start Josh and, and you know, you know, as well, maybe even before we get into the five different points, let me just ask you, what are you even personal, like personally excited about, you know, in the Gen AI world, you know, moving forward.

Yeah. I think the one thing that drives me is access and accessibility. What I mean by that is being able to reach more people with less input. In other words, like you're going to go ahead and create content and utilizing AI is either through accessibility or captioning or converting your voice to a different language, you're going to be able to reach more people. I know that when I create my content, it's very much usa, Europe, some of India, and that's about it. And in the future, I'll be able to reach the whole world without much lift. And I think that's amazing. And not only that, think about all the individuals in other countries who, via language barrier, have wonderful ideas. All that's going to be broken down. So I can't wait to see how that shows up in 2024.

Me as well. All right, well, hey, before we get into the list, which I'm so, so excited about, as a reminder, if you're joining us live, get your questions in for Josh. What do you want to know about the Future of Gen AI in 2024? And thank you everyone for joining us. Ben saying he's, he's joining us from Dallas as well. Kevin saying good morning from Atlanta. Monica saying the stream looking sharp. Yeah, we had some tech problems this week, so we had to, had to try to make this a little better. We had to get ready for Josh. You know, Josh coming in with the big, the big hits right now, but let's start at the top. Josh, what is maybe number one on your list of things that we're looking forward to in Gen AI for 2024?

Yeah, I think the big topic for 2024 is going to be data and the organization of data and how corporations and even individuals will go about collecting their data and leveraging it. And I know that currently, you know, a Gartner projection says that within corporations, 75% of companies are just sandboxing right now. But they are showing up in 2024. And the big story there is their data. If we think about like OpenAI and how they position themselves with GPT4, well, they're leading the charge because they have the best data. They went ahead and siphoned the whole Internet and leveraging it, a large language model and it's showing up. Think about Adobe and Firefly. What, what are they leveraging? They're leveraging all of the image data, you know, and all of the information that they have with Sensei and taking full advantage of the data. And so I know that with corporations with consumer data or customer data, like point of sale, I think one of the issues that may come up is customer privacy around data and the balance there. And so we're going to see as we move forward this aggressiveness of companies to collect the data to leverage AI, but then probably a pushback from the consumer. Like, no, this is a little bit too invasive. And I think we're starting to see that right now.

Yeah, Josh, the, the dork in me and the digital strategist is, is so happy that you said data number one, because it seems like companies think of this on the back end, right? They, they try to dive into gen AI and then they try to figure out data later. What's, what's maybe in your experience, one common mistake that you see companies making when it comes to their, their data collection or how they even use data when it comes to gen AI, I.

Think it's just dirty data practices. And let me clarify what that means. I mean, let's say that you're a frontline sales and you're entering things in CRM, right? You're going to go and check the box that you entered something in CRM. But everybody is entering the information in differently or they're using abbreviations or they're going in just not even putting information in, but the action is occurring. And so I believe that practices in around clean data data that is actionable is going to be the first step before even leveraging AI. Because why would you even build a large language model around inefficient or wrong data? That's going to be a huge issue and hopefully nobody spends the money to go ahead and put forth that effort and then find later on that they can't even leverage the model because the data is just incorrect or outdated.

Yeah, absolutely. And we talk so much when working with large language models and just generative AI in general, like, oh, garbage in, garbage out. But it's not just prompts, it's literally what you give to your model access to. So I'm so glad that was number one. Josh, what's, what's number two on our list?

Number two for 2024 is automation. And we're beginning to see that right now where, you know, you take applications like Zapier or Make and you can start seeing instances where individuals are not only leveraging prompt engineering, but they're leveraging additional applications and putting them in a workflow. We're seeing application developers implement generative AI inside their applications and collapsing down workflows and so automation of your task, whatever you do day in and day out, is going to show up strong in 2024. I bet for myself personally, every day I'm taking a look at the landscape of tools that are out there and my, my workflows, my personal workflows and, and it's impacted every day where I could go in and now leverage tools where I record a video and now the video is a transcript and I can take the transcript and put into an AI workflow and get five different outputs and put those into my channels. I would take hours and hours to do that in the, in the past and now it just takes minutes.

