HUGE AI NEWS: OpenAI Releases Sora, Fully AI Generated Games, New AI Agent, Recreating The Brain...

Oh, one of the first stories that actually released this week was of course, the O1 preview transforming into the O1 full. And of course, this now actually has advanced image analysis. So I think this is one of the things that is really underrated about O1. Not only do you have Pro mode, but one of the main things that you do have is Advanced image analysis. Image analysis is something that is quite underrated because it's not used by everyone. But if you have an image, there is a billion different things that you can do. And this is something that was released with the full version of owon. I know a lot of people aren't taking advantage of this, but I can guarantee you that in a few weeks you're going to see some crazy, crazy prompts from individuals around the globe showing you all exactly what they've managed to do with O1 image analysis. And of course, with O1 now, the 014 version. A lot of people at launch were stating that this version was kind of disappointing. However, the benchmarks actually kind of lied because the benchmarks that were actually there for O1 were a little underestimating exactly what O1 was. So if you remember the benchmarks for O1 and Zero1 Pro mode, a lot of people were talking about, why would I pay, you know, $200 a month for this? And essentially, after a lot of people have actually began to use the Zero1 Pro mode, I'm starting to see a different vibe in terms of what people are not expecting out of OpenAI, but the kinds of results that they are getting and the kind of, I guess you could say, vibes that I'm hearing from people that are using this model for some of the most advanced use cases. So, for example, I'm seeing people say, wow, the O1 Pro mode is really, really worth it. And Zero1 is honestly so much better than I had thought. So you can see right here as well, what I've done is I've shown you guys the differences. And one of the one I wanted to highlight, you can see on competition code, you can see that the 01 preview compared to 01, there's actually nearly 100% jump in terms of what you're seeing over there. So we can see that 26 to 64, that's really crazy. And then of course, I don't think everyone is going to buy this, but I think some people might just because of how powerful it seemingly is. But of course, that is the fact that you do have the 01 Pro mode, which is essentially the model that thinks for the longest. And what's crazy about this is that this is just.01. And we can see that the benchmarks are just continually increasing with the amount of compute that we do add to the model. And I do wonder what's going to happen with further models like 020304. And one thing that I do want to quickly add here, and this is something that people just continually, continually forget. Anytime you're looking at any AI benchmark, one thing that I want you guys to remember is the fact that when we look at competition, Math, Competition, Code, PhD, Science of Questions, any absolute benchmark, remember that benchmarks, almost all of them have some kind of error, which basically means that these AI models are a lot smarter than we think. Because when we see the models getting 94, 95% on the test, usually that means the model has saturated the benchmark. I mean, if all of those benchmarks that I just spoke about, a lot of them have maybe 2 to 3% errors or maybe 5% errors. So when you see a lot of these models hovering around the 95 to 96% area and you're thinking, wow, I wonder when these models are going to get 100%. Understand that with some benchmarks it just simply isn't possible. So that's why I'm stating that in the future, Sam Altman stated that, look, benchmark saturation is going to be a thing. These models are going to be able to completely ace any benchmarks. So it's going to be really interesting to see what that means for the AI space. And of course with this one, one of the things they focused on with 01 Pro mode, which cost $200 a month, is the reliability. So these results were based on four out of four. So they did four tests and if you got it right four times, they that was the only time they counted that response. Now, something crazy that was really cool was Google's Genie 2. Now, Genie 2 was absolutely incredible because I think this was something that went really underrated under the radar simply because we don't have access to it yet. But this was something that was launched by Google and I think it was one of the things that just is like mind blowing when you think about what it means for the future of AI. Now, of course, you can see on screen what you're able to do is simply create video games by simple text prompts. So you can say, create me a game that exists on Mars. Create me a first person shooter in this area, and you can literally explore them. Now, I do know that, you know, multiplayer games are pretty much a lot different compared to these single player games. But I do still believe that the applications for this are going to be completely different. Like if we can manage to figure out how exactly we can, you know, solve these generative worlds and make them consistent in terms of the consistency from looking to one way to looking another way. And that's something that GENIE has been able to solve. It's going to be really, really interesting to see how the gaming industry is impacted by this. I know some people would love an AI generated game. The idea of playing games that are procedurally generated, everything is completely new, that has endless, endless playability, is going to be something that I think in the near future, maybe, let's say 10 to 15 years maybe, games are going to be AI generated in a way that every person has their own uni tailored experience. And I wonder what that will do to the replayability of a video game if every single time it's AI generated, everyone has a new and crazy experience. So this was something that I wouldn't underestimate because Genie 1 was 2D and now Genie 2 is actually 3D. So this was a huge, huge improvement in terms of what they were able to do. And this was actually even better than the Minecraft AI that was released, not just, I think maybe one or two weeks ago. So this was something that I think went under the radar, did make a video on it, but I know that this is something that they did miss out on. So it's going to be really interesting to see what happens once this stuff finally gets integrated into other games and of course when demos do become available. So that's what I'm really, really excited for. So that will be really interesting. Then we had Google's Gencast, which is an advanced AI powered weather forecasting model developed by Google DeepMind. This basically leverages machine learning techniques to deliver faster and more accurate weather predictions compared to traditional models. In this video you'll see an overview of exactly what it's capable of and how AI, regardless of lms, is actually changing the entire world.

