OpenAI'S "SECRET MODEL" Just LEAKED! (GPT-5 Release Date, Agents And More)

and uh we think that within maybe a year or two from now like the models will be unrecognizable from what they are today and so this year we also plan to push that boundary even more and we expect our next Frontier Model to come um and and provide like a step function in reasoning uh improvements as well so there was actually a very interesting announcement that was made but including myself a lot of people didn't actually realize what the announcement was and it was something that was quite under the radar but in this video I'm going to be showing you guys all of the secret announcements and some of the secret updates that are coming to opening eyes models in the future well in the very close future including some of the key dates that were actually unveiled at a secret presentation so one of the things that you can see here is this is an image that has been floating around on the internet for the past 24 hours and I've confirmed that this image is from the Viva technology event which is commonly known as vivatech and it's an annual technology conference dedicated to Innovation and startups it's held in Paris in France and was founded in 2016 by the Publishers group and the event takes place at the Paris Expo and it's pretty much the or I should say one of Europe's largest tech and startup events and it's mainly focused on Tech Innovation along with some other key business insights and from this image it seems pretty simple but there was something that a lot of people did Miss so we can see here that on the image that you you're currently looking at we have three main points so what we do have is we have a situation where we have the 2021 which is the gpt3 era The Da Vinci model and this was of course in 2021 you can see now and this is actually super interesting and this is why I think this video is remarkably important you can see that we moved in 2023 to the GPT 4 era which is here so you can see that this is around the time of GPT 4 being released and being deployed and what's very interesting is that it now shows a new piece of information that I would say is a little bit interesting you can see that they describe this as GPT next okay so I think that maybe GPT 5 might not be coming and when I say that I don't mean GPT 5 isn't actually coming what I mean is that GPT 5 as you think of it I think open AI are most likely planning a lot more than people think and of course that is something that we even recently saw with the recently demoed GP so it's crazy because it shows us that may 2024 which is as you can see here today and you can see it says may 2024 but what's crazy is that they've actually given us the release date for this GPT next model so you can see that if you look at this dot right here we can see that this is actually November 2024 and this date is very important for a few reasons which I'm going to explain in a moment but I think one of the first things that you know really surprised me was of course the fact that this is called GPT next and not GPT 5 now what's really crazy about this is that the craziest thing is that we can see that there is clearly some kind of increasing capability so it is very hard to see this but on the left hand side here it says model intelligence so you can see that gpt3 is intelligent was around this level GPT fors intelligence it doesn't really Benchmark it but I'm guessing that this is GPT 40 so you can see that there is a slight Improvement there although the Improvement is slight the thing that you need to take into account is the fact that even if improvements are slight it does mean that a lot of use cases are going to be pretty insane because if the model can get smarter and it can become more reliable then it means the industries that it can impact are going to be a lot more overall so I think one of the most important things that we could see here is that the model intelligence from GPT 40 or gp4 completely does a huge jump we can see that literally from this level to this level we can see that it's that amount of jump but from here it is a quite big jump and in fact I probably should be using some actual arrows apologies for my terrible drawings but the point I'm trying to make here is that it seems that the kind of jump that we're about to get here with this GPT next model it looks really surprising and it's something that they've constantly reiterated that these future models are going to be very intelligent in terms of how smart these systems are and whilst yes there might be other features this is something that we do know now one thing that I did want to talk about this gptx model because of course they could have simply put that this is going to be GPT 5 although of course they don't want to officially announce it could just be a place holder for GPT 5 I think that it

might not be GPT 5 but I'm going to dive into that one second but one thing I want you guys to know is that this release date right here of November 2024 is a key date because this makes sense for the release date of the next model whether it's GPT 5 or whether it's GPT next whatever other models there are I think it's important to note that this date has been said by openai a few times so one of the key things coming up this year and I know some people don't live in America so you might not pay attention but there are the 2024 United States elections this is going to be taking place on Tuesday the 5th of November and you might be thinking okay but those are the elections what does that have to do with actual AI systems like I mean that's politics this is technology in fact those things are very closely intertwined because open AI themselves did actually make a statement regarding this and the elections are actually a reason for the delay of GPT 5 as many people did think that GPT 5 was