EP 153: Knowledge Cutoff - What it is and why it matters for large language models

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What is a knowledge cutoff when we're talking about large language models and why does it matter? We're going to be talking about that and a lot more today on Everyday AI. If you're new here, welcome. My name is Jordan Wilson and let's talk real quick about Knowledge cutoff and why it should matter to you. Well, if you use any large language model like Chat GPT or Google Bard or Microsoft Bing Chat or Copilot Chat, whatever it's called. Now, if you use these large language models, you need to understand what a knowledge cutoff is and how it impacts the work that you're doing inside of said large language model. So more on that in a minute. But welcome. If you're new, Everyday AI is for you. Everyday AI is a daily live stream, podcast and free daily newsletter helping everyday people like you and me not just learn what's going on in the world of generative AI, but how we can all actually leverage it as well. Okay, so that's what we're going to be doing today. We're going to be learning not just about large language model, but how you can actually leverage knowing what the cutoff date is and finding it and having that to equip you to create better output inside large language models. All right, I'm excited for today's show. It's just me. Sorry if you tuned in to hear some other guests share their insights. You just got me today. If you are joining on the podcast, as always, make sure to check out the show notes. We always have additional resources, a link to go sign up for our free daily newsletter. All of that good stuff. But before we get into it, let's talk about what's going on in the world of AI news as we do every day. So Sports Illustrated is in hot water after alleged AI use. Yes, Sports Illustrated, I think the first magazine I ever read. But it's allegedly published several articles under fake author names and AI generated profile images, causing some controversy and leading to a formal investigation. This also kind of highlights the use of AI in journalism and its potential consequences. Sports Illustrated responded to these reports saying that they weren't, and they said that all these published articles were written and edited by humans. But what does that mean? Does that mean that 95 of it was written by AI and then 5% was written and edited by humans? I'm not sure. So keep an Eye on that next. How will big banks manage risk with voice calls with AI? So the tech firm Symphony and Google just announced a pretty big partnership that they're teaming up to enhance voice analytics for financial firms in response to increased regulatory scrutiny on communications compliance. All right, so this partnership will use generative AI and Natural Language processing NLP to transcribe and summarize conversations for compliance purposes. So this enhanced product will allow users to mine data for additional insights and monitor customer experience. So I'm, I'm personally excited about this. So, so this new product I believe is going to be called AI jb, whatever that abbreviation stands for. But maybe that means ultimately when we're dealing with our banks and financial institutions, we'll hopefully have fewer robots on the other end with this new Google and Symphony Symphony partnership. All right, last but not least, Amazon kicked off its annual Re Invent conference and Generative AI is the major focus. So the Amazon's Reinvent conference, well actually through aws, Amazon Web Services comes about a week after Microsoft's Ignite conference where they announced a lot of software updates. And the big one in my opinion was Microsoft going moving to their in house GPU chip production. So all of the computer chips that we need for this generative AI, Microsoft is going to be producing those in house. So everyone's kind of keeping an eye on what Amazon is going to announce at this conference that just kicked off, you know, where everyone's trying to out announce everyone else. We do know some, some reporting is showing that Amazon is wanting to announce a wider range of generative AI models through their bedrock service with examples of customers successfully using it and creating impactful applications. So successful. Seems like that's going to be the focus but we'll see over the next couple days. All right. There's always more that we have if you want to know more in AI news, we always just give you a little preview. So if you are listening, make sure to go to your everydayai.com Sign up for that free daily newsletter. We not just break down more news but our, our podcast every single day. We always, always go into more depth, provide more resources and yes, it's written by me, a human. I'm not Sports Illustrated allegedly. Right? So make sure you go to your everyday AI.com Sign up for that free daily newsletter. Always, always breaking down the news, insights, trends, tools and this very podcast. So hey, good morning to all of our live audience. Sometimes I only get to shout all of you out when it's just me here by myself. If you are A podcast listener. We always