Nvidia Will “Still” Surpass Apple’s Valuation

Posted on May 29, 2023June 30, 2026 by io-fund

This article was originally published on Forbes on May 24, 2023, 07:45 am EDTForbes on May 24, 2023, 07:45 am EDT

My coverage on Nvidia as an AI leader began in 2018 (yes, really – five years ago). Since then, I’ve covered the AI microtrend for this specific stock 27 times on my research site, which is the equivalent of a novel.

I’ve also gone on record to say that Nvidia will surpass the valuation of Apple. That particular analysis compared the impact that AI will have to mobile, with AI adding $15 trillion to GDP compared to mobile’s $4.4 trillion. Mobile brought us three FAANGs: Apple, Google and Facebook. It has been my stance for years that AI will bring us a new set of FAANGs, one of which will be Nvidia.

However, now is not the best time to buy the stock. Rather than flatly tell you that while offering no way forward, I want to continue providing value to my readers by discussing when my firm plans to buy the stock again.

But also, we should discuss why the market is rallying on this company specifically. Good investors must do both – understand what makes a company stand out while being patient on price.

AI is Not a Buzzword for Nvidia

Short sellers mistakenly believe that AI is a buzzword for Nvidia. This is true for many stocks, but not for the leader in parallel processing.

Here is what I wrote five years ago on the topic:

Nvidia is already the universal platform for development, but this won’t become obvious until innovation in artificial intelligence matures. Developers are programming the future of artificial intelligence applications on Nvidia because GPUs are easier and more flexible than customized TPU chips from Google or FPGA chips used by Microsoft [from Xilinx]. Meanwhile, Intel’s CPU chips will struggle to compete as artificial intelligence applications and machine learning inferencing move to the cloud. Intel is trying to catch-up but Nvidia continues to release more powerful GPUs – and cloud providers such as Amazon, Microsoft and Google cannot risk losing the competitive advantage that comes with Nvidia’s technology.Nvidia is already the universal platform for development, but this won’t become obvious until innovation in artificial intelligence matures. Developers are programming the future of artificial intelligence applications on Nvidia because GPUs are easier and more flexible than customized TPU chips from Google or FPGA chips used by Microsoft [from Xilinx]. Meanwhile, Intel’s CPU chips will struggle to compete as artificial intelligence applications and machine learning inferencing move to the cloud. Intel is trying to catch-up but Nvidia continues to release more powerful GPUs – and cloud providers such as Amazon, Microsoft and Google cannot risk losing the competitive advantage that comes with Nvidia’s technology.

The Turing T4 GPU from Nvidia should start to show up in earnings soon, and the real-time ray-tracing RTX chips will keep gaming revenue strong when there is more adoption in 6-12 months. Nvidia is a company that has reported big earnings beats, with average upside potential of 33.35 percent to estimates in the last four quarters. Data center revenue stands at 24% and is rapidly growing. When artificial intelligence matures, you can expect data center revenue to be Nvidia’s top revenue segment. Despite the corrections we’ve seen in the technology sector, and with Nvidia stock specifically, investors who remain patient will have a sizeable return in the future.”When artificial intelligence matures, you can expect data center revenue to be Nvidia’s top revenue segment. Despite the corrections we’ve seen in the technology sector, and with Nvidia stock specifically, investors who remain patient will have a sizeable return in the future.”

-Free Newsletter and Seeking Alpha, November 2018 with AI Thesis repeated again in April of 2019Free Newsletter and Seeking Alpha, November 2018 with AI Thesis repeated again in April of 2019

When I wrote that, Nvidia was considered a gaming stock with high-risk exposure to crypto. What is astonishing is that the company was still considered a gaming stock with high-risk exposure to crypto a mere seven months ago.

You may recall, the stock was down 60% last year after a $2.5 billion miss on gaming, and the market was pricing in a long recovery due to Ethereum’s merge to Proof of Stake (PoS). The bears believed the Merge would flood the market with mining GPUs and Nvidia would be unable to overcome this setback.

At the time, there was no mention of Nvidia’s AI lead despite the H100 GPU being released the very next month! despite the H100 GPU being released the very next month! Instead, the market had investors believing that Ethereum, with only 200 million users, which is a smaller user base than Snap or Pinterest, could tank the GPU-juggernaut on the eve of the company’s largest release to-date: the H100 GPU.

The reason I’m emphasizing this is because my firm has worked hard to be a quality resource on tech stocks. Often times there is a major disconnect between the market’s pricing and a tech company’s positioning. There is no greater evidence of this than when Nvidia was down 60% seven months ago yet is the top performing stock in the S&P 500 today.

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Why the Market is Bulled Up on Nvidia

I want to take the opportunity to explain why Nvidia has the ability to arrive at a valuation that is 3X higher than its peers and in some cases 12X higher.

Source: YCHARTS

I’m not defending this valuation, rather I want to explain how it’s possible that smart money continues to buy up here.

The H100 is a Turning Point from Hardware to Software

“The Hopper architecture is ramping and it’s yet again going to disrupt the GPU and AI accelerator market. I’ve written quite a bit about Nvidia […] however, I will keep it simple by saying the A100 GPU is what led the company’s gains since Q2 2020 and the Hopper H100 GPU is what will lead the company’s gains for the next two years.” -Premium Site August 2022, following Nvidia’s $2.5 billion revenue miss.Premium Site August 2022, following Nvidia’s $2.5 billion revenue miss.

Note: the information below is a bit technical, so I’ve bolded the key points for a quick read.

For context, the A100 GPU was a monumental release for Nvidia as the Ampere architecture unified training and inference onto a single chip, whereas in the past Nvidia’s GPUs were mainly used for training.

The result is a 20x performance boost from a multi-instance GPU that allows many GPUs to look like one GPU. The A100 offered the largest leap in performance to date over the past 8 generations. One year later, the Ampere architecture had become the best-selling GPU architecture in the company’s history.

The A100 was special but it’s the H100 that is Nvidia’s iPhone moment. The reason is quite simple – it’s the release that will help Nvidia breakout from hardware and put the company firmly on the map for AI software.

Hardware has allowed Nvidia to become a $700B market cap company, but it is the recurring revenue from AI software that will propel Nvidia into a market cap worth trillions.

You know this story well: the relationship between a hardware company leveraging their position to capture the lion’s share of software —- because that’s exactly what Apple did. My contention is that the iPhone was successful because of the moat iOS developers created, and the additional flywheel from the App Store. I discussed this more in a webinar “The New Kings of Tech”

The H100 delivers 9X more throughput in AI training, and 16X to 30X more inference performance. The company also states in HPC application-specific workloads, the H100 is 7X faster. The goal of the H100 was not only to add more transistors and make the H100 faster, but to also offer function-specific optimizations. This is achieved through the transformer engine.

The transformer engine is one of the key aspects of the H100. Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.

Prior to transformer models, labeled datasets had to be used to train neural networks. Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly. Transformers are partial to the parallel processing that GPUs offer.

The Hopper architecture aims to answer one of the bigger challenges facing superfast compute, which is that moving data into traditional servers overloads the CPU and system memory and becomes bottlenecked by PCI-Express.

By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.

The DGX SuperPods scale into a super-GPU capable of 768 terabytes per second. To compare, the entire internet requires 100 terabytes per second. This results in 1 exaflop of FP8 AI performance that runs trillions of parameters. FP8 is most commonly used for inference yet may be used for training in the future due to boosting throughput.

Whereas traditional workloads required many connections exchanging small amounts of data, the workloads of the future will require data to be shared quickly between GPUs and storage. This is accomplished by bypassing the CPU and sending data directly to the GPU while using the network hardware to move the data.

This is ideal for enterprise use cases where people are more likely to use Ethernet while AI and HPC workloads continue to use the Quantum-2 based off Mellanox’s InfiniBand.

Not only will Nvidia begin to monetize through software on the DGX systems but accessibility will improve through CSPs, or cloud service providers. This is an attempt to democratize AI development while driving software sales. On a trailing 4-quarter basis, cloud service providers drove 40% of data center revenue. This is important as cloud service providers will help move DGX Cloud along and AI-as-a-service.

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

“The conclusion to my analysis is the same as the introduction, which is that I believe Nvidia is capable of out-performing all five FAAMG stocks and will surpass even Apple’s valuation in the next five years.” – Forbes and Free Newsletter, August 2021Forbes and Free Newsletter, August 2021

Per the analyst on the call: “So it seems like the incremental TAM is easily in the several hundred thousands of GPUs and easily in the tens of billions of dollars. But I'm kind of wondering what this does to the TAM numbers you gave last year. I think you said $300 billion hardware TAM and $300 billion software TAM. So how do you kind of think about what the new TAM would be?”

Huang aptly answered: “I think those numbers are really a good anchor still. The difference is because of the, if you will, incredible capabilities and versatility of generative AI and all of the converging breakthroughs that happened towards the middle and the end of last year, we're probably going to arrive at that TAM sooner than later.”