Yeah. And you know, Josh, I think that, you know, especially in the marketing and the digital world, for so long automation has been, you know, I won't even say a hot topic, but it's, it's been a requirement, right, for, for any, any business really to survive. If you're not automating, you know, you're really falling behind. But when we talk about, you know, kind of quote unquote stacking, right, because hey, now we're not just encouraging everyone out there to use all these gen AI tools and processes and systems, but we're also saying, hey, in addition to AI, you also got to keep your, your automation in there. You can't take it out. What's, what's your best, you know, some of your best advice for companies to balance that to, you know, because they might feel a little overwhelmed trying to dive into AI headfirst, but saying, hey, you got to keep, and maybe, you know, improve your, your automation as well.

The first thing is just documenting what those workflows are either at the individual contributor level or if it's external to the customer, what, what does that look like? And once you analyze those specific tasks, you then have an easier go at it. When you look across the landscape of tools and AI accessories and apps that are out there as far as what can we try? And it has to be low risk because the landscape is changing daily. In regards to AI tools. I would look for automations that are going to have the biggest impact on top line growth or the bottom line and your own personal productivity. You know, again, you know, you have a lot of individuals out there that are trying to leverage AI, document your workflows, be pragmatic, like really look at tools out there and try a few different tasks with AI and go, yes, this is going to save me hours here, let me go and implement that in my workflow.

Yeah, literally that, that step that you said there, Josh seems so simple. But it's also that so many, so few people I believe are doing it, like documenting their actual workflow. It's something I tell people all the time. People are like, hey Jordan, where do I get started with, with AI, it's like, all right, well where do you spend your most time manually, right? Like what's your processes? And sometimes that gets people scratching, scratching their head a little bit. Right? And hey, just, just, just as a reminder here, you know. Thank you, Brian. Brian says hey, for, for automation look at Task magic. What's, what's all, what's your guys's best recommendations for, you know, the two things that Josh has talked about so far with data automation and just what are, what are you all looking forward to in 2024? So hey, as a reminder, we have Josh Cavalier here, the founder of JoshCavalier.com where. Hey, we're sorry, Josh Cavalier, A.I. so what's, what's our number three way that Gen AI is going to show up in 2024? Josh?

Personalization that is going to be huge. And I know that a McKinsey report came out and said that 70 of consumers expect a personalized experience. AI is going to drive that. And I know that I have seen examples in the last two months that have just blown my mind honestly in regards to call center activity and how AI is going to completely automate call centers to the, to the point where somebody on the other line really doesn't even know that it's AI. And I know you probably have seen some of these demonstrations too. But you know, it really comes down to having the consumer or having your audience have the type of experience where it's meaningful to them. And AI is going to allow us to go ahead and personalize all these consumer based interactions or you know, whether you're delivering any form of media that personalized touch. And it can get down to like accessibility, even something that's a barrier like creating really good closed captions or open captions burned into a video. It's just kind of time consuming really. But AI is expediting that and allowing that personalization in there, whether you want to have your audio on or off or anything like that. So, you know, it's personalization of experiences out in the marketplace. It's personalization of media and I think we're going to see it show up big in 2024.

You know what, I could talk about this one for hours, Josh, because I feel there's two sides to the Gen AI coin. One, I Think it's going to help people in companies who truly care about the message that they put out there. It's going to help them do an even better job. But for those companies that maybe didn't care as much, or maybe they don't have the resources, or maybe if they're just looking for a shortcut, there's another side to that gen AI coin, which is putting out a lot of mediocre content at scale or a lot of just kind of, you know, not hot garbage, but medium garbage. Content at scale. But personalization, I think is so important because as consumers, I just think that we're going to be bombarded with more content than ever before because of how easy it is to create. Which makes then, Josh, the personalization part key, right?

Yeah.

How. How would you recommend a tool or process or what?