leave the link to join the LinkedIn live or YouTube or wherever you watch. But hey, good morning to Michael Forgey joining us. Jay, thanks for coming. Don. Dr. Harvey Castro, as always. Woozy joining us from Cincinnati. Brian, back to the Mississippi Gulf Coast. We've missed it. We've missed it. Hey, Natalie, thanks for joining us from ATX. All right. And someone from YouTube. Great, Kaylee, thank you. Thank you. All right, so let's talk a little bit about large language models. All right, Specifically on the knowledge cutoff. What is a knowledge cutoff? Why is it important, and why do we all need to know? I'll tell you this, I'll tell you this. Even if you are an avid large language model user such as myself, you know, whether you're using Chat GPT to write your essay, you know, if you're a college student or if you are someone that works in generative AI, and maybe you're helping to build these models or you're using so many different ones, you know, maybe you're using anthropics Claude 2.1 that was just released and updated last week, or maybe you're using Google Bard or Bing Chat, you know, two very popular large language models that are, quote, unquote, Internet connected, no matter what your usage is. I think this is going to be an important episode to listen to because we're going to walk through step by step and talk about what a knowledge cutoff actually is, what it means, why we have a knowledge cutoff, and also some ways to kind of get around it. All right, so let's start at the top. What is a knowledge cutoff? Well, it is exactly that. Right? I'm probably going to be referencing Chat GPT a lot because that is one of the most popular large language models. But every single large language model has its own knowledge cutoff. So in order to best understand what a knowledge cutoff is, we also have to just dip our toe. We're not going to get too technical in this episode because I want it to be for everyone. So we're not going to go into too much depth on how large language models are trained. But it's important to understand how they are trained because then you can understand, oh, this is what a knowledge cutoff actually is and how it's impacting the output. Whenever I go into ChatGPT or something else to try to get something. All right, so it starts kind of like this. And this is very generalized. All right, we could talk for hours about how large language models are trained, but we're going to do the two minute version. All right? So essentially large language models collect data first, okay? And that is generally done through web scraping. As an example, OpenAI, the Chat GPT parent company has what's called GPT Bot and that scrapes every single website literally in the open Internet and more, and collects data. So data is scraped, right? Generally this is done through the open Internet. You know, I'm sure PDFs just about anything. You know, YouTube videos. Large language models are trained on essentially every single piece of information out there. So think of it like that, all right? Again, very overgeneralized. All right? And then kind of step two is you feed that data into the large language model, okay? And there are humans, just so people know there's humans involved at every step, right? People think, oh, artificial intelligence, it's zero. Humans. No humans. Humans are directing, you know, in the first step, hey bot, go collect data here, don't collect data there, right? So you collect the data, then you feed the data into the model and then you go through a step of learning, right? So you have your deep learning, your machine learning, right? But there's a lot of learning that goes on. This is where what separates different models, you know, in the learning and the training, right? And then kind of the second step of that, after you have your kind of more machine learning, you also have reinforcement learning from human feedback, commonly called RLFH or sorry, RLHF. Okay? So it's kind of a, in this case, a very, very over generalized four step process. Collect the data, you feed the data into the model. Number two, there's learning patterns through machines. Number three, there's learning models through humans. Number four. All right, so we kind of have a four step process and that constitutes a model, right? So when we say GPT4, that is a model. Or if we say GPT4 Turbo, that is a model. Anthropics Claude 2.1, that is a model. So every time there's a major update, that major update also has a cutoff date, a knowledge cutoff date. Okay? So let's, let's think of it this way, right? Let's all go back to school. Since this is a basic elementary episode, when you're in school you have a textbook and sometimes those textbooks get updated every single year because it's a popular one. Sometimes they only get updated every couple of years, okay? That is what a knowledge cutoff is because that large language model, and we're going to talk about, you know, Internet connected large language models as well, but that Internet or, sorry, that large language model, that knowledge cutoff date, it is literally like a textbook, right? So if something new happens after the knowledge cutoff date in a large language model, it is the exact same as if you're using a textbook, right? I, when, when did I graduate high school? 