GPT-5 Previews, Googles Next BIG A.I, Military A.I , AI Devices, and SLOWING Down?

So with one of the craziest stories in AI and honestly this is the kind of part of AI that most people don't really like to talk about because this is something that we kind of think just isn't going to happen. But as you know, the real world is essentially very, very dangerous. And this is something that you all should, you know, be aware of. Now this is actually an old story, but it was recently made aware to me via a few posts on the Internet. And essentially a Chinese team of researchers have found that with the right design, robot dogs with machine guns can rival human marksman's. So the reason that this thing isn't that crazy is because. Well, I say isn't that crazy. It's actually much crazier than you think is because the video demo of this is just, I don't want to say shocking, but it did kind of shock me because as someone who has, you know, looked at AI in the past and you know, over the last couple of years, when you actually truly, truly see the raw, brutal nature of what, you know, I guess you could say incredible autonomous systems, you know, en masse, could really, really do, it's quite scary, you know, especially if you have an imagination that can kind of run wild like mine. It is very, very scary. So essentially what this is, is this is, you know, huge implications for war. So basically they, they, they demonstrate the feasibility of a legged strike platform. I'm guessing that, you know, the translation here isn't that good, but this is just, you know, a robot dog. I'm actually guessing that what we actually have here is a unitry dog. So I'm going to show you guys this quick video here. But it's pretty crazy. I'm not going to like play the full thing because I don't want there to be any, you know, blockades on like shock. It's not really shocking content. I mean it's on YouTube. But the video is pretty crazy because it showcases this robot dog and it's incredible. Like genuinely this is something that shocked me because I could see a world in a, in a few years time where, you know, you have these, you know, humanoid robot dogs roaming certain sites, whatever, and carrying out certain actions that depending on which side of the, you know, battlefield you're on, it's either going to be a great thing or it's going to be a bad thing. So this right here, like it had remarkable accuracy. Now the accuracy, I'm guessing, you know, right now is probably like 80 to 60 whatsoever. They said it rivaled marksman's which is, you know, it's surprising because if we take something like this and then we look at the pace of AI development across the board and we can see that, you know, across the board, like not just generative AI, LLMs and all that stuff, I'm talking about like across the entire field. Like when I was, you know, truly, truly in the depths of AI, like I'd be looking at, you know, like so many research papers every day, like I'd be eating my food and just going through the Arcsive website and looking at autonomous drone swarms, you know, just with a bunch of other people in discord and just looking at the small incremental changes and this kind of thing here, guys, I can promise you that this is going to get a lot better in the future. So one of the things that I'm thinking is that when is it going to be that we truly, you know, change from, I guess, a warfare that is one that is, you know, human to one that is autonomous. And I think that, you know, increasingly in the future we're going to start to see more and more autonomous warfare because it's going to be something that's far more effective. I'm not sure how much a US solder cost. You know, I personally don't think there's any value, you know, that you can truly place on a human, on a human life. I think they are completely priceless. You shouldn't be like, oh, one person is worth, you know, $10,000 or whatever, or whatever yearly salary it cost them. But I think that, you know, if you have, you know, a system like this that could simply, you know, run through a building and simply quickly annihilate and, you know, see targets, I think it's going to have remarkable, remarkable implications for warfare. So this is going to be something that is pretty, pretty crazy. We knew that this was going to be the case. We also saw the implications of AI in dog fighting. That was another area which is recently crazy. But the reason I wanted to include this is because this kind of forwards, this falls outside of the scope in which most people look at AI in right now. Because the spotlight is on, of course, OpenAI and of course how, you know, AGI is coming and you know, generative AI and how models can reason and learn and those kind of things. So I think this kind of thing, whilst it's, you know, not the best kind of news, it's still important to know that like, you know, the world is changing in a very interesting place and AI is really going to just dominate certain parts of the industries that we really didn't even think about. So then we did actually get a update from Google. This wasn't really like an update update, it was more so a pretty interesting interview with Google's DeepMind CEO and this was where he actually talk about with a 2 million context window, people can upload books the size of War and Peace or one long hour videos and expect accurate intelligent interactions with it. And he actually talk about, say, you know, some of the future developments undergoing work on their new project Astra. So they're working on ingesting live streaming videos that will work as memory aid for the elderly. That's going to help in practical everyday tasks. And I think this, you know, snippet actually does show us a very, very interesting take on how Google intends to use AI. Because one of the things that we've seen recently is that, you know, people like Demis, Hassabis and companies like Google, why whilst they might not have the best technology, and I say that because there is a small margin in terms of, you know, state of the art versus the next best technology, of course that technology is still incredible. I think that what people can see is that Google's genuine goal and intention is of course to help the world with their agile systems. Whereas the narrative from OpenAI has shifted to one where many people are questioning what they're going to do with that power. So take a look at the future of their AI assistants to, because I.

