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Ep 217: 7 Steps on How To ACTUALLY Use ChatGPT in 2024

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  • 28 Feb, 2024
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A Guide to Using ChatGPT in 2024

Artificial Intelligence is no longer just a term for tech enthusiasts; it has become an integral part of our daily lives and businesses. When done right, AI-powered tools like OpenAI’s ChatGPT can significantly enhance collaboration, productivity, and decision-making. But to gain maximum ROI, one must understand how to effectively use such technologies. Enter the guide to deploying ChatGPT in 2024, your compass to navigating this advanced conversational tool.

Understanding the Power of ChatGPT

Large language models like ChatGPT are trained using trillions of parameters sourced from the internet, facilitating responses that can cater to a multitude of business and personal applications. However, remember to approach ChatGPT like a new team member, ready to learn and improve. Cast aside views of it as merely an advanced tech tool, and embrace it as a part of your business operating system. It offers multimodal defaults, Bing-powered browsing, data analysis, collaboration tools, and memory personalization features crucial for business growth.

Navigating the New ChatGPT Features

In 2024, ChatGPT continues to evolve and improve its capabilities. The introduction of the memory personalization feature helps the AI remember details across multiple chats, hence improving contextual understanding. The ChatGPT Vision feature allows users to upload photos and derive meaningful insights, while the Data Analysis mode enhances data scrutiny, yielding important information for business decisions.

Leveraging the Power of Priming a Chat & Tracking Tokenization

To unlock ChatGPT‘s potential, it is essential to train each instance of it for a specific task. Believing in the idea that each chat is a dedicated expert trained for one specific purpose, the concept of priming aims at ensuring that the AI model retains its memory. To further solidify the system, incorporate tokenization, a process where words are transformed into tokens based on their context. Keep track of memory consumption through a token counter extension, as exceeding memory limits can lead to AI hallucinations.

Why Prioritize ChatGPT Plus for Business?

As businesses continue to engage with AI, serious users should strategically switch to ChatGPT Plus – the paid version. It provides exclusive capabilities and it is connected to the internet via Browse with Bing, delivering real-time information. However, being critical of the results generated, given the possibility of outdated or false data is integral.

Securing Data & Respecting User Privacy

Although AI opens up a range of possibilities, it also calls for responsible handling of information. In a world where data is the new oil, always remember never to upload any confidential, proprietary, or private information into any large language model, including ChatGPT. For enterprise versions, learn how your data is handled by consulting with representatives to guarantee informed and safe usage.

Embracing ChatGPT

Undoubtedly, advancements in AI signal a paradigm shift for businesses in 2024. But to leverage the full potential of these innovations, a fruitful interaction with ChatGPT is crucial. Approach it as a valuable team member, prime it for specific tasks, leverage the new functionalities, and make data security & privacy a priority. By following these steps, businesses are well on their way to riding the AI wave towards growth and success.

Don’t allow the future to leave you behind. Adapt, engage, and conquer the market with the compelling capabilities of ChatGPT. Time and technology wait for no man – or business. Now is the time to step into the future of AI-assisted operations.

Topics Covered in This Episode

1. Understanding ChatGPT
2. New Features in ChatGPT
3. Data Privacy and Security in ChatGPT
4. Future Directions and Advancements in Large Language Models

Podcast Transcript

Jordan Wilson [00:00:17]:
You’re using chat gpt wrong. Sorry. I mean, you’re thinking about it wrong, and you’re barely getting anything out of it. So I’m gonna tell you today not just what you’re probably doing wrong with chat gpt, but hopefully, over the course of one episode, to give you all of the best chat GPT information that we’ve covered over 200 plus episodes of everyday AI. And today we’re gonna go over on the 7 steps on how to actually use chat GPT in 2024. Here’s why we’re doing this episode. Number 1, things change so quickly in chat gpt. And number 2, actually, this was our most popular episode, and I still had thousands of people listening to an old episode a month.

Jordan Wilson [00:01:09]:
And I can’t I can’t do that anymore. We gotta bring you the most up to date and accurate information. So that’s what we got going on today on everyday AI. So welcome. If you’re new here, everyday AI, it’s for you. It’s a daily livestream, podcast, and free daily newsletter helping everyday people like you and me not just learn what’s going on in generative AI, but how we can also just leverage it to grow our companies and to grow our careers. Alright. So real quick.

Jordan Wilson [00:01:36]:
You might see something. This episode is actually presented by Taplio. I’m excited about that. More on that later, but we are live. But I didn’t even wanna spend too much time on the AI news. I think it’s too important. So So we normally do that every day. So make sure to go to your everydayai.com.

Jordan Wilson [00:01:53]:
Sign up for the free daily newsletter. I made sure that there wasn’t anything huge breaking, you know, Gemini 2.0 or, you know, now all of a sudden, Chat GPT does your laundry or anything like that. So, if you do still want the AI news, make sure to go to your everydayai.com. Sign up for the free daily newsletter. It’ll be going out here pretty soon. And our website is a free generative AI university. No matter what you wanna learn about, whether it’s chat g p t or other large language models or maybe AI, image, companies like Midjourney. It’s all on there.

Jordan Wilson [00:02:23]:
So you can go read every single newsletter we’ve ever done. You can go read and rewatch every single livestream we’ve ever done. Alright. Does that sound good? Hey. And let me know if you’re joining us live. I’d love to I’d love to hear from you. What is your one biggest chat gpt question? Alright. And chances are I’m I’m gonna get to it.

Jordan Wilson [00:02:45]:
I wanna know from you. Right? This is a live stream. And you you know what? I was I was doing some math, you you know, last night. I was I was doing some last minute preparation, and I’m like, I’ve answered probably around 3,000 questions on chat gbt. We do a live training, like, twice a week. Normally, I get about 40 like, 40 to 50 questions and have been doing that for, almost a year now. Right? Just under a year. So if you have a Chattopd question, even if you’re listening on the podcast, I put my information in there.

Jordan Wilson [00:03:19]:
Make sure to reach out to me, and I’ll I’ll go ahead and try my best to answer your question. But let’s start high level. Alright? Let’s start high level. And I want you first to have a little bit of patience with me. Alright? We’re gonna be a little bit all over the place, but not just have patience with me, but also have patience when you’re working with a large language model like chat gpt. Alright? There’s a reason why. You know, sometimes, I go on these long winding stories, but that can be how humans learn something best. Alright.

Jordan Wilson [00:03:53]:
But I want you to first know this. Chat GPT is not an AI tool. Alright. I’m gonna say that again because it’s worth repeating. Chat GPT is not an AI tool. It is a business operating system. It is a complete suite of the next generation of artificial intelligence, and you can use chat gpt to literally not just automate your business, but you can accomplish just about any task within ChatGPT. So before we even get started, because I know so many of you probably think of ChatGPT as, oh, it’s an AI tool.

Jordan Wilson [00:04:39]:
You know, it can write a blog post. Yeah. It it it can. You know, that’s like saying, you know, an airplane is is somewhere where you eat peanuts. Yes. You know, but it can also take you around the world very quickly. Alright? So first, before we even dive into this, I need you to change your mind frame on what chat GPT is. Yes.

