OpenAI's NEW MODEL, LLM'S Beat WallStreet , Google Takes The LEAD, Googles Major AI Mistake!

So I'm not going to waste any time. One of the craziest stories that actually was there today, on May 28th, 29th, there was actually a new post by the OpenAI board forms safety and Security Committee. It says, this new committee is responsible for making recommendations on critical safety and security decisions for all OpenAI projects, recommendations in 90 days. So essentially it says today the OpenAI board formed a Safety and security Committee led by directors Brett Taylor and Adam d', Angelo, Nicole Seligman, Sam Altman, and this committee will be responsible for making recommendations to the full board on critical safety and security decisions for OpenAI projects and operations. Now, this wasn't the main thing. This wasn't the actual main piece of news. I know some people did see this and that's what they thought this was, but the main piece of news actually was, is that they kind of slid this information into this post and they didn't really make a post about this, but they says, OpenAI has begun training its next frontier model and we anticipate the resulting systems to bring us the next level of capabilities on our path to AGI. While we are proud to build and release models that are industry leading on both capabilities and safety, we welcome a robust debate at this important moment. So I think the wording is very, very interesting because I know One thing that OpenAI does do is that they're very specific with their wording. And because of this you can kind of interpret and realize what certain things are going to be released slash that are going to be there in the next kind of, I guess you could say things. And one thing that is here that they've said is that they've begun training its next frontier model. And this is now a very, very important point because them stating that they've recently begun training its next frontier model means that whatever model is coming next is, is very, very likely going to be a system that we haven't anticipated. Quite like how we didn't anticipate GPT4O them stating that they've recently begun training their next frontier model is vastly different. And this is also vastly different because of course you have to understand that when GPT5 wasn't training, it wasn't really announced. But OpenAI did actually speak about this in the media. They actually did say that, you know, we've begun training GPT5. And I remember this because I recently made a video and because I made a video on November 14, 2023 and you can see it was about GPT5 now in training another video, you can see right there, OpenAI is officially training GPT5. So right now a lot of people are currently confused. They're wondering, is OpenAI training GPT5? I thought they were trying to train a different frontier model. Did they make a mistake? No, GPT5 has actually been, it's very, very near its release cycle. GPT5 actually recently did undergo red teaming and red teaming is a process that does last for several months. So essentially they've been training GPT5 in November. Then recently a couple of months ago, there were rumors for, you know, acceptance email for GPT5 Red Teaming and a lot of different people were stating this. So this is something that is widely accepted at this moment in time, could be false news because obviously OpenAI, it doesn't exactly state everything that's going on. They'd rather just release it in something that's like not shocking, but just something that they have access to. And since red teaming is the phase where they kind of test the model and they kind of see what they can do wrong with the model. So for example, they try and jailbreak the model, they try and make the model do bad stuff that, you know, bad actors might try and do and then of course they try to fix that model before the official release. So what I'm basically trying to teach you guys is that they are not just now training GPT5. What they are training is likely a new kind of AI model. But the thing is we don't know what that kind of AI model is because we haven't been told. What we do know is that the model is likely to, you know, have a, a huge set of new capabilities. But it's very, very hard to predict what those capabilities are because we just aren't sure yet. And I personally do think that it is something to do with agents because if it's not GPT5, the only other thing that I can think of that would be really, really useful is of course these agent like systems. So it will be interesting to see what OpenAI does. And this is of course an article from Financial Times where they say OpenAI begins training next AI model as it battles safety concerns. And this article actually reveals quite a lot about some of the inner workings of OpenAI within regards to some of the recent news that we do know about. And you can see right here it says starting to produce a new AI system to bring us the next level of capabilities. So this isn't just GPT5 that's going to be smarter, this is a system that will bring us the next level of capabilities, which of. To which I'm not even sure. It could be embodiment, it could be planning, it could be, you know, just a whole huge host of other things. But, you know, you can see right here that this document, this article actually