Today, Nvidia trades at 1.5X this TAM at $773 billion compared to an achievable TAM of $600 billion. This would suggest the stock price does not yet fully reflect the future market opportunity. Also, compare this TAM of $600 billion to Apple’s revenue of $394 billion, which helps illustrate why I said in the past that Nvidia Will Surpass Apple’s Valuation.

Every Thursday at 4:30 pm Eastern, the I/O Fund team holds a webinar for premium members to discuss how to navigate the broad market, as well as various stock entries and exits. We offer trade alerts plus an automated hedging signal. The I/O Fund team is one of the only audited portfolios available to individual investors. Learn more here.Learn more here.

What to Expect in the Upcoming Earnings:

If we set aside the AI thesis for a moment, you can see below why Nvidia has rallied as the revenue is expected to rebound from (-21.4%) for the upcoming quarter to as much as +32% growth by fiscal Q3 ending in September. The popularity of the H100 could lead to a beat somewhere across these next few quarters. In addition, the RTX40 Series lower-end model will be released today for $299 and up, and this may further help the gaming revenue for Q2 and beyond.

Nvidia is unique in that the healthy growth is expected to continue into the foreseeable future — long after the company laps the quarters of the crazy gaming miss. What we don’t want is to invest in companies propped up temporarily by low comps. This is not the case with Nvidia.

Here is Nvidia’s revenue growth over the past five quarters, which shows the effects of the gaming segment:

Source: I/O FUND

As stated in our previous earnings coverage on Nvidia, all segments are expected to grow sequentially. I believe this is a major contributor for the rally we are seeing. The market saw what we saw, which was a sharp rebound in the fundamentals and that is critical to understanding why Nvidia is the top stock in the market right now.

Compare that picture to this one:

Source: I/O FUND

It’s not only the top line that is rebounding but also the bottom line too (which makes sense but is important to point out):

Source: I/O FUND

Moving along, data center revenue was $3.75B in Q1 FY23. The projected mid-point above is $4.075B, representing 8.7% YoY growth and 12.7% growth sequentially. Here is what was said on the call:

“Thanks for the question. First, talking about our data center guidance that we provided for Q1. We do expect a sequential growth in terms of our data center, strong sequential growth. And we are also expecting a growth year-over-year for our data center. We actually expect a great year with our year-over-year growth in data center probably accelerating past Q1.”

Source: I/O FUND

So, what we don’t see in the graph above is what the “accelerating past Q1” will be and this is the one data point that can get the stock to move AH.

Where Nvidia’s Price Will Go Next:

With the cash we raised throughout 2022, NVDA was the primary target of deploying some of this cash once our analysis signaled a bottom was in place. The below is a real-time trade notification we sent to our members on the October 13th.

Source: I/O FUND

Since February of 2022, we have been systematically taking gains at key levels. Even with logging sizable wins in this position in 2023, it remains our top position while still having enough cash to buy at lower levels.

It is our belief that NVDA is setting up for a sizable pullback, which we believe will open the door for better long-term entries. The reasons for this are below:

The structure/pattern of NVDA’s bounce signals caution. If we look at the pattern off the October low, it may feel like a straight line up; however, you can clearly see 3 swings (marked a, b, c). The first swing up off the low (a), a bearish retrace that makes a higher low (b), and the current swing that we are still in (c).

Source: I/O FUND

When we see a 3 wave pattern off of a major low, more times than not, it is a corrective bounce in a larger downtrend. While it may feel impossible at such heights, please keep in mind how sentiment can and does work against us as investors. It felt like tech could never go down in late 2020, and then it felt like it would never go up in Q4 of 2022.

Nvidia is no different, and what we have is a pattern that suggests a larger pullback than most expect is likely, at minimum. So, until this 3 wave pattern can morph into a 5 wave pattern, the odds favor a sizable pullback soon.

Further evidence of this can be seen in how NVDA is now at a significant supply region that marked the top in late 2023. We are now in the region that would constitute a double top playing, and note how price keeps trending higher with less momentum.

We are approaching a double top in conjunction with one of my favorite “sell signals” – when you have price making 3 higher highs, while the momentum indicator being used is making 3 lower highs. This is clearly happening on multiple time frames, which we believe warrants caution.

Similar patterns can be seen on the weekly chart of NVDA below. As price pushes higher, it is doing so on less momentum and less volume. When we see the same pattern on multiple time frames, it further builds the case for caution.

Source: I/O FUND

Regarding the targets we are tracking for entries, there are two general paths I see playing out from the price data in the above charts.

The Blue Count suggests that we completed the large degree uptrend that started in 2018. This would put is in a very large corrective rally with the final leg lower coming later this year/early next year. This would have us retest the October lows, and possibly slightly lower. The big tell for this count playing out will be if the coming pullback is a 5 wave pattern pointing down. If we see a large 5 wave drop from the highs, it is signaling that NVDA will likely go lower than most are anticipating.

The Red Count suggests that the October low was THE low. This will still set us up for a sizable pullback into the $220 – $167 region before setting up to make a run to new highs. This count implies that the large uptrend that started in 2018 is not complete and will be targeting fresh highs in the coming year. The tell for this scenario will be if the coming pullback is a 3 wave pattern. If we see a 3 wave pullback, we will look to be heavy buyers in the general target box just outlined.

Conclusion:

My firm tracks Nvidia very closely due to its leading allocation in our portfolio. We saw evidence of a gaming bottom in November, which we published about here. We also felt Nvidia had masterfully timed it’s RTX40 Series with the Ada Lovelace architecture plus the H100 release to drop exactly when the crypto mining selloff would be most felt. We discussed this here in September. These points were entirely overlooked by Nvidia critics.

Yes, a $2.5 billion revenue miss is crazy – but what was lying beneath the surface for chances of a quick recovery? The devil is in the details and not a lot of investors or analysts care to look into Nvidia’s complex hardware products.

For my readers, it has worked out in their favor that talking heads prefer to discuss stocks after they are up triple digits in price, and that the masses are collected around hindsight narratives. My firm is carefully and patiently building an AI portfolio that we believe will outperform institutions and hedge funds. Taking our sweet time to enter Nvidia at the lows – as we have done for the past five years and will continue to do so for the next five years — is part of that strategy.

Our firm issues real-time trade alerts when we buy, sell or trim stocks. You can learn more and view our other notable wins here.

Nvidia Q1 Earnings: Est 100% Growth for Data Center in Q2 is Bonkers

Posted on May 25, 2023June 30, 2026 by io-fund

You’ve probably already heard by now that Nvidia’s guidance for fiscal Q2 of $11 billion was 53% higher than analyst expectations of $7.2 billion. The stock is up 25% after hours, adding $200 billion to its market cap.

Originally, the stock was up +15% and then shot up to +25% when the CFO mentioned the beat is coming from the data center, plus when it was confirmed H2 would be also strong with visibility on supply.

We’ve been talking about this rebound for several months. It’s been the subject of quarterly webinars, free editorials and our earnings updates, as well. I was starting to feel like a broken record about the “H2 Semi Rebound” – especially on our last webinar — but I guess it was for a good reason because we got a helluva rebound today.

The rebound now looks like this:

Data center was expected to grow 9% YoY yet beat expectations at 14% YoY growth in the current quarter. This was stated in the opening remarks: “We expect this sequential growth to largely be driven by data center, reflecting a steep increase in demand related to generative AI and large language models. This demand has extended our data center visibility out a few quarters and we have procured substantially higher supply for the second half of the year.”

If Nvidia is adding roughly $4 billion in revenue, primarily driven by the data center, then Q2’s growth will accelerate to an incredible 100% growth rate, up from $3.8 billion in the year ago quarter. It also means the data center will roughly double from the first quarter (sequentially) as the segment was $4.28B in the current quarter.

Put another way, this means Nvidia’s data center segment in the upcoming quarter will be as large as the company’s entire revenue this quarter – if we assume $7.75B in the data center compared to $7.2B total revenue this quarter. See below for analyst Q&A around this.

The other segments are, you guessed it, rebounding too. The sequential numbers show this quite clearly. Here are the official numbers:

Data center revenue of $4.28B up 18% QoQ and 14% YoY
Gaming revenue of $2.2B, up 22% QoQ and down (-38%) YoY
Pro Viz revenue of $295 million, up 31% QoQ and down (-53%) YoY
Automotive revenue of $296 million, up 1% QoQ and up 114% YoY

The gross margin was strong at 64% in the current quarter and the guide is for 68.6% in the next quarter – per the CFO: “Gross margins have now largely recovered to prior peak level, and we have absorbed higher costs, and offset them by innovating and delivering higher valued products as well as products incorporating more and more software.”