Jordan Wilson [00:05:00]:
It is a large language model. Yes. It is technically an AI tool, but it’s not. It is so much more than that. Alright? So let’s let’s keep this thing going. Like I said, it is a business operating system. And here’s the thing. It’s not a quick fix.

Jordan Wilson [00:05:19]:
Alright? Chat gpt is not a quick fix. You really have to spend time to understand it and spend time working with the model to get the most out of it, and that’s what today’s show is all about. Those 7 steps on how to actually use it. Alright? And, hey, if you are joining on the podcast, I always appreciate it. This is one of those you might wanna come watch the live stream. Alright? I I am sharing, sharing some slides here, but I wanna do my best to to walk and talk through everything. But I like to tell people this. Where you spend your time right now is probably doing these things.

Jordan Wilson [00:05:56]:
You’re probably doing a lot of meetings. Right? So prep work and follow-up. You’re probably learning a lot in your job. Right? When I say knowledge workers, right, ChatchBT can do so much of what knowledge workers are doing right now. That’s what you do when you sit down in front of your computer. So it’s a lot of meetings. Number 1, Learning. You’re constantly learning new things.

Jordan Wilson [00:06:14]:
You’re reading. You’re taking notes. You’re keeping an eye on your competitors. Right? Writing. So you’re writing documents. You’re writing emails. You’re writing maybe blog posts. Right? You’re analyzing things.

Jordan Wilson [00:06:27]:
Right? So so spreadsheets, charts, etcetera. And then presentations. Maybe you’re creating presentations, sales trainings, pitching someone to try to get a new client. Right? What I just described there, meetings, learning, writing, analysis, and presentation, those five things, if you work in front of a a computer, those five things probably take up 80% of your day or more. And I’d love to hear from our our livestream audience, and and thank you everyone, for for joining us. Caroline, thank you. And and Justin, thanks thanks for joining. But how much of your time would you say is spending is spent doing those things? Like I’d say, most people is 80%.

Jordan Wilson [00:07:08]:
And here’s why I’m taking a while. Yes. I’m doing a big wind up here before we get our list started. Because so many people, even people who are still using chat gbt on a daily basis, are not using it right. Right? Those things, meetings, learning, writing, analysis, presentation, that’s what most all knowledge workers do a large percentage of your time, and you can do all of those things inside chat g p t. Right? Shannon said that’s 99% of her time. Alright. So now that we got our our mindset, right, I first wanna go over the capabilities of chat gpt plus.

Jordan Wilson [00:07:46]:
Alright. Yes. There’s a free version. Yes. There’s a paid version. That’s actually, I’m gonna give I’m gonna give something away. That’s our first step. Alright? But here are the capabilities of ChatGPT.

Jordan Wilson [00:07:58]:
Again, I’m starting high level because this is for beginners to advanced users. Ready? So you have a multimodal default. Alright. That includes the ability to launch Jet GPT Plus and browse with Bing, use the data analysis mode, which, if you catch if if you caught our newsletter, they’re working on a new update to that. You can use DALL E, create AI images, vision, chat gpt can see, and document upload. Alright. There is the new version of GPT 4, which is called GPT 4 turbo. You have GPTs, the ability to quickly, create and customize, versions of chat GPT for your own use.

Jordan Wilson [00:08:39]:
You have a GPT store, so all those custom GPTs, there’s, apparently millions of them that are already made. You can go search for them and use them that other people have made. Vision, we just briefly talked about this, so now we’re gonna go a little bit more into these modes. So with Chat GPT Vision, you can literally upload a photo of anything and say, what is this? Or if, you you know, if if you have a leaky sink or something, you can say, what’s going on here? I don’t know. Right? So chat gpt can can see with vision and obviously reason. Right? Browse with Bing. Browse with Bing’s important. We’re gonna be talking about this when we talk about hallucinations, but, you know, chat gbt, or gbt 4 has an April 2023 knowledge cutoff.

Jordan Wilson [00:09:22]:
So the ability to browse with Bing inside of chat gbt is huge because it it reduces your likelihood of hallucinations. Right? DALL E, we talked about great to be able to conversationally in one chat. Right? To be able to, you know, you could be planning out a project and then, hey. Say, hey, Dolly. Could you create a visual that goes along with that project? Right? Data analysis. Alright. So that is its own technically, it used to be its own mode. Right? But now you can just use it in the multimodal default mode.

Jordan Wilson [00:09:53]:
So if you call to data analysis, it actually does a great job at advanced computation. Alright. And like I said, if you read the newsletter, you saw that, Chat gpt is rumored to be releasing a new version of data analysis. Then you have Teams. Alright. Chat GPT isn’t just, hey, this is just me working on my own. You can have Teams. So there’s a Teams mode for Teams from 2 to a 149.

Jordan Wilson [00:10:18]:
Alright? There’s some extra data privacy cons some extra data privacy options in there, and the ability to better work with your teammates. Alright. Memory. Oh, had the GPT store on there twice. Hey. This wouldn’t be everyday AI if there wasn’t at least one error on a slide. Right? That’s how you know it’s made by me, a human. Memory.

Jordan Wilson [00:10:40]:
So the memory personalization, a lot of people are talking about that. I’m gonna get to that later. There’s pros and there’s cons, and we dive into that more in today’s newsletter as well. But, essentially, it allows ChatTPD to remember certain things from chat to chat, which is a huge shift in the way that large language models in general work. Alright. Then you have document upload, the ability to upload a document into ChatGPT. Alright? So I’m starting there because I know, you know, I know a lot of you joining here, on the live stream, you know, like like, Woozy joining us and and Nancy. Right? I know a lot of you all on the live stream here are advanced power users, and that’s why I love having your comments and your insights.

Jordan Wilson [00:11:22]:
Right? But I know a lot of people listening on the podcast as well, you know, are newbies, and that’s okay. So I wanted to first start with an overview. Right? ChatGPT is not an AI tool. It is a business operating system. Alright? And then I wanted to show everyone as well, here’s the capabilities. Because so many of these things, so many of these nine things that I just went over, have just been either released or updated in the last 3 months. Alright? So it’s important that we all get on the same page. Alright.

Jordan Wilson [00:11:51]:
I think we’re good now. So now without further ado, let’s get to the 7 steps. Enough wind up. Right? Alright. We’re counting them down, alright, to build up build up the drama. Alright. So the first one is step 7. Use chat g p t plus, not the free version.

Jordan Wilson [00:12:15]:
Alright. So let me just give you some examples. Right? I like to think of it as as a map. The free version of chat GPT, which is GPT 3.5, it’s like a map. Right? It’s nice. It’s there, but it’s it’s not dynamic. It’s static. Alright? If a road changes, you’re screwed it with if you have a map.

Jordan Wilson [00:12:38]:
Right? The the pro version or chat GPT plus is $20 a month. Right? And all those, most of those capabilities that I just listed off are, exclusive, to the chat gpt plus version. So when you use the $20 a month chat gpt plus, and y’all, this this episode’s not sponsored by OpenAI. FYI, I’m not getting paid to say this, but you should be using the plus version. My gosh. Right? So that is in in that scenario, that’s like having Waze on your smartphone. Right? It’s always up to date. Right? There’s all these other features that are constantly being being rolled out.

