Surprising New Report Shows You Can Benefit From The AI Boom

McKinsey estimates generative AI could add $2.6 to $4.4 trillion annually to global productivity. The video highlights investment opportunities in Nvidia, Cerebras, and Lightmatter, which makes photonic chips claimed to be roughly 10 times faster and 90% more energy-efficient than current GPUs.
Questions this video answers
About $2.6 trillion to $4.4 trillion annually.
$1.3 trillion by 2032.
Over 200% (presenter’s claim).
Reportedly ~10× faster than the fastest Nvidia GPU while using ~90% less energy (presenter’s claim).
About 18 picojoules per bit for typical Nvidia/AMD servers versus ~2 picojoules per bit for their system.
Chapters
So there was a recent report, and I probably shouldn't say recent, but this report is rather important on AI and the impact on the economy. And you really do need to pay attention to this because the ramifications are quite staggering. So right here you can see that there was a report from McKinsey and Company and essentially they said that generative AIs impact on productivity could add trillions of dollars in value to the global economy. That's trillions with a T. They also said our latest research estimates that generative AI could add to the equivalent of 2.6 trillion or 4.4 trillion annually. Now, I don't know about you guys, but $4.4 trillion every year in the economy is absolutely incredible from one advancement, okay? And the crazy thing is, is that there is so much to go on, okay? And this is what they're saying is going on every single year. Now, of course, with this, it means that there are vast amounts of opportunities for people like yourselves who are interested in AI because you're paying attention to the next advancement that many other people just aren't. Which means that if you're one of the early investors, you could be looking at a sizable sum for the foreseeable future. Especially something that we do want before AGI arrives. Now, what's also important to note is that this is just beginning. The era of generative AI is beginning. This is a excitement before you guys think. GK is palpable and early pilots are compelling. But a full realization of the technology's benefits will take time. And leaders in business and society still have considerable challenges to address. These include managing the inheritance risks and of course, determining what new skills and capabilities the workforce will need. Which is why you have to understand that right now, this $1.3 trillion market by 2032 is going to present some serious opportunities. And if you don't believe the claims I'm making, just take a look at this. So if you don't know what this is currently, what I'm showing you guys right now is of course the chart of Nvidia Corporation. Now if you aren't familiar with Nvidia, they are the company that makes graphics cards. Now with the graphics cards, they essentially the backbone of AI, because you know the system like ChatGPT and you know Google's Gemini, in order to make those AI systems, they have to go through a training run in which they are trained and fine tuned with, with lots and lots of data. Now in order to do that, they need Nvidia's chips and Nvidia is the world's largest producer of these graphics cards. And you can see that their company has skyrocketed, going over 200% last year. Now you might be thinking, okay, so AI happened, a stock price went up. What on earth does that have to do with me? Well, you should be taking advantage because some Nvidia employees are taking it as a semi retirement mode. And even middle managers may make $1 million a year or more. Remember guys, middle managers making a million dollars a year or more, and that is due to the fact that their compensation is in stock. And with the stock price so high, these guys are making an absolute killing. Now you might be thinking, okay, now I didn't invest in Nvidia before, I probably should have. I missed out. And I'm not a middle manager at an AI company. So how on earth am I going to take advantage of this new generative AI opportunity considering that I don't own an AI business and I'm not currently invested in anyone? Well, this is where this comes in. Now, this platform was something that I found and I decided to do this video because it is a really, really, really effective platform. Because what they actually do allow is unlike traditional platforms like where you can invest. Like, these guys actually allow early access to investments and they have speciality in AI. This is a link to, as in your link to private equity. This is actually a sponsored video. But I wouldn't just do sponsored videos about any of them. I really did vet these guys because I wanted to make sure their claims are accurate. And after doing more research, I can't tell you guys how eager I am to be investing in some of these things because this is one of the only platforms that directly allows you to invest in some of these innovative AI companies that people are just starting to realize. So if you're thinking about signing up to this platform, why not take a look at some of the innovative companies that exist on this website that are really putting put in a position for explosive growth come the next couple of years based on industry projections. When I'm talking about innovative companies, the reason I understand that these companies are innovative because I've actually looked at the research that goes in into companies like this. So what you're seeing on screen right now is a company called Cerebras. Okay? And essentially WSE2, as you guys can see, compared to the latest GPU claims that it can train neural networks that previously took months to train and in just minutes, okay, they are saying, okay, that they could literally train systems in minutes. Now think about this, guys, okay? How crazy would it be for a company to be training chips that you can literally train AI systems in within minutes, okay, or even days? That would be absolutely incredible. Now, we know there's going to be tons of advancements and tons of new companies, but companies like Cerebras ones that are making the technology that will be the backbone of this innovative technology era are going to be very, very important.
