STILL EARLY! Why I'm STILL Buying Nvidia Stock (NVDA)

it was another Blockbuster quarter from Nvidia you take a look at the revenue I mean it is outrageous these numbers Revenue Soaring Over 200% in the third quarter from last year I mean they are the only game in town when it comes to AI those gpus are essentially gold and it almost seems like nothing is stopping this company anytime soon Nvidia is quickly becoming the most powerful company in the world because it has a monopoly on the most powerful chips in the world and after one of the best earnings calls of any company in recent history there's really only one question left to ask is this the top for Nvidia stock or are its best days still to come your time is valuable so let's get right into it Nvidia posted record revenues of $18.1 billion for the quarter which is up by a mind blowing 206% from a year ago and it's 34% higher than their most recent record-breaking quarter analysts expected 16 billion dollar which was actually already pretty aggressive and this was still 12% above their expectations Nvidia also posted $42 of earnings per share that's 19% higher than analysts expected up a whopping 49% from last quarter and almost seven times higher than a year ago I do want to point out something about nvidia's year-over-year numbers if you look back at their performance from last year you'll see that they were actually hurting pretty badly and if you break down their revenue by segment you'll see that nvidia's gaming business which was their biggest business unit at the time was basically in freef Fall I'm not the kind of investor who only covers the good parts of stocks that's why I made videos talking about the problems with nvidia's consumer gpus and why their gaming segment was collapsing in quarter 2 and quarter 3 of last year a collapse that that segment still hasn't fully recovered from today while their data center revenues have nearly tripled over that time frame those bad quarters are a big reason why Nvidia is seeing triple digit growth year-over-year today and why we should see more crazy numbers for the next two quarters before they start to slow down Dr dramatically so don't say I didn't warn you about 9 months from now anyway I don't think anyone could have predicted the sheer pricing power that Nvidia has right now with their data center Solutions not just their h100 and upcoming h200 gpus but their hyperscale networking products like infiniband which I've actually been talking about for a while now but surprising Wall Street analysts was just the beginning Nvidia also reported 74% gross margins that's up almost 4 Points quarter over quarter and over 20 points year year over-year see what I mean about those year-over-year numbers and they're expecting next quarter to be even better guiding for $20 billion in revenue and 75% gross margins 75% margins on Hardware is honestly insane but this is what happens when a company is virtually uncontested in the single fastest growing Market on the planet so even though Nvidia stock is currently near alltime highs it's actually a lot cheaper than it used to be wait the stock is cheaper now even though it's near alltime highs here's a quick CNBC clip of Stacy Raskin managing director and Senior semiconductor Analyst at Bernstein research explaining exactly what I mean at these levels do you still invest in Nvidia is it still compelling or do you put your money to work in something like AMD or Intel or another chip name that you cover I'll be honest so like Nvidia I do like and again you mentioned the stocks up whatever it is two or 3x earnings are probably up four or 5x on a valuation basis the stock is actually very cheap you you could argue it's even cheaper than some of these other ones like AMD um everybody with Nvidia there what they're worried about is that the numbers are getting so big so quickly you just worry about sustainability now that being said I still think this a the a opportunity is massive I still think we're really early I'm convinced in in five years in 10 years we'll be talking about numbers that are materially higher than what we are talking about today so with Nvidia like as always I think you need a strong stomach that stock has ups and has it it's ups and it's downs but I still think we're really early I think the the opportunity is massive I think they're in the driver's seat I think you have to own it and the stock is even cheaper than Stacy made it sound because nvidia's earnings are actually seven times higher than they were a year ago not four or five Nvidia actually has a lower PE ratio than other fantastic AI companies like Tesla and paler in fact if I go to mumu's valuation tab for NVIDIA I can see the price to earnings ratio Going Back 2 years it's well below average which means I'd be paying a lot less for every dollar that Nvidia earns if I buy the stock right now and below that I can see how Nvidia compares to others in their industry they're about twice as expensive but that makes sense given how fast they're growing this app is honestly like having a financial analyst right in my pocket and if I go to their company page I get a high level summary of their earnings all the analyst ratings their quarterly earnings broken down by business segment and tons of financial indicators that can show me when it's a good time to buy Mumu is by far the most comprehensive trading app that I use for stock market research and investing it's even replaced a few