Jordan Wilson [00:13:15]:
So it’s like having, you know, a smartphone. Right? Like, if you wanna navigate somewhere you’ve never been before, would you want a map that was maybe printed 5 years ago, or would you want a smartphone that has the best service? Right? It has a GPS in it, and you can do anything with it. Right? Or even I like to say, you know, a a tricycle versus Tesla or an encyclopedia versus Google or a typewriter versus a laptop. Alright? The free version of chat gbt is extremely limited. So if that is what your, you you know, your whole relationship of chat gbt is is mainly through the lens of the free version, you can’t be using it. Right? If you’re serious about using ChatGPT, if you’re serious about getting the most out of large language models, and by far, this is not even close. Sorry. Google Gemini Ultra 1.0 Ultra 1.5, chat GPT, because of all these other features runs laps around every other large language model out there.

Jordan Wilson [00:14:14]:
It runs laps around any gen AI tool out there. Right? So I have a little little chart, here kind of showing the differences between the the free version and the paid version of chat gbt. So there is actually a a kind of an advantage to the free version. It’s a little faster, and it’s, you know, there’s less limits. Right? But, you know, I’d rather work with the chat gbt plus. There is a limit, so you get 40 messages every 3 hours. Right? And the free version of ChatGPT is is a little faster, but all these, you know, especially with the new turbo version of, GPT 4, you know, there’s really not a big difference anymore. There used to be, but not anymore.

Jordan Wilson [00:14:57]:
Right? So some people would always say, oh, look at how fast the free version is. Why why do I care? Well, you don’t get all these other things in the free version. All these, you know, plugins, which are going away more on that later, advanced data analysis, this multimodal, the ability to create your own GPTs. Right? No code. All of that is only available in the paid version. Alright. So you can’t you can’t skip that. Alright.

Jordan Wilson [00:15:26]:
So next step. Step number 6 on our 7 steps on how to actually use chat gbt in 2024. You have to understand how a large language model works. Alright? Yes. The first version is you gotta use the right one. The second step, right, is you have to actually understand how it works. Alright. So there’s a lot.

Jordan Wilson [00:15:51]:
Right? And I’ve I’ve literally had 50 minute episodes where I just talk about tokenization. Alright. So, you know, Shannon, I saw your your comment here asking about token counters. All that’s gonna be in the newsletter. Don’t worry. So but you do have to understand that a large language model thinks and responds in tokens. I know that’s weird, but it doesn’t actually understand words. It converts all of those words that we put into that prompt.

Jordan Wilson [00:16:22]:
It converts everything into tokens. Alright? That’s important to understand because that just emphasizes the need for more clarity in your communication. Alright? Because two words can mean the same thing. So that’s why, you you know, we teach, and I’ll probably mention this a couple of times, you know, the PPP method, which is prime prompt polish. That’s our free course. We’re actually blowing it up and and rebuilding it from scratch because of plugins being gone. But anyways, that’s what we teach in the course is that you have to go back and forth and use more words because of the tokenization process. Alright? And, you know, I know my my my fellow dorks out there aren’t gonna like when I say this, but, the easiest way to think about what a large language model is is think of it as the world’s most advanced, the world’s most advanced autocomplete system.

Jordan Wilson [00:17:17]:
Right? Yes. It’s generative. It’s it’s it’s technically, you know, just predicting the likelihood of of what the next word is gonna be based on the trillions of parameters that a large language model is based off of. Alright. That’s another important thing to understand about a large language model is how it’s built. Right? So, essentially, with a large language model, it has gobbled up the entirety of the Internet, the open Internet, the closed Internet, other other pieces of works, etcetera. Right? It doesn’t necessarily know what’s good or bad, but it’s trained by humans. Right? So these models, they go out there, they they gobble up all of the information of of humankind that’s essentially ever existed.

Jordan Wilson [00:17:58]:
You know, even stuff that you don’t know exists. It’s the large language models have already gobbled it up and then it’s trained by humans. Right? And then and this is again oversimplifying it, and this is for beginners because I know my my advanced crew here in the live stream, you you probably understand this. But then when we talk with chat gpt, it changes everything into tokens, and then it looks at its big 1.8 trillion parameter, big neural network brain. And it makes sense of those words. It turns them into tokens, and then it looks at its big old database of everything on the Internet. And it says, okay. Based on these words, based on the tokenization of these words, and based on the context that it’s gaining through tokenization, it’s saying, here’s what I believe that they are asking.

Jordan Wilson [00:18:42]:
Right? It’s oversimplified, but keep in mind, chat gpt, like all large language models, are generative. Right? So that means you are going to get different results. There is literally a regenerate button within chat gbt. If you ever wanna really understand how a large language model works, click that regenerate a couple of times. Change 2 words and click, you know, click enter again and see how much different your results can be. So you can run the same or a very similar prompt in chat gpt or any GenAI system and get wildly different results or different outputs. Alright. So another very important thing, And we’re gonna get more into this when we talk about the features and how to use all these features.

Jordan Wilson [00:19:28]:
But, chat gbt 4 or chat gbt plus is connected to the Internet. Alright. So that’s a good and a bad thing. So with browse with Bing, browse with Bing used to be its own mode. Alright. So you used to kind of have a default mode and then you had a browse with Bing mode. So essentially, you know, OpenAI has a partnership with Microsoft. So Chat GPT has a fantastic feature called browse with Bing, and it’s in the default mode.

Jordan Wilson [00:19:56]:
But you might not always know when it uses it because it can go kind of fast. So unless you’re really looking at it and it’s not always going to, you know, do a link and, you know, give you a link and say, hey. I did a quick search. Here’s what I found. Sometimes it just might spit out that information and you might miss it. So it’s very important to know that in the default mode, when you are using ChatGPT Plus, it is connected to the Internet via browser Bing, which is both a good and a bad thing. It’s a good thing because the knowledge cutoff, which we’re gonna talk about more, the knowledge cutoff for GPT 4 as of now is April 2023. Right? And that’s actually kind of old.

Jordan Wilson [00:20:32]:
That’s 11 months old. Right? So think what hasn’t changed in 11 months? Right? When we think about ChatGPT Plus is a business operating system, Basically, anything that you’re working on in your business has probably changed greatly in the last 11 months. So it’s very important to understand that how and when you put in a prompt into chat gpt or you, you know, put in a a response, you have to understand what’s going on under the hood. Right? So essentially, chat g p t decides through tokenization and context if what you’re asking on requires it to browse with Bing. Right? We’ve done so much kind of like blind a b testing on this with different accounts, different chats. Right? Sometimes it will just respond without, you you know, seeing if if it’s, you know, information past 2023. Sometime it’ll say it, you know, hey. I browse with Bing.

Jordan Wilson [00:21:27]:
Here’s the output. Sometimes it will browse with Bing, but won’t even necessarily tell you because it’ll bring in information past April 2023. You always have to be testing when you’re using chatbotian. You have to understand how it works. It’s literally why we’re doing this episode because so many people are getting this piece wrong. So that’s important to know. Alright. So here’s here’s a good example.