Think it's rather important is this million token long context. Actually we extended it to 2 million tokens now and maybe we can go a lot further than that. And that means you can now ingest, you know, all of War and Peace or you know, even like an hour long video and, and then ask questions of the system about it and it can answer back intelligently. And that opens up whole new possibilities for you know, as an analysis tool or a sort of research assistant. But also for then with Astra are streaming live video obviously and then doing things like remembering. I think the thing you're referring to is like remembering something that happened a long time ago ambiently in the video stream. And it could be, you know, super useful I think for you know, an elderly person to remember where their medicine is or you know, where your car keys are or something like that. So I just think there's, we've barely scratched the surface of what I can imagine these things will be used for.

And I completely agree with that. We have honestly scratched the surface on how transformative this technology will be. Which you know, begs the question how much is AI going to change our world? And some of the people on these frontier labs, I truly do wonder what goes through their mind sometimes. Because you know, even in this interview he does talk about how like literally people have literally. I know I said literally three times but the point is I'm trying to drive home the point that it's very hard to conceptualize to the average person who isn't keeping up with the pace of development on AI how crazy this technology will be. Because whilst yes, some technologies aren't, you know, ready for certain applications, I think the monumental change is going to be when people, you know, it affects their day to day lives. Like when people saw the ChatGPT demo, you know, demos of GPT2 and GPT3 had existed long before that. So people who you know, saw GPT2 and GPT3, they essentially weren't really surprised. But with GPT 3.5, you know, just placing that in the public eye and the public view, that was something that truly, truly did surprise a lot of people. So I think, you know, this entire interview I'm going to give you guys the link to that because I think it is pretty cool. But it is something that, you know, goes to show that truly this isn't some kind of hypey kind of conference or anything. But the true nature of AI is going to be felt worldwide very, very soon. So one of the things in the AI industry that actually has a lot of people concerned about their security is Microsoft 3 core feature. So if you don't know, basically Microsoft had this feature where as you can see right now I'm recording my screen and I'm doing whatever if I wanted to, I guess you could say remember what I was doing and essentially I could just go into the recall tab bar and I could search exactly what I was doing. And essentially you have an on device thing that basically records your entire computer screen. But using generative AI you can find a way to basically search through the entire recording to find out exactly what you did in order to recall information. So essentially Microsoft unfortunately had to backtrack this feature. I guess you could say in a sense, but I going to make sense of some of the details. So the article says that Microsoft is making changes to a controversial feature announced for a new range of PCs powered by artificial intelligence. As it was flagged as a potential privacy nightmare, the company billed the recall feature for Copilot plus as a way to make users lives easier by capturing and storing screenshots of their Desktop activity. But of course, you know, people claimed that hackers might be able to misuse the tool and it saves screenshots, making the feature opt in instead. So previously the feature was on by default, which is pretty insane if you think about it, because it's like you're forcing people to do something which is not really against their will, but you're not really making it obvious to them exactly what's going on. Like, I can imagine a bunch of people, you know, having this installed on the device and them not essentially not really taking advantage of it, because a lot of the times they just have so many pointless features. So putting this on their device and especially when there have been so many privacy issues in the past, is pretty, pretty difficult. So essentially what they're just doing right now is they're basically just stating that they're making it easier for people to choose to enable Recall on their copilot PC and improve privacy and security safeguards. Because I'm not going to lie to you guys right now, this is something that's in its early phases and it would be awful if this kind of thing proves that it could be hacked and someone could use this to, you know, for, find out whatever banking information you have or find out what kind of things you get up to online. Either way, it doesn't matter what you're doing on a computer. Your right to your privacy is something that you should have. And I think this does kind of threaten it a little bit if they were just going to implement this natively on the system without making you, you know, initially be able to opt in instead of opting out. So I think this is a good thing because, you know, you don't really, really want this trend of people just, you know, embedding generative AI into everything, because right now that is, of course, what it does feel like. But it's important to remember that, you know, you do have to remember that security is a big thing because a lot of the times there were even like leaks from ChatGPT of people's personal sensitive data by simply putting in a basic prompt. And it would literally output someone's name, their address, their email, their phone number. It was pretty, pretty crazy. ChatGPT OpenAI, they managed to patch it pretty quickly, but it's important to, you know, roll out these features so slowly because if you don't test them, things can go pretty, pretty wrong. And I do think that one of the features that Recall had was it's going to be able to see exactly what's going on your computer and to be able to tell you, you know, exactly what you should do. Because there was even a Minecraft demo which was remarkably fascinating on how it could navigate and understand what was going on in the world and