Earnings Call:

This question pointed toward the “doubling” of the data center revenue:

C.J. Muse

Yeah. Good afternoon. Thank you for taking the question. I guess with data center, you are essentially doubling quarter-on-quarter, yes, two natural kind of questions that relate to one another come to mind. Number one, where are we in terms of driving acceleration into servers to support AI? And as part of that, as you deal with longer cycle times with TSMC and your other partners, how are you thinking about managing their commitments there with where you want to manage your lead times, in the coming years, to best kind of match — best match that supply and demand? Thanks so much.

Note: the answer was long so this is an excerpt

Jensen Huang:

“And what happened is, when generative AI came along, it triggered a killer app for this computing platform that's been in preparation for some time. And so, now we see ourselves in two simultaneous transitions. The world's $1 trillion data center is nearly populated entirely by CPUs today, and $1 trillion, $250 billion a year, it's growing of course. But over the last four years, call it a $1 trillion worth of infrastructure installed. And it's all completely based on CPUs and dumb NICs (ph). It's basically unaccelerated.

In the future, it's fairly clear now with this — with generative AI becoming the primary workload of most of the world's data centers generating information, it is very clear now that — and the fact that accelerated computing is so energy efficient, that the budget of the data center will shift very dramatically towards accelerated computing and you're seeing that now. We're going through that moment right now as we speak. While the world's data center CapEx budget is limited, but at the same time, we're seeing incredible orders to retool the world's data centers.”

Here was a good question about what Q3 and Q4 will look like if Q2 is this strong, and can supply keep up with the demand:

Vivek Arya:

Thanks for the question. Could I just wanted to clarify does visibility mean data center sales can continue to grow sequentially in Q3 and Q4 or do they sustain at Q2 levels? I just wanted to clarify that. And then Jensen, my question is that, given this very strong demand environment, what does that do to the competitive landscape? Does it invite more competition in terms of custom ASICs? Does it invite more competition in terms of other GPU solutions or other kinds of solutions? How do you see the competitive landscape change over the next two to three years?

Colette Kress:

Yeah, Vivek. Thanks for the question. Let me see if I can add a little bit more color. We believe that the supply that we will have for the second half of the year will be substantially larger than H1. So, we are expecting not only the demand that we just saw in this last quarter, the demand that we have in Q2 for our forecast, but also planning on seeing something in the second half of the year. We just have to be careful here. But we are not here to guide on the second half of that. Yes, we do plan a substantial increase in the second half compared to the first half.

Conclusion:

Nvidia is our largest position and we have taken gains along the way. The plan right now is to wait for a pullback to add more. This earnings report may have changed what the pullback looks like as it’s certainly a historic earnings report in many regards – I do not believe we’ve ever seen $200B market cap added in one day. The reason this much market cap was added AH is that the acceleration of 100% growth in the data center is bonkers considering most tech companies are struggling with a sharp deceleration.

I had put in an editorial that Nvidia investors can take their sweet time adding to this position. This is true, so don’t panic. You haven’t seen anything yet. Once software starts to kick in, it’s going to be an unbelievable ride.

The risk with Nvidia is two things: Broader Macro Events and China. As Jensen Huang recently said: “There is only one China.” If the chip war heats up, China cannot be replaced and the effects would be devastating to the chip industry. Macro continues to be a wild card and tech is especially sensitive to macro. I don’t mean to end on a somber note but I want to make sure we talk about the risks so you’re mentally prepared for it.

Nvidia Q1 Earnings: Est 100% Growth for Data Center in Q2 is Bonkers

Posted on May 25, 2023June 30, 2026 by io-fund

The rebound now looks like this:

The other segments are, you guessed it, rebounding too. The sequential numbers show this quite clearly. Here are the official numbers:

Data center revenue of $4.28B up 18% QoQ and 14% YoY
Gaming revenue of $2.2B, up 22% QoQ and down (-38%) YoY
Pro Viz revenue of $295 million, up 31% QoQ and down (-53%) YoY
Automotive revenue of $296 million, up 1% QoQ and up 114% YoY

Earnings Call:

This question pointed toward the “doubling” of the data center revenue:

C.J. Muse

Note: the answer was long so this is an excerpt

Jensen Huang:

Here was a good question about what Q3 and Q4 will look like if Q2 is this strong, and can supply keep up with the demand:

Vivek Arya:

Colette Kress:

Conclusion:

Nvidia Q1 Earnings Prep: What to Look For

Posted on May 24, 2023June 30, 2026 by io-fund

Feel free to join me on the forum tomorrow for an initial reaction to the earnings report.join me on the forum tomorrow for an initial reaction to the earnings report.

Everyone is expecting Nvidia to selloff soon (including the I/O Fund!). It’ll be interesting to see if popular opinion is proven wrong, only because the market has a way of proving everyone wrong. Call it 2022 leaving a mark to where tech investors are fully prepared to sell now that a stock is up triple digits. But certainly, nothing is wrong with putting money in the bank. We have to perform on an annual basis so clocking gains is something we do frequently and we issue real-time trade alerts to this effect. Knox has included his trading plan below. You may want to handle this position differently due to its strong, long-term potential. In fact, tomorrow I am publishing a free article entitled “Nvidia Will Still Surpass Apple’s Valuation” so that helps frame where I think this company is headed.

If we set aside the AI thesis for a moment, you can see below why Nvidia has rallied as the revenue is expected to rebound from (-21.4%) on for the upcoming quarter to as much as +32% growth by fiscal Q3 ending in September. The popularity of the H100 could lead to a beat somewhere across these next few quarters. In addition, the RTX40 Series lower-end model will be released today for $299 and up, and this may further help the gaming revenue for Q2 and beyond.

Here is Nvidia’s revenue growth over the past five quarters, which shows the effects of the gaming segment:

Compare that picture to this one:

It’s not only the top line that is rebounding but also the bottom line too (which makes sense but is important to point out):

What’s also important to consider is that Nvidia is expected to grow 20%+ on the top line through mid-2025 and 20%+ on the bottom line through mid-2025.

I will stick my neck out and say that these estimates are too low. Once we start to see AI software contribute to sales and once we add in automotive, Nvidia will be the most hated stock on the market because either people will have tried to short it and gotten burned, or people will have not bought it and will be quite angry with themselves over it.

The H100 is capable of putting up an earnings surprise or two, but most importantly, analysts are not able to truly model AI software yet (at all). Nvidia is going to power every vehicle one day, and drivers will be paying a monthly fee for the software.

That doesn’t mean the company won’t see pullbacks. I’ve included Knox’s most recent TA below.

Moving along, data center revenue was $3.75B in Q1 FY23. The projected mid-point above is $4.075B, representing 8.7% YoY growth and 12.7% growth sequentially. Here is what was said on the call:

So, what we don’t see in the graph above is what the “accelerating past Q1” will be and this is the one data point that can get the stock to move AH.

Gaming will be “meh” this quarter at an expected (-45%) growth – but again, let’s see if we get a decent guide for Q2:

Fiscal Q1 Earnings Consensus:

Here are the nitty gritty numbers for quick reference

Revenue and EPS:

Current quarter revenue of $6.52B for growth of (-21.4%)
Next quarter revenue of $7.08B for growth of +5.7%
Current quarter EPS of $0.92
Next quarter EPS of $1.06

Margins:

Overall, the current quarter margins are higher than FY2023 (ending in Jan) but lower than FY2022. Note, we are currently in FY2024 for Nvidia.

Gross margin guide of 64% is lower than the 57% from FY2023 (ending in Jan)
Adjusted gross margin guide of 66.5% is higher than 59% in FY2023
GAAP Operating margin guide of 25% is higher than 15.7% in FY2023
Adjusted Operating margin guide of 39% is higher than 33.5% in FY2023

Cash Flow:

In the year ago quarter, Nvidia posted $1.73B in op cash flow and $1.35 billion in free cash flow. Margins were 21% and 16.2%, respectively.
Last quarter, Nvidia posted $2.25B in op cash flow and $1.74B in free cash flow. Margins were 37% and 29%, respectively.
The company has $13.3B in cash and $10.95B in debt.
The company returned $1.15B to shareholders in Q4 with $7B remaining for share repurchases

Revenue Segments:

Data center: $3.85B to $4.3B
Gaming: $1.9B to $2.05B
Auto and Pro Viz: $550M to $580M

Additional Notes:

Below are excerpts from an upcoming newsletter that will hit inboxes prior to the earnings report. We have published on the H100 and A100 many times on our premium site but am including this as a quick reference point. If you’re looking for more background, I would read this analysis here on AI software which was published for premium members.analysis here on AI software which was published for premium members.

I want to take the opportunity to explain why Nvidia has the ability to arrive at a valuation that is 3X higher than its peers and in some cases 12X higher.

I’m not defending this valuation rather want to explain how it’s possible that smart money continues to buy up here.