Jordan Wilson [00:21:48]:
Right? Here’s a good example. So in this example, I said, how much has NVIDIA’s stock grown the past year? Alright. And for whatever reason, when ChatGPT responded in this case, it was just trying to access, information from one site. It was trying to look up something on the from The Motley Fool, a very famous financial website. So, I didn’t tell it to browse with Bing. Right? But obviously, it understands by the context when I’m saying how much has the stock grown in the last year. And all that happened is it looked on one what it looked on one website. Right? So it didn’t give me a result.

Jordan Wilson [00:22:21]:
It didn’t know. Right? So if I regenerate it and run the exact same thing, now it tells me NVIDIA stock has experienced significant growth over the past year with an increase of more than 210% since January 2023. Right? But that was actually outdated as well because when it browsed with Bing and when I clicked the little site, the source that it cited, that was from the end of January, which was 30 days old. And I just did this screenshot like 3 days ago. Right? So that was still technically incorrect. I did the exact same prompt one more time, and this one was much better. It said over the past year, NVIDIA stock has seen a total return of, you know, 236%, etcetera. But this information on the 3rd iteration is was actually accurate at the time.

Jordan Wilson [00:23:07]:
Right? So each time, one time it didn’t really use browse with Bing or use it correctly. And then it did use browse with Bing and it brought back some inaccurate information. And then the third time it used browse with Bing and it brought back correct information. Alright? And all of this is happening behind the scenes. You might not know. If you’re new to ChatJPT, you might not know what’s going on. Why I’m walking and talking you through it and showing you examples. Alright.

Jordan Wilson [00:23:35]:
So like I said, Browse with Bing is both very powerful, but it can also give you outdated or false information. You gotta keep that in mind. Alright. We’re doing we’re doing a lot of water y’all. A lot of water today. There we go. I’m actually if you couldn’t tell, you know, maybe if you’re if you join into the live stream daily, I might look a little different today. Right? I’m actually in in New York.

Jordan Wilson [00:24:02]:
I’m not normally in the, the Chicago home office. Alright? So I’m more little more thirsty today. Alright. So step 5. Alright. Step 5. You need to use new features strategically and know what they do. Alright.

Jordan Wilson [00:24:16]:
Let’s talk about that a little bit. All those new features. Right? We talked about them. But something we didn’t go into great depth is number 1, plugins are going away. If you listen to the everyday AI show at all, you know, I love plugins because it was an unfair advantage. Alright. So yes, we still do have these, these GPTs, these custom versions of chat GPT. You can train them on your own configuration instructions.

Jordan Wilson [00:24:40]:
You can upload your on your own documents, right? So chat GPT or that gpt, has a better idea of what you wanna use it for. Right? So, OpenAI has been phasing out plugins, and they officially said, hey, they’re going away in March. So or you can’t start new plugins in March. So with that, chat g OpenAI is saying, hey. You don’t need GPTs. You need or or sorry. You don’t need plug ins because we’re doing chat gpts or we’re doing plug ins. Oh, man.

Jordan Wilson [00:25:10]:
So so here’s here’s the difference y’all. It’s not the same thing. Using GPTs is not the same as plugins, at least right now. So right now, GPTs work a little differently, alright, than plugins. What I loved about plugins and what we taught in our free prime prompt polish course, and if you do want access at any time, just put PPP, and we’ll make sure to send that to you. But plugins could could work together. They could work autonomously. So you could go through and train a chat.

Jordan Wilson [00:25:36]:
That’s always what we teach, and you could put in one prompt. And then those 3 little plugins that had 3 very different, you know, different, features, they could work autonomous, autonomously. They could work with each other. Right? You can’t do that with GPTs. You can only work or mention 1 at a time. However, in the same chat, you can mention unlimited GPTs. Right? So it’s not limited to 3, which is nice. So there’s pros and there’s cons.

Jordan Wilson [00:26:01]:
Right? So these new features, you have to use them strategically. However, you can’t use 3 or 5 or 10 GPTs in the same prompt or the same, at the exact same time. Like, you could use 3 plug ins at a time. Alright. So the reason why, you know, I really wanted to go over this piece and actually let me get let me get some exacts here. Right? So, plugins will be new chats, with plugins will be disabled. There we go. We got the actual date there on, March 19th.

Jordan Wilson [00:26:32]:
Right? So you can’t create new chats with plug ins after March 19, 2024. And your existing plug ins that have, your existing chats that have plug ins will no longer be usable after April 9th. Alright. So let’s just quickly show what a a GPT looks like. Alright. So this is a new feature, and I think they’re very powerful, but you have to use it correctly. I see so many people, even the experts, using these new GPTs incorrectly. Alright.

Jordan Wilson [00:27:02]:
So real quick, and if you’re listening on the podcast, it’s simple. Creating a GPT, right, for our for for all the downsides I don’t like, creating them is so simple. So it is a no code or low code. Right? So you can literally just go in. It’s kind of meta or, you know, inception, but you can chat with chat g p t to create a g p t. So you don’t have to know code. Right? And then there’s, you you know, as you’re building it, you get a little preview. Right? And then you can go on the back end and go to con the configure tab.

Jordan Wilson [00:27:31]:
So essentially, after you have this conversation with the GPT builder, it will create configuration instructions for you. You can go in and change those or modify those as well as upload documents. So in this example, you know, I was just uploading, you know, Jordan writing samples. So as an example, if you wanted to create a GPT that sounded a little more like you, it’s not gonna be great, but, you know, that’s one thing that you could do there. Alright. So here’s, here’s where you have to understand the downside of these GPTs and how a lot of people are using them wrong. Alright. So you can use a GPT in its own mode.

Jordan Wilson [00:28:07]:
Right? So a dedicated, kind of chat that is just with that GPT. Or in the default mode, you can use the GPT mentions feature. Okay. That is the way you should be using it. As far as I know, and I’ve done a lot of testing on this, there is zero zero reason to ever use a g p t in its own mode or in its own window and not just use the default mode and mention it. Number 1, if you’re doing that, you’re you’re you’re kinda stuck there. Right? And you lose some of that functionality and some of those capabilities that you would have in the quote, unquote default mode of chat gpt. And here’s the reason why.

Jordan Wilson [00:28:48]:
So many GPTs, which is is actually good and it helps them work better, but they’re very refined. Right? So, you know, as an example, a lot of g p t’s have browse with Bing disabled. They might have DALL E disabled. Right? And those configuration instructions might really limit. So if you’re trying to, you know, let’s say you’re using a a a data analysis GPT. Right? And it’s it’s great. Right? It’s powerful. It’s it’s great at, you know, Python, and it’s great at, you know, creating spreadsheets, whatever.

Jordan Wilson [00:29:19]:
Right? But if that GPT does not have access to browse with being enabled, and if you wanna, you you know, get some information, if you wanna use what’s in that GPT chat, you you gotta start a new one and do all this copying and pasting. So when I say using these new features strategically, I mean just that. You should almost always be using any GPT in the mentions. So in the default mode and then mentioning them. Alright. And then when you’re done getting the information from that GPT by default, the GPT is going to stay there, and you are going to still be quote, unquote talking. You you just gotta exit out of it. Alright? And then just return to the normal default chat.

