BREAKING: OpenAI INSIDER Drops BOMBSHELL "AGI Achieved"

This might be one of the most important videos that we do make because this is concerning a topic that has been recently discussed in the artificial intelligence space. And this is referring to a major breakthrough at OpenAI from many anonymous sources that are telling us that OpenAI have achieved the major breakthrough that many were speculating around last week, which additionally led to the firing of the OpenAI CEO Sam Altman and a whole host of many other decisions. So right here you can see on this article it says OpenAI made an AI breakthrough before Sam Altman firing stoking excitement and concern One day before he was fired by OpenAI's board last week, Sam Altman alluded to a recent technical advance the company had made that allowed it to push the veil of ignorance back and the frontier of discovery forward. I will be showing you guys that clip later because it is a real clip so from Sam Altman that was recently made by himself. So this isn't just some random person saying this. These are comments from the CEO himself. It says the cryptic remarks at the Apex CEO Summit went largely unnoticed as the company descended into turmoil. But some OpenAI employees believe that Altman's comments referred to an innovation by the company's researchers earlier this year that would allow them to develop far more powerful artificial intelligence models. And a person familiar with the matter said the technological breakthrough spearheaded by OpenAI chief scientist Elia Sutkova raised concerns among some staff that the company didn't have proper safeguards in place to commercialize such advanced AI models. And this is an article from the Information, the same place that was giving us all of the breaking news when OpenAI was going through quite the tumultuous period. Now we do know that this article does hold some credence because not only did Sam Altman make numerous statements, there have been numerous things that we discussed in previous videos that allude to the fact that AGI potentially and most likely has been achieved on some degree internally. So let's take a look here. One thing that we did want to include was the fact that Elon Musk also did take a look at this article and stated that it was extremely concerned concerning. Now, of course this makes sense because Elon Musk is an avid player in the AI space whilst owning companies like Tesla and of course his new company X AI, which recently launched the GROK large language model which is said to compete with ChatGPT. But now let's take a look at the article that Elon Musk tweeted himself. You can see that this is another article covering the exact same topic, but from a little bit of a different angle. And it says OpenAI researchers warned the board of AI breakthroughs ahead of the CEO Alster, sources say. And this is of course from Reuters. So this is on November 23rd, which is of course today, and this was only a couple of hours ago. Now it says head of OpenAI's CEO Sam Altmans Alster Several researchers wrote a letter to the board directors warning of a powerful AI discovery that they said could threaten humanity, two people familiar with the matter told Reuters. Now I find it interesting choice of words here that they said could threaten humanity, as that is something that is only largely discussed or talked about when people are saying that those who are discussing it are largely AI doomers. But if this is true, then this could mark the very next category and evolution age large language models because this means that we've discovered something that would lead them to greater capabilities. So so it continues to state that the previous unreported letter and AI algorithm were key developments before the board's ouster of Altman, the poster child of generative AI, the two sources said. Prior to his triumphant return late Tuesday, more than 700 employees had threatened to quit and join back Microsoft. Which is of course something that you do know now, of course what was also interesting, it says that the internal message to staffers referred to a project called Q or Q asterisk I'm just going to call it Q for now. And a letter to the board before the event weekends, one of the people said. An OPI spokesperson said that the message sent by longtime executive Mira Moratti alerted staff to certain media stories without commenting on their accuracy. So essentially what we have here is the name of this project. We're just going to call it Q or Q. So this is why you've been seeing on Twitter recently, everyone's been talking about this because this is the codename this is. Now we don't know what it refers to, but there are some interesting theories with as to what it refers to and we're going to get into that later because there's a lot to discuss regarding the capabilities of this model and how exactly it works and why this is probably true. The article continues to state that some at OpenAI believe Q Star could be a breakthrough in the startup search for what's known as artificial general intelligence, aka AGI, one of the people told Reuters. OpenAI defines AGI as autonomous systems that surpass humans in most economically valuable tasks. Given the vast computing resources, the new model was able to solve certain mathematical problems, the person said on condition of anonymity because the individual was not authorized to speak on behalf of the company. Though only performing math on the level of grade school students, acing such tests made the researchers very optimistic about Q's future success. So we do need to talk about how why acing such tests made researchers very optimistic about Q's future success. One thing I've seen online and from many people on Twitter, they're saying that acing such tests doesn't mean anything because if they can perform maths at the level of grade students, this doesn't absolutely mean anything. Now I'd like to firmly disagree because the next slide is going to show you and this was pointed out via a tweet. I don't remember which tweet this was, but I want you all to see this because this is from OpenAI's actual page. So take a look at this piece of information. So what we have here is something from OpenAI and what you're looking at is something called predictability scaling. So it says here a large focus of the GPT4 project has been building a deep learning stack that scales predictably. The primary reason is that for very large training rungs like GPT4 it's not feasible to to do extensive model specific tuning. We developed infrastructure and optimization that are very predictable behavior across multiple scales. To verify this scalability we accurately Predicted in advance GPT4's final loss on our internal code base which is not part of the training set by extrapolating from models trained using the Same methodology but 10,000 times less computer. So you can see right here that OpenAI's code base next words prediction as it continues and continues, continues. We have the observed and then we have the prediction. And of course we have GPT4's abilities which means currently that essentially they were able to predict GPT4 capabilities before training it. And if you don't believe me, take a look right here. You can see that this is tweeted by Peter Welinder. He used to be the research lead at OpenAI and now he's the VP of products at OpenAI. This is the guy that worked at OpenAI for for six years. He says important detail in GPT4 blog post. Our research team were able to predict how smart it would be before it was trained and it is very likely that that is what they are saying about Q or this new secret model. And this does make sense because not only did we get this blog post, which is from GPT4's blog post, and not only we did get this article, we also got some of Sam Altman's statements. So. So one of the statements that Sam Altman made that you should check out, which I will play now, is that Sam Altman did talk about how they managed to discover some ability, but they push the veil of ignorance back and they advance forward for humanity. That's probably not the like four times.