The H100 is a Turning Point from Hardware to Software

In August, I wrote on the premium site:

“The Hopper architecture is ramping and it’s yet again going to disrupt the GPU and AI accelerator market. I’ve written quite a bit about Nvidia […] however, I will keep it simple by saying the A100 GPU is what led the company’s gains since Q2 2020 and the Hopper H100 GPU is what will lead the company’s gains for the next two years.” –Premium Site August 2022, following Nvidia’s $2.5 billion revenue miss, following Nvidia’s $2.5 billion revenue missPremium Site August 2022, following Nvidia’s $2.5 billion revenue miss, following Nvidia’s $2.5 billion revenue miss

Note: the information below is a bit technical, so I’ve bolded the key points for a quick read.

Hardware has allowed Nvidia to become a $700B market cap company, but it is the recurring revenue from AI software that will propel Nvidia into a market cap worth trillions.

You know this story well: the relationship between a hardware company leveraging their position to capture the lion’s share of software — because that’s exactly what Apple did. My contention is that the iPhone was successful because of the moat iOS developers created, and the additional flywheel from the App Store. You can read more here.

By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.

This is ideal for enterprise use cases where people are more likely to use Ethernet while AI and HPC workloads continue to use the Quantum-2 based off Mellanox’s InfiniBand.

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

Last year, CEO Jensen Huang provided a total addressable market of $300 billion in hardware and $300 billion in software. Meanwhile, Elon Musk is deploying 10,000 GPUs in the cloud and there will likely be tens of thousands more to inference a widely deployed model for a social media generative AI project. Per the analyst on the call: “So it seems like the incremental TAM is easily in the several hundred thousands of GPUs and easily in the tens of billions of dollars. But I'm kind of wondering what this does to the TAM numbers you gave last year. I think you said $300 billion hardware TAM and $300 billion software TAM. So how do you kind of think about what the new TAM would be?”

What Levels We Plan to Buy Again

Even with logging sizable wins in this position in 2023, it remains our top position while still having enough cash to buy at lower levels.

It is our belief that NVDA is setting up for a sizable pullback, which we believe will open the door for better long-term entries. The reasons for this are below:

When we see a 3 wave pattern off of a major low, more times than not, it is a corrective bounce in a larger downtrend. While it may feel impossible at such heights, please keep in mind how sentiment can and does work against us as investors. It felt like tech could never go down in late 2020, and then it felt like it would never go up in Q4 of 2022.

Regarding the targets we are tracking for entries, there are two general paths I see playing out from the price data in the above charts.

We issue real-time trade alerts to our Advanced Members so please make sure you are signed up through our Trade Dashboard here to receive our buys, sells, and trims in real-time.Trade Dashboard here to receive our buys, sells, and trims in real-time.

Nvidia Q1 Earnings Prep: What to Look For

Posted on May 24, 2023June 30, 2026 by io-fund

Feel free to join me on the forum tomorrow for an initial reaction to the earnings report.join me on the forum tomorrow for an initial reaction to the earnings report.

Here is Nvidia’s revenue growth over the past five quarters, which shows the effects of the gaming segment:

Compare that picture to this one:

It’s not only the top line that is rebounding but also the bottom line too (which makes sense but is important to point out):

What’s also important to consider is that Nvidia is expected to grow 20%+ on the top line through mid-2025 and 20%+ on the bottom line through mid-2025.

That doesn’t mean the company won’t see pullbacks. I’ve included Knox’s most recent TA below.

Moving along, data center revenue was $3.75B in Q1 FY23. The projected mid-point above is $4.075B, representing 8.7% YoY growth and 12.7% growth sequentially. Here is what was said on the call:

So, what we don’t see in the graph above is what the “accelerating past Q1” will be and this is the one data point that can get the stock to move AH.

Gaming will be “meh” this quarter at an expected (-45%) growth – but again, let’s see if we get a decent guide for Q2:

Fiscal Q1 Earnings Consensus:

Here are the nitty gritty numbers for quick reference

Revenue and EPS:

Current quarter revenue of $6.52B for growth of (-21.4%)
Next quarter revenue of $7.08B for growth of +5.7%
Current quarter EPS of $0.92
Next quarter EPS of $1.06

Margins:

Overall, the current quarter margins are higher than FY2023 (ending in Jan) but lower than FY2022. Note, we are currently in FY2024 for Nvidia.

Gross margin guide of 64% is lower than the 57% from FY2023 (ending in Jan)
Adjusted gross margin guide of 66.5% is higher than 59% in FY2023
GAAP Operating margin guide of 25% is higher than 15.7% in FY2023
Adjusted Operating margin guide of 39% is higher than 33.5% in FY2023

Cash Flow:

In the year ago quarter, Nvidia posted $1.73B in op cash flow and $1.35 billion in free cash flow. Margins were 21% and 16.2%, respectively.
Last quarter, Nvidia posted $2.25B in op cash flow and $1.74B in free cash flow. Margins were 37% and 29%, respectively.
The company has $13.3B in cash and $10.95B in debt.
The company returned $1.15B to shareholders in Q4 with $7B remaining for share repurchases

Revenue Segments:

Data center: $3.85B to $4.3B
Gaming: $1.9B to $2.05B
Auto and Pro Viz: $550M to $580M

Additional Notes:

I want to take the opportunity to explain why Nvidia has the ability to arrive at a valuation that is 3X higher than its peers and in some cases 12X higher.

I’m not defending this valuation rather want to explain how it’s possible that smart money continues to buy up here.

The H100 is a Turning Point from Hardware to Software

In August, I wrote on the premium site:

“The Hopper architecture is ramping and it’s yet again going to disrupt the GPU and AI accelerator market. I’ve written quite a bit about Nvidia […] however, I will keep it simple by saying the A100 GPU is what led the company’s gains since Q2 2020 and the Hopper H100 GPU is what will lead the company’s gains for the next two years.” –Premium Site August 2022, following Nvidia’s $2.5 billion revenue miss, following Nvidia’s $2.5 billion revenue missPremium Site August 2022, following Nvidia’s $2.5 billion revenue miss, following Nvidia’s $2.5 billion revenue miss

Note: the information below is a bit technical, so I’ve bolded the key points for a quick read.

Hardware has allowed Nvidia to become a $700B market cap company, but it is the recurring revenue from AI software that will propel Nvidia into a market cap worth trillions.

By improving the bandwidth issue, Nvidia’s goal is to create more demand for their DGX Pod and SuperPod Systems, which in turn, will create more demand for their software.

This is ideal for enterprise use cases where people are more likely to use Ethernet while AI and HPC workloads continue to use the Quantum-2 based off Mellanox’s InfiniBand.

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

What Levels We Plan to Buy Again

Even with logging sizable wins in this position in 2023, it remains our top position while still having enough cash to buy at lower levels.

It is our belief that NVDA is setting up for a sizable pullback, which we believe will open the door for better long-term entries. The reasons for this are below:

When we see a 3 wave pattern off of a major low, more times than not, it is a corrective bounce in a larger downtrend. While it may feel impossible at such heights, please keep in mind how sentiment can and does work against us as investors. It felt like tech could never go down in late 2020, and then it felt like it would never go up in Q4 of 2022.

Regarding the targets we are tracking for entries, there are two general paths I see playing out from the price data in the above charts.

Super Micro: Sandwiched In The AI Trend

Posted on May 18, 2023June 30, 2026 by io-fund

Super Micro, also known as Supermicro, is sandwiched in the AI trend between hyperscalers and major chip design companies. The company is a server maker that started off by making motherboards and other components before it began making complete systems. The company is unique in that it sits between being an equipment manufacturer (Dell, HP) and being a design manufacturer (Foxconn).

The company competes with Dell, IBM, Hewlett Packard, and China’s Inspur. The chart below gives you a general idea of the landscape although Supermicro has doubled its revenue since 2021. The server maker is now a $6.8 billion company and ended 2021 as a $3.5B company (Counterpoint estimates were about $1B off) but the chart below is useful in visualizing the competitors.

The word “competitor” is being used loosely here as many of these companies will not necessarily be able to compete on liquid cooling for AI development platforms, or with Supermicro’s Building Block design. The companies pictured above have stagnated and this has worked out for Supermicro, a company that could have stagnated but continued to innovate instead.

According to IDC, the worldwide server market forecast is expected to deceleratedecelerate from 20% to 0%. Supermicro declined in revenue going into 2023, however, according to management, this is due to supply chain issues. This is important to distinguish as the 2023 bull case for Supermicro rests on the high demand the company is seeing, that due to supply chain issues, the company is unable to fill. The prevailing bull thesis is that Supermicro’s supply chain issues will ease in the near term.

