Ep 544: AI Magic – Convert Outdated Content into Engagement Gold

Topics Covered in This Episode:

1. Transform Outdated Content with AI
2. AI Tools for Efficient Document Updating
3. Google Gemini Deep Research Capabilities
4. AI Studio's PDF Transcription Feature
5. Enhance Presentations with AI Studio
6. Interactive Presentations with Gemini Canvas
7. Embedding AI in Presentations
8. Google AI Studio's Developer Features

Keywords:

Google Gemini, Gemini 2.5, AI Studio, Google AI Pro plan, Ultra plan, generative AI, convert outdated content, engagement gold, AI magic, interactive presentation, Commonplace AI tasks, Deep research, AI workflows, Google AI Studio capabilities, AI document transcription, Google Gemini Deep Research, interactive and slick interface, embedded AI capabilities, transcribe PDF presentation, factual keyword updates, targeted deep research, Google search grounding, transforming outdated documents, Canvas mode, integrate AI with presentations, automate mundane tasks, creative AI applications, AI-driven efficiency, enhancing content with AI, live AI capabilities, small language models, presentation refinement, knowledge worker efficiency, research improvements.

Podcast Transcript

Jordan Wilson [00:00:45]:
I've spent thousands of hours of my life using AI to create documents, which is kind of wild when you think about it. But, yeah, I actually did the math since, 2020, myself and my team, we've been using generative AI, large language models to create documents. But as of the last couple of months, that process has completely changed. And I think it's something that all of us, if we're a knowledge worker, if you get paid to sit in in front of your desk and, create value for a company, which is what many of us do, you probably also spend hundreds of hours a year now using AI to bring new life to old documents. It is something I think that a lot of us think, oh, well, if I'm using AI to do this, I'm doing it probably the correct way. And I'd argue you're probably not. So that's what we're gonna be tackling today on everyday AI.

Jordan Wilson [00:01:54]:
A little what I like to call a little AI magic and how you can convert outdated content into engagements gold. We're gonna be doing it live today for our new weekly series, put AI to work, Wednesdays. Alright. I'm excited for this one. I hope you are too. What's going on y'all? Welcome to Everyday AI. My name is Jordan Wilson, and I'm the host. And if you're trying to grow your company and career with generative AI, you are in the right place.

Jordan Wilson [00:02:23]:
We do this every single weekday, Monday through Friday with our unscripted, unedited daily livestream podcast, and then putting it all out in our free daily newsletter. So, if you're trying to grow your company and career with generative AI, you are definitely in the right place. So if you haven't already, please make sure to go to your everydayai.com. Sign up for our free daily newsletter. We're gonna be recapping everything that you need to know from today's episode in that newsletter. Alright. If you want the daily, AI news, sometimes we go over that on the live stream. Just go check out the newsletter today.

Jordan Wilson [00:02:55]:
But let's get straight into it. And and you all wanted this FYI. You said, hey. Yes. Let's do this new, this new weekly segment here on Everyday AI where I show you how I'm using AI for, my company here at Everyday AI. Or I might do just some other demos. Maybe they're not as applicable, but you all said overwhelmingly, yes. Once a week, let's show up on Wednesdays and learn together.

Jordan Wilson [00:03:19]:
So if you're on the podcast, I'm gonna do my very, very best, describing this. But just so you know, we always put a video. Yes. This is an unedited, unscripted. It goes out on video as well. So, make sure to check the show notes in your podcast. This is one of those. It's gonna be a little bit visual at the end if everything works.

Jordan Wilson [00:03:37]:
Right. Love doing live demos with generative AI. Nothing ever goes wrong there. But this might be one of those after you listen to it on the podcast. You're like, wait. I have to see how that's done. So make sure it's gonna be in the newsletter as well, but make sure you can go watch that video. So here's the problem that we're gonna tackle.

Jordan Wilson [00:03:53]:
And if you think about your work, right, don't pay as much, attention to the actual example that we're gonna be going over today. But I want you to think about your work. How much time do you spend updating old documents or repurposing old content and you're using AI? And I think sometimes we fall into this, false sense of security. Like, oh, well, as long as I'm using AI at some part of the process, I'm probably, you know, being efficient. And are you? Maybe. But I feel that there's so many new features, that the big AI companies have rolled out in the last just, like, last two months alone that have honestly kind of even challenged me for someone that's like I said, I I've used generative AI since 2020. And and I'm even having to rethink and rework my current workflows, but the average person, if you're a knowledge worker, you're spending probably hundreds of hours a year, whether you know it or not updating old content and probably using AI to do it, or maybe you're not. And if you're not, then this is really gonna be helpful, and just doing it sometimes manually.