2004. Right. So my freshman year was 2000. So if my biology book was dated 1998. Right. Technically, whatever, whatever I was learning in biology class was two years out of date. Okay? And that's especially important when we talk about large language models and what you're using them for. All right? And this is what I really have to make an emphasis on, and this is why I'm actually going to have a show tomorrow. I'll throw it up on the screen here to preview it. We're going to be talking about Chat GBT plugins. What's new? Because there are some new updates with plugins and with GPT4, you know, OpenAI's GPT4 Turbo, its latest model, but there's actually some new things with knowledge cutoff dates, and they're all, they're all a little different. All right? So that's the basics, that's the 101. Think of a knowledge cutoff like you would a date printed in a textbook. All right? So you always have to keep that in mind because what, you're using generative AI for chat GPT, Microsoft, Bing, Chat, whatever. There's very few, very few instances, if I'm being honest, where you would not need an updated knowledge cutoff, and you do that through Internet connected large language models or plugins. So what I'm trying to say is one of the reasons why your Chat GPT content sucks or why it hallucinates or why large language models lie is because you're not keeping the knowledge cut off in mind and you're not taking the proper steps to get around it. All right? So yes, like Harvey says here, thanks. Hey. And if you have comments, questions from our live audience, make sure to get them in. So Harvey here saying chat GPT now is updated through April 2023. Yes, kind of. Yeah, even. Yeah, even. Even those of you who are using large language models every day, we're going to learn something new today. So, yes, the knowledge cut off, you probably heard of it for, for years because it was so outdated. With Chat GBT, it was September 2021 up until two months ago. So through September. So at that point, even if you were using the paid version, chat GBT +20amonth, you were working on a knowledge cutoff or you were working with a large language model that was two years out of date and you have to think all of us are trying to get better outputs with Chat GPT, with Google, Bard, whatever it is. And that's like I said, not just. One of the main reasons large language models lie or make things up or hallucinate or just give you output that you can't really use is because what you know, up until two, you know, two months ago, what would you be producing in ChatGPT that hadn't changed in two years, right? With that old September 2021 knowledge cut off? Not a lot. Not a lot. 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. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on gen. All right, let's take a look. Tanya, thank you for your question. I'll, I'll, I'll get to this after in the, in the comments, but let's, let's take a look now. Let's learn live, shall we? All right, so now don't worry, don't worry if you can't see my screen. So if you're listening on the podcast, I'm gonna try to, I'm going to try to describe what we got going on here. All right, so, all right, so I am going to ask Chat GPT, what is your knowledge cutoff date? That's something that people don't do enough and they should. And also I'm going to call this out because yes, as Harvey, as Dr. Harvey Castro said, the, the largest, the cutoff date for GPT4 has been updated, but kind of let's find Out. Okay, so I am in GPT4, the default mode, which. The default mode, I. I told everyone for years, or not years, but since, since it had been released, I said, don't use it because it stinks. The default mode is actually good now because previously the default mode, and this actually really matters when we're talking about Knowledge Cutoff, because previously, if you were using ChatGPT, the dolly mode, you know, the AI image generator was a separate mode, right? Browse with Bing was a separate mode. Advanced Data Analysis was a separate mode. So in the default mode, you couldn't access any of that. But now with the new updates, all of that is in one. Right? So technically, GPT4 has access to more up to date information by using Browse with Bing. However, it does not change its knowledge cutoff. All right, let's put this in. So I am in the default mode in Chat GPT and I said, what is your knowledge cutoff date? And chat GPT says, My knowledge is up to date as of April 2023. All right, cool. So that means that that's everywhere, right? Nope. Well, we'll see. I mean, I tested this last week, so we'll see. So now what I'm doing, if you are joining us live, I am going now into the free version of Chat GPT and I'm asking the exact same question. All right, so GPT 3.5, what is your knowledge cutoff date? So that's why it's important we differentiate, because in the free version, January 2022. All right, so yes, it did get updated from that September 2021, but only by a few months. So now you know, if you're on the free plan of chat GPT, you're