EP 109: LLM Showdown - ChatGPT, Bing Chat, Google Bard, Claude 2 and Perplexity

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What is the best large language model to use? Should we be using ChatGPT, Google, Bard, Microsoft, Bing, or something else? Don't worry. Today we're going to tackle that and talk about probably the five most popular models and maybe put that question to rest and showing you the pros and cons of each of those. So welcome. My name is Jordan Wilson and this is Everyday AI. This is your daily livestream, podcast and free daily newsletter helping everyday people like me and you not just learn about AI, but how we can actually leverage it. All right, so I'm extremely excited today. Thank you. If you're joining us live. So if you are new to generative AI, or if you have a lot of questions about large language models, what they are, how they're used, which ones are best, this is definitely the show for you. If you use large language models every single day, I hope you can join the conversation, Drop in, let me know what your favorite large language model is. And as a reminder, if you're joining us on the podcast, check the show notes. You can always come in, click and come join this conversation that we mainly have going on LinkedIn and other places. But if you're an avid podcast listener, go ahead, come join us. All right, so good morning. Thank you everyone for joining. Extremely excited today for a little large language model showdown. And as a reminder, like I said, if you're catching us on the live stream, make sure to sign up for the free daily newsletter. Maybe if you're on the podcast, come join us on the live stream. We do each and every single day, 7:30am Central Standard Time, we go live and then we put it out on podcasts and shoot the newsletter out shortly thereafter. All right, so before we get into diving into all things LLMs, large language models, let's first quickly take a look at what's going on in the world of AI news. We do this every single day. So first, Pika Labs has released some new features. So the text to video platform and Runway competitor released some big updates. So, so Pika Labs AI Video generator has two main new features. So one is video typing and the other one is the ability to embed a company logo into a video. So video typing is essentially being able to insert text or words into an AI generated video and then also the option for the logo. So pretty cool. And we'll probably do an AI in five on that next week. All right, next, traditional stock photo giant is getting into the Gen AI game. So Getty Images is partnering with Nvidia to start offering AI generated images. So Getty has released their own AI photo generated tool called Generative AI by Getty Images. Not the catchiest name, but maybe, maybe they'll work on that. So currently it is paywalled on the Getty website and also it looks like it's going to be available through an API as well. So interesting development there, especially as Getty famously took Stability AI, another AI image generating company, to court for allegedly misusing their copywritten photos. But now they're embracing the tech. All right, Spotify is going all in on AI. So some recent updates which I think we shared about in the newsletter, but I wanted to talk about it here on the show. So they're allowing podcasters to replicate their voice with AI and to translate them in other languages languages. So maybe everyday AI will be coming to a language closer, closer to your home. Also, Spotify has slightly reversed course and said it won't remove AI generated music from their platform. So interesting. I'm gonna go ahead and do a four story today. Normally I cap it at three, but this one was extremely interesting. So a new Harvard study showed the impact of GPT4 and productivity. So this Harvard led study showed a 40% performance boost when consultants used GPT4. So this study was done with Boston Consulting Group, you know, one of the most well known consulting groups in the world. My only question is why only 40%? I'm wondering what kind of training everyone had beforehand. But to only have a 40% performance boost while using GPT4 probably means you weren't using it correctly. Sorry. So, Boston bcg, holler at me. I'll teach y' all how to use it correctly. All right, so let's get, let's get back to the topic at hand. Let's talk about large language models. What are your questions? What do you want to know about Chat, GPT, about Bard, about Bing, Cloud and Perplexity? Those are the five. I think there's others. Don't get me wrong, there's probably a dozen or so great AI powered chats, but I'd say those are probably the top five. I'm making that own list. But I mean, Chat, gbt, Bard and Bing are undoubtedly the top three. And then we just saw Cloud yesterday. Rake in a, I believe a 4 billion with a B4 billion dollar investment from Amazon. So they've already catapulted themselves up into that top Tier and then perplexity. I think perplexity is something that a large language model that not a lot of people talk about. So I want to know what are your questions about large language models? We're going to go over it live. I'm going to show you quickly the