Jordan Wilson [00:05:05]:
And when I say manually, yes. Even if you're using AI as part of a workflow, I think so many of us are still doing many manual steps. So, today, if you stick around for the next, you know, twenty five minutes, I'm gonna try to make this one a tight one. Here's exactly what we're gonna learn. Here's what we're gonna go over. We're gonna use AI Studio to transcribe a visual PDF presentation. I'm gonna tell you why that's important. We're gonna perform a targeted deep research based on that content with Google Gemini.

Jordan Wilson [00:05:34]:
We're gonna use AI Studio, Google's AI Studio, to bring factual keyword, factual new life to an older presentation, and we're going to embed get this. We are literally going to embed live AI capabilities into this presentation. Yeah. We're essentially gonna build a piece of AI software from an old document. That's why I'm calling this episode AI magic because it is literally so easy to do now. And I think this new announcement from Google literally got swept under the rug. Like, no one's talking about this, and it's actually pretty amazing. So stick around.

Jordan Wilson [00:06:13]:
That's exactly what we're gonna do. But before I go in and we're gonna start working through this live, I want you to think, especially if you're on the podcast. What's that one thing you do? Right? The one thing you do maybe, every day, once a week, couple times a month, handful of times a quarter. Right? Maybe you're up, you know, maybe you have a an onboarding form. Right? You know, or you create your company's onboarding, but there's new state laws. You have a new employee handbook. So you're kind of having to pull information from multiple documents and updating an old document, and then you're probably having to look up some information on the web as well. And maybe you're using, you know, ChatGPT to, you know, pull something from these two documents, and then you're using Google Gemini, to help you expand one, and then you're, you know, using perplexity to help you research.

Jordan Wilson [00:07:03]:
And, yes, you can do that. But I want you to look at the process we're gonna go over today. You you know, it's not, fully automated. Right? I'm not gonna, you know, sit here and build an automated workflow and, you know, with, you know, agentic AI sprinklings. I wanna do something very simple, very basic. You don't need to even have any experience. Alright? I'm gonna walk you through how to do this. And the crazy thing is most of this can be done even if you don't even have a paid account.

Jordan Wilson [00:07:32]:
Right? But even if you just have the basic, Google Gemini, pro plan, dollars 20 a month, or if you're a student, it's literally free for the next year. All right. That's all you need. So again, I want you to think, what is your use case before we go any further? I want you to think, do you have that use case yet? All right. I'm gonna take a sip of coffee because this one's might get a little wild and I want you to have your use case even. Hey, if you're following on the live stream, go ahead, do this live with me. Pull up Google AI studio, on your computer if you want. So that's just a istudio.google.com.

Jordan Wilson [00:08:09]:
Pull up Google Gemini as well, and then we're gonna get into it here. So let's start live. Okay. So I'm going to show you exactly what we're gonna be trying to do here. And, live stream audience, let me know. Can you see my screen? I think you can. But if you could let me know, I always appreciate it because one time I was going on for, like, eight minutes, and then I finally looked in the comment section and someone's like, oh, Jordan, we can't see your screen. You'd think after five hundred and forty times, I would have this down now.

Jordan Wilson [00:08:44]:
But, yeah, sometimes when you're just doing these live demos, you you know, they play tricks on you. Okay. So here's what I'm trying to do. Right? I said, hey. What is your use case? What old document do you want to bring new life to? Do you wanna make interactive? Right. That's another thing with generative AI. I think we have to relook at how we present information whether that's internally or externally. Right? I think so many things that even used to be boring PowerPoints.

Jordan Wilson [00:09:08]:
Right? They can be interactive websites. That's essentially what we're gonna do now. We're gonna turn an old boring website. We're gonna use AI to quickly, update, validate, expand that information. And then we're gonna not just make it interactive, but we are literally going to add AI elements to it. Right? Crazy. Alright. So here's where we're starting.

Jordan Wilson [00:09:29]:
I did a presentation, last year. Okay. So live stream audience, you should see this on my screen here. I did an episode called small language models, what they are, and do we need them? I believe this was, I should've looked this up probably about two years ago, maybe a year and a half ago. So, what I'm trying to say is I wanna do a new, presentation. I wanna do a new episode on small language models, and this is, you know, the outline is pretty good, but I know a lot of it's gonna be old, and I also wanna make this a little better. Okay. So that's ultimately what we're gonna be doing here is we are going to be, turning this old presentation into something better, something interactive, but we need to completely change and update the content, because the content in here.

Jordan Wilson [00:10:17]:
Right? So, you know, it's, what is a small language model? 14 facts you need to know. Right? So I go through here. And although the definitions necessarily haven't changed, a lot of the information in here is now extremely outdated. Okay. So we're gonna bounce around because, certain things take a little longer. Alright. Now I kind of have some, copy and paste prompts ready. So what we're gonna do because this is what's gonna take the longest, I'm gonna go into Google Gemini.