scheduled to be released in the summer however you can see right here open AI CTO Mira morati recently confirmed that the elections were a major factor in the release of GPT 5 we will not be releasing anything that we don't feel confident on when it comes to how it might affect the global elections or other issues she said last month so whilst yes we did just get a pretty crazy demo of GPT 40 a multimodal AI that just completely shocked the industry it is pretty incredible that you can see here that open AI are really concerned with as to what the future models are going to be able to do in regards to the election now I think it's going to be either one of two things one of the things is that because there is an election coming up there are always different discussions on what could happen and the kinds of you know conversations going on around privacy issues and just a million different conversations that are going to be had and the problem is that if open AI does release a model before the elections then you could face a negative PR situation like the public could be negatively thinking about open Ai and of course yes this week open AI have had a huge huge amount of bad news in their favor due to some of the things that have been going on at the company from people leaving to Sam Alman doing you know some questionable things depending on where you stand I think it's important to not release models during that time because it's at a time where if the technology is as truly Advanced as the graph shows us then it's definitely going to be more widely received as a model that is you know something that is threatening the individual democracy of the United States because if it has the ability to influence people then some individuals might say that this was all timed and you know with politics things do get really difficult really quickly so I think this does make sense now I could be wrong but the fact that we do have the open ey CTO stating that they're not going to be releasing anything and the fact that of course GPT next is in quotation marks here and that there's going to be that at November 2024 just after the elections I think November 2024 and considering that previous rumors around that time also did say that I think that this also does make sense now here's where he actually talks about the GPT next models this is a very fascinating clip and there is also this graph right here it is very very hard to see like but if you zoom in you can see that there is also this graph gpt3 era GPT 4 GPT next and you can see that this one doesn't actually have the dates on it so I'm guessing that before when they had the dates that may have just been a mistake based on proprietary information but of course now the information is out there although we don't know what date it's going to be we know that after November the 5th up until the end of November there's probably likely going to be some kind of model but anyways we are really excited for this but I'm going to show you guys what he talks about here cuz it's there are four investment areas I'd like to cover the first key priority that we have is textual intelligence and our core belief is that if we increase textual intelligence that will unlock transformational value uh in Ai and you can see on the screen here these are the two major models that we offer today GPT 4 the best model with Native multimodality that we just showed and GPT 3. 5 turbo 10x cheaper which is convenient for simple task where what you need is really U things like classification or very simple entity extraction and we really expect that the potential uh to increase

the llm intelligence remains huge and today we think models are pretty great you know they're you know kind of like first or second graders they respond appropriately but they still make some mistakes every now and then but the cool thing that we should remind ourselves is that those models are the dumbest they'll ever be um you know they may become Master students In The Bleak of an eye um they will excel at medical research or scientific reasoning and uh we think that within maybe a year or two from now like the models will be unrecognizable from what they are today and so this year we also plan to push that boundary even more and we expect our next Frontier Model to come um and provide like a step function in reasoning uh improvements as well the second uh of investment area for us is to make sure the models are cheaper and faster all the time and we know that not every use case requires the highest level of intelligence and so that's why uh we want to make sure that we invest and you can see here on the screen the GPT for pricing and how much it's decreased by like 80% in just a year uh it's quite unique by the way for a new technology to uh like decrease in price so quickly but we think it's like really critical in order for all of you to build and reach scale with what we're trying to accomplish and innovate uh with your AI native products so I think that short snippet from this Tech conference was rather insightful because he actually said a numerous amount of different things in that short snippet but I think some of them were more important than others of course he talks about the price decreasing but one of the things that he did mention that was rather fascinating and this is someone that is from open AI he actually speaks about the fact that literally within 1 to two years the models are going to be unrecognizable so that is something that even as someone who pays attention to the AI space and as someone who looks at all of the AI updates in many different things that I literally don't even post on this channel this is still something that is rather surprising and I think it's because humans do have a hard time at grasping the nature of exponential increases in terms of technology and intelligence so I