Yeah. Noise and the content creation, that's garbage. There are going to be amplifications of content. AI generated content because people understand how to be storytellers, they understand their craft, and they're going to go ahead and separate themselves from individuals that don't understand how a channel works or how to get a certain piece of content out. And so I think it really comes down to individuals that already have these skills of storytelling and putting out great forms of media leveraging AI. They are going to stand out in this, you know, this arena where there's just tons and tons of content. And, you know, I think really the crowd decides, hey, who's going to be up on top either through likes or, you know, pushing or driving a video forward in a channel. Yeah. So even though AI is going to generate a lot of noise, I still think you're going to have exemplar individuals out there creating amazing content. That's still going to resonate.

Yeah. I think being able to resonate and understand your client, I think is going to become more important than ever before. You know, I think in years past it was more of, you know, getting like, categories or buckets of, you know, your ICP or, you know, like, whatever acronym you want to throw out there. But you say, oh, here's our five, you know, customer types. Let's go after them. I think now you're going to have to say, here's our first 50 customer types, because you have to be that much more specific and, and more personalized. Right. Like, like Kevin here saying personalization. Totally agree. How about personalization of medicine? I. I don't know about that. Like, so here we've. We almost every day in the newsletter, there's Something some new news in the medical space about. Yes, personalized medicine going to the, even to the DNA level. So it's extremely, extremely use. Fascinating use case for sure. All right, let's, let's get to next on the list. Josh, what is our number four thing to look for with how generative AI is going to show up in 2020?

Sure. Number four is multimodal. And so what I mean by that is we just saw GPT4 Vision come online and accessible to the masses. What does that look like? We're going to see different kinds of workflows in all aspects of work with multimodal. I know that for myself, the first prompt that I used an image was a slips and falls image. It was a picture of a mop and a mop bucket, but just back behind a door there was two feet sticking out. Obviously somebody just fell. Right. I upload this image and it was shocking. It like went ahead and it knew exactly what was happening and it knew that somebody fell. And then I use that to go ahead and create some multiple choice questions and a video script and all kinds of different outputs around that specific event. Think about individuals walking around with a phone. They see something happening in their environment, their work environment, they take a picture of it and they're like, am I really seeing this? Like, should I be concerned about this? And AI is going to be right there to assist them and give them some background as far as a situation, a piece of equipment, anything like that. We haven't even thought about those workflows yet and how that shows up and how companies can leverage that technology. And so I think with multimodal, just not images. Right. So we're talking about being able to talk to ChatGPT, we're talking about uploading videos or taking text and having an output to a video. So you have all of these various multimodal workflows that are going to show up, that are going to reveal new methods of work, new methods that we can show up for our customers. And it's going to be just eye opening because you're going to have, this is going to be this massive period of experimentation that's going to happen that's going to reveal all these new ways that we can communicate and that we can interact with each other.

Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website will help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Gen AI. Yeah, you know Dr. Dr. Javi Castro saying he's been calling 2024-Mimodal. Yeah. I think a lot of people, even since November, right when Chat GPT was first introduced, you know, to the masses, I think people were like, okay, this is cool, you know, inputting text and getting text on, on the back end is great, but what about inputting photo video sound? What about on the output photo video sound? You know, even, you know, Josh, I'd love your personal take because you know, you talked about OpenAI and chat GPT just released their kind of, you know, quote unquote vision functionality over the last couple of weeks. But then you've had other companies, you know, Microsoft, Bing Chat has had certain functionalities. Google Bard has had certain, you know, kind of multimodal functionalities. How, how are we going to see it all come together? Or what is that magic recipe of getting the multimodal right? Because you know, it's been out there now in the wild for many months, but it still doesn't seem like it's just hitting just yet.

Right. I think the one issue is hardware, it's scaling. And so, you know, we have this period of time where everybody wants the Nvidia cards or people are trying to create Tensor chips and there's all this activity happening in the background. You, we still won't realize the full potential of multimodal at scale until we have hardware at scale that can support all these various types of outputs. And I think that's a reason why you start, you see like the appetizers of multimodal out there. It's not like the full course dinner. So it's a tease. And I can kind of premeditate how it's going to show up, but I still yet like for instance, just in GPT4, I can't use a plugin with an image upload and other multimodal type functionality. It's just kind of like cherry picking. What kind of option am I going to use on this prompt? And so I think we're going to see a maturation occurring once the hardware and the server farms are set up in such a way that can actually handle the true output types that we want.