Jordan Wilson [00:10:45]:
So that's just gemini.google.com. I'm gonna click the deep research option here. Alright? And I'll, talk you through deep research as this starts. I just put a prompt in. I'm gonna read it out loud here in a Google Gemini is, creating a plan on how it's gonna do deep research. I'm gonna have to approve the plan, and then we'll, I'll be able to talk through, that once we get or actually, just let me tell you the, the prompt right now. So, something simple. I'm actually gonna click start research.

Jordan Wilson [00:11:17]:
So I said, put together or sorry. Please put together, a comprehensive report on month by month happenings of small language models in 2025. Be detailed, accurate, finding examples, understanding trends, etcetera. So, again, nothing nothing crazy there in the prompt. Essentially, it's just being like, hey. Go find month by month what has happened with small language models in 2025. Because like I said, I think this presentation is either from late twenty twenty three or early twenty twenty four. And regardless, I know large, small language models have changed so much in 2025.

Jordan Wilson [00:11:55]:
I don't even want information from 2024 or something like that in this new document. Right? When I'm doing a new episode, on everyday AI, I do like to understand, historical trends in content, context. Right? But I don't like to present old information. This is one of the things. Right? As we do this AI work, you know, put AI to work on Wednesdays. I want you to kind of go into my head because people will always be like, oh, Jordan, like, how do you use AI? Right? This is one example. I have much more complex and automated workflows, but, I wanted to start with something simple. Even though there are some manual steps here to put these different pieces together, I wanted you to kind of see what we're doing.

Jordan Wilson [00:12:38]:
Okay? And if you haven't used, Google Gemini's deep research recently, it is really, really good. Okay. And here's why. Because back in, what was that? That was February, I believe. I should know that. When was I in, when was I in Las Vegas for Google IO? When was that? February I I can't even see it now. May. No.

Jordan Wilson [00:13:07]:
No. I wasn't at gosh. This is why I need to sleep more, y'all. I wasn't at that one. I was at Cloud Next. Alright. That was in April. Alright.

Jordan Wilson [00:13:15]:
There we go. So, Google updated their deep research in April with Google Gemini 2.5 Pro. This is, by all really measurements, the most powerful model in the world. Google even updated it, last week even though it was the most already the most powerful model in the world by almost every single benchmark imaginable, including blind the kind of blind taste test that is, LM arena. So one thing when they updated their deep research, they made it much, much better. So if you don't know what deep research is as we do our, like, let's put AI to work. Remember what perplexity was, right, like, a year ago? Think of that times a thousand. But the difference is, this is, using a thinking model.

Jordan Wilson [00:14:00]:
So, Google Gemini 2.5 is obviously a hybrid model. So when it needs to think and go very slowly and plan, like a smart, researcher would, it will do that. When it needs to just be fast, it'll do that as well. So, I can go here and it is thinking about the research. Right. So I can go through. I'm not gonna read this, but it's actually thinking about my very simple research prompt I gave it, and then it started to do a round of research. So it looks like it went, to about 10 websites.

Jordan Wilson [00:14:30]:
And then after going the to those 10 websites, it actually started to reflect and think of the information that it found on those 10 websites Right. Pretty interesting here that, out of the 10 websites, it went to a lot of Microsoft websites, which I find interesting. Right? So, you you know, in this use case anyways, even though I think Google's Gemma three, Gemma's Gemma three n is the best small language model, It's actually looking at, information from all across the web. So right? So, I do like that about Google Gemini. It's not just, you know, saying like, oh, Google's, you know, small language model is the best even though it pretty much is. Alright. So then it's finding this information and then it's saying, hey. Based on all this information, I've actually now figured out I have to go research more.

Jordan Wilson [00:15:16]:
So it went out to 10 different websites. It thought about it. It reflected on what it found in its research based on my original query, and then it decided, yo. I actually need to go find way more information. Alright. So then it went out to, looks like another, 12 or 15 sites. Same thing. Right? So, it is agentic in its nature.

Jordan Wilson [00:15:36]:
Right? So, I didn't have to do a lot of, tricky prompting in order for it to accomplish this level of research. Right? So, as we're scrolling through, live stream audience is seeing it. It's doing this now. That's seven times, eight times, and it's still going. So we're gonna we're gonna let this finish because we're, eventually gonna use this information in part, to partially update our presentation. But now you have the part of, of our little, AI magic, tutorial here. Alright. Before we get going, have to pause for a word from our sponsors at Google.