provide real time advice to the player. Not sure if it's going to be used by a lot of people, but I'm sure in some scenarios it's going to be very, very applicable. So now, in a bit of Elon Musk news, Elon Musk is actually planning the world's largest supercomputer in Memphis. Now this is a piece of news that isn't as big, but it's a piece of news that we knew because we knew he was building a supercomputer, but we didn't know he was building the world's largest supercomputer. And so the reason that this story is so crazy is because I think the world is entering a new phase where we're starting to see these huge, huge supercomputers start to become developed and start to go online. Of course, at least earliest next year when we're going to see these next level foundation models actually get built and we're going to be able to see a lot more generative AI and a lot more different AI systems trained quicker. Because if you think about it right now, one of the biggest constraints that we do have is the limited compute. Think about it like this. When you are training a model and you're trying to train an even bigger model, you basically don't even have compute for a lot of other things. We initially saw this with OpenAI's GPT4. The problem was, is that they didn't even have enough compute for inference. People were only allowed to send 25 messages to a powerful AI system. Is GPT5 going to be the same? OpenAI, they're trying to build an 100 billion computer called Project Stargate, and Elon Musk is building the world's largest supercomputer in Memphis. Now what's crazy about this is that he actually said that he wants to get this done by 2025. And I'm guessing that he's going to be using a lot of the recent investments, whether it be from Tesla, from X AI to be buying tons and tons of Nvidia GPUs in order to ensure that this data center is, is going to be powering the next level of whatever AI infrastructure he needs. Now, of course, some of it's going to be for his X AI company, which I do think is probably going to make some significant strides in the coming months and years in regards to AI because they seemingly have been doing very, very well in whatever vector they've been chasing. And I think that as well with the fact that they've already got the huge infrastructure with Tesla, I think they're going to be able to combine those forces to come up with some very, very fascinating things regarding embodied AGI. So this kind of project to which Elon Musk says should be online by 2025. Of course Elon Musk and his date do have, you know, not the best track record in terms of being on time, but I do think that that kind of factory is going to need an enormous amount of power to, to which the question is, you know, how are we going to do this? And I've seen, you know, a lot of politicians start to even talk about nuclear energy being one of these main fuel sources. And you can even see here that data centers doubling power demand seen stressing energy grids. So essentially electricity demand from data centers, AI and cryptocurrency miners will surge by 2026. The Paris based International Energy Agency has said in a January 20, January report. After consuming 460 terawatt hours worldwide in 2022, it's going to be more than double in 2026. And basically what they're stating is that look, these kind of data centers that are going to be building the next level of foundation models and these lex frontier AI systems, they are going to be truly, truly demanding a huge amount of energy. And that is, you know, I guess it's kind of a concern because you'd not only need power for the data center, you also need cooling for the data center. So there's all of these crazy, crazy things going on that just lead to not inefficiencies but just more demands overall in terms of the infrastructure requirements to run these kinds of giant level systems. So we're probably going to see some large, large level construction things be taking place in the next couple of years as these supercomputers are being built and as these massive data centers to power all of this AI is going to be built. And I think, you know, whichever company manages to build out the infrastructure the fastest and of course the most effective compute are going to be the leaders in generative AI because as we know one of the main bottlenecks to AI is of course energy slash the data center problem. So it's going to be interesting to see how the actual economy responds to this. If they're going to be welcoming this, if the Energy demands can even be met for these data centers and how the entire problem is navigated. Now you can see here this is a tweet by Yan Le Khan and I think this is a tweet in response. No, I think I know this is a tweet in response to this, but this is something that I do want to talk about because I would argue that this is one of the biggest debated things in AI right now, because this is one of the biggest paradigm shifts that we could potentially have before artificial superintelligence. And basically the biggest debate that's going on right now in AI is whether or not we are at this inflection point that is going to lead to, you know, logistic growth or exponential growth. So essentially this guy says right here, and he's on the open endedness team at Google DeepMind, he says, like everyone else, I am extremely excited and optimistic about AI progress, but since there seems to be the misconception that it is really easy to make predictions about the future, it's for exponential trends, let's just draw lines on a log scale. This is a reminder that while observing an exponential trend, for example compute or neural network parameter increases, we can never be fully certain what we are observing is in fact following a logistic trend before the inflection point. Before the inflection point, both trends look the same. So basically what he's stating here is that look, before we get to this inflection point, and I should mark this with this right here, you can see that if you just didn't have this, like this was completely white and we're only looking underneath right here, we can see that both of these follow the same pattern. They both decide to go up just like this. So to the naked eye, to anyone, you know, if you're watching a graph go up like that, you're thinking, ah, you know, the growth is probably going to be