Now in the history of OpenAI. The most recent time was just in the last couple of weeks. I've gotten to be in the room when we sort of like push the front, the sort of the veil of ignorance back and the frontier of discovery forward. And getting to do that is like the professional honor.

So now that you've seen that clip, and that clip was very, very recent, which is quite interesting considering all the information going around. And I think it's. And I think it's rather fascinating that this statement by Saab Altman would be made at the same time that there is these certain leaks and that other things are going on, which I will continue to discuss. Now, there was one statement that people are saying where Sam Altman said, is this a tool or, or have we built a creature?

But it has been. I think this is like definitely the biggest update year for people yet and maybe the biggest one we'll have because from here on, like now, people accept that powerful AI is going to happen and there will be incremental updates. But there's like, you know, there was like the year the first iPhone came out and then there was like everyone since. And at this point, like, you don't even really know the difference between this one, like last year's one. So this was like, I think a big moment. One thing that I am happy about.

Is.

I think people are viewing these systems as, correctly as tools, artists in particular, but other people as well. And there was this, I think there's a real moment of fear which is like, is this a tool we have built or a creature we have built a second? I think people now view this as a new thing in the toolbox of humanity, are doing like really remarkable things with it.

And I do want to firmly say that Sam Altman has previously multiple times stated that it's not a creature. So any of these statements that people are saying, I definitely think that this comment was taken out of context. And I'm going to show you guys the full clip so you can see the entire context and not be confused. But. But that doesn't mean that Sam Altman isn't hinting or at least giving us certain hints towards this AGI because we've known that Sam Altman has made comments and made previous statements and then retracted them when they were also looked at further. So one of the things that he also looked at after looking at these clips, you can see that it says, ChatGPT boss says he's created human level AI. Then he said he's just memeing AGI has been achieved internally at OpenAI. Sam Altman writes on Reddit before backtracking, and I did a whole video on this around two weeks ago where I took a deep dive into every single AGI claim and all these secrecies that were taking place. Many people hadn't realized that OpenAI secretly made several changes to their website to showcase that they were going to be moving towards an AGI future. And if you thought that that was not weird, you, you should take a look at some of the clips from that video, which I will include now because they have a more deep dive into some of these AGI specifics. So you can see right here that currently the core values have shifted to AGI focus and it says, we are committed to building safe, beneficial AGI that will have a massive positive impact on humanity's future. Anything that doesn't help with that is out of scope. So that is crazy, because they've put this as the first point, meaning that currently something has changed to OpenAI to where they've decided that AGI is going to be their North Star. And by North Star, I mean their focal point for where the company is going to go. Which means that systems like ChatGPT and Dall E3 are going to potentially be subparts of this AGI. And what's interesting is that they said anything that doesn't help with that is out of scope. So maybe this means that OpenAI was working on certain things and certain products that weren't necessarily going towards AGI but may still be AI based. And now they've decided, you know what, we're not going to be working on that anymore. We've now decided to just be focusing on AGI. So that is why this is a secret bombshell that they secretly dropped silently updating their page. And we now know that this is pretty insane. Now, further on in the video, you might be thinking, who on earth is Jimmy Apples and why does his statement on AGI even matter? Jimmy Apples, if you didn't know, is essentially an OpenAI leaker. We aren't sure of what he is or what he does, but we do know that he always does have early information about GPT4 or whatever OpenAI is currently working on. If you're wondering about any skepticism regarding his statements, previous statements around OpenAI have come out with 100% accuracy. For example, he actually tweeted and got the Release date of GPT4 a week before it was even announced. Meaning that he definitely has some kind of inside information. Now, many sources speculate that this Jimmy Apples guy is someone that spies on people near the OpenAI headquarters. Now you can see that there's a 10 minute video which goes into this and they talk about how Jimmy Apple says that let's pick a random date and 3/14 and then of course GPT4 is of course announced on that exact date. We know that this person, whoever they are, definitely has some inside information. Now back to the statement about AGI. He said that AGI has been achieved internally on September 18, 2023. Now what's crazy is that a week later the CEO Sam Altman tweeted that AGI has been achieved internally. Okay? And he tweeted this on a certain post. And then what was crazy was that he