apps that I was paying for and if you sign up right now you can get up to 15 free stocks and 5.1% interest on the cash in your account but this offer ends soon so make sure to download the app using my link below today and a big thanks to Mumu and to you for supporting the Channel all right so that's why Nvidia stock is cheaper now despite trading your all-time Highs but chip companies like AMD and Intel are doing everything they can to get a piece of the pie and even Cloud providers are coming out with their own data center chips shouldn't Nvidia be worried about all of this competition are you serious look no business is immune to disruption and 75% margins can't last forever but I don't see any threats to Nvidia anytime soon for example the most direct competition for nvidia's h100 GPU is amd's MI 300X which Launches on December 6th here's another quick CNBC clip of Stacy Raskin explaining what amd's chip means for NVIDIA but how much competition are they about to get from AMD from Intel from maybe Microsoft we're expecting chips to be a part of ignite out this year do investors need to consider that when they think about buying at these levels I I mean look you you you talked before the break about seeing who's pulling ahead of the pack Nvidia kind of is the pack like let let's let's be honest here um they're continually moving the goalpost and everybody else is trying to catch up and even if they catch up to where Nvidia was which I don't know that they are um Nvidia is still moving ahead I think it's really tough like a AMD actually gave us some numbers already for what they expected for their um uh AI sales next year maybe this puts it in some context they said that their product next year was called the mi30 and they said they thought they would do you know in excess of2 billion in sales next year I would say if Nvidia does $50 billion in data center sales next year that will be viewed as incredibly disappointing at AMD is going to do two I mean it's it's single digit percentage probably of what Nvidia is likely to to deliver that that's what I mean when I say they are the pack Nvidia just has too much of a head start in the AI chip Market kind of like how Tesla has a massive Head Start in the electric vehicle Market but the big difference is that most people only own one car at a time so every vehicle Tesla sells is one that their competitors did cloud service providers don't work like that they need to handle an incredibly diverse set of workloads most of which still don't even involve AI today data centers are actually portfolios of different hardware and software Solutions designed to match the workloads they support as demand for a specific kind of workload grows a cloud service provider will buy more of the right kind of chips to support it that's where all of nvidia's competition actually comes in every data center manager is trying to deploy the right mix of systems to optimize their costs so they'll buy chips from AMD and Intel to offload whatever workloads they can from nvidia's gpus since they're so expensive and in some cases it might make more sense for them to build their own chips like Microsoft's Azure Maya 100 or Google Cloud's tensor processing units by the way this is why it doesn't really make sense to compare Tesla's D1 chips and training tiles to nvidia's gpus and dgx pods Beyond a few highlevel numbers Tesla's chips are designed specifically for video processing and machine learning to support full self-driving that's why Tesla also built a massive compute cluster made up of 10,000 Nvidia h100s which came online at the exact same time as dojo and while Tesla showed off three other GPU clusters using over 10,000 Nvidia A1 100s during their previous AI days Tesla's chips aren't magically better than nvidia's and they're not worse they're just different but Tesla only built them because Nvidia couldn't keep up with demand that lack of Supply is why nvidia's chips are so expensive in the first place which changes the math around which chips Tesla needs to buy versus which ones they should build themselves to optimize their costs just like every other data center but that raises an important question if nvidia's chips are so expensive why does everyone keep buying them my God that is the best coffee I've ever tasted why the hell are we making meth something many investors may not realize is that Nvidia doesn't just sell gpus nvidia's CEO Jensen hang has been announcing tons of new products and services across the entire AI stack all year here's a quick clip of him explaining the huge leap in performance that nvidia's Solutions give data centers over their current configurations the GPU server is no longer the computer the computer is the data center your goal is to build the most costeffective Data Center not build the most cost effective server back in the old days when the computer was the server that would be a reasonable thing to do but today the computer is the data center so for $10 million you buy 48 GPU servers it only consumes 3.2 gawat hours and 44 times the performance let me just show it to you one more time this is before and this is after and this is so if a data center switches to Nvidia systems they could do around 150 times more work with the same amount of power or power the same size large language model at around 4% of the cost and this isn't even on their H2 200s this is why demand for nvidia's data center products is through the roof right now not just