For centuries, humans have struggled to understand the weather. From putting a wet finger to the wind, listening to cricket chirps and looking to the stars for answers. Now we believe AI can help us advance and understand how we can predict it. Meet MetNet 3 and GraphCast are deep learning models designed to generate more accurate weather forecasts. Traditional methods work by simulating entire systems with hundreds of variables interacting with. In practice, this means abstracting those variables into equations and then Manually coding them into algorithms. Our AI models take a different approach. They analyze past weather data to learn cause and effect relationships between weather conditions. These learnings allow the models to find subtle trends and patterns inside the data which they extrapolate to predict what could be coming. MetNet3 and GraphCast outperform the best systems in the world, seeing further into the future more accurately, efficiently, faster and in better detail for every day and even extreme weather. MetNet3 is already improving the accuracy of 24 hour weather forecasts on Google Search and we have Open sourced the GraphCast model which the ECMWF is using to generate forecasts and make them accessible on their website. Imagine a future where we can help people to prepare earlier for hurricanes, enable farmers to grow better crops, or even help us decide if we should pack an umbrella. AI won't just help us predict the weather, it'll help people make better decisions about their lives.

I quickly do want to add that I know that this video of gencast was cool, being able to predict the weather and stuff like that, but I do think that like in the future a lot of AI tools are going to be able to really predict things that we may not have thought. Like there was even a study on how they use GPT4 to I think with the degree accuracy of 80% accurately predict state by state what the results were, which is just like mind blowing. Like I couldn't even fathom how that was even possible with GPT4. And this is why I say that these LLMs are a lot smarter than we think. So I'm thinking in the future AI is going to be predicting a lot of different things and weather is just one of those many different things that's going to be able to do that. Now of course previously last week I spoke about how Amazon introduced a whole host, a whole suite of models. They introduced Micro Nova, Light Nova Pro, Nova Premiere. But I didn't know that Jeff Bezos was actually, you know, very, very engaged in terms of the AI going on at Amazon.

What is it that you're doing at Amazon?

AI.

AI, yeah. So I mean there are a few things, but small. But it's 95% AI.

And where do you.

It's just so. Because we're literally working on a thousand applications internally. So AI, you have to remember AI, modern AI is a horizontal enabling layer. It can be used to improve everything. It will be in everything. This is most like electricity, these kind of horizontal layers like electricity and compute and now artificial intelligence, they go everywhere. There isn't, I guarantee you there is not a single application that you can think of that is not going to be made better by AI.