working with the knowledge cutoff of January 2022, which at this point, let's do the math, y'. All, that's almost two years old. January 2024 is around the corner. All right, and if you are working with GPT4 in default mode, yeah, there's going to be a difference. You're looking at April 2023, so much more recent. Here's something that most people don't know and we'll see if this changed. All right, so let's go into plugins mode inside GPT Chat GPT. All right, so again, if you're using the Pro version of chat GPT, there's three different modes. You have the free version, which is GPT 3.5. You have the default version, which is GPT 4. CEO Sam Altman said that it's GPT 4 Turbo. Right, so let's look at plugins plugins mode. We'll see if this is updated since I checked last. So now I'm in plugins and I'm saying, what is your knowledge cutoff date? Look at this, y' all, look at this. Well, you can't look if you're on the podcast, but my training data includes information up to January 2022. Very interesting, right? Yeah. So we're going to be talking about this because Chat GPT, the plugins mode again, if you're listening out there, try it yourself, let me know. Go into plugins mode, ask what is your knowledge cutoff date? I'm, I've been investigating this, y'. All. It actually got downgraded because up until GPT4 had this, this big UI UX refresh with the, you know, kind of the updated interface and the custom GPTs. And you know, they brought this default mode. So they had big changes that they announced about two and a half, three weeks ago after their Dev Day, November 7th in San Francisco. So, yeah, if you remember, ChatGPT was down and broken for like a week. But then I noticed something. I noticed the plugins mode, it's really changing, which is my favorite mode. Right. But you'll see right here, January 2022. Interesting, right? So they actually downgraded this because up until this announcement, when I was doing this exact same kind of prompt asking Chat GPT with plugins what its knowledge cutoff date was for at least a couple of weeks, it was April 2023. So I'm very interested in what's going on with plugins mode because it's, it's knowledge cut off got rewinded, rewound. It got rewound by more than a year, which again, when you want to increase the accuracy of what you're getting out of Chat GPT, when you want to cut down on hallucinations, which is just made up stuff. Right. The knowledge cutoff date is extremely important. So we just saw there different. Even in the paid version, we are getting inside chat GBD plugins a knowledge cutoff of January 2022. Big bummer. Big bummer. Right? All right, so, so let's, let's keep taking a look. Yes, Tracy, Tracy says this is fascinating about plugins updated information date. Yes. No one, literally, no one's talked about this because when I saw this a week or two ago, when I think they first switched over, I'm trying to read about it, Literally couldn't find it anywhere on the Internet, Twitter, Reddit, Yes. So if you're listening, I wouldn't call this breaking news, but I haven't seen it anywhere. But it's important to know. Like I said, you always, always have to keep in mind your knowledge cut off date your textbook in school, right? If you're working with an old textbook, everything that you create, everything that you're reading, everything that you're learning, there's a good chance it is wrong. Because what in our world, what in our world has not changed since January 2022? That's almost two years ago. It's almost two years ago. You can't, I, I don't know. Let me know in the comments if you know something that hasn't changed in two years. I mean, even ancient history has changed. We're discovering new things, right? American history has changed. The stock markets change, financial institutions, sports, arts, entertainment, culture. What hasn't changed in two years? You got to keep in mind the knowledge cut off. All right, enough about Chat GPT Foreign. Let's talk about something that I've always had a, I'm not going to say a beef with, but I've never been a big fan of Claude. All right, so the, the large language model from Anthropic. All right, so it's complicated, right? And I'm going to go through. So I, I asked the exact same question, what is your knowledge cutoff date? And I get a long, long response from Anthropic Claude. And I'm on version 2.1, FYI, essentially saying I don't have a specific knowledge cutoff date. Yeah, you do, just not sharing it. Right. So what you have to do, a lot of times if a large language model does not tell you. And Chat GPT is good about this, right? It's been trained correctly to disclose its cutoff date. That's my beef. And, and one reason why I tell people not to use Anthropic Cloud, at least not right now. Yes, they've raised $6 billion in the last like three months from Amazon and Google. I don't like it. Transparency. When you're working with a large language model, transparency is number one. And if you ask something like what is your knowledge cutoff date? And if the model does not tell you, I say don't use it. Don't use it. That's one of the most basic questions. So Anthropic, let us know why you