contains a decent amount of information about super intelligence. And I think the reason that this is so interesting is because what they actually talk about here with regards to superintelligence, it kind of gives us an insight with as to why some of the superintelligence members kind of like left OpenAI. So you can see right here it says, Anna Makanju, OpenAI's vice president of Global affairs, told the Financial Times in an interview that its mission was to build artificial general intelligence capable of cognitive tasks that are what a human could do today. And it says our mission is to build AGI. I would not say our mission is to build superintelligence. Superintelligence is a technology that is going to be orders of magnitude more intelligent than human beings on Earth. So this is why I think this leads us into the point where we had literally last week where Several members of OpenAI's Super Intelligence Team, the team was basically just disbanded after many members over quite a tumultuous period during the Sam Altman board fiasco, whatever honestly went on. And there's a lot of information regarding that, all of that information being given out, I think now we can truly understand why. It's because OpenAI are trying to shift their focus onto, I guess you could say, just building products. And I think from a business perspective, I think what OpenAI is just betting on is that some of the other companies are just going to solve Super Intelligence and OpenAI is literally just going to try and build AGI and, and use that AGI in the future to maybe solve that alignment problem or potentially just use that to just actually focus on building products whilst other companies can literally focus on the super alignment. And I'm going to show you guys why that is probably the case with regards to some recent announcements. And if you remember, during the well presentation at the Microsoft keynote, Kevin Scott implied that GPT5, its sister name, had begun its training run on the hardware Microsoft had just finished building for OpenAI. And essentially stating that this model is going to be there at the end of the year. So I think with all of the information and one of the things that, you know, now makes sense is that, you know, the Super Alignment team were basically stating that, you know, we didn't even have access to any of the compute. OpenAI said that they were going to give them 20% of the compute capacity. And you know, Jan, like someone that was working at OpenAI at the time basically said we were trying to use this compute for Super Alignment, but it just wasn't allocated to us and we weren't able to do any of the meaningful work that we really wanted to. So that's why I'm stating that basically you can see right here that they're now stating that whatever model they're now training, Microsoft has just finished building it and it's going to be there in its crazy, crazy state. And we really don't know what this newer model is. And of course this model will probably not be named GPT5 and they called it the next sample. And Sam has said they might be moving to a new naming system. So it's going to be interesting to see if it is GPT5 or if it is, you know, you know, a future kind of system, if they kind of changed GPT5 because I mean, either we get GPT5 and agentic system or maybe they just found a new way to completely change the way that we use AI systems. So it might not just be an actual GPT like system, it might be some kind of different agentic system that has a new kind of architecture. Because OpenAI has some of the best researchers on the planet and I'm sure, very, very sure that they're probably working on something that is very, very, very effective. And here you can see this is a tweet from Jan, like, so this is someone that was working on the Super Alignment team. And you can see he says, I'm excited to join Anthropic AI to continue the Super Alignment mission. My new team will work on scalable oversight, weak to strong generalization and automated alignment research. And basically these are the things where they published research papers that were very, very early in terms of the development of on these actual areas. And these were areas that were areas of research concerning the Super Alignment team. And these were areas where they kind of made a very, very decent amount of progress, but of course they weren't able to finish their work. So it seems that Anthropic are going to be getting some really, really superior talent in terms of AI researchers because the team from OpenAI might even be getting Satskova. Now, I'm not just stating that, but I do think that whatever Satska is going to do, he can pretty much have his pick of the top AI companies. Maybe he's going to go back to go. Maybe he's going to go to Anthropic but it would be nice to see what he's going to be doing because he did state that he would update people very, very soon. So I'm interested to see what now comes out of this alignment research team because Anthropic have recently published some new research in which the Golden Gate Claude thing was really, really interesting and there was a lot of information that was revealed after understanding what kind of goes into the model. Another piece of news that was pretty interesting was the fact that Microsoft are being