According to the most recent Investor’s Presentation, Supermicro grew 5X faster compared to the industry average for subsystems and server systems. While there is pressure for tech management teams to cut costs, Supermicro may be more insulated by working closely on making AI systems with the most cutting-edge chips. This includes AMD 4th Generation Zen Epyc processors, Intel Xeon and soon Sapphire Rapids, Nvidia Grace CPUs and Ampere Arm-based third-gen CPUs, Nvidia’s A100 and H100s GPUs, AMD’s MI250 and MI300 GPUs and Intel’s Ponte Vecchio GPUs.

Another piece to the bull case for Supermicro is the near-term goal to reach $10 billion, which will put the company behind Dell and Hewlett Packard. Should the company reach its $20 billion long-term goal, then it could very well be the leader or at least a strong rival to Dell and HP. If/When this happens, it’ll be due to AI systems. It was stated on the call that AI/GPU and rack-scale solutions represented 29% of our total revenue and the company expects “significant future growth.”

Supermicro’s revenue quickly accelerated last year due to one large customer in Q3 2022 to Q1 2023. This one large customer, which was later identified as Meta, accounted for upward of 20% of revenue in June and September of 2022. By December, Meta had accounted for 10% of revenue. This was the subject of a short report. However, if you invest in a small cap or low mid-cap semiconductor company, there is going to be high customer concentration.

There was also a hint on the call that another customer may be ramping: “an existing Cloud Service Provider customer represented more than 10% of revenues for the first time.”

Liquid Cooling

As the performance of CPUs and GPUs increase, the heat these systems generate increases. Liquid cooling is becoming a popular alternative to air cooling to sustain maximum performance with the added benefit of driving down costs for supercomputers. According to a press release in 2021, liquid cooling can improve data center power usage effectiveness (PUE) and total cost of ownership (TCO) “by over 40% on power costs.”

Here's a quote from the CEO on the importance of this competitive advantage:

“The power consumption and thermal challenges of these new technologies have risen dramatically and 40KW or even 80KW rack solution demands are getting stronger and popular for computing hungry DC and industries. Having high power efficiency and air/liquid thermal expertise has become one of our key differentiators of success.”Having high power efficiency and air/liquid thermal expertise has become one of our key differentiators of success.”

In 2022, Supermicro stated that liquid cooling is being used in 10% of supercomputers but will grow to be used in the “vast majority” in order to offset the heat generated by power-consuming components. The company offers Direct to Chip cooling, Immersion cooling and Rear-door Heat Exchanger cooling. This design works better than air cooling, which needs air conditioning and server fans to run constantly.

Direct to Chip Cooling: Running a cold liquid over the top of a running chip by using a pump to circulate liquid. This is a closed loop system, or also known as a self-contained cooling system.
Immersion Cooling: The system is immersed in liquid for cooling.
Rear Door Heat Exchanger: Uses a specialized rear door to the rack where coolant absorbs the heat.

Water removes heat better than air. Liquid molecules are closer together than air molecules, which results in higher heat transfer. Artificial intelligence/Machine Learning and Big Data require massive amounts of data processing, and as future generations of CPUs and GPUs are released, these systems will exceed air cooling capacity.

Liquid cooling also solves CPU throttling, which occurs when CPUs and GPUs overheat and are throttled back to avoid damage to the chip.

AI Development Platforms

AI development platforms remove the need for disparate hardware and software by offering an end-to-end platform. Supermicro has partnered with Nvidia to offer Certified systems with the new H100 GPUs for the Nvidia AI Enterprise Platform.

These systems come with 3-year AI enterprise software subscriptions, and include workflows, frameworks, pretrained models and infrastructure optimization, in the cloud, in the data center and at the edge.

Supermicro is closely partnered with Nvidia on the H100 GPU rollout with air flow designs that reduce fan speeds, lower power consumption, lower noise levels and lower the total cost of ownership.

The most recent system announced in March enables AI workloads to be run in offices and the system can be rack-mounted, as well, for data center environments. The self-contained cooling system reduces operating expenses and helps the machine to run quietly for AI, deep learning, machine learning and high-performance computing (HPC) applications.

Supermicro is able to deliver workload optimized products quickly because of its building block design. The AI market is moving quickly, and SMCI can build and validate systems partly due to a modular design that allows systems to be updated from new products, such as when Nvidia, AMD or Intel have new design releases.

Financials:

Supermicro saw strong price action due to strong guidance for next quarter and due to strong guidance of 20% revenue growth for fiscal year 2024, which begins in July.

The current quarter revenue and EPS missed management guidance and analyst estimates. SMCI reported $1.28 billion for fiscal Q3 growth of (5%), which missed guidance of $1.48 billion, at the midpoint. GAAP EPS was $1.53 and Adjusted EPS was $1.71. This compares to management guidance of: “GAAP diluted net income per share of $1.75 to $2.02 and non-GAAP diluted net income per share of $1.88 to $2.14.”

This was Supermicro’s first miss dating back to 2019. Management said the following about the miss: “The shortfall was primarily due to key new component shortages for Supermicro’s new generation server platforms which have been mostly resolved to-date.”

The fiscal Q4 revenue guide was for $1.7B to $1.9B, which is above the $1.64B that analysts were expecting. The EPS forecast form management is for $2.21 to $2.71, compared to analyst expectations of $1.76.

Per the earnings call: “If supply conditions improve sooner, we expect to be above that range, despite some economic headwinds ahead. In other words, I continue to expect our fiscal year 2024 revenue to be at least 20% year-over-year growth and we are accelerating to reach our mid- to-long-term growth objectives of $20 billion per year.”

According to a previous earnings call, the CFO stated: “GPU prices and CPU prices are going up, especially with the new refreshes that are coming out. So we anticipate that [average selling prices] will continue to go up.”

At 20% growth, the company will surpass $8 billion in revenue next fiscal year, ending in June. The FY2025 analyst estimates are for growth of 11%.

Margins:

Server solutions and systems come with thin gross margins. Despite thin margins, Supermicro is a company with strong earnings with EPS of $10.73 for FY2023. Please see below for questions from analysts on the call regarding gross margin.

Gross Margin of 17.6% compares to 15.5% in the year ago quarter. The company stated GM was lower due to product mix and new platform ramps.
GAAP operating margin of 7.7% compares to 6.6% in the year ago quarter. This is lower compared to previous quarters this year in the 9% to 10% range. The company stated it was lower due to lower revenue.
GAAP net margin of 6.7% is up from 5.7% a year ago. This is lower compared to previous quarters this year in the 9% to 10% range.

Cash Flow:

The company reported strong cash flow in the current quarter with a margin of 15.5% for operating cash flow and 14.8% margin on free cash flow. This equals $198 million and $190 million, respectively. There is $362 million on the balance sheet and $187 million in debt.

Notably, the company has lumpy free cash flow with FY2022 and FY2019 ending negative. Here’s a snapshot of the most recent quarters:

Source: Investor Presentation

Supply Chain Issues

According to management, Supermicro’s decline in revenue growth is due to supply chain issues. Per the CFO’s opening remarks:

“Fiscal Q3, 2023 revenues were $1.28 billion, down 5% year-over-year and down 29% quarter-over-quarter, which was below our initial guidance range of $1.42 billion to $1.52 billion. The shortfall was primarily due to key new component shortages for Supermicro’s new generation server platforms which have been mostly resolved to-date.

We note that our shipments against a record backlog may be constrained by supply chain bottlenecks due to high demand for our advanced AI server platforms.”

Supermicro builds complete systems, and the supply chain issues can extend beyond CPUs, GPUs and memory to also include difficulty obtaining metal-oxide-semiconductor field-effect transistors (MOSFETs), diodes and capacitors. If there is low availability with these components, the systems won’t be complete in order to ship. According to The Register, lead times were at 26 weeks back in October compared to the 10-14 weeks that is the target for a healthy supply chain. This is an improvement from 40 weeks a year ago.

Here was another comment on the earnings call:

“These new AI product demands from top-tier companies have led us to challenges in terms of new key components availability.

Compounded with the economic headwind, our Q3 results were reflective of these difficult yet opportune conditions. The good news is that we have already started to address these component shortage pressures over the past few months and we are in a much-improved situation going forward. We have started to produce and ship some back orders since April.”

Risks:

Investors risk entering a frothy AI market. Most tech investors have mastered the extreme exuberance followed by extreme fear that tech seems to oscillate between. We are nearing extreme exuberance on AI with social media exploding over Chat-GPT and Bard. It’s rarely a good sign, and I’m saying that as someone who is exposed to AI-related stocks and benefits from this exuberance. Entering AI stocks right now should be done with a stop in mind.

This company had a short report out earlier this year that caused the stock to selloff. You can read the concerns here.

Regarding fundamentals, the gross margin is the primary concern raised in the earnings calls.

Here was one question from an analyst:

Nehal Chokshi

And what about with respect to gross margin?

