The Crypto On Nvidia’s Balance Sheet

Plus, the “Nvidia Playbook” August 29, 2024 [WEBSITE]( | [UNSUBSCRIBE]( Nvidia holds ONE crypto, plus Davis Wilson joins us again to share his bullish price target. The Crypto On Nvidia’s Balance Sheet CHRIS CAMPBELL Dear Reader, The Pony Express was the mid-1800s’ version of instant messaging—riders shaved delivery times down from months to just 10 days. Until, that is, the telegram came and rendered it obsolete. Today, in an age of instant texts and emails, it all might seem a bit boring… But, in terms of advancing communication, it was a huge deal. And what could happen soon with AI is way bigger. In fact, there’s nothing really like it in history to compare it to. On the scale of efficiency gains (10,000x+), it may as well be a leap to telepathy. And, no surprise… Nvidia is at the tip of the spear of this trend… Alongside a lesser-known crypto quietly sitting on Nvidia’s balance sheet. Enter DisTrO, or what I’m calling… Telepathic AI To be clear, DisTrO is NOT the crypto on Nvidia's balance sheet. (More on that in a moment.) DisTrO stands for "Distributed Training Over-the-Internet." Put simply, it’s a new method designed to make training large AI models more efficient. But HOW it does so is nothing short of magic. Let’s start with the basics: Large AI models are complex systems with billions or even trillions of parameters (like neurons in a brain). They need to be adjusted or “trained” to perform tasks. (Tasks like responding to prompts, recognizing images, translating languages, etc.) To train these models, you need A LOT of computing power. Often this is provided by GPUs - specialized processors for heavy computation - like NVIDIA provides. Most of the time, one GPU isn’t enough. So multiple GPUs have to work together. During training, each GPU works on a piece of the model and needs to share results (gradients) with the others. This requires a lot of data to be sent back and forth, which is why these GPUs need to be connected by high-speed, specialized networks. Also, the size of the data grows with the model size and number of GPUs. Therefore, for large models, the bandwidth requirements become astronomical. This creates a HUGE barrier to entry. Typically, only large tech companies can afford to set up and run these systems. DisTrO could change that. Decentralized Training This gets in the weeds a bit, but here’s the gist: DisTrO employs a special optimizer (DisTrO-AdamW) designed to reduce the frequency and volume of data exchange. Get this: it can reduce the data shared between GPUs by up to 10,000x or more. And WITHOUT degrading any quality or speed of the training process. By the way, this is pretty breaking news. You’re probably one of the first to see it laid out in simple terms. A report by Nous Research - an elite team of AI researchers - just revealed it’s possible this week. Check out this chart below from Nous. All-Reduce + AdamW is the traditional communication method (All-Reduce) + traditional optimizer (AdamW). Distro + AdamW replaces the traditional methods. Obviously, this is a profound leap. But the wider implications aren’t instantly obvious. In short, AI training can shift from being location-dependent to being completely decentralized. See, in traditional methods, the need for constant communication between GPUs requires them to be closely-knit. Because so little data needs to be transferred between the GPUs… With DisTrO, it’s technically feasible to train models even when GPUs are spread out geographically. Even when they’re connected over standard Internet rather than specialized networks. Again, WITHOUT taking any more time or losing any of the quality. Instead of huge data centers humming with thousands of interconnected GPUs… Imagine a vast network of computers—from beefy gaming rigs to even modest laptops—all working together to train the next breakthrough AI model. This Could Change Everything DisTrO could change AI development by making it more accessible to a broader range of organizations. Startups, academic institutions, and individual researchers could now participate in training large AI models without needing expensive infrastructure. When no single company controls the training process, researchers and institutions gain the freedom to collaborate and explore new techniques and models. Even in regions with less advanced infrastructure. This boost in competition fuels innovation and drives forward more progress. As costs decrease, smaller companies could compete with industry giants, potentially disrupting existing market dynamics and enabling new business models. No less… The impact of DisTrO might also extend to hardware and infrastructure. By reducing the need for high-bandwidth connections, DisTrO could influence the design of future GPUs and data centers. Data centers might become more decentralized and modular. There’s ONE crypto that will benefit the most from this trend. By no coincidence, it’s the only crypto that Nvidia currently holds on its balance sheet. AND It’s the ONLY crypto in our Paradigm Mastermind Group portfolio. (By the way, we beat Nvidia to the punch.) Not yet a member? [Click here to see if it’s right for you](. Who else could benefit? If you guessed Nvidia, you’re on the right track. Speaking of the Nvidia. Today, we invite Davis Wilson back to share his “Nividia Playbook”... and his bullish price target. Read on below. 