Yeah, you bring up a good point. And even if we're just talking about ChatGPT, like, one thing I would personally love to see, Josh, is like, yeah, we have these great kind of multimodal options now within chat GPT, you know, you have your, your DALL E3 inside chat GBT. Yeah. And then you have your ability to, you know, kind of use, you know, your voice and, and to upload, you know, photos. But they're all in separate modes. Right. So I keep thinking like, oh, is this right now as we have it truly multimodal? It's like, I'd say probably not because I, you know, in, in my opinion, one of the best use cases of Chat GPT and I talk about it all the, all the time. One of the most untapped things right now in the business world is using Chat GPT with plugins. But at least right now you can't use Dall E3 in the, in the plugins mode and you can't use the kind of the new Vision feature in the plugin mode either. What's your take on that? Is that like that as a big, as a big miss or, you know, maybe it's just more of a feasibility and software engineering feat that would require more.

Yeah, so I mean, I think, I think that aspect of it needs to be worked out for sure. Like, you know, as far as, like from an engineering standpoint to get all that squared away so that you can expedite the content creation process. But I think in the, in the meantime, what we're going to see, and I was talking about this where before we got on the show is a good example of how multimodal shows up is in the tools that we use day in and day out, like PowerPoint or. I was, you know, the example I was telling you about was Adobe Captivate and I saw an amazing demonstration at a conference a few weeks ago where they have a tool called Adobe Captivate where you can go ahead and just simply prompt in a topic and some learning objectives and it builds the entire course out for you. Perfectly laid out. But here's the thing. They're also leveraging Adobe Firefly to generate the perfect image for that content that's true multimodal. Like, we can go in and we can orchestrate, you know, individual bits of content from a multimodal standpoint, but it's when we have applications that leverage true multimodal experiences and allow us to go ahead and create content at scale, that's really good content. Man, that is a massive game changer because we're just like, we're playing in the minor leagues right now. What I saw was major league. And I think that we are on the cusp of a period where an individual is fully empowered to create the content that they envision, but they never had the skills to do it. And so I think that is, that that's the true look of what multimodal is going to be and how it shows up for us.

Such, such good point. Yeah, Josh, Josh has some great insights. You know, with Adobe, he had some, some things going on with them. And hey, as a reminder, we've hit this list very hard. And if, if you maybe joined in the middle or if you can't keep up, maybe you're, you're also, you know, drinking your morning coffee, doing the dishes, whatever, don't worry. Go to your everydayai.com Sign up for that free daily newsletter. We're going to be literally hitting these things point by point in the newsletter. So don't worry if you didn't catch up because we, we are now at our final one. And just to quickly recap, Josh, that we had, number one, data. So these, these are the five ways Gen AI is going to show up in 2024. So number one is data. Number two is automation. Number three is personalization. Number four, which I just took us on a side rant on, is multimodal. And then what is our last. What is that number five, Josh?

Number five is prompt engineering. And let me just say, prompt engineering is dead. Long live prompt engineering. So it's been fascinating because I know that with my peer group, I have a lot of peers that say you won't need to understand how to prompt as you move forward. And I think there's some truth to that. You know, the more I get into it and the more I see what's happening with applications. There is a balance that's going to occur as we work with AI. You're going to get guidance in regards to prompts. And I see it right now in Adobe Firefly. I see it happening now. When you do a dolly image, you might enter in five words, but behind it is a prompt that has 20 words. It's going to guide how the image looks. I get it. But going back to point number two of automation, if you truly want to have agency, if you truly want to have autonomy, prompt engineering is still going to be in play in 2024 because these models change. And if you want to have, again, empowerment of your output, empowerment of your automation, you still will need to understand how to prompt engineer. Like, you'll need to understand the model itself. And then based upon the words that you give it, the output types that are coming back. And if you don't understand that, well, you lose agency. You, you are now the tails wagging the dog. At that point, you are asking the vendor, whoever's creating this tool, to basically do the prompt for you. And I see this with prompt as a service, right? There's a lot of tools out there that are prompt as a service, and you're leaning on them for the prompt. Now, some tools I use have prompt as a service, but they allow you to use your own prompts. So when I do a video, it gets transcribed. I can then leverage my own prompt to go ahead and create the educational output types that I specifically need. Very, very detailed, saving me tons of time. It's these other tools that are out there where you're leveraging on their prompt, and it's just okay, right? So I think prompt engineering is going to be important in 2024, but it's just going to show up different for everybody. It depends upon, you know, your. How you're comfortable with technology and whether you want to go down that road or not.

