Transcription

So open AI came out with a thing called deep research. You might've heard of it. Yeah, it's kind of amazing. I've been using it, but you know, what's not amazing. It's price tag. If you want to use the sucker, you have to be a chat GPT pro user, which is $200 a month. Now I pay for that because I want to play with stuff, but I want you to be able to play with stuff too. So I was scrolling through Twitter and I found this guy's tweet data. No, not that data. David came up with his own open source implementation of deep research. Essentially you get the same capability without paying 200 bucks. I have to try this. So you and me, we're going to try it right now. I'll show you how to set it up. We'll do it together and we'll do a little bit of side-by-side comparing open AI's deep research to well, open source, deep research, keeping in mind this deep research is using open AI. Many three. Oh, I can't even say the thing. Open AI, many three. Hi. It's the dumbest name ever. I can't remember anything. It's using that. Get your coffee ready. Let's get started. Now, before we go crazy, let's talk about what is this deep research thing? Well, normally with AI, we get very, very quick answers, just blah, blah. And it's they're okay answers, right? Like it's good. But with this, with deep research, it's doing what it says. It's doing some deep research. It'll take five to 30 minutes to do a deep dive providing. I think people say PhD quality research. So it would take a normal person or a normal PhD person hours or days to research a topic. I'm talking in depth, like going out to web pages, reading pages, coming back and referencing others and quoting and citations, all that nerdy stuff. It does that in 30 minutes. I was talking with my producer Alex and we're like, you know, I love it when it takes longer to answer me like AI, like, you know, we're all bragging about, Oh AI, this is fast. This is so fast. I love it when it takes longer. I feel like it thought more about something. I feel like it's giving me a well-rounded answer. It's got multi-step reasoning. It's like going out to web pages, doing some data analysis, doing another search. It's kind of thinking like a human. Many people are thinking this is the first real step to AGI. And one very annoying thing about AI and the answers it gives us as we can't really trust it. Like even chat to be teased. Like, yeah. Sometimes we get stuff wrong. So what's really cool about the research is that it has citations for every, for most of the things it says, it says, Hey, don't take my word for it. Here's the link right here. That's pretty killer. And this sucker is multimodal. So you don't know if you don't know what that means. It can look at pictures. You can look at texts. It can look at PDFs. It can process all of this, these types of data. So tell you what, right now let's try a little deep research. I almost said deep search, deep seek, deep research. I'll click on my deep research button here and I'll search for a hard hitting topic research, which animal is better cats or dogs. Give me a thorough answer, a definitive answer based on science. Now what's cool is it won't just like go off to the races going, okay, got enough context. It will ask me for more context. This is also going to be available in the open source version of this. So we're getting to that here in a moment. I'll just say all of the above. Now we'll say sometimes it will just kind of get stuck here and not do anything. And I'd be like, Hey bro, you good. And he won't be kind of like what he's doing now. Oh wait. Okay. There we go. So it started the research task. Now it should even pull up a little tab on the side, on the right and show me what it's thinking any day now. I'll tell you what, we'll let that sit here. I know you want to know the answer. You're going to watch and wait. Aren't you? I'm not, I'm not even going to put timestamps. You're going to have to watch the entire video, but now let's check out this open source thing. Again, this chat GPT deep research right now costs 200 bucks. This guy's like, nah, all you're going to need is a chat GPT or open AI API key, which is not free, but it's significantly cheaper than 200 bucks a month. It's pay as you go. And he even has a nice little diagram here. Essentially here is the thought process. It's using what's called SERP queries, which I just found out because I started playing with crew AI. If you haven't played with that, Oh my gosh, video coming soon. It's so much, it's a big world. And this will also be using the Oh three mini high. I think I got it this time. So let's go to the get hub and get this set up. It's actually really quick to get the setup. We're really only going to need two things. Well, three things. We'll need a fire crawl API, which is free. Don't worry. And an open AI API will also need a node JS environment, but we're going to do that inside of a Docker container because you know how I roll. Also, I'm pretty new to fire crawl API. This thing's amazing. They do have a hosted option, which is free. Well, up to 500 credits. I'll get logged in real quick with my Google account. And seriously, it's so easy to get this API key. Cause right. When you log in, it's just sitting right here, ready for you to copy it. So make sure you have that. And