Jordan Wilson [00:16:15]:
This podcast is supported by Google. Hey, everyone. David here, one of the product leads for Google Gemini.

Google Gemini [00:16:22]:
Check out v o3, our state of the art AI video generation model in the Gemini app, which lets you create high quality eight second videos with native audio generation. Try it with the Google AI Pro plan or get the highest access with the Ultra plan. Sign up at gemini.google to get started and show us what you create.

Jordan Wilson [00:16:46]:
Alright. So this is probably gonna take, another couple of minutes. So I'm gonna move on to our next step, and then we're going to check back on this deep research. I do find and this is not just with, Google, Gemini, same thing with chat, GPT, other platforms. Sometimes the deep research looks like they stall out, but it actually doesn't. So if you're ever, like, looking, kinda like on my screen, it's like, wait. Is it still going? A lot of times, what you can do is just, there should be a toggle here kind of like, you know, it looks like a clock, and you can make sure it's like, okay. Is it still moving? Is it not moving? I've had this happen with just about any platform that does deep research.

Jordan Wilson [00:17:27]:
You can always just refresh the browser, FYI, and you're not going to kind of lose your work or lose your place. Alright? So what is ultimately is gonna happen once this Google Gemini deep research is done, we're gonna have a document and then we're gonna use that inside Google's AI studio. Alright. So let's go ahead and jump into AI studio, right away. So if you don't know Google AI studio, right now it's free. Right? I say right now because there's rumbling is on the Internet that, you know, Google is eventually just gonna move away from, this kind of free model, and you're gonna have to use your own API key. But y'all, I've been and I've been saying this for literally months on the show. I feel criminal how much I've been using Google AI Studio.

Jordan Wilson [00:18:13]:
I mean, I should actually do the math and see, oh, if I was paying for this, how much? But I've been using it. Yeah. So sorry if I'm one of the you you know, I'm sure there's a lot of people like me, who use this for a lot. But Google AI Studio, it's technically made for developers. Right? But I'll say this. Over the last six months, a lot of the features, the user interface, the user experience, it's actually made it a lot more beginner friendly. So even though this is technically a platform built for developers and there's gonna be some settings in here in AI studio that you're like, wait, what is this? Don't worry. It's actually very simple.

Jordan Wilson [00:18:52]:
And I'm gonna just show you the basics of how we're gonna be using it. Alright. So I have a simple, kind of prompt, that I have ready here. And I'm gonna start reading this and uploading a couple of files as we go along. Alright. One other thing to to to know on the right hand side of Google AI Studio, there's gonna be a lot, especially, if if if you are a beginner or at least a beginner in AI Studio. You might not understand all these things, right, but there's a different, you know, the model drop down. You can use the different, the different models up there.

Jordan Wilson [00:19:23]:
We're gonna use, obviously, the newest version of Gemini 2.5 pro preview, six zero five. So this is only, like, three days old now. There's something temperature. That's essentially the creativity, so you can turn that down, and, you know, it's gonna kind of take away the creativity or you can turn it up. It's gonna be more creative. There's some other toggles here such as structured outputs. You know, if you want, always Google Gemini, or sorry, Google AI Studio to, you know, output something in a structured way, you can go and build that. We're not really gonna do any of that.

Jordan Wilson [00:19:55]:
The only thing that we're gonna toggle on here is we're gonna toggle on this grounding with Google search. So all that means is, yes, we're telling Google AI Studio, hey. You can go use Google. Right? You can go use the web, as well as the model that you're using in any information that you're gonna be inputting. Alright. I do have a little bit of a long prompt here. Don't worry. I'm gonna explain what we're doing.

Jordan Wilson [00:20:18]:
Alright. So I'm saying to AI studio, I'm sharing two PDFs with you, a presentation PDF and a research PDF. So the research PDF is still, being made, right, inside this, let's see if we're done. Still not done, but looks like it's almost done. So we're creating a research PDF from the Google Deep Research. Alright? And then the presentation PDF is this older, version. Like I said, this is the old small language model presentation. So a lot of times, when I do these live streams, I have a set of slides on the screen.

Jordan Wilson [00:20:54]:
So, know, when I say it's unscripted, you know, I have, like, bullet points. Right? But I'm just talking not, like, off the cuff, but I'm talking unscripted. But, you know, I generally have, some, kind of slides to show the, to show the live stream on it. So I'm telling Google AI Studio, these are the two documents that I'm uploading. And then I'm telling it, ultimately, I want you to update this content for a new presentation, because I'm saying the presentation, small language models, presentation PDF is a PDF pres of a presentation I gave nearly two years ago. The PDF is a research PDF called, then the name, and I'm saying this is a starting point for updating the presentation, a starting point. Alright. So I'm saying I would like you to do a couple of things.