pros and cons. This isn't going to be one of those episodes where it accidentally goes to 45 minutes, but I want to say what's up to everyone joining us. So Parimi, thank you for joining. Val, good morning. Mike, thank you for joining. Harvey Castro, happy to be here. Happy to have Harvey on the show, I think in two days. Josh saying good morning from Dallas. Thank you. Thank you all for joining. And if you do have questions, get them in. What's up? Brandon Cox, Sanford, good to see you. All right, let's get it going. What questions do you have? I see a couple questions. I'm going to go ahead and star them right. At least on my end. Don't worry. If you have a specific question, let me know. Harvey says throw in poe.com yeah, pose good. Except at least I think the last time I checked, like two weeks ago, you still can't use, you still can't use plugins on po. I don't think I could be wrong. All right, let's get into it. Let's start talking about LLMs. So very quick overview, especially if you're new. What is a large language model? The simplest way for the everyday person, for me to explain a large language model is it is the world's most advanced form of autocomplete, trained on the history of the Internet, you know, usually billions or trillions of data points essentially. Right. Without getting super technical and talking transformers and neural networks, I'd say that's a fairly easy way to describe it. Right. All these large language models, they're trained on heaps and heaps of data. Essentially anything that's probably ever existed on the Internet is in some of the largest large language models. Right. But essentially they are models. That's what I always teach people, you know, when working with large language models, you shouldn't be using it like you would use a traditional search engine, which is one input, one output. That's not how a large language model works best. Right. Contrary to what, you know, influencers on the Internet who are trying to sell you a book of prompts might tell you you should never just be copying and pasting one input and looking for a great output that might only give you a 40% increase in productivity. When I think you could easily, easily double your productivity or more using a large language model. All right, so that's the simplest overview. Now let's talk about a little bit about models. Right. So let's look at OpenAI, Bing Chat and Perplexity. Right. So it's also important to understand the relationship between Microsoft bing Chat and OpenAI, the maker of Chat GPT, GPT4 technology. Right. Microsoft is the biggest investor. I, I don't know the exact number. I think it's like 49 or something like that. I could be wrong, so don't quote me on that. But I believe it's, you know, nearly half ownership stake in OpenAI. So it's important to know that those two do work hand in hand. Perplexity, I believe recently they also announced the option in the paid version to connect to Claude 2 as well as GPT4. Right. So essentially we have chat GPT, Bing chat and perplexity all use GPT4. They also, it's important to know Bing Chat uses other models. You know, they're not, you know, telling us everything, but it is based off of GPT4 and other models. All right. Bard from Google is based on Palm 2 and then Cloud from Anthropic, their model is Cloud 2. Okay. So that piece is important to understand that some of these share models, some have multiple models that they're using. Right. But that's important too because it's going to sometimes produce similar results. So you might get somewhat similar results at times if you use open AI's chat GPT and if you use Microsoft Bing Chat. And we're going to do that live, so don't worry. But I tell like I'm going into models because of this. If you are working heavily in large language models, which you should because that is the future of work. Right. Obviously Copilot did a less an episode on that yesterday, so. But that's ultimately based off of large language models. Right. So it's important to know which offerings or which chats, AI chats, whatever you want to call them. I don't often call them AI chatbots, but some of them share very strong similarities and some are very different. Right. The reason I say that is a lot of times even my workflow, you know, I have two screens here and I'll split each screen in half. Right. So this is how I'll normally work. If I'm doing some heavy, some heavy deep work, I'll usually have Chat GPT with plugins on at least two to three of those four and then one is usually perplexity or I'll either have Cloud or Bard. So the reason I do that also is to switch up the models because you will get, you know, even if you're training a chat in the same way, which that's what you should always do because it's a model, you'll still get very different results. All right, I hope that's a good enough overview. And yes, Gemini coming soon from Google should, I think it is allegedly supposed to be much more powerful than GPT4. So yeah, that's also important to understand is, you know, these, these models and these companies are constantly changing and you know, that's where all the money is going right now. You know, we talked about a 4 billion billion