Yeah, it's. And let me, let me even hit rewind, because I think some of our audience, Josh, is, you know, following us. Some at this one might be scratching their heads. So I'll maybe oversimplify it here, but, you know, when people ask, what is prompt engineering? You know, there's, there's very technical answers to that, or you can just say it's learning how to properly work with any generative AI model. Right? So it's, it's knowing how to go back and forth, how you should be formatting your prompts. And I would say, you know, maybe getting. Getting more out of the same or getting more out of less, I would say is the most oversimplified way to talk about prompt engineering. But, Josh, I actually have a hot take, and it goes along with part of your, you know, prompt engineering is dead. Long live prompt engineering number five. But my hot take Is, I think prompt engineering is, is going to become deprioritized actually, which, which might not make sense, but in some recent experiences I've had, you know, even as an example, working with, you know, mid journey back when it was, you know, the version four point something versus now when you're working with mid journey, five point whatever, much fewer words give you fantastic results where it didn't used to be, like it didn't used to be that way. And then if anyone has used Dall E3 inside of chat GPT when you give it a prompt. So you know, Dall E is the new AI image generating model within OpenAI's ChatGPT. When you give it a short text prompt, it actually expands it in four different ways. So are our models going to be taking like this, Are the models going to be taking care of, you know, quote unquote, traditional prompt engineering for us?

Well, eventually. But if I'm trying to go ahead and create learning objectives or multiple choice questions or very, very specific outputs, not generic, not like common outputs, like an image, but if I'm, if I'm driving towards very, very specific type outputs, you know, like a report, like a 20 page report. Right. I don't think a simple five word prompt is going to go ahead and guide an AI for a 20 page report. So I think, you know, getting back to the point of, you know, it depends upon how you want to use the tool, I think. Well, here's an analogy. So when the Internet came out, you had a choice. Were you going to learn HTML, JavaScript and CSS? Some people said no. And that's fine because you can go ahead and use tools that will automatically create web pages for you. But for those individuals that learn those languages now they have agency, now they can go ahead and leverage, you know, being able to create modifications of their website or whatever the case may be, or for my, in my area, modifying or putting special elearning content together because they know how to, how to program. So it just depends upon your level of comfort. Again, there are going to be individuals that know prompt engineering that are able to take work and look at it differently and do different problem solving. But you know, for those of you that don't want to do prompt engineering, you're going to be fine. I mean, you're still going to be able to increase your productivity and show up using AI. It just depends upon what level you want to take it.

Yeah, Josh, great point there. Yeah, I guess the more complex or, you know, the more outputs that you may be wanting from the generative AI model, you probably still will need a certain level, you know. All right, so we do have a couple questions here. We got to our top five. So a question coming in is, is how can AI organizations tell the return on. Return on investment of learning programs? Or maybe I think this is from earlier when we were talking about, you know, using, you know, generative AI to create, you know, courses kind of like, you know, with the Adobe platform. But we're, or maybe in general, how can organizations know the return on investment of whatever they're putting into generative AI?

Yeah, they gotta keep track of, like, task, you know, doing task analysis and figure out how long does it take to actually produce some certain type of output. I mean, if you're not tracking, you're just guessing at that point. And so it's going to take work. This isn't going to be easy. You know, you can't just do anecdotal, like, oh, we're working faster. Like, well, what does that mean? And so, you know, I think there's going to be a period of time where when you analyze your work, when you actually map your workflows out, how much time does that one task take in Canva or, you know, PowerPoint or whatever the case may be, document it. And then now when you use your AI tool, how much faster is that task? And obviously, you know, based upon productivity and what an individual contributor is putting out over the course of the week, or a whole entire salesforce, like, is they showing up different each week? Because we're using AI automation to contact 20 additional customers. A certain type of way you gotta track and you, and you have to be really intentional as far as what those data points are, because there's, there can. You can be tracking all kinds of different things, but what are the inflection points? Like, what's going to truly impact the KPI? And then are you tracking against that as you are going in and implementing AI?