then for the open AI API key, you'll need to get set up with a account with open API, open API, open AI. You'll go to platform.openai.com. You'll get logged in or sign up. Normally, I think it's connected to your chat GPT. Uh, if you already have a subscription, but the 20 bucks a month or whatever you pay does not include this, this API usage will be pay as you go, which if you're just doing this real quick for a few things, it's going to be pennies. If you're doing crazy stuff, it's going to cost you crazy money, but we're not doing anything crazy right now. But once you're logged in and you have a credit card, you can go grab your API keys. I'm going to create one right now. Now with both of our keys ready to go, we can now set up our Docker environment. Now you don't have to do it with Docker. If you prefer, prefer, just doing NPM, he shows you how to do it right here. I like Docker. It keeps things separate, secure, nice and safe. Now, if you're like, I don't know what Docker is Chuck. And, um, please help me. I've got a Docker video right over here. Go watch it, get set up, get it installed. It's very easy. It's on Mac windows and Linux. And here in windows, you do have to run it inside WSL, which is another thing. If you don't know what that is, that'll blow your mind. But I want to watch my WSL instance right here. And my video on that is right here. It's essentially Linux on windows. We'll first use the get clone command to clone the repo deep research. You will need get installed, but thankfully on most, uh, installations like Mac and Linux, it'll already have get there. If you don't got it, go get it. I'm sorry for that. I'm going to CD or jump into the deep research directory. And then inside here, I'm going to add all the stuff I need to create my Docker container. You don't need to know what Docker is just follow along, but it will help to know what it is to kind of understand what I'm doing here. First, we'll create an environment file. We'll type in nano, the best text editor in Linux period. We'll specify our file dot E and V dot local. And we're going to add two things here, our fire crawl API key and our open AI API key odd mine right now, just like this fire crawl underscore key, have that equal within parentheses, your API key. You want to grab mine, copy that key, paste it here. And then just under that, my open AI underscore key equal Mikey, where'd you go, buddy? There you are. That's all we need for that file. We'll hit control X Y enter to save type in outlast. You should see our file rep. Actually, no, you won't see it. It's hidden. Type in L S dash a L and you'll see it right here. That's what that dot does before a file. It'll hide the file. Now we're going to create what's called a Docker file. So we'll do nano Docker file just like this. And I'm going to copy and paste this configure. This is essentially describing a Docker container. We're about to build. I will have all this config below and a nice little blog post on blog.networkchuck.com with control X Y enter to save. And the one last thing we're going to create our Docker compose file type in nano Docker dash compose dot YML. We'll paste this configure. And again, this will be below control X, Y enter to save. And then because we're doing environment variables a bit differently, we'll have to change one file type in LS, right? You are right now we're going to change the package dot JSON file. So we'll do nano package dot JSON. This won't be scary. I promise. It's going to be one little file right here. The start TSX dash environment file, blah, blah, blah, blah. We're just going to backspace this a bit to where it looks like this, just like this control X Y enter to save. And now we're ready to go. Actually, all we have to do is run one command. We'll type in Docker compose. And you may have to do a pseudo at the beginning of this. I'll go ahead and do that right now. Just in case Docker compose run dash dash RM. This will actually remove the container. Once we're done with it. And then we'll call the container deep research, ready, set, go. Oh crap. We got an error. Oh, you know what? I don't know what it is. We messed up our package dot JSON file. Let's jump back in there real quick. Package dot JSON. It's not proper JSON. We didn't put a comma. You probably saw this, didn't you? We didn't put a comma after our start right here. There we go. Proper JSON. Control X Y enter to save the up arrow to run that command one more time. And come on, it's working exciting. What would I like to research? Hmm. Let's research the same thing. I would like to know what is better or what animal is better cats or dogs. And then we'll control the breadth of the research defaults to four. We'll just do four and then depth. So the first one was how wide second one's, how deep, what does that mean? Exactly? I'm not sure. I haven't, I haven't done the breadth and the depth on this yet. We're playing with it right now and it's creating the research plan. It's going to ask you actually ask me the questions that chat to BT just did earlier. Similar ones. Yeah, that's pretty cool. All of the above. Let's do data driven scientific. Sure. Okay. And now it's researching coffee break while it does it. Now I'm not sure if I've exhausted my API key usage. Let me go look. Oh no, I haven't. I