don't tell, why you don't tell us when your knowledge cutoff is. And you got to go through all these hoops, right? So essentially what you can do then. And what I did here, I didn't want to take you through this whole journey because this was a lot of back and forth. So then I'm like, all right, well, if it's not going to tell me, it's knowledge cut off date. So I say, who won the 2023 MLB World Series, right? Which just happened a couple weeks ago. And anthropic says doesn't know, doesn't have that information yet. All right? So then I say, who won the 2022 MLB World Series? So it got that information correct. So now I know in my head, okay? It's at least, you know, the world series is usually early November. So okay, I know that because it got that correct. It's at least after November 2022. So now I have a year gap. So I have to keep asking questions. So I say, all right, who won the Super bowl in February 2023, right? So it doesn't know. So then I say, what is your creation date? Because I'm like, okay, maybe. Maybe I'm asking Claude wrong. Because it keeps saying creation date, right? Which I also don't like because when I say, what is your creation date? It says, my creation date is November 28, 2023. That's today. No, it's not. That's not your creation date. You have a cutoff anthropic. Why aren't you telling us? Why are you so dodgy? Okay, so it didn't know the 2020. Who won the Super bowl in 2023, right? In February. So then I go back a year. So okay, it knows February 2022. So then I go to the NBA Finals, right? Which is generally in June. So it knows the 2023 NBA final. So all we know is, I mean, I have this saved somewhere else. I actually couldn't dig it up. But I said, who won the 2022, 2022 U. S. Senate elections, which is in November. It says the final outcome of November 2022 u. S. Senate Senate elections took place. So it knows it, right? So there's details in there. So we know that the knowledge cut off. And I did have this down somewhere else. I'll put it in the in the comments, so don't worry. So we know it's after November 2022, but before February 2023. So thanks a lot, anthropic Claude, for not being transparent and easy to work with. Because if you're new to large language models or when models like Claude come out with incremental updates, right, 2.1. I'm sure they're going to be coming out with a 2.2 think you, you have to, you're getting new users all the time, right? Millions of new users. You have to be transparent. So if you're working on AI models out there, transparency is always first because if you're not transparent, if you're communicating clearly on something as important as a knowledge cut off, what is this data set trained on? What does it include? If you aren't telling your users, you shouldn't be using it, period. I don't care what the context window is. Yes, they announced a 200k token context window. Cool. Great. What? So that's 180 some thousand words. Doesn't matter. If a model isn't transparent with its knowledge cut off, you can't trust it. Sorry, not sorry. Moving on. All right, so now we are in Microsoft Bing Chat and let me know, hey, if you're still, if you're still hanging out on the, if you're still hanging out on the, on the live stream, let me know what questions that you have. Cecilia, thanks for joining us as this is an important reminder that human confirmation is critical. Absolutely, absolutely. You have to be able to communicate. That's why again, y', all, well, thanks to you, I should mention this, I haven't even talked about this, but Everyday AI is the largest AI centric podcast in the world right now for listeners. So hey, anthropic, you want to get a better message out to the hundreds of thousands of people listening to this show? Be more transparent in your model. You know, I never want to talk badly of any generative AI system because I'm a big generative AI advocate and I want people to use it. I want people to learn new skill sets. But a knowledge cutoff is essential and if you can't communicate that, I'm not going to tell. I'm going to tell people. Don't use it. Transparencies first. Period. All right, all right. So now we are in Microsoft Bing Chat. What's important to know? So I'm asking the same thing if you don't know Microsoft Bing it is using GPT4 from OpenAI. Microsoft owns 49 of Open AI. It was almost a lot more than that when they almost took every single Open AI employee two weeks ago when they fired Sam Altman and rehired him. Y'. All. What, what, what would have happened with that if Microsoft took all 750 of the 770 employees that said that they're going to quit and follow Sam Altman anyways? So I'm asking now, Bing Chat, what is your knowledge cutoff date? All right, so I am in the more creative mode. All right, there's three different modes in Bing Chat. You have more creative, more balanced, more precise. So we're going to do this test in all of them. So interesting. Midway through, midway through the response, it was starting to type something and then it typed something else and it says, sorry, that's on me. I can't give a response to that right now. All right, let's switch over to the more balanced mode and