think this is going to be a truly transformative period in terms of what is going to come out of this company within the next 5 to 10 years because if he's stating that literally the models are going to look unrecognizable within 1 to 2 years I mean in 2026 this isn't far away you know 2 years is a very short time period especially for these kinds of technological developments now something that he also said that I thought was also rather insightful was that he mentioned a step function in reaching and for the next models this likely means as we've already discussed that this is a significant discret Improvement in the ai's reasoning capabilities rather than a gradual incremental Improvement and essentially this just means that you know in contrast to the gradual Improvement that a step function implies a sudden substantial Improvement at a particular point which is followed by a new level of capability and this change is most more abrupt and significant compared to the gradual improvements and with the reasoning abilities current models like the gpt3 and GPT 4 have of course made significant strides in their ability to reason and understand and generate text but their abilities to reason can still be limited in certain contexts so the GPT NEX models means that a step function in reasoning could mean that they make a substantial leap in their ability to understand process and generate more complex abstract and logical forms of reasoning and because of that increased level of reasoning it means that they've got improved problem solving and this means that these models are going to be better at tackling complex problems that require multi-step and logical reasoning of course this means enhanced understanding this means that the AI could understand context and nuances in a more humanlike way leading to more accurate and relevant responses decision making these models would likely be able to make more sophisticated decisions based on the information provided similar to higher order thinking and like I said before this is just once again going to open up a lot more applications they even spoke about how you know it's going to be able to do medical research we've seen that Google has been pushing widely on that Frontier with the medical Gemini and they've achieved remarkable benchmarks and I wouldn't be surprised if openi are doing something in that realm now one of the things that I also want to talk about was of course the fact that this release date is rather fascinating and the name of the model did actually make me think about something that was spoke about previously you can see here that we have a model that is called GPT next but one of the things that I spoke about

when covering the Sam Alman Lex Freedman interview was the fact that he said something rather insightful he said that the future models that he releases might not actually be called GPT 5 and of course there might be GPT 5 because they did trademark it but he did state that you know whatever the next model may be we're not sure when it's going to be released or what called oh that's the honest answer is it blink twice if it's this year before we talk about like a gp5 like model called that or called or not called that or a little bit worse better than what you'd expect from a gbt 5 I think we have a lot of other important things to release first I don't know what to expect from gbt 5 you're making me nervous and excited uh what are some of the so right there you can see that Sam mman is actively talking about how they are going to release a few things before gbt 5 of course you know we've seen things like voice engine we've seen Sora we've seen a bunch of other things but you know the way how he talks about how these future models might not even be called what we are expecting them to be called is of course rather fascinating too now one of the things that you may have seen recently was this from Microsoft and this is basically where they talk about the levels of compute that they using to train the next Frontier models and currently we can see that the diagram they use sharks and marine life to I guess you could say help us understand the scale of compute that they are currently using we can see that we have a shark here then of course we have an orca and a whale so I mean the stock increase in terms of the capabilities from this graph going back all the way to the first graph are very similar the gpt3 the GPT 4 technology is only a little bit and then of course the next levels I think maybe open ey clearly have discovered something incredible and they're probably going to shock the world because if you're using that much compute to train something and you've also improved your architecture then I think the amount of capabilities that you can get is truly surprising and I think this is so surprising because not only do we have maybe not improved architectures in terms of the Transformer but I'm talking about certain techniques that open AI are pioneering and that they're using to advance the frontier in terms of the reasoning and the capabilities of their models and I'm going to show you guys a short snippet from this clip where it's actually spoken about in great context about why this is so pivotal and the only reason I'm showing you this is because now with the added context from this slide here where we can see that oh wait and the only reason I'm showing you guys this clip is because now with the added context of this previous graph where we can literally see in terms of the capabilities jump I think it's important to understand the compute side behind it that Frontier forward and like we showed this slide at the beginning like there's this like really beautiful relationship right now between sort of exponential progression a compute that we're applying to building the platform to the capability and power the platform that