exponential. However, there are usually S curve graphs which do happen and this is where the things get mature and things start to taper off, which is this logistic kind of growth right here. However, I think of course there are some cases where the exponential growth just keeps on increasing and it just goes up in a straight line. But the problem is is that currently many individuals, including myself, find it quite hard to predict where on earth this inflection point is going to be and of course where that growth might start to taper off. Now I personally do think that this inflection point is going to be driven by one or two factors, one of them being the Things that we previously discussed, number one being of course compute capacity. Of course, as you know, powering these data centers is no easy feat. You powering these dentist and a lot of compute to do so. So that is going to be a proper problem. So essentially the energy compute problem is basically one of the biggest problems that we're going to have. And of course I think we're going to have the safety issues, slash the kind of issues upon regulation to where these models start getting bigger and bigger and better. And then of course there might be more and more regulation around what things can kind of happen. So if we start to run out of energy compute in order to train bigger models, I do think that of course there are literal physical implications and physical inflection points that are going to drive the logistic curve. But of course there is the slow, not slow, but hidden theory of once we get to the point of automated AI research, that's when we're going to get exponential growth. Because if the AI can do a type of research to where it can make itself much more efficient and much more effective at solving problems, then growth is likely to be exponential. Because you could duplicate 1,000 AI researchers, leave them running 24, 7 in a loop where they just publish AI research and just continue to test it and iterate and improve upon that. We could have a decade of AI research comprised into just 12 months. So I think that what is likely to happen is that before we get these factories, these huge data centers online, I think the growth might taper off around GPT5 or GPT6. But once that compute is built, I think then it's going to be basically like this where we have a small inflection point, things taper off and then we go to another one again. So I think overall that is likely what we're likely to have overall. Because I think that whilst yes, this big trend does happen in a lot of technologies, you know, you've got the Garten hype cycle, a variety of, of many different things. I think that what we're basically seeing now is something like this to where, you know, you have like GPT 3.5, then of course you have GPT 4 with a lot of the other foundation models there. And then GPT5 is apparently going to be the same kind of jump anyways. So we're then going to have that slow, you know, growth and then of course that taper off until these models get online. I do think that once we do have these massive supercomputers online, I do think that you know, all it takes is automated AI research to be solved and then the graph just goes up. Maybe not indefinitely due to physical constraints of the actual world, but the growth does start to look more exponential in that area. But the problem is that this is very hard to judge without OpenAI's input, because right now all AI research is essentially private. And this is what Yalekhan was basically saying. He said, you know, I've made this point so many times, the beginning of a sigmoid looks like an exponential. Not only can we never be fully certain to what extent we are observing isn't in fact following a logistic trend before the inflection point, we can always be certain that every single exponential trend eventually passes an inflection point and saturates into a sigmoid. So continuing an exponential trend beyond that inflection point requires a paradigm shift. Basically, you require a certain breakthrough if you want whatever curve it is that you're doing in order to go up to the next kind of sigmoid curve. So that's what you kind of need. Because no physical process can grow indefinitely. There's always, you know, friction in terms of the dynamics equation that eventually become dominant. Energy consumption, heat dissipation, quantum effects, thermal fluctuations, communication bandwidth, mass, energy density. Basically you're going to reach the physical limits of Earth, even if you're trying to grow something indefinitely. So even processes that appear exponential on a long time scale are actually a succession of sigmoids. So what I just spoke about the sigmoids, where you have one that is there and then it's kind of like followed by another and another that's basically built on the back of every other paradigm shift. And it says a good example is Moore's Law, which is getting saturated right now. But the exponential progress of the last seven decades is due to a succession of technological paradigm shifts that weren't preordained. Basically, you didn't even think about them. So each paradigm behaved like a sigmoid, each sigmoid overtook the previous one. And then of course, it seems exponential. Now, whilst many people are dogging on Rabbit or hating on humane or whatever it is, whichever kind of product is in the spotlight for absolutely quote, unquote awful. I want to highlight this demo by Sanders Sar on the Brilliant AI glasses by Brilliant Labs ar. This is basically open source AI technology that is truly, truly incredible. I saw this on Twitter and honestly, I'm surprised I didn't retweet this before because it's a remarkable demo that actually shows the usefulness of generative AI when combined with hardware that actually makes sense to use. I do think that this is where meta smart glasses are going in the future. But I want you all to take a look at this because this is leveraging your phone connectivity and audio and actually, you know, some of the kind of generative AI apps that we use today. And basically this is, you know, it's incredible. I want to show you guys this because once you realize that, you know, augmented reality is going to be a thing, you're going to start to realize that. And I know that many people have seen this before, that this form factor truly does work.