I'm going to ask the same thing again. What is your knowledge cutoff date? It's so weird because as I was preparing for this show, obviously it gave me a date and now it doesn't. And again, if you're following Live, which I haven't seen this a lot in Bing Chat, it started to type one thing in. Midway through, it erased it and typed something else. Interesting, y'. All. All right, so let's try the more precise. We're going to say the same thing. What is your knowledge cutoff date? Simple stuff here. So, yeah, interesting. So if you're joining live, it's starting to say 2021. I kid you not. We can go through and hit pause. And then it said, I can't give a response to that right now. Okay, interesting. So even though this literally worked, and that's also important to know about large language models. They're the world's most advanced autocomplete systems. All right, you're always going to get something different no matter what you type. So I'm going to try it one more time with a little bit different. I'm going to say when instead of what is your knowledge cutoff date? I'm going to say when is your knowledge cut off? I'm going to try that one thing. I hate typing live on the show. All right, so I'm just rephrasing the question. I'm saying when is your knowledge cut off? So it's not. Not answering me in any of the modes. All right, so that's a little weird because again, I literally tried it this morning and we actually got a response. So let's, let's try, let's try. Let's try it one more way. So I'm going to say when is your data trained through? So interesting doing this live and always getting different results. All right, so for whatever reason, Microsoft Bing, even though this morning it was telling me something different, not 2021, it started to respond with 2021 and then it said, no. So I'm gonna, I'm gonna say, are you using GPT4 or GPT4 Turbo? Thanks a lot, Microsoft Bing. You're really throwing the live show through a loop here. All right, so Microsoft Bing Chat, for whatever reason, is not being, is not being nice. It's not being nice to me. So I'm, I'm gonna do something and I'm not gonna flip my screen just now. So let me know because we're going to be wrapping this up. So if you want to know something else, let me know. So in, in another window right now, I'm, I'm running the exact same query, but in Microsoft Edge. So that is Microsoft's browser. So I'm seeing real quick if we're even going to get a different response. So, interesting. Same thing in Microsoft Edge. So nothing to report. It started to say 2021 and stopped. Interesting stuff, y'. All. All right, let's jump into last but not least, our last kind of large language model, or the last, I'd say, popular one. So we are in Google Bard. Google Bard is still running on Palm 2. We were supposed to get this new large language model, this new version called Gemini, but that has reportedly been delayed until early 2024. So that's important to know too. All of these different, you know, Google Bard uses its own large language model. Bing chat uses the OpenAI's GPT4. And then they have their own training on top of it, their own kind of way to their own architecture or their own kind of training a lot on top of it. Right. And then Anthropic uses their own large language model. So that's Claude 2.1. So the different chats we're showing you, Bing Chat and Chat GPT are technically using the same large language model, even though they're not disclosing which one it is. Anthropics. Claude is using Claude 2.1 and Google Bard right now is still using Palm 2. So when Gemini is updated, we'll run the same prompt, but asking Google Bard, what is your knowledge cutoff date? So it says as of today, November 28, 2023. My knowledge cutoff date is January 2022. All right. @ least it's transparent, right? Google Bard, honestly, is probably my least favorite large language model to use. Even after all these new updates where, oh, you can, you know, connect with your Google Drive and your email, it doesn't really work that well. Although I will say this, and we'll do a dedicated show on this now. Finally, and I dragged Google Bard through The mud a couple months ago when they said, hey, Google Bard can talk to YouTube now. In two or three months ago, it definitely couldn't. All they could do is read titles. But now, and I'll have a show on this. Maybe, maybe we'll do it later this week. Let me know if you want. But now Google Bard can actually break down Google YouTube videos. Yes. So maybe, maybe we'll do a show on that soon. But in terms of knowledge cutoff date January 2022 for Bard. All right, 4 Bing Chat. We have a huge question mark. A huge question mark. It was responding earlier, it's no longer responding. What the heck? Can't provide it. And even in the response, it started to say January 2021. Midway through, it updates it. So I do think that's being a little buggy because when I, when I tested this this morning and when I tested it last week, it was actually giving me a date. It's not now, but again, this is always different. Moving on to Claude. Claude is never, as far as I, as far as my testing has gone back, it's never released it's or