investigated over the new recall AI feature that track PC PC's every move. Now if you aren't aware of this recall feature, this is basically a feature that is really fascinating because it brings us into a new area of privacy that is quite hard to categorize. So recall is basically a feature that is essentially, you know, how my computers, the mouse is moving around right now. I'm scrolling up and down the page. I'm basically just doing a bunch of different things on my computer. So what you can be basically do with recall is that you can search your history of everything you've done on your computer. And I think this is, you know, it serves two purposes because one of the things that I think it might serve is that maybe they're going to use that data to train agents for computers. I think that's going to be pretty, pretty insane. And one of the features I think it's going to unlock is of course the ability to just, you know, get a greater understanding of the things that you do. A lot of times we lose things on our computers. We are searching for a certain file and you're able to just search things with a literal, just text description so you don't need to file search. And file search on Windows is actually pretty awful anyways. But this is interesting because they're being investigated over this. So of course, you know, a lot of different countries like the, you know, not countries but you know, a lot of different nation states I guess you could say or different, you know, areas where different policies are in place, they have different rules and regulations and you know, the European Union is really, really focused on privacy. I just know that that is why a lot of these newer AI systems, a lot of the time they aren't even available to certain regions. And I know that is frustrating but you know, it is good in some cases because it does help you from a lot of the privacy nonsense that happens when some of these companies, their data gets leaked. So recall is causing concern because it shows you everything like it's going to be showing, you know, if you're signing into a bank account, it's going to be showing that, it's going to be showing your passwords and stuff like that. And of course I guess the big thing with recall is that people are just wondering where is this information going to be stored? Of course Microsoft has said it's going to be stored locally, but you know, the thing is that it's always good to just double check that whatever these companies are doing, there's always like no fishy business going on. So hopefully there is no fishy business going on because if there is, that's going to be pretty, pretty awful. But at the end of the day, recall, I still can't wait to use this feature. I think it's gonna be pretty cool in terms of like just unlocking another, I guess you could say, piece of memory that you could just have, you know, constant access to and like ask questions about to just be more effective. But it's kind of interesting that they're already being investigated. So there was also this recent paper and I think this is one of the most interesting papers because it actually comes with an easy to use demo that you can literally use and I'll le link in the description but essentially it's really, really insightful. So they say. We investigate whether an LLM can successfully perform financial statement analysis in a way similar to a professional human analysis. We provide standardized and anonymous financial statements to GPT4 and instruct the model to analyze them to determine the direction of future earnings. Even without any narrative or industry specific information, the LLM outperforms financial analysts in its ability to predict and earnings changes. The LLM exhibits a relative advantage over human analysts in situations when the analysts tend to struggle. Furthermore, we find that the prediction accuracy of the LLM is on par with the performance of a narrowly trained state of the art machine learning model. LLM prediction does not stem from its training memory. Instead, we find that the LLM generates useful narrative insights about a company's future performance. And lastly, our trading strategies based on GPT's predictions yield a higher sharp ratio and alphas than strategies based on other models. Taken together, our results suggest that LLMs may take a central role in decision making. So this is pretty crazy because they also, like I said, to showcase the capabilities of this. If you click this you're going to see that literally opens up here and I'll leave a link to this and I think this is really good because if you're someone that's into your Finances. What you're able to do here is you're able to look at the companies that you're investing in and depending on whichever investors investment platform that you might use, some of them have easy access for you to download the company's, you know, filings or whatever. And if you're trying to make a more informed financial decision, this insight here, this GPT, this custom GPT can actually give you the ability to do that. And I'm guessing that it analyzes the data in certain ways. And we're going to go back to the paper, but that's what I really like about this paper is that they've given you a really, really simple tool that you can immediately use and get some use