Jordan Wilson [00:29:57]:
Alright? All that information will stay intact. The reason is I see a lot of people doing this, a lot of even quote, unquote experts who are teaching people. They mentioned a GPT, and then even when they’re done, it is still there in their sidebar and they’re still are in their top bar, and they’re still technically chatting with it, and they don’t know. Right? So anytime it’s there, even if you are not using it, you have to exit out. Otherwise, if that GPT does have limitations or, certain ways to act in its configuration instructions, whether you know it or not, you’re still using that. Alright. We’re going into the intricacies here, but I wanted to make sure that even whether you’re a newbie or an expert, that you’re getting a lot out of today’s episode. Alright.

Jordan Wilson [00:30:40]:
Another new feature, and this is being slowly rolled out. Alright? I love I love this. Made, Duvall, said made a GPT to help make GPTs. Same thing. Same thing. So so good. Such a smart such a smart thing to do. All right.

Jordan Wilson [00:30:58]:
So memory personalization is another new feature. All right. We’re spending a lot of time on this because I know that people are going to be listening to this episode for months to come. So this feature has not fully been rolled out yet, but it is being introduced and a lot of users have this. So this new memory personalization allows chat gbt to remember things across chats, which on the surface is amazing. Right? That’s great. And you can always go in to check to see if you have it. Again, you have to have chat gpt plus, go into personal into your settings, go into personalization and you can toggle memory on and off, and then you can manage it as well.

Jordan Wilson [00:31:34]:
So from if you click to manage memory, you can go through. And these so essentially, when you are talking to chat gbt, it’s going to take things automatically. That’s the key here. It’s going to automatically start grabbing facts. Right? So is it a little weird? Yeah. Is it helpful? Absolutely. Right? So, you know, in this example, if you have a 2 year old daughter named Lisa, Lina, it’s going to remember that. Right? So it’s gonna remember that across different chats.

Jordan Wilson [00:32:01]:
So you can kind of think of it like, you know, retargeting. Right? If you visit a website and, you know, you get pixeled and there’s a cookie on there, right, and you go to another website and you see an ad for it. So it’s kinda like that. When you start different chats, it’s gonna start to remember things about you or things that you’ve told it. So chat gpt by default will remember certain things about you without you asking, or you can ask chat gpt to commit something to memory. Personally, I’m not gonna be using this a lot, and I think that most people probably shouldn’t at least as it is now. Here’s why. Number 1, I don’t think it’s great you that, chat g p t is going to automatically put things into memory.

Jordan Wilson [00:32:38]:
It would be good if it gave you a notification or if it asked you. Right? If you put a lot big, big, long, you know, conversation and it’s like, okay, you know, know, these are the things I wanna commit to memory and you can click yes or no, but that’s not how it is. Right now, this works behind the scenes and is committing things to memory. So here’s an example of why that might not be the best. Alright? It might not be the best because what if you don’t want chat gbt to remember all of those things? Right? As an example, what if you’re using chat gpt for many different clients. Right? Or maybe you have many different writing styles or, you know, maybe you are using it for for personal and for work. You probably don’t want those those certain things creeping in to all of your other chats. So personally, because I use chat g p t for every aspect almost of my life, this is actually a feature I am not going to use probably at all until they change how it works.

Jordan Wilson [00:33:35]:
Alright. So quick recap of the new features in the default mode. You can mention any g p t and you should be doing that. Also keep in mind the browse with being in the new features in the default mode. You have to really understand because that’s where a lot of people are getting bad, are are are getting bad outputs. Right? It’s because they don’t know how all of these new features work. So again, here’s here’s what I was referencing earlier. Right? So when you mention or when you at mention a GPT, it kind of pops up there in the in the top bar.

Jordan Wilson [00:34:09]:
So once you’re done, you know, and you can mention any GPT just by hitting the at. Right? And it’s only ones that you’ve used before, but then once you’re done. So as an example, in this screenshot, I’m, mentioning the web reader GPT because maybe I wanna visit a specific URL, which browse with Bing cannot do. Another advanced tip for you guys. Right? But then when I’m done, when I’m done, you know, using web reader, I need to exit out. I need to click the x button and then go back to using the default mode. Otherwise, whatever, you know, restrictions that might be on that gbt are gonna follow me around everywhere. So keep that in mind.

Jordan Wilson [00:34:45]:
Alright. Here we go. We’re gonna go fast now y’all. Hey. Cecilia said, love that you ran away to New York City. You know, I’m gonna be back in Chicago in 2 days. Don’t worry. I gotta hold it down for all my Chicago people.

Jordan Wilson [00:34:59]:
Alright. Here we go. Number 4, keep track of memory to reduce hallucinations. Yes. Someone was asking about memory earlier. We gotta get a little dorky here, y’all. We gotta get a get a little dorky. So here’s what you need to know about memory.

Jordan Wilson [00:35:17]:
There are 32,000 tokens in memory right now. So here’s what that means. That’s about, give or take, 26,000 words. Alright. So when you are chatting with chat gpt, and hopefully we’re gonna get to this here in a minute, but you’re gonna be going a lot of back and forth. Alright. So you need to keep the memory in mind because it has a 32 1,000 token context window of memory, which is about, like I said, 25, 26,000 words. So all of that back and forth with chat gbt in that chat, once you kind of get past that 32,000 tokens, it is going to start to forget whatever is at the top.

Jordan Wilson [00:35:55]:
Right? So, yes, use a token counter extension. The one that we use is literally called token counter. So, you know, if you use Chrome or Edge, you can use it in there and we’ll be linking to that in the newsletter. Alright. Today’s newsletter, y’all, I’m being honest. I already wrote it and it’s probably the best newsletter I’ve I’ve written in 220. So much good stuff in there. Like, I should probably be selling today’s newsletter alone for, like, $200.

Jordan Wilson [00:36:21]:
There’s that much information. 1,000, literally thousands of hours of using the GPT technology. I didn’t even say this. Our team’s been using the GPT technology since 2020. Right? I told you I’ve I’ve we’ve trained 25 100 business leaders on how to use chat gpt. All those questions, thousands of questions, all those answers. Literally, today’s episode and the newsletter is is a culmination of all that. Alright.

Jordan Wilson [00:36:44]:
But you need to keep memory in mind to reduce hallucinations. So hallucinations mentioned it before, but that’s when Chattopetee kinda lies. Right? That’s when Chattopetee might tell a half truth. Right? Or be a little ambiguous, or or show some ambiguity. Right? And a lot of times it does that because you don’t do a good job. You, the user, don’t do a good job when you are starting a chat. You just put in a big prompt. Right.

Jordan Wilson [00:37:07]:
And you don’t take the time to train it. All right. So you need to keep track of memory. So as an example, I mentioned, you know, a token counter. So I have a screenshot. Right? So in this specific chat, I’m showing that it says, oh, you’ve used about 13,000 tokens here or about 10,000 words. Okay? So I know in that one chat, if I keep that token counter up, once I get to 32,000 or if I let’s just say I get to 35,000 tokens. Right? So 3,000 tokens over chat gpt’s memory limit, its context window.