Now, whilst everybody is focusing on AI, I also am focusing on AI and I I'm using this 60 second window to shamelessly plug my AI grid academy. This is something that I've recently revamped where over 200 people are using AI agents and prompt templates to make money. And every week we share a bunch of different resources on how people can take advantage of this AI revolution. As we know that many companies are focusing on this as their future. One of the things I have is a workshop Wednesday which is going to start in 29 hours, which is I break down winning strategies into simple actionable steps. I have private videos where I'm showing you guys exactly how to use AI agents to make money. Then on Fridays actually showcase the best AI tools to automate a lot of this stuff. And of course on Sunday I actually break down various case studies from in the community and of course around the Internet on people that are actually making serious money with AI. If that is something that interests you, don't forget to check it out. It's going to be one of the first links in the description. And now let's get back to the video. Now one of the crazy things that actually happened this week was Vaheer Kazimi, who has a PhD in machine learning and more importantly actually works as a member of technical staff at OpenAI, said something absolutely incredible. He stated that in his opinion they already have achieved AGI. And it's become even more clear with 01 that we have not achieved better than human at any task, but what we have achieved is better than most humans at most tasks. Now I've got to be honest, that first sentence, that first very line that just like, I'm even like speechless trying to say this right now. Because if it is true that OpenAI have achieved AGI, that would be a monumental milestone in terms of human achievement. So I think this thing right here, of course him stating that, look, in my opinion we've achieved AGI and I think the fact that a lot of people would say, okay, OpenAI didn't actually say that, but this is a member of technical staff at OpenAI and he's actually said in his opinion they've already achieved OpenAI and his opinion they've already achieved AGI, I think it's really important to see where we are in terms of the AI space. I remember before it was laughed about to talk about AGI coming very soon. I remember certain YouTubers were saying AGI within seven months or whatever, and a lot of people were laughing at them. But a lot of people are now stating that, look, we potentially have AGI in December, which is definitely a lot quicker than most people did think. And it's going to be really interesting because I think the biggest thing that you can take away from this is the fact that as we move from 01 to 02 to these thinking models, it's going to get really blurry to see what AGI is. And the biggest thing that I would say is going to be really difficult for everyone is the fact that a lot of times when we do have new technology, unless it impacts you directly on a day to day basis, you aren't truly going to understand how, how impactful that technology was. The reason ChatGPT was so crazy is because all of these college students could use it. Anyone could use it to write an email, you could use it to draft a legal document. Sometimes it was something that on a day to day basis you could actually use. And I think that even if we do get to AGI and remember I spoke about how the fact that with Pro Mode it's basically good at really, really advanced tasks, which the average person just doesn't have any use for, I think it's going to be really difficult for the world to grasp the, the level of change that we're experiencing now. Someone actually talks about this quite a lot. Brian Chesky, the founder of Airbnb, actually talks about the fact that, you know, things are changing, but in terms of other advancements, we also got llama 3.3 70 billion parameters. So I got to be honest, LLAMA keep surprising me. I said llama, it's supposed to be Meta, but they keep surprising me in terms of how much they are doing. And it seems like they really, really, really ramped up their AI efforts with the kinds of things that they are producing. They've revealed a lot of different things that they are working on in the AI space. And one thing I do like about Meta is that they're working on things that are not just LLMs, which is just truly fascinating. Solana 3 3.70B is actually the latest iteration in the family of large language models from Meta. And this One, of course 70B has 70 billion parameters. Now this one is designed for high performance natural language processing tasks while maintaining efficiency and accessibility. So this one is, you know, fine tuned for instruction following tasks, making it highly effective for dialogue and task specific use cases. And we can see that the improvements are pretty Incredible, because one thing that's really funny, and it's actually crazy how often this happens, is that if we actually just take a look at how Llama 3.370 B performs, and if we compare that to the recently released Amazon Nova Pro, we can see that it manages to just edge it out in various cases. I mean, the MMLU is 86 and the Amazon Nova Pro is 85.9. Now, I do think that different models have different, different qualitative differences which aren't visible by just numeric values, which is of course something that a lot of people think. Of course, once you use the model, you're going to figure out quickly that some of them are good at certain tasks while others just completely fail. But what I want to tell you guys is that it's crazy that Amazon can release a model this week, and then just next week or three days later, Llama can release another model. And it doesn't make the model obsolete, but it just means that you thought you had something and then someone else just releases their own model, which is like, it's crazy to realize how quickly this stuff is moving. And of course the price difference is absolutely incredible, which is what this model is meant to be. It's meant to be a really effective model that you can use for a variety of different use cases. So it's going to be really interesting to see a lot of people building stuff with this model. I'm going to be someone that is, of course, starting to build these models as well. Like I said before, I'm going to be doing stuff like this in my community. It's going to be really interesting to see how well this model performs on certain benchmarks. And it doesn't seem that far as well off GPT4O. So some people are basically saying that this is like a local GPT4O. So it will be interesting to see how that model performs compared to that. Now, speaking of local models, will you take a look at this? So open source managed to do something crazy. Open source video has gone absolutely, you know, wild. We've got open source video Kunyan, which is like, I don't know the craziest thing about this. Genuinely, guys, I was seeing this video and I thought this stuff looked really