dollar investment into Anthropic from Amazon to improve and build upon Cloud. So these models are constantly changing and constantly improving as well. That's a great point to bring up. All right, let's go here and see them in action. All right, we're going to do something just super quick, all right, just so we can see pros and cons. So I'm gonna go, I'm gonna do pros and cons, but also show you some of the best features and pros and cons. All right, so here we go. Here is Google Bard. If I'm being honest, I'm not very impressed with Google Bard. If I'm being super honest, I do think when they kind of upgrade to Gemini it will be much better. But something that I really like about Google Bard and I'm going to go ahead and put this test prompt in and I'll, I'll tell you what this test prompt is and why I'm running it. So all I'm saying is, please tell me about Microsoft's recent announcement on Microsoft 365 copilot and what the November 1 release entails. Please keep it simple and give me a brief bullet pointed list. Right. So super, super simple stuff here. And luckily Google handles it with ease. So I will say this, even though personally I'm not the biggest fan right now of Google Bard, it is probably the easiest large language model to learn on. It has the most easy to understand user interface. The user experience is actually pretty good if we're talking about quality of outputs and functionality and utility, it's not, it's not in the top two by far. Also, you know, people are, you know, were initially raving about the new extensions from Bard, you know, which essentially help connect Google Bard to other Google products like YouTube, your Gmail, Google Drive, I believe, etc. Google Flights, right? Here's the thing on workspace accounts, it's not available for everyone yet, right? You'll even see my account right here. I don't have extensions. I have to log into my personal Gmail because we use the, you know, G Suite or Google Workspace for our email at Accelerant Agency, the digital strategy company that I own. And so that's a downside. And even when I, when I tested the extensions out, to tell you the truth, not that great, right? At least for what I would want to expect. As an example, you can't summarize YouTube videos and obviously Google doesn't want that because they want you to spend time watching those YouTube videos so they can get their ad revenue, right? It can't, you know, interact and write in Google sheets. So these are all things you can do in Chat gbt. So, you know, when people say, oh, you know, Google Bard is great and look at these extensions. Well, the extensions, at least compared to chat GPT, lack utility, period. You know, it's probably tough news to swallow if you're a huge Google Bard fan. However, I do love the user interface. It is the easiest. So if you want to teach, you know, a parent or you know, an aunt or uncle or you know, a co worker that's maybe not as tech savvy about large language models, I'll say 100% bard. It is the easiest interface. You can click to upload an image, which is great kind of that multimodal that that chat GBT OpenAI just announced yesterday and will be releasing, you know, you can speak and, you know, speak your commands and then hear the response by default. Again, these are things coming to Chat gbt but not here yet. So in terms of user interface, user experience, ease to use, best to learn on, I'd say definitely, you know, Google is, is where it's at. They also do have this double check response which they just announced I think last week. If I'm being honest, I don't think it's very useful. If anything, it's just a marketing angle, I'd say, because half of the time, you know, so when I click that here, you know, if you're listening on the podcast, it's, you know, out of the bullet points it gave me, you know, when I asked it to give me bullet points, it gives me sources for some and highlights them. But then you just go to, you get to thinking like, okay, what about the ones that aren't highlighted? Does that mean Google Bar just made it up? Right? So that's why this whole fact check thing? And people are talking, you know, because one of the biggest things with large language models is they lie, they hallucinate, they make stuff up. Well, is this really useful? If you click the, you know, the quote unquote kind of fact check button and it just highlights 50% of what's on there? Not really. It's not really useful to me. Yeah, like, like Val said, you can already tell nothing like plugins from chat GPT. Absolutely. All right, so let's go next. So we gave Google Bard a little run there. All right, so now I'm going to run the same prompt. Here we are in Anthropic Cloud two. All right, so what's interesting here, Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on Genai. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team. Or you can just click on the partner section of our website will help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on gen AI. So what's interesting here, and I'm actually a little shocked, I do these live too, right? I love learning things along with you. So this isn't like I spent 10 hours preparing this episode. It's a daily show. I can't spend 10 hours. But what's actually surprising here, which I don't know how, so I'll have to investigate this later. Cloud actually got some things right about a recent event. So it did say Microsoft announced a new AI powered feature called Copilot coming to Microsoft 365 on November 1st. So that could in theory be inferred from the prompt that I gave it, which I said, please tell me about Microsoft's recent announcement. Right. And everything else. There is nothing else specific that lets me know that Cloud is actually accessing up to date information. Everything else is extremely general. So let's quickly talk about cloud. So one advantage that cloud has I think over all other competitors. Well, there's two things. One, if you look at the bottom of the screen, it has the built in capability to upload documents, right? The biggest thing is PDFs. Okay, again you can do this in chat GPT. You obviously, probably, if you've listened to the show ever before, you probably know, you know I'm a huge fan of chat GPT with plugins. So that is probably one of the best advantages for cloud. You can upload documents, which is great because in theory you can quickly train cloud on your company data. Again, never upload private documents to any large language model because most all of them use anything you upload to train their models. So don't upload anything sensitive proprietary, classified, don't do that. However, you can in theory upload your entire website or your entire writing catalog into anthropic cloud. The other great thing about cloud is it has a bigger memory, right? We're not going to get, you know, too dorky into tokens, but essentially Cloud has a 100000 token memory, which all that means is it can remember things for a much longer period than all of these other large language models. So those are two pretty big benefits of cloud. And they did just recently announce kind of their, their paid pro. I also believe it's $20 a month. Correct me on that if I'm wrong because I know we have some avid large language model fans in the house. So let's go ahead and go to Perplexity, which love perplexity. So I'm going to go ahead and turn on Copilot. Okay, so everyone uses this, this Copilot name, which is confusing. You know, you have Microsoft copilot, GitHub, co pilot. Now you have Perplexity Copilot, Pilot. But anyways, that enables a more advanced model. So I'm going to go ahead and click that little. Put my little prompt in there again, just showing you guys this live. I'm saying please tell me about Microsoft's recent announcement on Microsoft 365 copilot and what the November 1 release entails. Please keep it simple and give me a brief bullet point list. Right, so you'll see here Perplexity is a little slower, which is a funny thing to say because these large language models, when you think of what they're actually computing, are lightning fast. So perplexity is a bit slower. However, if you're talking about out of the box accuracy out of the box, avoiding hallucination and lies. Perplexity, hands down, is heads and shoulders above everyone else. And it's not even close. I'm actually perplexed. Accidental wordplay. I'm perplexed that, you know, someone hasn't acquired perplexity specifically, either OpenAI, Microsoft or Google or maybe Anthropic will, I don't know. But Perplexity, I think is a huge player. And you look at the response here that you got, it's amazingly detailed and accurate. Right? So as an example, if you compare this to the response that we got on Cloud Cloud, it's like, I don't know if it's lying to me or not if I'm being honest because it did give me some recent information, but it looks like it just inferred that from my prompt. Right. When I. When we look at Perplexity, Perplexity, I haven't even done this yet. I haven't ran this on all models. And I already know Perplexity will win in terms of, well, 1A and 1B, but it is extremely accurate. So this isn't. Perplexity is not as creative, you know, it's not as flexible. But if you want the best of a large language model and accuracy, Perplexity is, is where it's at. I love Perplexity. I always will have at least one Perplexity window open whenever I'm doing any kind of large language model work. There's other great features and again, yes, recently they did announce down here that you can use Cloud2. If you're on a pay plan, you can use Cloud2 or GPT4. So you can choose between those two different models when you use the Copilot feature. All right, so important to know, but Perplexity is huge. What do y' all think? Do you like. Does anyone in here like Perplexity? Just me. Am I dorking out? All right, Shannon. Shannon, thank you for joining us. Shannon says Perplexity came so close to my voice at one point I forgot for a second I wasn't typing to myself. Yeah, if I'm being honest, I don't use Perplexity a whole lot for more creative writing or content writing. I do think, at least for me Chat GBT is the best at that. But yeah, I'd say pretty much aside from Google Bard, I've been able to do a pretty good job at, you know, replicating a tone of voice or a company brand voice in most large language models. Pretty good at that. Yeah. Harvey said Perplexity Chrome