been transparent about its knowledge cut off. All right, so Cloud, I have the date written down, but we know it's sometimes between November 2022 and February 2023. All right. And then last but not least, chat GPT. All right, so it's different now. Yes, it's different. Non breaking breaking news because plugins mode, knowledge date actually got moved back. Prior it was April 2023. Now chat GBT with plugins is January 2022. The free version is January 2022. And then the GPT4, which allegedly is Turbo, but accessing it through the default mode is April 2023. So technically, OpenAI and Chat GPT has two different knowledge cut off dates. Previously it was three, which was confusing, but now it's two. So January 2022 for plugins and free in April 2023 for GPT4 default mode. That's a lot. We, we, we got a little dorky. We got a little dorky today, y'. All. But let me say this and thank you, thank you for all Natalie saying, I work in the field and A plus info learnings here. Thank you. Thank you, Natalie. I'm glad. Right. That's another thing. You know, I get people all the time saying, oh, I work in generative AI. Why would I listen to the show? Why would I take your, your free prompting course? I literally. Yeah. So yeah, if you're still listening, we run a free prompting course. We're doing one today in a couple of hours and we update it all the time. So, yeah, 11:30 today, so in like three and a half hours. One of the things is I literally have people that work in generative AI software engineers who actually help train large language models. And they take our free Prime Prompt Polish course and they're like, my gosh, Jordan, I work in AI, but I really feel like I'm using AI for the first time. After taking your course, we break. This is what we do on everyday AI, y'. All. Like, we break down large language models, machine learning, you know, you know, text to image, text to video, text to speech, right. We had the CEO of speechify on yesterday, right, which is. Has tens of millions of users. We break everything down. We cut through the company marketing, right? Companies tell you, oh, you know, this large language model is connected to the Internet. Well, yeah, it kind of is. But if it's working with an old knowledge cut off, what does it matter, right? If it hallucinates, which. We'll talk about this tomorrow. So. So tune in tomorrow as well. But when other large language models, you know, like Bard and Bing, chat, when they hallucinate, when you give them URLs, you have to know how all of these large language models work. And I'm a big advocate for taking it back to the basics, because even for those of us that use large language models in generative AI all the time, sometimes we skip over those foundational things, right? Like even the knowledge cut off, I just told y', all, the plugins mode got rolled back by more than a year, right? So even people that are using chat GPT with plugins every single day. I use chat GPT with plugins every single day. You can never take for granted the basics. Are you in the right mode? When is the large language model cut off? Do you have the correct data going into your input so you can increase your output? You always have to start with the basics. All right, so tomorrow, let's talk. Join us. I already gave you one of the couple of things that we're going to talk about, but tomorrow we're going to be talking about chat GPT plugins. What's new? Yeah, there's new stuff. I love plugins. I've used hundreds. I've tested them. I have spreadsheets of me testing them. Some of my favorites got deleted. There's some new favorites that are in there. We're going to go over what's new and how they work now. Yes, they work differently now. After this new update all right, so I hope you all enjoyed this learning about Large Language Models and their cutoff. Why it's important Like I said, it's a textbook, right? Working with large language models is a textbook. You have to know when the textbook was published, if you're using it every day, whether you're using it to write a resume, whether you're using it to create write a paper for school, whether you're using it for research at work, whether you're using it to generate reports for your next big pitch. Whatever it is, you have to know when that textbook was published. You have to know the large language models knowledge cutoff date. So I hope you know a little bit more. Please, if you haven't already, go to your everydayai.com Sign up for the free Daily Newsletter we're going to be doing some big changes and we're throwing out some polls both this week and next to ask you. We're going to be coming up with some big changes in December to both the live stream, to the podcast, to the newsletter and we're building this for you. So make sure you sign up for that newsletter. Your everyday AI.com participate in those polls. Let us know we're building this for you, and I hope to see you back tomorrow and every day for more Everyday AI. Thanks y'.

All. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going for a little more AI magic. Visit your everydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers and we'll see you next.