actually edited this comment and said obviously this is just memeing. Which when AGI is achieved, it will be announced and it won't be announced with a Reddit comment. So at the same time it seems that Sam Altman is aware of this OpenAI leaker and he understands that whatever is going on behind the scenes, that Jimmy Apples is likely to know a decent amount about it. So at the same time, I find it super interesting that Jimmy Apples goes ahead and says AGI has been achieved internally. Then little bit over A month later, OpenAI start to talk about AGI and state that AGI is simply their main focus and their core values. Anything that doesn't help with that is out of scope. Which leads me to believe that Sam Altman and his team at OpenAI are much closer to AGI than we initially think. So we do have this tweet that breaks it down and I'm not going to read all of this because I don't want to confuse many of the standard viewers and sometimes you can get confused. So I'm going to just try and break this down in the most simplest way possible. But you can see right here that this is quoting the article and he says you need this type of thing to solve really hard math problems. And it's really probably closer to, to reinforcement learning with AI feedback. Then we have a comment from Elon Musk that says it's some kind of alphazero self play applied to large language models. Now if you don't know what he's referring to there, he's referring to the fact that AlphaGo, which is one of the state of the art models that was able to do crazy things, including beating the AlphaGo world champion with unorthodox moves and doing things that nobody could predict. It was because it was able to use something called a tree search where it was able to throw think in a radically different way. And because of that it was able to make radically different moves. And essentially Elon Musk here is stating that it's going to use this kind of technology. So it's going to be like alphazero self play applied to large language models. And essentially what that was as well was that AlphaGo actually played against itself millions and millions of times and then became the best player in the world. It didn't actually need to play humans anymore, it just played itself and and iterated upon that data. Then of course we have the Q learning explanation. So Q learning is basically a type of reinforcement learning which teaches computers to learn by rewarding them for making good decisions and then penalizing them for making bad ones. This is something that you've heard before, but this one is a bit different because it allows you to make long term decisions. So if we get into the six stages of this, we have the environment and the agent, which is where you have the environment like a video game or a maze, you and the agent, which is the AI or computer program that needs to learn how to navigate this environment. Then of course we have the state and the actions. The environment is made up of many different states, like different positions or scenarios in the game. And then there's many different actions that you can take in the game, like moving left or right or jumping. Then we have the queue table, which is the cheat sheet that tells the agent what action is best to take in each state. At the table it's filled with the guesses because the agent doesn't know the environment yet. Then of course we have the learning by doing. You start to explore the environment and every time it takes an action in the state, it gets feedback from the environment. It rewards the positive points and penalizes the negative points. Then of course it updates the Q table and then the Q table essentially considers the current reward and the potential future rewards. This way the agent doesn't just learn to maximize immediate rewards, but can to consider long term consequences. Over time it gets more and more accurate and and it becomes better at predicting which actions will yield the highest in rewards and eventually it can navigate the environment effectively. So it goes on to state here, and this is from GPT4, that Q learning is like playing a complex video game where over time you learn the best moves and strategies to get the highest score. Initially you don't know the best actions to take, but as you play, the more you learn, you're going to get better and better at the game. And that's exactly what Q learning is. So here are some of the tweets from the wider AI community that have been on Twitter that are rather interesting that I thought I'd share. And it says what could OpenAI's breakthrough Q be about? It sounds like it's related to Q learning. For example, Q denotes the optimal solution of the Bellman equation, alternatively referring to a combination of the A algorithm and the Q learning. One of the natural guess is that it's alphago style Monte Carlo tree search of the token trajectory, which is previously of course what we discussed. And it says that previously papers like AlphaCode showed that that even very naive brute force sampling in an LLM can get huge improvements in competitive programming. The next logical step is to search the token tree in a more principled way. So it says indeed Q seems to be about solving math problems. Then of course we have a very interesting clip here which is from Shane Legg, the founder and chief AGI scientist at Google DeepMind. And he actually talks about how this method that they're planning on using is pretty much exactly what we need in that next stage of evolution because. So take a look at that clip.