haven't done anything. I haven't paid anything. This is all free. Oh, it's doing it. This is so cool. Doing things on your own hardware, which this is not our own hardware, but it's open source and we're doing it in the command line. It just feels cooler. Open AI keeps things very mysterious. You don't really know what's happening here. You do this. The code is all there. No, I'm not sure if I mentioned what fire crawl was for. If I did, my rate limit was exceeded. This is why I would probably want to run this locally, which you can do that, but I just found this like an hour ago, so I can't do it right now. Check it out. All the URLs. It did some research. We're about to see our results. Now it said, it said it's a report.md. We'll look at that here in a second, but I think, yeah, here's all the research right here in Markdown right here in our terminal. What was the conclusion? I don't want to read all this. You saw it here, folks. Dogs are better. Take that suckers. I am a dog person. Sorry, cat lovers. Let's see. Let's see if chat GPT said the same thing. It said dogs. Yes, but check it out. I mean, the research is cool. So obviously chat GPT has a prettier interface, right? We've got links right in here in line, definitely pretty wordy, but I think we've got a similar output and we can control how deep and you know, how wide this goes as well on the open source side. What do you say we do one more thing? And by the way, let me know how you feel about that conclusion. Do you agree? You know, it's hard not to agree. It's it's AI. It knows more. It can, it can now research way better than you can better than I can. Let's do an age old question. And by the way, to run this again, we'll do the same command just like this, which OS is better for it professionals, Mac Linux or windows spicy, right? Let me ask the same question over here. Let's say system administration and network engineering and cybersecurity, all of the above. Should the analysis be on a cost licensing? No, everything, everything. It's the same questions. You notice it's asking similar questions. I mean, we are both using Chad GPT. Oh three mini high. Okay. Starting research. I will say my command lines a lot faster, although I do reach my rate limits. And I bet the research would be so much better if I didn't hit these rate limits. It is so fun watching the thought process of these AI's also extremely scary, but I don't know the more I play with AI, which it feels like I've been playing with new things every single stinking day because of releasing things at the speed of light, the more I play with it, the more encouraged I am for us it people and humanity in general, it's going to make us so good at what we do. And that's the question you have to ask yourself, or this is the question you need to ask yourself every single day. How can I use AI to help me do my job better? That's how you're going to stay ahead in this. Oh, I love me a good AI. That takes a long time to answer. It feels good. All right, let's see what, uh, actually I'm going to show at the same time. So video editor, don't show it yet. Dude, Chad GPT is taking too long. I have to go pee. Come on. Chad GPT is taking so long. I got a meeting with Jeremy Chara. Hurry up. Oh, it's finally done. Okay. And the conclusion, I saw it coming. You know what? I agree with this because I do the same thing as an it pro and to build competency in all three over your career. You'll need all of them. And I'm pretty sure this is the same thing. The deep research open source. Yeah. Here it is right here for it. Professionals. I'm resizing it. Uh, it's not a single West decision. It's implementing a hybrid strategy, utilizing each system strengths while utilizing rigorous platform, agnostic security practices, blah, blah, blah. You heard it here. Folks, Mac windows, Linux, use them all. All right. That's the video. Let me know if you try this. Let me know what you think about the conclusions. And, um, that's all I got. I'll catch you guys later. Oh, by the way, this video is sponsored by no one but me and my coffee network check. That coffee is also sponsored by my Academy network Chuck Academy. What is that? I can't tell you we're still building. It's still very new. Uh, but we're building something fun and you can actually join right now. It's 12 bucks a month. It's a introductory price. Nothing crazy. Kind of think of it as a Kickstarter. We're not doing Kickstarter by the way. It's not a Kickstarter. It's just, if you want to come see the videos as we're preparing them, the courses as we're making them, if you want to get into it, that's what you're going to see there. Nothing crazy just yet. Just know, I'm about to have a meeting on it right now. Literally after this recording, I'm meeting my business partner to talk about what we're doing. I would love to have you come join me in building this. That's the video. I'll see you guys next time. Hey, real quick. No, just as I'm making this video, hugging face said, they're coming out with their own agentic framework for deep search because they want to, I guess, beat open AI. Um, it's pretty cool. You can try it. Or maybe you can't, it's like not working right now, but Hey, everyone's jumping on this and I can't keep up. So I had to add this. There's my editor. Say hi editors.