Jordan Wilson [00:21:38]:
please transcribe the PDF presentation called small language model presentation PDF. Because guess what? How many times how many times have you been handed a presentation, a document, right, and it's your job to, update this now? And you're like, who put this together two years ago? No one knows. Who has the original, you know, PowerPoint file? Who has the original, like, PDF? Who like, who has this doc? Right? Who has the the Google slides? And no one knows. Right? And then you're like, oh, great. What am I supposed to do? Alright. So this is again one thing that the newest models, even six months ago, the base large language models were not very good at this. Now they are. So we're gonna have, Google Google Gemini inside Google AI studio transcribe the PDF.

Jordan Wilson [00:22:26]:
Here's why this is actually important and pretty impressive. This PDF is a bunch of images. Right? So it's literally gonna use computer vision, go through and grab all of this text. A lot of this information and you'll see here, like, as an example, slide three is just a screenshot from our website. But it's just this is a bunch of JPEGs. It's it's not like a proper PDF I created in Canva. It's a bunch of, like, images, screenshots. Right? And Google AI studio is actually gonna go through using computer vision.

Jordan Wilson [00:22:59]:
Yes. There's some text that it can, in theory, use a process called, like, OCR to grab that, but it's gonna use computer vision to grab all this as well. Alright. So that's an a huge win right there to be able to transcribe that entire PDF. Then, I'm telling it I need the transcription verbatim. Then I'm saying number two. Next, please analyze the document called research on small language models twenty twenty five PDF. Right? That is the, the document, that I am creating in this Google Gemini deep research.

Jordan Wilson [00:23:32]:
As I jump over, we are done. Great. Alright. So Google Gemini put this doc together. I'm going to go ahead and export it. Alright. So it's opening now in Google docs. That's a feature.

Jordan Wilson [00:23:44]:
I'm going to go ahead and rename this. Alright. And I'm going to save this as a PDF. Alright. On my computer. So again, I'm doing this all live. I have the old presentation saved. I have the new information saved.

Jordan Wilson [00:24:00]:
Alright. And actually, for use of time, I'm gonna start this prompt, as I finish it. Right? I wanna make sure that I have both of my files uploaded. Alright? So it's up it's uploaded. I clicked on the grounded, grounding with Google search, and I'm gonna go ahead and get this going. Alright. So let me tell you, kind of read out loud the rest of what I told it to do. So again, I said, here's the the old PDF that's the presentation.

Jordan Wilson [00:24:34]:
Then I said, here's another PDF that's the base of the research. Then I'm saying, you need to fill in the gaps on what additional research or clarification needs to be done. You should research deeply on the subject to understand trends. Focus on finding additional information from May 2025 to June 2025. So if you remember, originally, I told the Google Google Gemini Deep Research to focus on 2025. Okay? But now I'm telling, Google AI Studio and the Gemini 2.5 pro model inside Google, AI Studio to just focus on the last, like, five weeks. Right? Because it's been absolutely nutty. But I'm also saying, you need to look.

Jordan Wilson [00:25:17]:
Now you need to do a a separate thing here, because the deep research, I didn't say here's my old presentation. Here's what I'm trying to do. Now inside Google AI Studio, I am. So this is someone again, this I've spent thousands of hours in my life doing this, essentially combining, you know, two to3 documents and then doing additional research to fill in those gaps. Right? So if you've ever done anything, in, you you know, analytics and marketing, content creation, business, you know, business intelligence, you probably do a lot of, you know, document juggling. It's something that so many knowledge workers spend so much time. But I'm telling it, you need to go find the gaps and then you need to go addition go do additional research that's just information from May 2025 to June 2025 to understand the current state and clarify any questions you have. And then I'm saying essentially, number four here is after this extensive research, you need to update the presentation outline in its entirety.

Jordan Wilson [00:26:15]:
So in part of the step, it's gonna spit out the old presentation verbatim. It's gonna go, analyze the two documents that I upload. It's gonna go do additional research based on the holes and the gaps that it identifies based on what I told it to do. And then last but not least, it is going to spit out a new version of that presentation. Alright. So again, I just clicked, go on this about, two minutes ago. It's already done. Alright.

Jordan Wilson [00:26:41]:
So, you can always click, and I always, encourage people to do this. You should be reading the chain of thought or the summarized chain of thought here. Right? So you can understand, what the model is doing. And a lot of times what you'll see is it's gonna start to do something you're like, wait. That's not exactly what I wanted it to do. Right. And it's still gonna kinda finish the task and adjust on the fly. But this is the only way that you're gonna get better working at large language models.