we get and I just wanted to you know sort of without mentioning numbers uh which is sort of hard to do to give you all an idea of the scaling of these systems so in 2020 we built our first AI supercomputer for open AI uh it's the supercomputing environment that trained gbd3 and so like we're going to just choose Marine Wildlife is our scale marker so you can think of that system uh about as big as a shark so the next system that we uh built um scale-wise is about as big as uh an orca uh and like that is the system in uh that we delivered in 2022 that trained GPT 4 the system that we have just deployed is uh like scale-wise uh about as big as a whale relative to like you know this shark siiz supercomputer and this Mar siiz supercomputer and it turns out like you can build a whole hell of a lot of AI with a whale siiz supercomputer um and so you know one of the things that I just want everybody to really be thinking clearly about and like um this is going to be our segue to talking with Sam is the next sample is coming so like this whale siize supercomputer is hard at work right now building the next set of capabilities that we're going to put into your hands and yeah if you saw it there he said you can build a whole hell of a lot of AI with a large amount of comput so I'm really intrigued with as to what a whole hell of a lot of uh compute is going to be giving us but one thing I do note is that there is going to be a huge amount of capabilities now something that they also spoke about was of course multimodal agents this is going to be something that is here within the next level of Frontier state-of-the-art models I think that maybe this year we get something but there are also some things I do want to talk about with as

to why we might not get that but they also demoed the multimodal agents and of course you can see that their investment areas are the textual intelligence cheaper and faster models the custom models and of course multimodal agents so I want to show you guys this short clip because opening ey haven't really shown us that much in terms of the agentic workflows but I think it's important to take a sneak peek because agents are truly going to change the way that we interact with computers we really believe that like in the future agents may be the biggest change that will happen to software and how we interact with computers and depending on the task they'll be able to leverage text access to some context and tools um so and again all of these modalities that we mentioned will bring also like a fully natural and Noble way to interact uh with um to interact with the software one example of this that I personally Love Is dein by the team AOG they built like essentially an AI software engineer and uh it's pretty fascinating because it's able to kind of like take a complex task and it's able to not just write code but it's able to also understand the task create like tickets browse the internet for documentation when it needs to F to fetch uh you know to to fetch uh new information it's able to deploy solutions to create pool request and so on so it's kind of like one of those agentic use cases that I really love um and in fact like this tweet from Paul Graham earlier this year kind of caught my eye because he mentioned or realized that like the 22y old programmers these days are often as good as the 28-year-old programmers and I think when you reason about like how the 20 year olds are already adopting Ai and tools like divin it's no surprise that they're getting more and more productive thanks to AI another agent experience that I think this time is more towards consumer is Presto and Presto um is letting customers place all with their voice uh so using a voice agent and of course there's not many drive-throughs here in Europe but what I found compelling about this example is that it's really helping a market where um there's been a labor shortage and so in turn that helps um offer not only a great experience but also let uh the the staff actually focus on food and suring the customers but with that I'd like to dive into a couple more live demos to illustrate a little bit uh how you can build assistive experience IES and agents practically uh today so our first um incarnation of so yeah with that you can see that literally one of the things that this AI power drive-through system is it's actually been impacting people because one of the things that you might not understand about drive-throughs is that they're kind of limited to human intelligence and one of the things I was thinking about when I saw a demo in a weekly AI video I covered when someone was actually going through a drive-thru with an AI system and they basically spoke about how it was so crazy because you know an AI system is able to completely understand exactly what you want it's able to in other languages too and it's also able to converse with you in other languages too much more fluently than just someone who only speaks one language and isn't bilingual or able to understand other languages and it's patient and it's fast and I think it's something that's going to allow a lot more unique experiences so that's why agents are something that is very impactful because I think this is where you're really going to see that real life impact other than just in a day-to-day llm interface welcome to Wendy's what would you like can I have a chocolate frosty which size for the chocolate frosty medium can I get you anything else today no thank you great please pull up to the next window so now let's take a look at some of these demos of these agentic workflows that you can actually use and do uh and what they've shown Us in this presentation um incarnation of uh agents for developers is what we call the assistance CPI and the assistance API is a complete toolkit that all of you can use in order to bring assistance into your products so in this case here I'm building this like travel app called one the lust as you can see there's like a map on the right side but there's also an assistive experience on the left side and so this is completely powered by the assistant API so let's take a quick look if I say top five venues for the Olympics in Paris first of all first thing to note I don't have to manage any of those uh let's refresh the app a little bit sounds like we maybe lost