Jordan Wilson [00:37:42]:
So what that means when I’m at 35,000, it is going to forget what is at the top, or it is going to forget the first 3,000 tokens that I gave it. So, again, this is one of the things I see over and over that that people are getting wrong about chat gbt. Even people that use it every day every day. I’ve had very bright, intelligent, amazing people who literally give speeches on chat gbt. I kid you not. And they’re like, Jordan, I had no clue about how memory worked. That’s how memory works. You gotta keep in mind.

Jordan Wilson [00:38:10]:
And that’s one of the complaints we always see. Hallucinations and, oh, you know, I was using chat gbt. It was great. And then it started to forget things, and then the quality went down. That’s why you’re not keeping track of memory, and that’s when you start to get hallucinations. Y’all, I’m so tired. Finally. Finally.

Jordan Wilson [00:38:32]:
I’ve always I’ve always, like, joked about this. I can finally take a water break because today’s episode is we partnered up with Taplio. We’ve been using them forever. So here here’s actually me talking, about Taplio. And I’m gonna take a water break. This is great. I get to be like you guys now and and and watch and watch this. Alright.

Jordan Wilson [00:38:51]:
If you’re looking to grow your brand on LinkedIn and who isn’t, just do what I do here at everydayai. I use Taplio. So do you know that LinkedIn is 227% more effective at generating leads than other social media networks? You know I bring the receipts. But that is also why everyday AI has such a heavy emphasis on using LinkedIn for growth. And that is why I’ve been using Taplio. I’ve been a paid subscriber for Taplio since way before I even started the everyday AI show. So here’s the basics of Taplio. You can use their AI powered suite of tools to cover trending topics to write about, create great content 10 times faster, or engage with the right people at the right time more efficiently and turn followers into leads.

Jordan Wilson [00:39:33]:
That’s literally the feature I use the most. So here’s what you need to do. Go to taplio.com and sign up for a free 7 day trial of the plan that fits your needs. And then on checkout, go ahead and use my code everyday. That’s e b e r y d a y to get your 1st month for $1. It’s only good for a couple weeks, so make sure to go do that now. And check out the show notes as well. I’ll give you a little secret on exactly how we use Tapplio to grow everyday AI on LinkedIn.

Jordan Wilson [00:40:01]:
So let’s do this together and use Tapplio for growth. Oh, that was fun. So during that break sponsored by Tapio, I was doing some stretching, and I got hydrated because now we’re getting into the top 3. Alright. And and a little bit more, we’re actually gonna be giving away a year of Taplio. Alright. I’m gonna tell you how at the end and also I’m gonna tell you how in the newsletter. Alright.

Jordan Wilson [00:40:24]:
But here we go. Let’s get to the top 3 on the 7 steps on how to actually use chat gbt in 2024. Alright. Number 3, prompts don’t work. Don’t use them. Alright? I’m gonna try it too. I’m I’m gonna try hard here not to really, you know, be mean to Billy Boy, you know, the the 20 year old chat gbt expert who was previously an NFT expert, previously a crypto expert. Right? And he’s like, hey.

Jordan Wilson [00:40:50]:
You know, use all these prompts in my prompt book. I have, you know, 9,000 prompts for $99. Don’t use those. They don’t work. Alright. Here’s, here’s what prompts do. Here’s what prompts do. Alright? They get you from an f to a c.

Jordan Wilson [00:41:05]:
If you’re brand new to ChatGPT, yeah, go go go find a super prompt. Put it in there and see what ChatGPT can do. But that’s all prompts actually do. It shows you the capabilities, and it can get you from like an f to a c. Alright? Because technically and we’re gonna get a little technical here. But if you wanna get more dorky, I’d link to other episodes in the newsletter where we went into this in great depth and detail. Alright. Copy and paste prompting, which is what a lot of people do.

Jordan Wilson [00:41:31]:
They first try something on their own, doesn’t really work. And then they go try to find the longest prompt on the Internet and they put it in and they’re like, alright. Well, this is a little better, but still kind of stinks cause that’s not how a large language model works. Right? It’s not like a a search engine. It’s not like Google. It’s not where you put in one input and look for one good output. That’s wrong. Right? So all of the benchmarks.

Jordan Wilson [00:41:51]:
So there is something called MMLU. We’ve talked about this a lot. MMLU is, you know, widely considered the best benchmark for large language models to see essentially, can it reason like a human? Is it smarter than a human? Alright. So it’s the multitask language understanding. That’s MMLU. Alright. And every single test out there. Right.

Jordan Wilson [00:42:15]:
I’m gonna go ahead and skip to my graph here. Alright. Every single test, every single benchmark out there says that you get much higher results or much better or much closer to a human than if you use multiple shop promptings. So what that means, copy and a copy and paste prompt, in most cases, is essentially a zero shot prompt or a one shot prompt where you’re not giving any examples. You’re not going back and forth. You’re not having a conversation. Right? You’re thinking a large language model like ChatGPT is like Google. I put in a large input.

Jordan Wilson [00:42:49]:
I get a I get an output. Right? It’s not how it works. So a shot. Right? There’s something, you know, always the the the the highest scores on these tests is what’s called a a 32 shot chain of thoughts prompt. Right? Not gonna get too technical, but this chart here shows you. Right? A 5 shot prompt with the same large language model is going to always outperform a 3 shot prompt. Right? A a 3 shot prompt with GPT 4 is always going to outperform a 1 shot prompt. Alright? I don’t know why people hate math and hate science.

Jordan Wilson [00:43:31]:
Prompts don’t work. They get you from an f to a c. Alright? So we need to be doing what is essentially and again, I’m oversimplifying here. So, you know, if if you build large language models for a living, yes, you can still tell me I’m wrong, but I’m oversimplifying here. Right? But when you’re having a conversation and you’re going back and forth with a large language model, you are essentially doing, you know, a multi shot prompt, a 5 shot prompt, a 9 shot prompt. If you go back and forth 9 times, give 9 examples. That’s how a large language model works. Prompts do not work.

Jordan Wilson [00:44:05]:
Alright. Very low quality. So one thing I always like to pick on, right, if you tell a nearly 2,000,000,000,000 parameter large language model to act as an example, act as an expert marketer with 20 years of experience, that does nothing. Remember, we talked large language models with trillions of parameters have gobbled up the entirety of the open and closed Internet and more. Right? And guess what? There’s a lot of people on the Internet that say, I’m a marketer with 20 years of experience, and the large language model has gobbled that up. So Chat gbt has gobbled up bad information and good information. So if you think that saying something in a prompt, like act as an expert marketer with 20 years of experience, if you think that does something, it absolutely does not. We’ve done blind testing 20 times each way.