The future of AI enabled classes. They are the opposite of Vision Pro. They're lightweight, they look like normal glasses, and they cost $349. They're also quite different from the AI pin, which is trying to be a standalone device. While the glasses leverage your phone for connectivity, both of them have cameras and microphones. And while the glasses have an AR heads up display, this has a weird laser projection. And more importantly, the glasses are open source, community driven platform. Hey Noah, I'm making a video of you. Can you introduce yourself?

Hey folks, I'm Noah, your AR smart glasses wizard. I know stuff, translate anything and use the coolest AI mod like GPT and more to make your life a breeze.

Where could I find a hat that goes well with this outfit?

Close by.

You're right in Venice. Swing by Goran Bros on Abbot Kinney Boulevard. Trust me, they'll have a hat that screams I belong in a movie.

What can I make for lunch?

You've got tomatoes, onions, maybe some apples.

Look at this. Okay, like, imagine just having glasses on your head 247 that, you know, I guess is basically now like an iPhone. Okay. But you know, if you don't have any problems, it's literally just glass. You know, it doesn't like strain your eyes or anything, but you could literally say, hey, what am I looking at on my screen? Hey, what's in this fridge? What can I make here? Hey, is this out of date? Do I need to change this? Do I need to change this tire? I mean, I can truly see a future where this kind of application actually becomes really effective. Like especially since the text right here, it doesn't look that invasive at all. And it kind of, you know, seamlessly integrates. Now I think one of the main things as well is that with these glasses, I think over time, along with hardware innovations and software innovations and along with AI systems that we can effectively run on device and essentially make the inference a Lot faster. I think these kind of products are going to be truly the future of AI. So I think this demo, it shows exactly what we can do, especially with Project Astra and all those kinds of things. I mean, the next five years, can you just imagine the kinds of, you know, technology that we're going to have, especially combined with AI? I truly believe there's going to be, you know, an entire age of abundance and this incredible period of time. Now, the clip that you're about to see is probably the most important clip in the video. And I don't know why, but I actually lost this video. I'm glad I found it again. And this is a clip of the Microsoft CTO talking about the next level in AI. Now pay attention because I'm going to break down exactly what he says and why this is so important. And it's important because I'm just going to tell you why.