David Weigand

Yeah. So, Nehal, we — yeah. Back two years ago, we gave a 17% to 21% — 23% topline growth. Obviously, we’re in there at a minimum of 20%. And for the gross margins, we continue to, like I said, to wrestle with taking market share and also balancing that against gross margins.

But we’re confident with our new manufacturing facilities coming online that we will be able to improve our gross margins. And we also, as we come out of this quarter and we begin to ramp our new product offerings that we will be able to improve margins as well.

Here was another question about the gross margin:

Ananda Baruah:

But I would love to get a better understanding of how you guys are thinking about sort of the gross margin manifestation if we think about the continued layering in of larger footprint, which may come at a slightly lower margin. Is it really that over time, we just expect a greater presence of that lower margin business with some efficiency gains or is it just in the beginning here, the margin will be lower for the new business, but then collectively, the P&L gross margin expands over time?

David Weigand:

Yeah. So we’re looking at it and on — in the — your latter alternative, Ananda, and here’s why. So right now, there’s three things that we’ve been facing. We’re having to face more air transportation costs in order to make our deliveries. So that impacts our margin. And also, we’re having to pay other expedite fees. That impacts our margin.

Number two, we ran a lot less through our factories than in Q3 than we did in Q2. So your margin efficiency, your ability to spread your fixed costs, it’s tremendously impacted on a smaller scale. So as we scale up, we improve our margins.

Thirdly, the — as we ramped our new product offerings, there is an efficiency on these new — on the production of these new products. So we are going to improve the efficiency of these products, which will improve the margin. And so those three things alone speak to margin improvements.

Charles Liang

I can add some color. I mean, as I shared, I mean, we are building a $20 billion of revenue, hopefully in midterm and that’s why a grow our capacity and support a large customer is very important to us. Once our volume becomes higher, our costs will be improved and then business operation efficiency will be higher.

So we are doing better great way to grow our revenue. And so, I mean, once we start to reach that number under $10 billion to $20 billion, I guess, our gross margin will start to grow, because we won’t always invest for big growth after that.

Valuation:

Supermicro has an old school semiconductor top line valuation that reflects its roots as a server maker. Interesting enough, it’s trading at its previous 2015 high. The 5-year median is 0.46 but there’s been too big of a product pivot to rely on this for the future valuation.

On the bottom line, SMCI trades in line with Intel. The bottom line is probably a better gauge for this stock than top line. I took a screenshot with July 2022 marked so you could see where AMD typically trades when it’s not going through a major cyclical event with PCs. It also shows where Intel and SMCI were back in July versus now – about 50% higher valuations.

The 5-year median for SMCI is 15 and has been up to a 20 5-year median in the past.

Conclusion:

The AI market is frothy but we may take a shot at entering. If we stop out, then no big deal. We’d like exposure to Supermicro for its ambitions to overtake the incumbents, plus the clear path the company will take to do so.

Highlights from Google I/O 2023

Posted on May 18, 2023June 30, 2026 by io-fund

Google recently held its annual developer conference Google I/O 2023. Google is a large real estate owner with arguably more data than any other tech company in the world. This advantage cannot be overstated when it comes to training large language models (LLMs). In addition to having a strategic advantage for future development of LLMs with data, Google can offer advertisers instant ROI.

The primary announcements from the event were:

Google drops the waitlist for Bard and announces new features.
Google launches new Large Language Model, PaLM2
Unveils its new AI-powered Search.
Google Cloud announces new A3 supercomputer VMs built to power LLMs.

Google drops the waitlist for Bard and announces new features

Among the more exciting announcements at Google I/O, the company dropped the waitlist for Bard and the chatbot is now available in 180 countries and territories. Bard supports English, Japanese, & Korean languages, and will soon support more than 40 languages. Google is also rolling out features such as better source citations, the ability to export content generated in Gmail and Google Docs, support for more visuals and an upcoming Google Lens integration to analyze pictures and write captions.

Background on Google’s Bard:

Earlier this year, Google’s stock (Alphabet) tumbled 7% when chatbot Bard was unable to complete a search with 100% accuracy. During the demonstration, Bard returned incorrect information about which telescope was the first to take pictures of a planet outside the Earth’s solar system. This was a minor mistake given how far large language models and generative AI has come, rather it was the timing that was a bit flawed as OpenAI’s ChatGPT, the chatbot powering competitor Microsoft Bing, had been dominating headlines since its November 30th launch.

Microsoft, being an opportunist, took it a step further and announced Bing would now be powered by a faster and more accurate version of GPT-3.5 one day after Bard’s failed demonstration: “We’re excited to announce the new Bing is running on a new, next-generation OpenAI large language model that is more powerful than ChatGPT and customized specifically for search. It takes key learnings and advancements from ChatGPT and GPT-3.5 – and it is even faster, more accurate and more capable.”

Both companies have been preparing for this moment for many years. Microsoft invested $1 billion into OpenAI a few years ago with a new $10 billion round announced last month. Meanwhile, Google acquired DeepMind in 2014. Google also previously developed conversational neural language models such as LaMDA, which is used by Google’s Bard for its conversational AI technology.

Despite the mishap with Bard, it would be a human-generated mistake to think Alphabet does not command a place of leadership right now in generative AI. Alphabet was one of the first tech companies to focus and invest on AI and natural language processing (NLP). We pointed out to our premium research members in July of 2022 that ChatGPT is based on transformer architecture that Google initially introduced in 2017 when we said:

“Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.

Sequential text, images and video data are used for self-supervised learning and pattern recognition, which results in more data being used to create better models. Prior to transformer models, labeled datasets had to be used to train neural networks.

Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly.

Google first introduced transformer models in 2017 and transformers are used in Google and Bing Search. Transformers also led to BERT models, which stands for Bidirectional Encoder Representations from Transformers, and is commonly used for text sequences. Transformers are also used in GPT-3 (it’s the T in GPT) which improved from 1.5 billion parameters to 175 billion parameters. GPT-3 has the ability to report on queries it has not been specifically trained on.”

Earlier this month, Google’s CEO, Sundar Pichai, gently reminded the AI community of how cutting edge Google’s research is when he stated, “Transformer research project and our field-defining paper in 2017, as well as our important advances in diffusion models, are now the basis of many of the generative AI applications you're starting to see today.”

BERT was designed to help Google better understand search intent, as despite billions of searches every day, about 15% of those searches are for brand new terms. This prompted Google engineers to develop a model that could self-learn.

The result is that searches results are more accurate by taking into consideration the nuances of language.

Google launches new Large Language Model, PaLM2

Google launched a new Large Language Model, PaLM2, that will power the updated Bard AI chat tool and more than 25 other new products & features including productivity software (Gmail, Google Docs), Healthcare and Security.

PaLM 2 has the following capabilities:

Multilingual: The LLM is trained on more than 100 languages, which increases language proficiency
Reasoning: The LLM’s dataset has improved logic, common sense reasoning and mathematics
Coding: The LLM can generate code including programing languages such as Python, JavaScript and specialized languages such as Prolog, Fortran and Verilog.

Google Unveils its new AI-powered Search

The company has unveiled its new generative AI-powered search that will be subject to a waitlist. Google cites the example of the following search “what's better for a family with kids under 3 and a dog, bryce canyon or arches.” Previously, you had to break the question down into smaller ones, sort through the vast information available, and then put things together yourself. Now with generative AI, search will be able to better understand the question.

Generative AI will also provide a better experience for online shopping by instantly getting relevant information like reviews, images, and ratings. The new shopping experience is based on Google’s Shopping Graph, which has more than 35 billion product listings.

The company announced the ‘About this image’ feature, allowing users to identify fake images. It mentioned in its press release, “When the image and similar images were first indexed by Google, Where it may have first appeared, and Where else it’s been seen online (like on news, social, or fact checking sites)”.

Google launches new Large Language Model, PaLM2

The company launched the new Large Language Model, PaLM2, that will power the updated Bard AI chat tool and more than 25 other new products & features announced during the Google I/O 2023.

Its predecessor PaLM, launched in April 2022, was a 540 billion based parameter, and the company did not provide this detail for PaLM2. PaLM stands for Pathways Language Model. “What we found in our work is that it’s not really the sort of size of model — that the larger is not always better,” DeepMind VP Zoubin Ghahramani said in a press briefing ahead of the announcement. “That’s why we’ve provided a family of models of different sizes. We think that actually parameter count is not really a useful way of thinking about the capabilities of models and capabilities are really to be judged by people using the models and finding out whether they’re useful in the tests that they try to achieve with these models.”

PaLM2 is faster and more efficient than previous models. Some of the improvements highlighted by the company are that PaLM2 is trained for improved multilingual text, spanning over 100 languages, reasoning, and coding, including popular languages like Python & JavaScript. For example, due to the multilingual capabilities of PaLM2, it has helped Bard to expand to new languages. PaLM2 is available in four sizes: Gecko, the smallest, followed by Otter, Bison, and Unicorn. Other use cases include improved Workspace features while working in Gmail, Google Docs, and Google Sheets. PaLM2 can also be used for enterprise use cases like Med-PaLM2 in medical research and Sec-PaLM in cybersecurity.