Jordan Wilson [00:44:54]:
It does not do anything. A lot of times, it does more harm than good. I gave that example earlier of the NVIDIA stock. Think when you regenerate something different, when you regenerate something different. If I if you go through if you want to create an expert chat that is a marketer with 20 years of experience, you have to go through and teach it. Right? That’s what we teach in our free prime prompt polished course. Also, you gotta be aware of prompt injections. Again, something for a technical crowd, but a lot of people are using these super prompts and maybe not looking at them too closely.

Jordan Wilson [00:45:23]:
Yes. Just like any other software or hardware, there is something called prompt injections, which are dangerous, and you might not be seeing them happening under your nose. Alright? So that’s why I always recommend working with a large language model like a human. Alright? Which brings us to number 2, Prime chat gbt before asking for an output. Frank says good good content. Thanks, Frank. And Nancy’s clapping. Appreciate that, Nancy.

Jordan Wilson [00:45:54]:
Juan’s signing up for Tapio now. That’s great. Make sure to use the the code every day, Juan. Alright. So number 2, prime chat gbt before asking for an output. Here’s what that means, and this is what we teach. Alright? And check this out in our newsletter. But you need to create dedicated trained chats for specific task.

Jordan Wilson [00:46:13]:
Alright? Another, another thing that we teach in our free prime polish course. When you are creating a new chat, right, you click the new chat button in chat gbt. You don’t use that chat for everything. You don’t say this is my Wednesday, February 28th chat. No. When you start a chat, you do so with the intention of training it on one very specific skill set. Alright? And you go through and you have a conversation with it like a human. You talk back and forth.

Jordan Wilson [00:46:39]:
You share all this knowledge. You go through essentially training. Right? It’s it’s like if you have a new employee, you have to train them. You have a conversation, you don’t throw down, you know, a a big training manual and say, go to work. You you go step by step. You have a conversation. You go back and forth. You ask questions.

Jordan Wilson [00:46:55]:
Right? That’s what priming is. When you start a new chat inside ChatGPT, you train it for one specific purpose. Alright? So let’s say it’s for, the example that we were just kind of talking about, You know, the expert digital marketer. Let’s say it was a marketing strategist. Right? So you were gonna train it on that, and you don’t want an output. Right? You are literally when you start a new chat, you don’t say you are an expert strategist and you give all this information and you say, now build me a a a marketing plan. That’s wrong. You train it on a skill set first.

Jordan Wilson [00:47:28]:
You go through, you ask questions, you go back and forth, you share knowledge, and you make it better. You turn it into an expert. That is priming. You do not want an output. You want an expert skill set. Alright? And then when you go back in a week or in 2 weeks, you go back when you need that marketing strategy expert that you trained, you go use that chat that you built. Right? That you trained for that one specific purpose. You don’t use that for content creation.

Jordan Wilson [00:47:57]:
You don’t use that for data analysis. You only use it for that one specific thing. But, again, you need to prime chat g p t. People always go in and start a new chat, and they put this long prompt and they’re looking for an output. I say like this, Chat gpt, you have all those chats on the left hand side. Think of all those chats as expert employees that you can train in one specific skill set. That’s what the that’s the advantage of working with a 1.8 trillion parameter large language model. But you have to make each of those chats much more refined.

Jordan Wilson [00:48:30]:
You don’t you you technically want a small model in each of those chats. Right? You have to bring it down. You have to narrow it in and keep narrowing it. That’s what priming is on one specific skill set. And then you go back and you use that when you need it, and you don’t use it for anything else. But you also gotta keep memory in mind. Right? You do what we call as a memory recall. You know, it’s like clicking auto save, on a document or saving a document.

Jordan Wilson [00:48:54]:
Right? So saying like, please recap this this conversation so far, you know, in detail, everything that we’ve, concluded. Right? So you need to make sure that chat gbt is retaining its memory as well when you’re using these expert chats and you’re floating back and forth. Y’all, I cannot emphasize enough. You’re doing it wrong. That is how you use a large language model. Alright? How does, good good question. How does tokenization come into play? Well, tokenization, people think of it as 2 different things. So in theory, tokenization is when I put in words, chat gbt tokenizes.

Jordan Wilson [00:49:31]:
Right? Or it converts all of those words into tokens based on context. Right? The same one word can technically have 4 different kind of token values based on context. So tokenization is important, and that’s why it’s important to play with the tokenizer. I’ve done that before live on the show and showed you guys how to do it. But also that’s why prompting matters in in in the way of your language. Right? You have to be very descriptive in your language and go back and forth and make sure that chat gbt through its tokenization is understanding it. So Jay said, wouldn’t that be what a GPT would also be used for? Jay’s asking that. In theory, yes.

Jordan Wilson [00:50:12]:
I can’t get into this too much in-depth, the difference between training an expert chat versus training a GPT. Right? The problem with GPTs is the knowledge retrieval process is always changing. And personally, it is for me, it is too inconsistent right now with how it retrieves the knowledge, depending on how you set it up and how you configure it. It’s not as accurate, at least for me, someone that uses chat gbt many hours a day. It is not as accurate as putting it all in text. Right? It’s it’s kind of the, knowledge retrieval process, on your GBT can change a little bit just like, you know, it’s it’s a generative system. So that’s something, Jay, hopefully that helps. Alright.

Jordan Wilson [00:50:55]:
So priming is this. Right? Like I talked about. It is think of it like training a new employee. The same process that you go through with a new employee. So onboarding, training, reinforcement learning, feedback, testing, knowledge sharing, that’s the exact same thing you do when you start a new chat into chat gpt. Right? Alright. Let’s go to number 1. I was really trying to not make this an hour episode.

Jordan Wilson [00:51:20]:
We’ll see if I can still get in before the time limit here. Number 1, and we’ve been referencing this the entire time, but you need to talk to chat g p t like a human, y’all. Alright. So I have a love hate relationship with the term prompt engineering. Right? It’s technically fake, but it’s technically very real. Right? But but 2 years ago, 3 years ago, you know, people would would have you think it’s a science working with a large language model and that you had to be very technical. Right? Oh, you can’t use this large language model. It’s it’s for experts.

Jordan Wilson [00:51:52]:
It’s for technical people. Wrong. Right? Large language models and the way that they’re being developed and the way that they’re changing, it’s for everyday people like us. Chatt GPT is not made for experts. It is made for everyone. It is made for a 6 year old. It is made for a 96 year old. You do not have to know anything about prompt engineering.

Jordan Wilson [00:52:15]:
Think of prompt engineering as this. It’s having a conversation. Right? It is what we are doing right now on this live stream. Y’all are asking me questions. I’m trying to answer them as they pop up on the screen. Right? That prompt engineering. Are there better ways to do it? Of course. But you just have to treat chat gpt like a human.

Jordan Wilson [00:52:36]:
So it’s real, but it’s also very simple, like I said. You also have to keep in mind why you should be talking to chat gpt like a human. Well, large language models that we talked about earlier, they’re trained by humans. Right? So sometimes, I think early on, people were trying to come up with these overly structured, overly long prompts. Right? Well, hey, guess what? That can work very well sometimes. But chat gbt is not deterministic. It is generative. Right? So it is made to have conversations.