Just watch all of the things fall in place. To have, like, really durable memories with the systems, like reasoning, I think gets a lot better. So, you know, some of the fragility in the current models are can't solve very complicated math problems and has to, you know, sort of bail out to other systems to, you know, do very complicated things. I mean, the way that maybe I would phrase it is if you think of GPT4 and like that whole generation of models is things that can perform as well as a high school student on things like the AP exams, some of the early things that I'm seeing right now with the new models is like, you know, maybe this could be the thing that could pass your qualifying exams when you're a PhD student.

Like, that is incredible. Imagine an AI system that could literally do your PhD. I mean, the thing that makes that absolutely incredible is because that means that if the Microsoft CEO, who not CEO CTO, who actually has likely been in some GPT5 early previews, is seeing that these models are able to reason at a level which is much more advanced than prior systems, it likely means that we are nearing potentially an automated AI research. And if he's stating that you're basically doing your exams as you're a PhD student, that means that we're not far off from further iteration cycles where we do get to that level where AI automated research is solved. And the reason I talk about automated AI research so much is because that is the only thing that you need to automate in order to have pretty much exponential growth in AI. Because once AIs can do the AI research themselves, we can pretty much exponentially Scale that and then of course, compound those breakthroughs on top of another, which over time just gets you this truly, truly compounding growth period. So I think this is pretty, pretty crazy because like I said, GPT4, which many people use on a day to day basis, is quote unquote, a smart high schooler. So what do you think the, the vibe shift is going to be in the general public consensus when they realize that, holy crap, we have access to a PhD level researcher in our pockets that we can use on a day to day basis to reason about many different things. And it's just, you know, it's kind of mind blowing. Okay. I really don't even have much words to say about this, but, you know, this is going to catch a lot of people off guard, but I will be ready because, you know, this is something that we've seen coming. So if GPT5 is incredible in terms of its reasoning abilities and able to, you know, truly understand and you know, the multifaceted things it's able to do, don't be surprised because clearly here you're stating that this is going to be on the level of a PhD student who's able to complete that exam.

All right, let's crank it up. You're about to rock New York Tech League. Picture that crowd buzzing with excitement, feeding off your energy. You've got this. Bring that passion. Let them feel your vibe and show them what you've got. All right, let's crank it up. You're about to rock New York Tech Week. Picture that crowd buzzing with excitement, feeding off your energy. You've got this. Bring that passion, Let them feel your vibe and show them what you got.

And what you just saw was a GPT4O demo where OpenAI showcased their new flagship model in New York Tech Week. It was pretty cool. And it just goes to show that GPT4O is still pretty crazy in terms of what it can do. So for 2,000 subscribers, what I wanted to do was to relaunch my community. And essentially this is post AGI preparedness, where you get exclusive access to one of my post AGI frameworks, the framework that I'm using to navigate the world post AGI. And so far it's been really successful. My personal strategy for making money with AI and exclusive tutorials on how to actually use AI, and of course invest in AI and generate insane returns. So all of those things basically taking advantage of the AI revolution. This is. Currently, there's not that many slots left for free members, so if you do try and join now you can get it for free, but of course it's going to be actually priced in at around 19amonth. So if you're someone that's been supporting the channel for a while now, this is your chance to, you know, I guess you could say, learn AI with me because I'm going to be doing a lot of stuff here. I'm going to be posting daily about pretty much everything that's going to be beneficial in terms of AI. And I just wanted to make this quick announcement because I know some people might have missed this.