Jordan Wilson [00:27:05]:
And one of the ways I'm being honest. Right? Because even this version of Gemini, 2.5 pro preview, the six zero five version, it behaves much differently than the version that was released a month ago, the five zero six. I know that's different. You're difficult. Right? May 6 versus June 5. It behaves differently. So the only way that you can really know and understand is by kind of reading this chain of thought. Anyways, it goes down here.

Jordan Wilson [00:27:32]:
It says, I'm building a framework. I'm developing a presentation. I'm synthesizing foundational details, focusing on presentation refinement. Again, this is what Google AI Studio is doing under the hood. And then it says, focusing on presentation refinement. Again, a lot of that summarizing recent updates, because again, I grounded this in Google search. So it's going out and it's finding new information. So here on the outputs or the deliverables, here's what it's giving me.

Jordan Wilson [00:28:02]:
we have the verbatim transcript of the original or the older small language model presentation dot PDF. Remember that, what was it? Page three. Right? That was just a screenshot. Right? JPEG. Yeah. It did that. It went through. It said a grid of images with the following labels.

Jordan Wilson [00:28:19]:
Yeah. So it's very right. Today's large language models are extremely impressive at their ability to accurately, be able to see and analyze and create transcripts from very long, PDFs. Alright. So part one, perfect. It went through. It properly, transcribed the old PDF. Parts two and three, it did some, it says it did some research.

Jordan Wilson [00:28:43]:
So you can go through and read that if you want. And then part four, it is the updated presentation outline. So this is great. Alright. So, I'm not gonna go through and read all this right now. Maybe I'll go through and, you know, put the the human in the loop later, and and look at this a little bit and refine it and maybe do a new updated, episode on small language models. So yeah. I don't know.

Jordan Wilson [00:29:05]:
Live stream audience. If you wanna see that, just type in small. You know? If enough use say it. I don't I don't know. I don't know if if you guys are super interested and wanna learn more about small language models. Anyways, so it went through, and it did it very, very well here. So, so I'm looking. Okay.

Jordan Wilson [00:29:23]:
Page two, redefining the small in small language models. This is good. Right? Because it's saying, you know, how the definition, has evolved of what a small language model even is, which is, you know, super interesting with some of the more, recent small language model. So I'm I'm going through here, and I'm looking, in at least on glance, it looks like this is pretty accurate. So, you know, we have the Gemma three models that were just updated and released, the Microsoft five models, including five four. So I'm seeing it did a lot of good research, and it did additional research as as well. So not only pulled in the information that I gave it from the deep research, but I can see according to the citations in here, by looking, at the kind of, the output is I can always click on this information. So it's citing things.

Jordan Wilson [00:30:13]:
Right? So I clicked on this and it went to a a website, you know, customGPT.ai. Right? So I see not only did it go through, number one, it transcribed my old PDF. Number two, it looked at the additional research that I did inside of Google Gemini deep research, but I see it also by grounding Google AI Studio in Google Search. It went out and filled the gaps because that's important. Right? Because I almost like it was like handing it off to another assistant. It was handing it off to another person. Be like, yo. Here's a bunch of work.

Jordan Wilson [00:30:45]:
You need to double check everything. You need to find the gaps, and then you need to go out there and explore and find the gaps. Alright. This is a lot. We're not done. I said I wasn't gonna keep you for too much longer. So the last step that we're gonna do, two steps. We're gonna turn this into an interactive presentation, and then we're gonna add AI.

Jordan Wilson [00:31:00]:
And I'm gonna challenge myself to see if I can do this for in in less than five minutes. So, this is one of those times it's like, alright. Shut up, Jordan, and let's put AI to work on Wednesday. Alright. So all I'm doing podcast, podcast, crew here is I'm copying and pasting, these new updated slides. Alright. So it looks like it gave me kind of nine slides. Perfect.

Jordan Wilson [00:31:21]:
So I'm copying that. I'm going back into Google Gemini. I'm opening a new chat. I'm making sure to have Gemini 2.5 pro. I'm pasting all of this information in. Okay? I'm clicking the canvas mode. That part's important. Alright.

Jordan Wilson [00:31:36]:
And I think I have a little bit of a prompt here. Something simple. Right? You know, and then be great at prompt engineering or know anything tricky. All I'm saying is turn this content into a more interactive and slick interface, include everything verbatim. Okay. So I did do one test of this because I was just kind of curious, and it turned out really, really cool. Alright. So, the thing with generative AI y'all is it's generative.

Jordan Wilson [00:32:02]:
It's a roll of the dice. It's gonna be a little bit different each and every time. So this is now we have canvas mode inside Google Gemini. So if you don't know canvas mode, you know, a lot of the big, large language model players have something like this. So OpenAI also, their mode is called canvas. I think, Grok, has their version. Perplexity has labs, which is kind of different, kind of the same in some ways. Right? It can, go go do research and, build apps.