Now these foundational models are world models of a kind, and to do really creative problem solving you need to start searching. So if I think about something like AlphaGo and the Move 37, famous Move 37, where did that come from? Did that come from all its data that it's seen of human games or something like that? No, it didn't. It came from it identifying a move as being quite unlikely but possible and then via a process of search coming to understand that the that was actually a very, very good move. So you need to get real creativity. You need to search through spaces of possibilities and find these sort of hidden gems. That's what creativity is. I think current language models, they don't really do that kind of a thing. They really are mimicking the data. They are mimicking all the human ingenuity and everything which they have seen from all this data that's coming from the Internet, that's originally derived from humans. If you want a system that can go be truly beyond that and not just generalize in novel ways. So it can, you know, these models can blend things. They can do, you know, Harry Potter in the style of a Kanye west rap or something, even though it's never happened. They can blend things together. But to do something that's truly creative, that is not just a blending of existing things, that requires searching through a space of possibilities and finding these hidden gems that are sort of hidden away in there somewhere. And that requires search. So I don't think we'll see systems that truly step beyond their training data until we have powerful search in the process.

And then, of course, lastly, we do have the Google DeepMind founder Demis Hassabis saying that using a method called tree search to explore with a large language model is largely going to be the next evolution of LLMs, which they were planning to use in Gemini, which they haven't released yet. So if they manage to beat them to this, it would be a surprise since they've been working on this for quite some time. With that being said, let me know your thoughts on OpenAI's recent breakthrough and has AGI been achieved? I personally do think so, with everything said. And if it has been achieved, what do you think they're going to do next?