good, okay? Then I saw people actually run the model and they made videos and they posted them over Twitter. And it was genuinely one of the most difficult things to see whether or not content was AI generated. Because this open source video model, I don't know what they trained it with, but they trained it with stuff that was filmed on a RAW camera iPhone. So the footage that you see, it's not polished, but it's so awkward that you will believe that it is realistic, which just makes you question things even more. Like, there was a video of Trump, I think he was kissing another woman, that I genuinely sat at my desk for like five minutes trying to figure out whether or not it was AI generated. Eventually I realized it was, but it was something that I was like, okay, we've definitely reached the uncanny valley because this video generator is just incredible. And the craziest thing about all of this is that this is open source. Like, anyone can run this. There's providers that you can run this with. So this is something that I think is going to completely change the game because first it's their first iteration, and secondly, imagine what we have in three years when we have real open source video generation tools and software that is so, so effective. So I honestly am stunned by this one, genuinely. Like, when I saw the videos of Trump and Elon Musk doing certain things, I was like, what? This is AI generated? I was like, okay, okay, okay. New paradigm entered. And the fact that like I said before, it's locally running on people's devices is just absolutely insane. So, you know, if you start to see videos of famous individuals doing certain things, trust me, guys, you won't be able to tell. And now I would, you know, put on my speculative hat even more than you may already have. Another thing that was released was E11 bios game changing leap in brain mapping. Cheaper, faster and smarter. So they basically announced a revolutionary method to map the brain at a 100 times lower cost than traditional methods. And this advancement makes it feasible to study entire human and mouse brains, unlocking the potential for breakthroughs in curing brain disorders and creating human like AI and even simulating brains. And of course, you know, brain mapping or connectomics helps us understand how brain works down to the connections between individual neurons. And this actually could lead to building advanced AI systems that, that think more like humans. So they previously mapped the brain of a fruit fly, which was a pretty exciting milestone. And you know, scaling to a human or even a mouse brain is just extraordinarily complex because a mouse brain is 6,500 times larger than the fruit flies, and a human brain is just like millions of times larger. So, you know, when you're trying to map that size, it's like billions of dollars. So basically one of the things that they've managed to do is reduce the cost and being able to do this is something that is really incredible because now we're on that paradigm where we're going to be able to potentially do more mapping in terms of larger brains. So this is going to be pretty incredible with the prism that they developed. And it dramatically lowers the cost by solving the AI error problem. So neurons generate unique protein barcodes that basically act like IDs, making them easier to differentiate and proofread. And this BearCode system allows AI to become self proofreading, reducing the need for human involvement. And it also integrates various techniques. But when you just think about this, overall, this is just crazy for AI enthusiasts. For those of you guys, they're thinking, you know, we're going to get human AI soon. This is going to be something that, you know, might lead to that. So this is something that I thought was a niche story, but it is AI nonetheless. Now, of course, for those of you who are wondering what else happened in AI, we actually managed to get the crazy update from World Labs. I did cover this in another video. Most people didn't watch this video, but my, oh my, you're missing out because this company is doing something incredible. So for those of you who are wondering what the future of VR is going to look like and how you explore certain worlds with a simple text prompt, this is going to show you all that world. So this thing is essentially a large world model, an lwm, which integrates physics, semantics and spatial relationships to create realistic and immersive digital environments. So this has 3D world generation from images, and it can transform a single image into a fully interactive 3D environment with smooth camera controls. And you can interact with objects in real time. So the generated worlds actually adhere to real physics, you know, spatial relationships and object interactions. You know, you can manipulate, you know, lighting, you can manipulate the depth of field. And it's just really, really crazy in terms of what you're able to do with a reality that you literally just generated five seconds ago. So this technology has various applications across game developers, filmmakers. I mean, there's just a billion different things. Visual storytelling, architecture and design, education and training. I mean, this is the kind of thing that in its infancy, it's not seen like something crazy, but I think once you start to realize how crazy this is going to be, you're going to be like, okay, I understand that this moment was like the GPT2 moment for large language models. We also had something crazy by Elon Musk. He released this image generation tool that was internally developed at X AI and this was called GROK Aurora. So this model you can see right here can develop images that are pretty lifelike in terms of celebrities and famous influencers. And genuinely, I've looked at many different AI models and most of them can't replicate people like Sam Altman or other individuals. So it's going to be really interesting to see exactly how this stuff works because I've seen a few different things. I've also seen this right here. You guys can see Crook Aurora's celebrity likeness from this other user. And I've also seen some other examples where we've got individuals like Elon Musk doing pretty hilarious things. And I'm not gonna lie, I've seen them look super, super realistic. So if you ever wanted to generate something that was super, super realistic, this is of course the tool for you. Of course it's available on x.com you do have to, you know, pay that monthly membership or whatever. But I do think that it's really interesting that they developed their own AI model. They previously did have Flux, but for whatever reason they decided to develop their own image generation model. And it actually has a few, you know, things that it was trained on. It was trained on things like the cybertruck, the Tesla bot. So if you wanted to generate those things and you weren't able to do that before, this is going to be the model for you. And of course we had 11 labs introduce, you know, AI agents.