plugin. Fantastic. Agree. I use that as well. VAL loves Perplexity. Same. All right, let's keep it going, y'. All. So we're gonna. Unfortunately, I gotta switch. Switch. Switch browsers here. So some, some news is, it's not even that big of news, but we had to wait for a very long time to get Bing Chat. So Microsoft's AI model, we had to wait for a very long time to get it on Chrome and we were so excited. We're like, yay, it's on Chrome. But now they took it away. So I'm in Microsoft Edge now. So yeah, you used to be able to access all of these in Chrome, but recently within the past couple of days now you have to access this new model in Microsoft Edge. Just FYI. So you all know. All right, let's go ahead and run this. I hope, I hope Microsoft Bing Chat nails this about Microsoft Copilot. It would be kind of bad if, if it, if it didn't, right? All right, so put in the same prompt and again you can choose kind of, if you want to be more creative, more balanced or more precise, which is a great, a great option inside Bing Chat. It's similar to creating or selecting a model, but it is more focused on accuracy, which I like for the most part. I usually use balanced. All right, so you'll see the response here. Obviously it nailed it, right? Everything here, which I love, especially with Bing. I think Bing does the best job, aside from perplexity, at citing sources, which is extremely important. So you'll see here it brought up all these different sources at the bottom and you can hover over which actually, normally I don't see it like this. Normally I don't see where every single thing is sourced. It could be because I asked for a, a bullet pointed list that it decided to source everything. Whereas if I asked for more of a paragraph or, you know, a quick article on something, I don't think it would have sourced line by line. But Bing Chat is actually really good. I like that. You can always as. As you can see here, I'm hovering over. You can always, you know, do the thumbs up, thumbs down, copy, export, share, or continue on phone, which I think is a nice feature. The one thing that I'm not crazy about is sometimes even when you're on search and you toggle between the search and the AI chat, the two can kind of run into each other. So as you're scrolling on the search or scrolling on the chat, it'll jump over to the other one. Which is a little confusing. But aside from that, you know, some other features. So you can just go ahead and click on a new topic. You can add an image, which is great. You know, the ability inside a large language model to upload an image gives you so much flexibility, so much just cool use cases, right? And that's coming to Chat GPT pretty soon here. And then you can also use the microphone. So at least right now Bing Chat is, I'll say this, it is a little limited compared to others, but I do with Copilot's release today, right? Not, not the enterprise, you know, with all the apps, 365 copilot, but basic copilot features are being released today. So I see, you know, there, there is going to be an enterprise version of this, of Bing Chat as well as, you know, Chat GPT. So I do see some big advancements and improvements coming to Bing Chat soon. Right now it gets the job done. It's not my first or second choice usually, but I do think it's similar to Google Bard. It has a nice easy interface, but there are a little bit of some, some quirks. But I do expect Microsoft to be improving those soon. All right, last but not least, we saved, let's get the right one here. We saved my favorite for last. You know, it's fine. I am a little biased, so I'm going to go ahead and put that same prompt into Chat GPT with plugins. Okay? I've done a whole episode on plugins and this is why I always come back to ChatGPT. The ability to have more than a thousand plugins that actually can push the envelope of your day to day business development and business processes is invaluable. I sound like a, you know, it's, it's old man Jordan on the porch screaming at people like, why aren't you running your complete day inside of ChatGPT with plugins? You know, even if I'm being honest, even when I'm using a great large language model and all of these are great, all five of these are great. If I'm in Bard or Microsoft Bing Chat or Perplexity or Cloud for too long, I feel limited if I'm being honest. Because you're, you're still working in a silo, right? Whereas when you're working with ChatGPT, you're not as siloed. You know, you can tap in other plugins that give you access to the Internet, which is what I'm using here, right? So if anyone is wondering like, oh, how did you Access the Internet. You know, Microsoft Bing, they took browse with Bing away, which used to be a mode inside Chat GPT. Well, I have the browser op plugin and the box script plugin which are both tied to the Internet and have different, different capabilities. And if you are signed up, FYI for the pro course for prime prompt polish, we have a free course prime prompt polish. So type in ppp, I'll send it to you. But the pro course, we actually go pretty deep into these different plugin packs and their, their capabilities. But let's, let's go ahead and look at the, the result