Yeah. All right, I think, I think we have time for one or two more quick ones here. So Craig joining us. Craig, thank you for the question saying, do you think there's going to be some sort of governance put on AI tools via the government or industry leaders at some point. Just a great question. So, so maybe, Josh, you know, you and I are both based in the US So maybe let's answer this, you know, out of the scope of the US Because I think it'll be different. But yeah, will there be governance from, from the US on these different generative AI systems?

There will be But I'm trying to think about how to say this. You. There's a lot of influence in government, and so we, we have a lot of active players that are currently in government, that are influencing government. And so I, I think there will be governance, but it's going to be somewhat loose or open to where there's going to be growth with AI, and we don't know what that means on the other side. Right. And so we still have, we still have things that are going through the courts in regards to copyright. We still have issues of nefarious characters using AI in really, really bad ways that need to get clamped down on immediately. And so I think there will be additional guardrails out there in the marketplace, but I think in the US it's going to be somewhat loose. At least that's my take on it. From what I understand what's happening in regards, like, to the federal government and who is, you know, working there. I, I think it's going to show up, but I think it's gonna be somewhat loose.

Yeah. Yeah, I agree, Josh. And to answer your question, Craig, I'll be a little more bold. I was, you know, previously political journalist.

I don't think anything's gonna happen.

I don't think anything's gonna happen right now. You know, I talked about at the top of the show, right now, generative AI is too important to the American economy to thwart it at all. So I, I think there should be way more guardrails. There should be some sort of legislation, regulation. But unfortunately, I think some of the big, Some of the decision makers don't fully understand, and I think right now it's too important to the economy that lawmakers are going to do it. All right, Josh, we've been all over the place. We took some questions, we went over the five different ways generative AI tools are going to show up in 2024. But maybe if you pique someone's interest and someone out there now is like, okay, yeah, now I care about this. What is, what is your one message or your one takeaway that you can advise companies, maybe they weren't paying much attention to Gen aa, now they listened, and now they are, and they're like, all right, I got to get on this. What is your one piece of advice or one takeaway for those companies on how they can actually heading into 2024, make sense and make generative AI work for them?

Yeah, first and foremost, if you don't have an AI policy, please implement one, because that is going to dictate how your company and how your associates show up. So, I mean, if you're, if you're still here in October and you don't have an AI policy, get that in place. Once you have that in place, then go ahead and allow your leaders to go ahead and drive those individual conversations in the lines of business. As far as how AI shows up, they know craft, right? And they understand what their job is as far as productivity or whatever they're, you know, driving towards. And they're going to go ahead and give you guidance as far as, like, hey, AI is going to show up this way in accounting. AI is going to show up this way in it, whatever the case may be. But it's a discussion, it's a dialogue, and it's ongoing. So make sure that you're doing the hackathons and all these things to, you know, to test AI and do the work. As far as, like, the cost. Also, you know, whether you're implementing Microsoft Copilot or you're trying to, you think that you may have enough great data to build your own large language model. What, what, what's the cost of that? The maintenance of it, Right? What if we build whole functions around it? What does that look like? So I think the policy is first empowering your individual contributors to start using it and then have that conversation, ongoing conversation.

Such great advice. So many great insights and tips and tricks from Josh. So again, Josh Cavaliere, founder of JoshCavalier AI. Josh, thank you so much for joining us on the Everyday AI Show.

Thanks, Jordan. I really appreciate it.

All right. And hey everyone, as a reminder, we did cover a lot. Don't worry if you didn't miss it. Just go to your everydayai.com Sign up for the free daily newsletter. We're going to have be sharing more about different things that Josh is is working on with JoshCavalier AI and a whole lot more. So thanks for joining us and we hope to see you back for another edition of Everyday AI. Thanks, y'. All.

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