That's a huge difference. Just a quick example. The, the, the most efficient GPT 1 billion parameter model, it takes about 1200 lines of code to get that on a single GPU. Now, if you want to run a 40 billion parameter model on a thousand GPUs, it's going to take 28,000 lines of code, right? So you have to write a new 27,000 lines of code. Now for us, if you want to run a billion parameter model on our system, it takes about 1200 lines of code. But if you want to run a 40 or 100 billion parameter model on 12, 16, 32, 64 of our systems, you don't have to write any more code at all. And so not only is the machine faster to run the model, it's faster to get your model on the machine by avoiding all that distributed compute time.
And of course, they actually have set records for training the largest AI models ever on a single device, which actually show the capability. Now, of course, it is pretty hard to take on a behemoth like Nvidia, but you have to understand, guys, companies that have such a dominant market share are always going to be susceptible to market disruption by innovative makers like Cerebras. And, and I think that's definitely what we're going to be seeing here. And they challenge Nvidia by offering unprecedented computational power, memory capacity, bandwidth tailored specifically for AI and HPC applications. So it will be an interesting future. And that is going to be a company that I will be paying attention to. And even if you're not investing, even if you don't sign up to the platform, you should definitely be paying attention to these companies and how they're going to be changing AI. Because a company making a chip like this, where you could literally, you know, train AI within days or in minutes, is going to be an absolute game changer. Now here's the thing, okay? New technology is needed. This is a blog from a website that makes a crazy, crazy chip that I'm going to show you guys why in a moment, okay? So this right here is electricity demand. And if you don't know, okay, AI training Runs are very, very demanding. Okay? The compute needed, the extra needed, the energy needed for AI is something that is really, really becoming an issue because of course we're trying to remove to renewables. And of course right now there's an increased demand for electricity for training these generative AI systems. So it says here humanity is dedicating a significant amount of power to this development of AI. This energy consumption is increasing rapidly and it's getting worse. Computer chip technology has reached a point where even the latest advancements can't solve this problem. And light matter technologies offer a solution to reduce the environmental impact of AI. So we have another company which you can only really invest on on this platform, which is why I like this platform so much, because like I said, traditional platforms, you can't invest in these companies. You can only invest in companies after they're worth billions of dollars, which is always a larger risk. Of course there's risk with any investment. No risk is going to be risk free. But the point is, is that this technology company is essentially at a very unique point. Okay? This company is called lightmatter. And essentially what they do is they make chips that are way more efficient than the traditional ones. Okay? And there's so many different AI companies. Like, I could sit here for hours and hours about the amazing number of AI companies that are there. But I do think it is important to least try and capture some of the economic gains made by generative AI, because like, we do know with AGI and all this stuff ramping up, we know that many people are going to be out of jobs. And with ubi, you definitely want to be at least someone that benefits from it a little bit. So essentially with these chips, what they've done is they are photonic computer chips. Now, if you've never heard of these before, it's because they're a new style of chip. And essentially what they do, they are 10 times faster. They're reported to be 10 times faster than the fastest Nvidia AI GPU while are using 90% less energy. Guys, that is absolutely crazy. And that could reduce the environmental impact of AI, which is becoming increasingly important as AI's energy demands grow. And you know, okay, that the AI energy demand is going to keep going as these systems get more powerful. And essentially their photonic chips perform calculations at the speed of light, which could leave traditional transistor based chips behind even in terms of performance. And these chips can potentially scale performance by adding more wavelengths of light for every color added. And throughput can be increased by that number with the possibility of scaling up to 64 colors in the future. So I think, guys, this environmental impact, we know that everything is becoming more energy efficient. Like this company is positioned in such a crazy, crazy way and they reinvented how these chips do that. Now, like I said, there are many different companies that you can invest on. And I found a clip from the CEO in which he's actually talking about how crazy this environmental impact is because. Because even guys, even after I'm going to show you this clip, I'm going to show you guys, Sam Altman even saying that he needs to build some kind of energy company because the energy demands are pretty crazy.
What impact is this going to have on what we've already seen in terms of language models being built and you know, the number of, or the amount of data being processed by them?
Yeah, there's an interesting story here. So we're kind of bound by power usage and cooling at this point. Not light matter, but the world in terms of data center deployments, when things are heating up. Yes.