here. So obviously chatgpt nailed says, you know, here's a bullet point list. It has the announcement new visual identity. What I like about, you know, ChatGPT's response here, working off the same prompt is it did a little bit better job of categorizing and formatting things, which I know sounds weird, but even if you look at, you know, the response from Microsoft Bing Chat, it was just unsorted, uncategorized bullet points. The upside is they were all sourced and linked. But that's why I like in ChatGPT, I think it does a much better job of formatting without asking, without prompting. I think it always does a much better job than other large language models of formatting information in a way that our brains want to take it in or in in a way that we as humans learn best. I know that's like such a, like fine detail, but it's important, right? I've spent, I've lost the track of how many hours, Thousand or more, Probably a lot more. Thousands of hours inside of large language models. And the ability to learn and to take information quickly is such an under an undervalued part of a large language model. So, you know, when we look at this, obviously fantastic recap, we do get a couple sources in the prompt. I could have asked for more sources from these plugins, but we get the sources down there, which is great. Can even toggle through them. So if you're not using Chat GPT plugins, you definitely should be. All right, so that's the roundup. Went over the top five. I'm gonna get to a couple questions. I think we got time to go over a couple. Might not be able to get to them all. May Brett absolutely says perplexity sounds like a great one for technical tests. It's, it is good for technical. I always use it essentially for fact checking or sometimes I'll start, you know, I'll say this. I have chats Within Chat GPT that I trained to help myself and our team learn things right, which is great, but sometimes I'll just start because it's a little faster inside. Perplexity. I think it's great for that. All right, have a couple questions here. Let's get to them. And I want to make sure I get them. Ben, I think we have the old man Jordan meme in an old, in an old thread somewhere. I'll have to get it ready. All right, so Val says, why use double web browsing plugins? Great question. And I go over this more in the pro course. Are you coming to the pro course, Val? I gotta make sure I sent you the information. So we have one today and tomorrow and we'll get, we'll get another one going in a couple weeks. But different web browsing plugins have different capabilities. We actually have a huge chart, ran through more than 20 Internet connected chat GPT plugins and tested each and every one of their abilities across four major categories. So for a lot of the work that I use Chat GPT for, it's a lot of Internet research, it's a lot of learning things. And different plugins have different capabilities. So even browser op and box script in our testing and we literally. I don't know anyone else that has put through 20 plus Internet connected plugins and has created a spreadsheet on their capabilities. But as an example, some Internet connected plugins have the ability to read PDFs, some have the ability to, you know, summarize YouTube videos, and you can only have three plugins active at any time inside ChatGPT. So you do have to be wise about, you know, not just getting a one trick pony. You do want a Swiss army knife that you've tested. All right, I hope that makes sense. Need the Pro course. All right, I got you. All right, let's see. I think we have another question here. All right, let's go. Kevin, thank you for joining. So Kevin says, have you ever used a combination of them to craft something? If so, what do you tend to start with? Which one do you tend to end with? Oh, such a good question. Yes, all the time. All the time. I, I kind of started to answer that, but usually I'll do two things, Kevin. So one is I'll run a parallel chat. And again, I'm always training chats. It's never, you know, one input, one output. So I'm saying if I'm going to sit down and go through the work of training a new chat to give it a new skill to Share resources, all of these things. I'm going to usually do the thing in a separate large language model with a different. A different model, right? So not just doing it to those that are using GPT4, but sometimes I'll run a parallel in Bard or Cloud, because if you're going through the process, essentially you're going to be just doing a lot of copying and pasting, so it's not a lot of extra time, but you get double the output or double the possibilities and you will get wildly different outputs, you know, when using even the GPT4 models from, you know, Bing Chat Chat GPT perplexity, you'll get wildly different results than Bard in Cloud. So yes, all the time. I tend to start actually a lot of times in perplexity. It's a quick way to. And that actually goes to user interface, because ChatGPT is great, I love it. The user interface is clunky, you know, you have to scroll through. I have probably thousand, a thousand plus chats and you know, I even need to do a better job of saving them, putting them in a spreadsheet. But the