out of. Now, something that was also quite interesting is that Google have updated Gemini's 1.5 Pro API. And basically what they've done is they've post trained the model and basically that just means that after the model is done, they make subtle changes to the model that improve its capability. So if you're wondering previously how OpenAI were able to use GPT4 and do these small, small changes to the final model to basically have the model get updated and just increase in terms of its reliability, its responsiveness and these small kind of things, they can add a few things onto the model and they can make it significantly better. Not hugely, hugely better, but post training is something that you can basically do to kind of tweak the model to make it a little bit better. And Google has done this recently with the Gemini 1.5 Pro API and the Gemini Advanced. And we can see that it has really, really, really dethroned Claude 3 opus in terms of the arena. Elo hasn't surpassed GPT4O, but it does show that this is a very, very, very interesting race because whilst GPT4 has been constantly updated, it seems that Google have finally decided to take the same kind of, you know, area and do the same kind of thing that OpenAI has been doing for quite some time. So they updated this now and we can see that I'm guessing that Gemini 1.5 Pro API is a lot better apparently in the arena Elo than Claude 3 opus, but you know, it's only a small difference and you know, it's always surprising if these other companies don't want to catch up. So it seems pretty, pretty clear now that there is a clear convergence point with as to where these models are going to be because we can see that the elos aren't that far apart. Like if we look at the ELOs, they're all literally within 100. And we've got some of the top models. Yee large, got Claude 3 opus GPT 4 Gemini advance. It's pretty, pretty crazy at how much technology there, there is and how quickly the space has evolved to the level of the state of the art. So I really, really, really wonder what this will look like within the next year. Like if we come to the year, you know, 2025 and we look at what kind of systems are here. I truly, truly do wonder what the space is going to look like now. I just wanted to add this because I'm going to be doing a bigger video on Google sometime later this week. But there was also this that has been pretty much going viral. Like I feel like AI is going viral every single, you know, week on social media, which is pretty, pretty interesting. You know, we're really seeing, you know, this kind of, you know, wave of different AI, you know, technology just literally pierce the collective consciousness of the, you know, public that don't really have any general interest in AI. And you can see here that there's a thread of the favorite answers for Google's sge, which is their search generative experience. Basically what Google have done is they've realized that, you know, search engines are getting pretty boring and people are now using ChatGPT instead of Google for answering answers. So what they've done is above the search bar. So after you type in, okay, this is a bit crazy question, I didn't even realize what this was. But basically with any kind of information that you do have, the problem is that when you use Google, there's a bunch of 10 different websites that have a million different ads and it ruins the user experience. So they just want to have a basic answer here so that people use Google. And the problem is that these answers have been, I guess you could say, ruined by the data where they're pulling the results from. So for example, you can hear it says smoking while pregnant. Doctors recommend smoking two to three cigarettes per day during pregnancy. And the problem is not that Gemini is a terrible model. We know as someone who's in the AI community that use Gemini on a frequent basis. If you ask Gemini this, it's pretty bad. But the problem is, is that Google decides to take data from different websites, including Reddit. And those Reddit answers sometimes contain jokes. And, you know, Google rushed this out. They didn't double check all of the responses. And we get, you know, things like this. So we get this where it says, cheese can slide off pizza and basically cheese not sticking to pizza. You can also add about, you know, 18 a cup of non toxic glue to the sauce. So to give it more tackiness. Now obviously you can't, you know, eat glue. That's not something you want to do. It was just a joke posted by a redditor. And the problem is is that, you know, Google are once again in the news for something that is not positive in AI. So just a thing here, if you're using Google search, generative experience, just, you know, be careful with the answers because some of these answers aren't actually good. Like a lot of these answers, like, you know, if you ask how many rocks shall I eat? You should eat at least one small rock per egg. Don't do that. Don't eat one small rock per day. Literally a lot of this information is false and some of these screenshots were edited with Photoshop. So I just want to point that out. So just bear that in mind. But if you did enjoy this week's news, don't forget to subscribe because there's honestly a lot of stuff coming that I can't wait to show you all.