Jordan Wilson [00:53:07]:
And, you know, Sam Altman, the CEO of OpenAI has talked about this a lot in future versions of chat gbt, whether that’s gbt4.5 or gbt5. He said the reasoning is going to be much better than where it’s at now in, GPT’s ability to to rationalize and reason, right, or to understand things. Right? Again, the most important skill set right now. I was at a, venture capital event a couple weeks ago, and, a CEO asked me. He said, I have a daughter in college. She wants to get into large language models. I said, what’s the most important skill set for her? I love this question, by the way. He actually asked me this, And I didn’t has he he’s like, okay.

Jordan Wilson [00:53:47]:
She go into prompt engineering, you know, computer science. I said, yeah. You can do those things. I said, the skill set is communication. You have to be able to talk to chat gpt like a human. A good example is is Midjourney. I know. Another Gen AI system.

Jordan Wilson [00:54:04]:
Right? But Midjourney v 3. Right? You had to talk to it in prompt speak. Right? You had to use all these all these parameters, you know. Oh, I have to hit space, comma, space. Right? Like, all these very structured rules. Right? And if you didn’t, like, speak Midjourney v 3 prompting, you weren’t gonna get great results. Right? But now look, in the newest version of Midjourney, Midjourney v 6, I can talk like this. I’ve actually done examples where I just click record on the mic and I talked to Midjourney and I say, hey, here’s the image that I want this from this AI image generator.

Jordan Wilson [00:54:38]:
It does a pretty good job. You know? So think of chat gbt and large language models the same way. They’re constantly improving. And y’all, I’m trying to get you to where the puck is going, and we need to skate there together, not where the puck is at today. Let me say that again. We need to start building our skill sets for the future of large language models. And we’ve already seen Sam Altman and all the CEOs are saying that they are making all of these large language models and these generative AI systems less complex. They’re making it more for the everyday person.

Jordan Wilson [00:55:13]:
Right? I mean, Microsoft ran a commercial at the Super Bowl that showed literally everyday people getting the most out of its Copilot AI system. Right? This is the future. The future is prompting everywhere. If you’re not already prompting on a daily basis, you’re going to soon. Right? Apple’s going to be releasing Gen AI into, presumably into its smartphones, into its computers. Microsoft Copilot is starting to pick up steam and popularity. Right? So as a knowledge worker, whatever device you are on. Right? And that’s why, yes, this is about ChatGPT, but it’s about so much more.

Jordan Wilson [00:55:49]:
Talking to large language models or small language models like a human is so important. You have to have great communication skills. Right? We had an entire episode with Abram, from OpenAI. Right? An ambassador at OpenAI. He actually does more speeches and more teaching than literally anyone at OpenAI except for Sam Altman. And this is literally what we talked about. We said, you know, his example is a teacher talking to a student. Right? My example is is you’re a CEO talking to new hires.

Jordan Wilson [00:56:21]:
Same thing. Alright? To get the most out of Chatt GPT, you have to change your mindset. It is not a content creation machine. It is a business operations system. Alright? Business operation system, and you talk to it like a human, and it can do anything. So the power of written communication is through the roof. That’s why I think teachers, journalists, English majors, writers are great inside of Chat GPT because that is how not just how it works today, but that’s how it is going to work even more in the future. Alright.

Jordan Wilson [00:57:02]:
Let’s recap. This was a long episode. There’s a lot of information in here. And y’all, I can’t emphasize enough, you gotta go read today’s newsletter. So I’m gonna say it. I’m gonna say it here. Go to your everydayai.com. Sign up for the free daily newsletter.

Jordan Wilson [00:57:16]:
Check the show notes. If you’re listening to the podcast, you could sign up there. I’m not kidding. The value of today’s newsletter, it’s a long one. Right? It’s a little more structured than than this, you know, 1 hour livestream. It is worth a lot of money. I’m just gonna say that. Alright? If you understand these rules, your outputs are going to be so much better.

Jordan Wilson [00:57:42]:
Alright. Before I recap these, I actually see a very important question. Thank you for this one, Monica. So she says, what should we know about entering, proprietary or private info data into chat gbt? Great. Yeah. Let’s let’s end there before we go over all of our, recap our rules. Don’t upload any confidential, sensitive, proprietary, you know, private health information into chat gpt. Don’t do it or any other large language model right now.

Jordan Wilson [00:58:05]:
Right? The, I will say this. If you have an enterprise version, though, if you have an enterprise version of of Copilot or an enterprise version of Chat gpt, that answer might be a little different, obviously. Right? And you should be talking, you know, to your rep at open AI or your rep at Google or your rep at Microsoft to understand, how those systems are handling that data. Right? I don’t have access to, aside from Google Gemini enterprise, I don’t have access to, you know, these larger enterprise systems, so they have data handling a little different. But if you are on the free version of Chat GPT, if you are on the team versions of Chat GPT Plus or or if if you’re on Chat GPT Plus or Chat GPT Teams, you need to not upload confidential or sensitive information into Chat GPT. Great question. Thank you. Alright.

Jordan Wilson [00:58:56]:
Here we go. We’re gonna recap everything, and we’re gonna wrap up the show here. Alright. Our 7 steps. Alright. 7, use chat gpt plus, not the free version. 6, understand how large language models work. 5, use new features strategically and know what they do.

Jordan Wilson [00:59:13]:
4, keep track of memory to reduce hallucinations. 3, prompts don’t work. Don’t use them. 2, prime chat gpt before asking for an output. And 1, talk to chatGPT like a human. Y’all, this was a long time in the making this episode on the 7 steps on how to actually use chat gpt in 2024. I hope this was helpful. Shout out to Taplyo.

Jordan Wilson [00:59:42]:
Again, make sure to check out, our newsletter if you do want to win a year of Taplio. So thanks to them for partnering with us on this episode. If this was helpful, y’all, and I hope it was. Like I said, this is the culmination. I’ve spent more than 1200 hours inside of chat gbt. I’ve spent thousands of hours in the GPT technology dating back to 2020. I’ve taught more than 25 100 business leaders how to use chat gbt. I’ve answered thousands of questions.

Jordan Wilson [01:00:13]:
This was a lot of work to put this together. So if you do have questions, keep them going. Right? I’m gonna go jump in when I have time later. There were some questions I didn’t get to. If you’re listening on the podcast, thank you. Go ahead. Reach out to me if you have a question. But the biggest thing I want you to know y’all is ChatGPT is for everyone.

Jordan Wilson [01:00:31]:
It is not an AI tool. It is a business operations system. Alright? And if this was helpful, I hope it was, please consider sharing this with a friend. Please consider leaving us a 5 star review on Spotify or Apple. Or if you’re on the livestream here, you know what? This episode took dozens of hours. It’ll take you about 10 seconds to just click that repost button, please. That would be super helpful. Because you know what? There’s bad information out there.

Jordan Wilson [01:00:58]:
There’s too much bad information. There’s people trying to scam you about AI education. It should be free to all of us. It should be available to all of us. We should all have a place that we can come together, learn the facts together to grow our companies, to grow our careers. That’s what we’re all about here at everyday AI. I appreciate y’all, and we’ll see you back tomorrow and every day for more everyday AI. Thanks, y’all.

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