Jordan Wilson [00:32:31]:
You know, Anthropic has a very popular, version of this called artifacts. But, essentially, what's happening on my screen right now is I pasted in all this information, and it's building something with code. All right. And you'll see now it's done. Right. So it took like all of thirty seconds, and this is really, really good. I, I hate to say this looks way better than my website. It essentially created an interactive presentation.

Jordan Wilson [00:33:00]:
So it says small language models in 2025, the year of on device agentic and specialized AI. And then the subhead is how efficient powerful models are moving from the cloud to your pocket. Then it says Jordan Wilson, founder and host, everyday AI. It even put the, the the the website there, youreverydayai.com, at the bottom. Really, really good. The thing is, this made it interactive. I see this little slide, thing right here. So I could if I wanted to, instead of doing my my old and ugly kind of slides that I build in Canva, I could literally just do this.

Jordan Wilson [00:33:34]:
Live stream audience. Number one, have you used Canvas before? Number two, are you impressed with this? If you're not, just wait. So, let me slide through. So when I click next, it's actually really nice. Okay? There's this nice little slide animation. Right? I didn't have to build any of this. It actually looks like the branding looks pretty cool. Right? It's kinda dark.

Jordan Wilson [00:33:59]:
It's got these pops of colors. The main page had this, like, gradient. Like, it looks really, really good. Like, this especially the title page, this looks like a designer, like an actual designer made it. There's literally a gradient, layer across the text. It's it looks really good. When I go slide to slide, there's a nice, transition. There's a there's an, an outline box.

Jordan Wilson [00:34:24]:
This looks like I use, like, a high end template or I paid a designer to put this together. It looks really, really good and then it's interactive when I flip. Alright. So there we go. So we're not done. We're not done here is something. And this is one of those things. Remember I said, this little thing got swept under the rug and remember I said, wait, we're going to not only update an old presentation with AI more efficiently and more effectively.

Jordan Wilson [00:34:52]:
And we're going to create something that's interactive, but we are going to embed AI capabilities into it. And guess what? With Google Gemini one click. So it's very small. This is one of those features. I wish that Google literally just did a full, like, keynote presentation about this at IO. It was part of their presentation, but it shouldn't been like a main feature. This is wild. All right.

Jordan Wilson [00:35:16]:
So it just says add Gemini feature. So it's this little, you know, button in the lower right hand corner. I'm going to click it. That's all I have to do. So now I have in, well, not now in like probably thirty seconds, I'm going to have AI capabilities embedded in this presentation, and then I will be able to share this with people. Alright. So it's telling me what it's gonna do. So it says summarize slide.

Jordan Wilson [00:35:43]:
So it says summarize slide. Click this to get a concise AI generated summary of the key points on the current slide, and then it says, deeper dive. This button uses the slides headline to ask the Gemini API for more detailed information. So, that's pretty cool. It doesn't look like it's done yet. So I don't know if you understand what's going on, but think of all the different AI tools that you've used before. Right? A lot of them, you know, they're using either the Google Gemini, the OpenAI, the anthropic API to bring some sort of AI functionality to a website or a SAS that you use. We literally just did that in one click.

Jordan Wilson [00:36:25]:
All right. So let's see an example. All right. So I'm going to go to, page two. All right, here we go. So before okay. It's still an interactive presentation, but now I have AI capabilities built into this thing, and I didn't have to write a line of code. Alright.

Jordan Wilson [00:36:43]:
So I can literally just click this summarize slide button here. Alright. And it did this nice little, you know, animation. It says contacting Gemini. Alright. And it gave me a, kind of shorter, and more like in kind of plain English definition. Right? So it just simplified, my content, that was maybe a little more in-depth, maybe a little more technical. And then there's also this other button called deeper dive.

Jordan Wilson [00:37:11]:
Alright. So let's see what what happens here. So this one, it says contacting Gemini. All right. We'll see what the deeper dive, version does. Maybe it's just going to make it much longer. All right. We'll see what happens here.

Jordan Wilson [00:37:26]:
So, yeah. Live stream audience. Thanks for sticking with me. This one to take it a little longer. It's doing a very deeper dive. Oh, wow. Oh, geez. Okay.

Jordan Wilson [00:37:36]:
This went like super deep just on this one slide. Okay. Yeah. This is pretty impressive. So, this slide, was on, kind of the the moving goal posts or how the definition of a small language model is changing. Alright. So the, the one button made it much shorter. The button made it much much longer.