for nvidia's dgx h100s or their h200 gpus but also their networking technologies that companies like Microsoft Google and Tesla are using in their data centers remember remember those three big Computing clusters from Tesla's AI day filled with nvidia's A1 100s well they're networked with nvidia's infinite band as well in fact a good portion of nvidia's latest earnings call focused on these networking Solutions nvidia's Chief Financial Officer Colette Crest highlighted that Microsoft uses over 29,000 M of infiniband cabling in azure's data centers that's more cable than it takes to circle the globe and annual revenue from nvidia's networking Solutions now exceeds 10 billion a 155% increase year-over-year thanks to a five-fold increase in infin band orders don't sleep on nvidia's networking Solutions another data center solution that I think investors are really sleeping on is nvidia's modular mgx server platform this one platform can have many different configurations for many different kinds of applications like cloud services and gaming high performance Computing and data analytics digital twins for manufacturing robotics Telecom and of course AI training and inference all you have to do is switch out which chips you're using depending on your need and because Nvidia is supporting these form factors across future generations of their Hardware they're locking in their data center customers for many years to come not to mention that the cost of switching away from this ecosystem down the road will be too high for most data centers to really do it by the way super micro just started shipping the first Nvidia mgx systems last month and I'm excited to hear more about them in future earnings calls nvidia's Gaming revenue came in at almost $2.9 billion which is up over 80% year-over-year and 15% quarter over quarter even with lower demand for high performance PCS I think that demand will Trend back up over time though as generative AI makes its way into more desktop applications and increases the need for more powerful gpus Beyond video games nvidia's professional visualization automotive and OEM segments accounted for less than 5% of their overall Revenue combined so I'll keep covering them in other videos like I always do I know this video is running a little long but I want to be thorough because nvidia's Data Center business accounts for over 80% of their total revenue it's by far their fastest growing segment and it's where they're innovating and investing in the most today so if you feel I've earned it consider hitting the like button and subscribing to the channel that really helps me out and it lets me know to put out more research like this thanks and with that out of the way there's really only one question left to answer would I still invest in Nvidia after this earnings call like I said I don't think any other company can compete with nvidia's current AI data center Solutions which is made up of much more than just gpus on top of that Nvidia is actually increasing their pace for new releases they recently announced their h20s which are set to ship in quarter 2 of next year but they're also expected to announce their next Generation GPU architecture called Blackwell which should be a significant upgrade over Hopper they'll be rolling out their B100 Data Center gpus and Grace Blackwell Super Chips as well as new Blackwell based gpus for PCs and of course we should expect big upgrades in their infiniband and other hyperscale networking Solutions as well the only risk I didn't really mention is US sanctions on selling AI chips to China which I don't see as a big risk at all even though China accounts for 20 to 25% of nvidia's overall data center Revenue it's also the riskiest portion of the revenue today in the past Nvidia complied with by selling slow down versions of their A1 100s and h100s to China but in their latest earnings call collect Crest confirmed that Nvidia expects less revenue from China going forward and their $ billion Revenue guidance for next quarter already accounts for that to me this means two things first it means that the drop in revenue from China will be more than offset by Revenue growth from other regions and second it means that envidia is trading out risky revenue for more predictable and stable Revenue over time that's why I think it's pretty fun funny that nvidia's stock dropped after such a great earnings call and finally even though Nvidia stock is near alltime highs it's the cheapest it's been basically since chat GPT came out due to their earnings Rising much faster than their market cap so yes I'm still buying Nvidia stock and I'll keep buying it until a real competitor comes along which is exactly why it's so important to understand the science behind the stocks thanks for watching and until next time this is ticker simple U my name is Alex reminding you that the best investment you can make is in you

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Keywords: nvidia, nvda, nvidia stock, nvda stock, nvidia gtc 2023, jensen huang, gtc keynote, nvidia keynote, openai, chatgpt, gpt4, msft, microsoft stock, msft stock, goog, googl, goog stock, google stock, artificial intelligence stocks, nvidia stock news, semiconductor stocks, gpt-4, nvidia news, jensen huang keynote, nvidia 2023, ai copilot, gpt5, nvda stock news, tsla, nvidia earnings, nvda earnings, tsla stock, tesla stock

Id: hKAapBunwXo

Length: 15min 33sec (933 seconds)

Published: Mon Nov 27 2023