Network top five venues for the Paris Olympics the first thing to not is like I don't have to manage that conversation history is automatically managed by the assistant API from oppi uh and so I don't have to kind of manage my prompt and so on not sure what's happening here let's take a quick look might have lost some Wi-Fi or connection nope let's try one last time let's go to Rome ah there we go sounds like the Olympics was bad luck but uh sounds like we're back so yeah I don't have to actually manage any of those messages the conversation history is automatically uh managed by openi the second thing that's really cool to go out here is that as you could see when I started to interact with these messages the map zoomed automatically and that's one of my favorite features when I build agents it's called function calling and function calling is the ability for all of you to bring knowledge about um your unique features in your app and your unique functions over to the model in this case GPT for so if I say top five um things to see in Rome let's see what happens here in theory uh what should pop up here is once again an interaction between the text and the map here we go so now as you can see as we talking to the model it's able to actually pinpoint the map because it h it knows that this feature exists so it's really cool and that's like already available as part of the toolkit of the assistant CPI now another tool I wanted to call out here is uh knowledge retrieval and we know so many of you want to bring like factual data into the conversations with models like GPT foro and usually you have to build like a retrieval stack to do so and we've learned from so many developers how complex that can be and so we've made a ton of improvements in our retrieval stack and so I'm going to try to see if I can actually demo this in real time so I actually bought this like book to prepare a trip to Italy from Lonely Planet it's a pretty comprehensive book it has like 250 Pages it's like 95 megabytes so I hope the upload is going to work taking a bit of a risk here um but what's happening in real time is like as soon as the file will be uploaded it will be automatically embedded by the assistant API so that I don't have to um think about any of these things to do I will be able to just start interacting in the conversation and say based on this book what's the best photo spot in laio so before I press enter I'll show you quick look at page uh 126 I believe let's go to page 126 so the page 126 talks about laio right and so I'm going to like ask the question here what's the best photo spot in laio and as I'm browsing the book we're noticing here that like the photo opportunity was mentioned on page 128 and it's supposed to be Pano and boom in real time we were able to found in find in this book that this is exactly the place um uh for a photo spot and again I had to do no engineering work I just had to upload the file in the conversation that's were all taken care of for me last but not least there's also another tool that I want like to highlight called code interpreter and code interpreter is disability to write python code in the background to answer some very precise questions usually around like numbers and math and financial data so here for instance if I were to say in this conversation um we are sharing an Airbnb um 44 it's €1,200 what's my share plus my flight cost of let's say 260 Now by asking this question this is not a typical thing that llms do great at by default right but what's happening behind the scenes is that we're actually Computing all of this including con currency conversion and so on by writing code in the sandbox and once again as a developer I have nothing to do but because a poni is managing this does not mean it's a blackbox in fact if I go here and if we refresh the threads um we should see here that this is the exact threads that we've been you know feeding and you can see we we're going to Rome like all of the messages we see the function calls that I highlighted to annotate the map and here this is the python code that was written behind the scenes to actually answer the question you know compute the currency conversion divide by number of people and so on so really like the assistance API complete toolkit with conversation history with access to retrieval and files you can upload now up to 10,000 files in retrieval and even code interpreter and function calling all of this what you can build on from day one so let me know what you think about future models I mean one of the things that is a little bit confusing is the fact that they do have GPT 6 and other names trademarked so I'm wondering if they're just going to continue with the traditional methods but it is quite hard to predict considering the fact that open AI is a company that comes with a lot of drama and of course a lot of surprise and with the rate that AI is exponentially increasing in terms of the capabilities and everything new being discovered what feels like every week I mean you know the capabilities trying to predict a year two years three years

from now are quite hard but I think from this we do know that you know November there's probably going to be a new model released whether it is GPT next 5 I can say one thing it's certain is that it's going to be a Monumental leap in terms of the capabilities and usabil of what we're about to see okay that was