Jordan Wilson [00:38:03]:
So I could go through here, I believe in text prompt. Let me actually see if I can do this. I'm gonna say instead of, summarize slide and deeper dive, I just want a chat box, where the user can ask questions of Gemini slash the slide itself. Alright. So I I think I've done this before. I don't know if this is going to work, essentially updating, the, kind of the AI embedded capabilities. We'll see if it does or not. I actually don't remember.

Jordan Wilson [00:38:42]:
Hey. But this is why we do these things live. But, let's see. It says, of course, I can make that change. I've replaced the summarize and deeper dive buttons with a single collapsible chat widget in the bottom right corner. Now you can use the ask Gemini button to open a chat window and ask any question you have. The AI's responses will be contextually aware of the slide that's nuts. Contextually aware of the slide you are currently viewing, allowing for a more more natural and interactive q and a experience.

Jordan Wilson [00:39:13]:
Alright. So it is again, y'all, I've written zero code. And if you'll see here inside the canvas mode, it is writing the actual code here, live. Right? So, there's hundreds of lines of codes, of code, and then in the preview window. So this is what Gemini, one of the features of Gemini canvas, which is very powerful, feature by the way. Just one of the features. So it essentially wrote the code for me, and now I'm previewing it. So let's just do an example here.

Jordan Wilson [00:39:44]:
Let me go to that same, slide two. So it says the small language model, a constantly moving target. Alright. So now I'm gonna say ask Gemini. Let's see if this works. Okay. Cool. Alright.

Jordan Wilson [00:39:57]:
So I'm not even gonna say I'm gonna say explain, this slide in basketball terms. Keep it simple. Alright. So let's see if this, let's see if this works. So, literally live stream audits. It embedded like a legit, like chat bot into this presentation, where it looks like I can just chat with Gemini. So let's see if it is contextually aware. So this slide is about how the definition of small language models are changing.

Jordan Wilson [00:40:29]:
So it said, okay. Let's break this slide down using simple basketball analogies. Think of the small language model as a small player on a basketball team. Small keeps changing. Then being a small player used to mean you were really short, like, maybe under six feet. Now the definition has changed. We now consider some players small players even if they are quite taller, like six foot eight. It's very true.

Jordan Wilson [00:40:54]:
Right? It's very true. Like like, thirty years ago, you know, if you were a a a small forward in the NBA, you could be, like, six foot five. Now if you're a small forward, you're, like, six ten. So that's a great explanation, just on how even you know, I'm straight up flabbergasted. Do you see now when I, like, when I encourage you all, this took no time. You know, 90% of it is me blabbing on, right, trying to do a good job, you you know, describing how to do this step by step, but I could have done this in less than ten minutes. Right? Yes. You still need the human in the loop.

Jordan Wilson [00:41:34]:
I would have spent more time on the front end, more time on the back end. But the majority, 80% of the work got done in less than ten minutes, and it is extremely impressive. If you would have even told someone like me, someone that's covers AI every day for two and a half years, that something like this would be possible, that I could go find my old documents, just hand it over, dump a bunch of information that there would be an agentic thinking model that would go pull information from multiple documents, do additional research, spit out something great that then I could use inside a a similar platform, and it could build an interactive presentation and embed AI in there? Alright. How is that for putting AI to work on this Wednesday? Alright. So, I hope I hope this was helpful y'all. So, I think you all said you wanna keep doing this thing on Wednesdays. So let me know, option one, option two, option three. What should we do next week? Do you want to do option one, NotebookLM, advanced workflows? If you want that, just type option one.

Jordan Wilson [00:42:44]:
I'm also gonna have this in our newsletter. So at youreverydayai.com in today's newsletter, you know, make sure you go vote. Option two, co creating with Gemini canvas mode or option three, building useful AI dashboards for nontechnical people. Alright. So what do you wanna do next week? It's up to you. I work for you. I hope this was helpful. If so, please, if you haven't already, go to youreverydayai.com.

Jordan Wilson [00:43:12]:
Sign up for the free daily newsletter. That's where right. We can learn all we want, you know, watching this live, you know, learning together with our livestream audience, podcast audience. Appreciate you guys. But where you leverage this is the newsletter. That's where I go I go, like, write this with my fat fingers. Right? And I'm gonna say, hey. According to everything we talked about here, here's the most important, insights, and here's actually some new additional information that maybe we didn't have time to get to in the show.

Jordan Wilson [00:43:41]:
So we do that every single day on the website, youreverydayai.com. I hope you go put AI to work for you today, this Wednesday. I can't emphasize enough how much just simple practice. Right? Simple practice doing this every single day, and it's hard to keep up with everything. But that's what we're gonna be doing on putting AI to work Wednesdays. Thank you for tuning in. If this was helpful, please repost this, share this with someone, and I hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.