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Then of course, one of the last things that we actually had was OpenAI Sora. This was something that I found to be really, really incredible in terms of, you know, just like how good this thing is. We look at the other Chinese models that have managed to surpass OpenAI in terms of deploying their models. But when we actually take a look at what OpenAI is able to do in terms of the quality, in terms of the prompt adherence and in terms of the physics of these models, somehow OpenAI just manages to edge out the entire competition. So this is something that if you're living in the UK like me, unfortunately it isn't currently available, unless of course you're pretty sneaky and you use a vpn. But this is something that I think is going to be pretty useful to a lot of creative individuals. Now one of the things that I actually think was probably the best thing to come from this, and I say that because looking at how AI video is, if you actually want to create AI films, this is going to be what you use and this is going to be in the video. I'm just going to scroll through here to show you guys exactly what I mean. But basically I covered this in yesterday's tutorial. There was something called the storyboard. And the storyboard allows you to basically say, I want a stalk to do this, then I want the animal to do that, then I want the animal to do that. And it's just going to be really, really useful in terms of creating fully fledged films in an AI world. So this is going to be something that I personally find to be really creative, really interesting, and there's going to be a flood of AI videos. So it will be interesting to see how people do that. Of course there's a feature like blend, there's also some other features where you can recut. There's a million different things that you can do with Sora. So it's not just a video model that they've announced. They've actually announced this platform, and on that platform, they've actually got a whole host of tools, and you can really get to controlling exactly how the model works. So this is going to be something that's really effective. Do apologize for the glitches there, but if you did enjoy the video, don't forget to see you guys in the next one.