UI UX isn't the best in ChatGPT or if you need to add a plugin, you know, search for it. I, I spend so much time uninstalling plugins because I have so many installed, they're hard to find. So a lot of times I'll start in perplexity and take those results and bring them into Chat GPT or Bard. All right, hopefully that answered the question. Brian, what's, what's going on, Brian? So, Brian with a quick question. If you are not accessing the Internet for an analysis of data, which has the best memory and analytical ability? Well, memory, you can definitively say cloud. Just a hundred thousand tokens. No one else has that. So memory, hands down as cloud, analytical ability is probably up for interpretation. In my experience, it depends on also what your input is, right? Because if you're going heavy data, that's going to change the answer. If you're just looking for, you know, strategy or competitive analysis, that changes the answer. I'd say for the most part analytical ability without knowing what the input is. I'd say normally Chat GPT with the correct plugins runs laps around everyone, right? Because if you're talking analytical ability, it's like, okay, well we can use the wolfram plugin inside ChatGPT and you literally give it like genius superpowers, right? So I will say analytical, I would say Chat GPT just because of the ability to connect different plugins. All right, let's see. Question from Michael. What's up, Michael? So Michael says, seems like you are mostly into Chat GBT perplexity. And Bard, what do you use cloud for? Great question. Sometimes I'll use Cloud when I need a quick. When I need to quickly chat with a PDF, right? If I'm in a time crunch or if I need to have a very long conversation with a PDF, then Cloud is the best for that. You know, cloud is the only one by default where you can click and add a PDF, which is actually a pretty big benefit because even, you know, I ran through. I'm gonna have a video coming out this week with our AI in five. We do it every single day. So sign up for the newsletter. FYI, I'll put that plugin now. Go to your everydayai.com sign up for the newsletter. But I did do a huge like PDF plugin recap inside Chat gbt and they're great, but a lot of times you have to first upload a PDF to a server somewhere and or separately use have an account with one of the PDF plugins. So if I'm ever in a time crunch or if I don't just want to go through the hassle of uploading a PDF, you know, navigating to it, right? Clicking, copying the. The PDF URL for Chat gbt, then I might go into cloud. All right, Ben, one more. I, I think I'll do one more question. I'll get to the rest of them after. So Ben's asking, when you've trained a large language model, you do you find it forgets the training and runs out of. Yes. Oh, gosh, yes, it does run out of memory. You know, also have another video showing this probably this week. But even within Chat gbt, it starts to lose its memory pretty quickly. You know, OpenAI has said that 32K or 32,000 tokens, which I think is like 26,000 words, is available to everyone in GPT4, but it's not. It's available via the API, but at least in my testing and everyone else, you know, if you're using GPT4 inside chat GPT, I believe it still has an 8K memory, which isn't a lot. You know, 6,000 words goes quickly, Ben. So that's why I said there is a pretty big advantage to anthropic cloud if you're working in very long chats. What we teach in prime prompt polish, which is, you know, our PPP course for Chat gbt, we teach everyone how to do a memory recall because again, I'd rather do a memory recall when you start to kind of quote unquote run out of memory and still have all of the amazing business capabilities of chat GPT with plugins than to use Anthropic Cloud, which has a longer memory, if I'm being honest. Right. You can literally, with one click of a button, automate very long, complex tasks within three different plugins within chat gbt, which you can't do anywhere else. So, all right, I think we got to some questions. Didn't get to them all. I didn't want this to turn into a marathon episode. So as a reminder, I'm going to try to get to more, more questions here after the show. But please, if this was helpful, let me know. Did, did y' all learn anything? Hey, if this was helpful, go ahead and you know, if, if you're listening on, if you're listening live, just repost this, repost this to your network. If you're listening on the podcast, share this episode with a friend. Right? If you're listening on Spotify, Apple, you know, you can click that little share button, send it to someone. I think this is a fundamental skill set for any working professional in the future. You have to understand how large language models work. You have to know the pros and the cons and they're always changing. So to keep up, go to your Everyday AI dot com. Sign up for the free daily newsletter. We gave our website a little, little love, little facelift there, so check that out as well. I hope to see you back not just for more large language models in the future, but I hope to see you back for another episode of Everyday AI. Thanks, y'. All.

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