The company also said that it’s working on a more powerful model called Gemini and it will also be available in various sizes so that it can be easily deployed to various products.

Google Cloud announces new A3 supercomputer VMs built to power LLMs

Google Cloud announced the A3 GPU supercomputer that can be used to train and run Artificial Intelligence and Machine Learning models. While the A3 GPU supercomputer is on a private preview waitlist, the previously announced G2 VMs are now in general availability. The G2 VMs are powered by the new Nvidia L4 Tensor Core GPUs. The company said that it is the first cloud provider to offer these new GPUs for serving generative AI workloads.

The A3 GPU VMs are made of eight Nvidia H100 Hopper architecture GPUs, 3.6 TB/s bisectional bandwidth between A3’s 8 GPUs via the Nvidia NVSwitch and NVLink 4.0, 4th Gen Intel Xeon Scalable processors, and 2TB of host memory.

The A3 supercomputer can deliver up to 26 exaFlops of AI performance, thereby improving the time and cost of training large machine learning models. The A3 workloads will be run on Google’s Jupiter data center networking fabric which the company states “scales to tens of thousands of highly interconnected GPUs and allows for full-bandwidth reconfigurable optical links that can adjust the topology on demand.”

Conclusion:

I would not be surprised if we exit 2023 with a reimagined way to use Search Engines. The iteration cycle here is likely to move quickly compared to AVs or the Metaverse, as there are real-world applications where AI can be applied without safety issues (AVs) or friction in terms of user adoption (Metaverse/VR headsets). Instead, the scale has already been built with Search being a viral, daily activity used by nearly every human on earth. AI advancements will simply improve what is already in place.

Cutting-edge chatbots can be quickly deployed on the search engines that already exist, and this is a substantial difference from other overhyped, early-stage technologies. Their accuracy may still need time, but they're probably not too far off from being deemed “reliable enough.”

Investors should expect that AI will become a winner(s)-take-all market. In time, the difference in how search and other applications operate in terms of user experience plus ROI for advertisers will help carve a larger lead.

Premium Members should check the forum for updates on our timing for an entry into the stock.

Highlights from Google I/O 2023

Posted on May 18, 2023June 30, 2026 by io-fund

The primary announcements from the event were:

Google drops the waitlist for Bard and announces new features.
Google launches new Large Language Model, PaLM2
Unveils its new AI-powered Search.
Google Cloud announces new A3 supercomputer VMs built to power LLMs.

Google drops the waitlist for Bard and announces new features

Background on Google’s Bard:

“Transformers are becoming one of the most popular neural-network models by applying self-attention to detect how data elements in a series influence and depend on one another.

Transformer models eliminate this need by finding patterns between elements mathematically, which substantially opens up what datasets can be used and how quickly.

The result is that searches results are more accurate by taking into consideration the nuances of language.

Google launches new Large Language Model, PaLM2

PaLM 2 has the following capabilities:

Multilingual: The LLM is trained on more than 100 languages, which increases language proficiency
Reasoning: The LLM’s dataset has improved logic, common sense reasoning and mathematics
Coding: The LLM can generate code including programing languages such as Python, JavaScript and specialized languages such as Prolog, Fortran and Verilog.

Google Unveils its new AI-powered Search

Google launches new Large Language Model, PaLM2

The company launched the new Large Language Model, PaLM2, that will power the updated Bard AI chat tool and more than 25 other new products & features announced during the Google I/O 2023.

The company also said that it’s working on a more powerful model called Gemini and it will also be available in various sizes so that it can be easily deployed to various products.

Google Cloud announces new A3 supercomputer VMs built to power LLMs

Conclusion:

Premium Members should check the forum for updates on our timing for an entry into the stock.

Shopify’s New Margin Profile

Posted on May 15, 2023June 30, 2026 by io-fund

Shopify was once a market darling yet has been in the penalty box over its margins for some time. Independent of the market’s very positive reaction to the news, it’s a good idea to revisit Shopify and determine what the new gross margin may look like and also what risks remain. Below is a link to the most recent webinar that details why we are in wait-and-see-mode with Shopify as the technicals are not providing the setup we are looking for right now. However, should we get the right setup, we want to be ready with a clear fundamental outline of what to watch for.

Shopify Over the Past Year:

Shopify greatly benefited from the ecommerce boom during Covid, with revenue rates accelerating to 90%+ growth rates and GAAP operating margins of 12%. Like many management teams, starting in late 2021-2023, Shopify came under pressure for investing in growth. The market was particularly concerned with the company’s investments in distribution, such as the Shopify Fulfillment Network with costs of $1B and the acquisition of Deliverr for $2B.

This acquisition came at a bad time as Deliverr increased stock-based compensation (SBC) when the market was growing concerned with SBC across the board. Stock Based Compensation increased from $151 million in H1 2021 to $257 million in H1 2022. The company stated that SBC plus payroll taxes is at $750 million for the full year. This number was later revised to $575 million for the year.

Shopify Fulfillment Network

In order for Shopify to continue to scale and take on Amazon, Shopify pursued building fulfillment centers to provide two-day shipping to 90% of the US population. This expansion front-loaded costs with management stating they do not expect to recognize the benefits of scale until ~2024.

Furthermore, management explained on previous earnings calls that they expect 100% of their gross profit in 2022 to be reinvested into growth initiatives over the next few years, signaling that OpEx and CapEx will equal gross profit, which will limit earnings growth. Shopify also had stated that it expects to hire more engineers in 2022 compared to 2021, “despite an exceptionally competitive market for top talent.” These expectations for a rise in expenses in the near term, during an inflationary environment caused a landslide in Shopify’s stock price.

Moreover, management left analysts in the dark when questioned about the ROI and payback of its Shopify Fulfillment network (SFN) investments. Specifically, CFO Amy Shapiro responded to an analyst question about SFN payback by stating that “we're not going to get into the details of how we view payback ROI [for SFN]. But what we can assure you is, we've always been strong allocators of capital to the right opportunities to grow the various parts of the business at the right time, and this is no different.”

The market does not like uncertainty and the lack of commentary about the cadence of ROI on its SFN investments also pressured its valuation.

Over time, it became apparent that Deliverr was dilutive to gross margin as management stated the 46% gross margin in Q4 was due to “Shopify Payments and Deliverr.”

Reduction in Capex Costs and 20% Headcount Cuts

Shopify announced plans to layoff 20% of its workforce following a previous announcement the company was reducing 10% of its workforce. This is roughly 3,000 employees.

The company is also selling its logistics business to Flexport for 13% equity. Flexport was last valued at $8 billion so the equity is worth about $1 billion. Shopify acquired 6 River Systems for $450 million and Deliverr for $2 billion, which are part of the equity exchange.

According to Shopify’s management team, the goal for SFN was to spend a total of $1 billion by 2024. Through 2021, the company had spent $117 million. In Q2 of 2022, an analyst asked the Shopify management team if they had plans to exceed the $1 billion investment in Shopify Fulfillment Network and the CFO said there are no plans to expand that amount at this time.

As of Q3, the company had $4.9 billion in cash.

Merchant Solutions Versus Subscription Solutions

Merchant Solutions is a lower margin business at 37.2% gross margin and is 75% of the company’s revenue and is also growing at a higher rate than Subscription Solutions.

In the current quarter, Merchant Solutions was at 31% growth for $1.1B in revenue compared to Subscription Solutions at 11% growth for $382M in revenue. Previously, Shopify had a gross margin in the 55% range. The total gross margin today is 47.5%. The Cost of Goods Sold is 53% of revenue compared to COGS previously of <45% or revenue. Notably, COGS inched upward to the 49% range prior to the Deliverr acquisition closing. This is likely due to Shopify Payments.

The Deliverr acquisition was announced in May of 2022 and was completed in July of 2022. Meanwhile, Shopify reported softer gross margins prior to this date.

My understanding is that Stripe fees and credit card fees weigh on the Shopify Payments business. Per the company: “And within our Shopify Payments business, we continued to see gross margin pressure due to the greater mix of Plus and higher mix of credit cards versus debit cards compared to Q1 last year.”

The company also stated the following about the gross margin in the upcoming quarter: “Q2 gross margin percentage is expected to be similar to our Q1 gross margin percentage with the expected benefit from the pricing changes to be offset by the pending sale of our logistics business and the continued growth of Shopify Payments, which is a lower-margin business.”