🚨🚨 Altucher Issues MAJOR Alert! 🚨🚨 Heads up… I just issued a major alert for one tiny stock. If I’m right, this could be the biggest winner I’ll recommend in 2024. But you can only access it if you act immediately. [Click here right away.]( The Nvidia Playbook - Here’s What Happens Next DAVIS WILSON Nvidia reported another blowout quarter last night. Here’s the breakdown: - Earnings per share: 68 cents adjusted 64 cents expected - Revenue: $30.04 billion $28.7 billion expected - Nvidia expects $32.5 billion in current quarter revenue, versus $31.7 billion expected Excellent results by any measure. The stock still sank on the news… Investing is hard. So what happens next? Let’s look at the playbook. By “playbook” I’m referring to an interesting trend in Nvidia’s valuation over the last three quarters. I think it can tell us what direction this stock will move over the next few months. To start, let’s take a look at the stock’s historic price/earnings ratio. The stock is very much in line with its five year average. Now zoom in on just the last year. The dramatic drops lower coincide with earnings releases. The “E” in P/E gets larger as the company reports higher profits, hence the overall P/E ratio decreases. In other words, Nvidia gets cheaper when this chart goes down. You can see an interesting trend appearing. In each of the last three quarters, Nvidia announces earnings and the P/E ratio drops to ~50x. Then, over the next three months the stock price rises, hence the P/E ratio increasing until the next earnings report. When that next earnings report is released the same playbook gets executed. The P/E drops sharply to ~50x and the stock slowly ticks higher over the next three months. This playbook has happened like clockwork over the last three quarters. The reason is simple: Investors realize they can buy the most powerful, profitable, and important AI company at a bargain valuation. Well, today we woke up after last night’s earnings and Nvidia is once again trading around ~50x. What do you think? Is this time going to be different? Let’s continue to look at the facts. - Last night on the call, Nvidia CEO Jensen Hwang reiterated the fact that demand for Nvidia products is still incredibly strong and that we’re still in the early stages of developing AI. - Microsoft, Amazon, Alphabet, and Meta all recently announced they’re not slowing their AI development spending anytime soon. - The Blackwell delay is a non-issue. Previously this was the stock’s biggest red flag. Plenty of positive news regarding Nvidia’s business. Very few negatives. Yet, this time is different and Nvidia should trade at a lower valuation than it has in years? I’m not buying it. After last night’s earnings, Nvidia’s trailing twelve month earnings is $2.16 per share. The stock has consistently traded up from ~50x P/E after reporting earnings to ~80x over the last three quarters. I’m betting this quarter is no different. $2.16 in earnings multiplied by an 80x multiple gets you to a $173 price target. My guess is we’ll see this by mid-October. According to the playbook. Best, Davis Wilson For Altucher Confidential Rate this email Like Dislike Thanks for rating this content! Looks like something went wrong. Please try to rate again. Congrats, you earned this… As one of my readers, you qualify for [this special deal.]( Only a small fraction of our readers will have the chance to see this. Fortunately, you’re one of them. All you have to do is [click here now to see how to claim your special deal.]( ☰ ⊗ [ARCHIVE]( [ABOUT]( [Contact Us]( © 2024 Paradigm Press, LLC. 1001 Cathedral Street, Baltimore, MD 21201. By submitting your email address, you consent to Paradigm Press, LLC. delivering daily email issues and advertisements. To end your Altucher Confidential e-mail subscription and associated external offers sent from Altucher Confidential, feel free to [click here.]( Please note: the mailbox associated with this email address is not monitored, so do not reply to this message. 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