I mean, that is, that is the key, right, Is that this creates a bit of a heat issue.
No, absolutely. And if you look at that heat issue, part of it is that the interconnect bandwidths, how many bits per second are leaving these chips, is growing very, very fast. And so if you look at what we're doing with passage, it's about 10 times better energy efficiency. So 18 picojoules per bit for the typical type of inside the box communication that you would see with an Nvidia server or an AMD server. Take that down to two picojoules per bit. And I know this sounds quite technical, picojoules per bit. But the point is 18 divided by 2. It's a big difference.
What is a picojoule?
10 to the minus 12 Joules Joule is a unit of energy, right? Yes.
So you can massively reduce the amount of energy which then gets rid of the heat and the cooling and then.
You can put more compute in the rack and all that real estate that you build out is now more useful. If you didn't want to add more compute, the power bill went down. So that's nice. And by the way, the power bill is about 50% of the cost for running the data.
For those of you guys who don't think a lot of these AI companies are needed and you probably shouldn't be investing in them, I mean, I'm not trying to give you guys investing advice. I'm trying to tell you guys that you need to take advantage because a lot of these companies are going to be growing. So here's Sam Altman even stating that during Davos, okay, we still don't appreciate the energy needs of this technology, which is expected to consume an enormous amount of electricity as it matures. And he said there's no way to get there without a breakthrough. We need nuclear fusion or we need some radically cheaper solar plus storage or something at a massive scale. And Sam Altman, of course, as you guys know, is the CEO of OpenAI. And even he's talking about the fact that, you know, we need technology like this that actually allows for the vastly cheaper and faster production of AI. So I mean, guys, this stuff is pretty crazy, okay? This platform allows you access to so many different things. And this is why, guys, I'm talking about this platform so much. It's because one of the things I realized when looking at AI is that I was eager to try and invest in some of the companies, but I noticed that companies like OpenAI are private. These guys are private companies. Like if you're trying to buy OpenAI stock, you won't be able to. And I'm sure many of you guys were probably early on in the AI space looking at OpenAI, thinking, Man, if I could just invest in a company like that, I, I'm sure I'd be able to reap at least some of the benefits, some of the economic and financial benefits of AI. But of course it's a private company and other companies out there like Claude and all these other generative AI companies, they're just simply private, you know, you're not allowed to invest in them. But guess who is. That's people who are actually in the private space. Now of course, many of us don't have the connections and the networks to be able to get in and invest in a kind of seed round. Which is why platforms like linqto are actually really, really necessary to for the standard investor because they allow you to invest in these companies that you traditionally really can't. So you can invest in leading startups and essentially it's really easy access to private investment. And I genuinely wish that I found this earlier because if I'd found this earlier, guys, this would have been such a good thing at the start of the generative AI boom, because it would have meant that I would have gotten in earlier and probably already reaped some of the benefits from majority of these companies. You can see here we've got snaplogic, Spark, Ignition, Light Matter, the company I just talked about and of course, Lambda Labs. Of course we've got Cerebras, which I just talked about. Guys, this is a crazy, crazy opportunity. And essentially all you have to do is open an account with the link in the description, add your funds, and then of course, you can begin investing. You can see there exactly how it is. And it's a really simple platform. It's not absolutely crazy or anything. There's nothing too hard. And I really do love this platform. It was also a very fascinating video that they made, and it only got 500 views. Now you might be thinking, why'd the video get only 500 views now? That's because most people don't really know about these AI companies, which is why I'm glad I managed to find this investment platform, because I'm now going to be one of the early ones being able to benefit from such a remarkable opportunity. And AI literally was. The global AI chip market was $14 billion in 2022. Then it grew to $383 billion in 2032. That's what they're expecting it to do. And of course they're saying that based on history. During the fiber optics boom, related companies saw huge growth. And this company experienced 10.10x growth in one year. So there's going to be so many companies that do benefit. And of course, Light Matter is one of those companies that they're talking about, and essentially they're talking about this easy access platform. So I think this platform is really cool. Let me know if you guys think so as well. I'm definitely going to be signing up and doing some investments with this platform because I really do not want to miss this opportunity. And I definitely feel like this is the last industrial revolution. And as some are speculating that these AI technologies are going to fuel the fourth industrial revolution, I definitely don't want to miss out on any opportunities that there might be. So with that being said, you can click the link in the description to sign up and hopefully you guys have enjoyed today's video.