Within Merchant Solutions, the lower margin Shopify Payments is a major contributor to the company’s growth: “Q1 Merchant Solutions revenue was $1.1 billion, increasing 31% year-over-year or 33% on a constant currency basis, driven by the increase in GMV, continued penetration of Shopify Payments and the contribution from Deliverr. $27.5 billion of GMV was processed by Shopify Payments in the first quarter, 25% higher than in the first quarter of 2022. The penetration rate of Shopify Payments as a percentage of GMV was 56% for the quarter versus 51% in Q1 of the prior year.”

More on Q1 Earnings Results

Revenue of $1.51B beat estimates by 5% and EPS of $0.01 beat estimates of ($0.04). The company doesn’t offer guidance yet said they expect Q2 to “grow at a similar rate” as Q1 on revenue growth and gross margin to also be similar. That implies revenue growth of 26% in Q2 and gross margin of 48%.

The company expects operating expense dollars, when excluding one-time items related to the planned sales of their logistics business and severance, to decease by mid-single digit percentage compared to operating expenses in the first quarter of 2023.

Notably, analyst consensus is that Shopify exits the year with revenue growth of 16% but with the expectation that Shopify will be profitable on an adjusted basis into the foreseeable future. The last few quarters, adjusted EPS has been negative.

In addition to the news that Shopify is spinning off the Shopify Fulfillment Network and reducing headcount by 20%, the company also reported an acceleration in key metrics.

Primarily, gross merchandise volume (GMV) was up 15% this quarter to $49.6 billion, or 18% on a constant currency basis. This compares to 16% on a CC basis in the year ago quarter.

Gross payments volume also grew to 56% of GMV at $27.58 billion, up from 51% of GMV in the year ago quarter.

The attach rate, which is defined as revenue divided by GMV, was at 3.04% compared to 2.79% in the year ago quarter. This translates to merchants buying more products and solutions from Shopify and was the highest attach rate the company has ever reported.

Will Margins Continue to Improve After Logistics is Sold Off?

Margins this quarter were weaker across the board:

Gross Margin was 48% down from 53% in the year ago quarter
GAAP operating margin of (13%) was down from (8%) in the year ago quarter
Adjusted operating margin of (2%) compares to +3% in the year ago quarter
Adjusted net margin of 1% compares to 2% in the year ago quarter

In the chart above, Shopify’s GAAP operating margins reached (-15%) in Q2 of last year and bottomed out at (-25%) in Q3 before rebounding to (-11%) in Q422 and dipped back down to (-13%) in Q123.

Based on management’s Q2 sales, gross margin and operating expense dollars commentary, we calculated how this could potentially impact GAAP operating Margins next quarter. We came out with a range of between (-10%) to (-5%). The upper end of the range will be reached if Shopify is able to attain its sales target. If so, GAAP operating margins, while still negative, will improve dramatically compared to Q123 if (-5%) is reported.

And if they do, the next question will be if Shopify can reach positive GAAP operating margins in the 2nd half of 2023? To provide some context, the last time these margins were positive was in Q4 of 2021 when it reached +1%.

Despite efforts to reduce operating expense dollars, much of the margin improvement will still be dependent on future sales growth, which is hard to predict given the current macro environment. It will also be dependent on product mix, per the analysis above.

For 2023, the blue sky scenario is if Shopify can hit the upper range of the implied GAAP Operating Margin in Q2 of 2023 and indicate it’s moving closer to positive margins by sometime in 2023/early 2024.

Given the price action post the Q1 earnings release, it appears the potential significant improvement in GAAP operating margins from Q1 to Q2, coupled with the divesture and short covering has likely been reflected in the stock price for the time being.

Cash Flow:

The company had operating cash flow of $100M in the most recent quarter for a margin of 6.6% up from (2.1%) in the year ago quarter.
Free cash flow margin was 5.7% up from (3.4%) in the year ago quarter.
The company has $4.9B in cash with $914M in debt.

Valuation:

Shopify has certainly traded at a higher valuation but not for about a year. The market will need to decide if 2022 valuations are the new norm or if the market can march higher based on historical valuations.

Conclusion:

As stated, the optimism that surrounds the Logistics business being sold off has not addressed the fact that Shopify Payments is a lead contributor to growth and continues to weigh on the gross margin. We will use a blend of fundamentals and technicals to help with our timing as this company is sensitive to the economy due to exposure to consumer spending and small to medium sized business (SMBs).

Please reference the last Advanced webinar here for our buy plan and technical setup.

FAAMG Stocks Trading At Precarious Valuations

Posted on May 15, 2023June 30, 2026 by io-fund

This article was originally published on Forbes on May 10, 2023,07:45am EDTForbes Forbes on May 10, 2023,07:45am EDT

The mega-cap stocks that are known as FAAMG reported earnings recently. These names are driving the market higher, especially Microsoft and Apple. In fact, the percentage of Microsoft and Apple’s combined weighting in the S&P 500 has never been higher.

The S&P 500 weighting is according to market cap, which is price times float. The longer buying happens in these two names, accompanied with selling in other areas of the index, the percentage weighting becomes stretched to unhealthy extremes. This is not characteristic of a burgeoning bull market; instead, it is the type of behavior we usually see at market tops.

Also worth noting, since the February top, we are seeing a strong rotation into Big Tech while aggressive selling is taking place in other areas of the market. Take a look at the market cap weighted NASDAQ-100, which has over40% weighting into the FAAMG stocks, compared to the equal weighted NASDAQ-100.

Source: I/O FUND

While the NASDAQ-100 has made a series of higher highs, led mostly by the FAAMG names, the equal weighted index has made a series of lower highs. We are seeing similar price action in small caps as well as most economically sensitive sectors. This is typically not the sign of a healthy market.

FAAMG Stocks Trading at Precarious Valuations

As you’ll see below, there’s little room in FAAMG valuations compared to their 5-year historic averages. Apple and Microsoft both trade above their 5-year median on the top line and bottom line whereas the others are getting quite close given the low growth rates and macro uncertainty. The only exception is Amazon.

Microsoft is leading on valuation at 10 compared to the FAAMGs that are at 7 or below. Most are within range of their five-year average valuation except Amazon at 2.0 today compared to an average valuation of 3.6.

Source: YCHARTS

Amazon has a P/E ratio of 247.79, compared to 32.96 for Microsoft, 29.22 for Meta, 28.13 for Apple, and 23.32 for Alphabet. The FAAMGs are trading within range of their historical valuation except for Amazon with a five-year average P/E ratio of 93.48.

Source: YCHARTS

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FAAMG Earnings Overview:

There were some puts and takes in the most recent earnings reports. Despite price telling us we could be nearing a top, there are some fundamental signs that FAAMG stocks may be overstretched in the near term.

Below, you’ll find that consensus points toward a bottom for FAAMG stocks yet it will require consensus materializing in the coming quarters in order for the stock price action to hold. In other words, the market has front run the rebound in growth and now we must wait and see if this rebound unfolds.

Alphabet: Search is Resilient

Alphabet’s revenue grew by 2.6% YoY or 6% in constant currency, for a total of $69.8 billion, primarily helped by the resilience in Search and the momentum in Cloud business. Although this is marginal growth, below you can see that Alphabet is expected to accelerate in revenue growth over the next few quarters from 2.6% to an expected 9.4% in Q1 of next year.

Source: SEEKING ALPHA

Operating margins were soft at 25% of revenue compared to 30% last year. Net income declined (8.4%) YoY to $15.1 billion. This resulted in EPS of $1.17 compared to $1.23 for the same period last year.

Source: YCHARTS

The drop in profits was mainly due to $2.6 billion in charges related to the reduction in the company’s workforce and office space, and was offset by $988 million in depreciation from servers and network equipment.

Google Cloud revenue grew by 28% YoY to $7.45 billion and reported its first profitable quarter bringing in $191 million operating income.

Microsoft: Top Line and Bottom Line Beat

Microsoft’s revenue grew 7.1% YoY and 10% in constant currency to $52.9 billion. Management’s revenue guidance for next quarter is $54.85 billion to $55.85 billion, representing YoY growth of 6.7% at the mid-point. Similar to Google, a noticeable acceleration is expected in the second half of the year.

Source: SEEKING ALPHA

Azure grew by 27% and 31% YoY in constant currency and came in at the higher end of management guidance of 30% to 31%.This is down from 38% growth in constant currency last quarter. Next quarter will also mark a deceleration with management guiding to 26.5% in constant currency. This includes 1% from AI services.

Source: I/O FUND

Operating income grew by 9.8% YoY to $22.35 billion. The net profit margin was 34.6% compared to 33.9% in the same period last year which resulted in EPS of $2.45 compared to $2.22 in the same period last year.

Source: YCHARTS

Meta: Back to Positive Growth

The company’s revenue grew by 2.6% YoY and 6% on constant currency to $28.6 billion. This is a positive as Meta’s revenue has declined YoY in the last three quarters.

Management’s revenue guidance for the next quarter is between $29.5 billion to $32 billion, representing a YoY growth of 6.7% at the mid-point. Analysts expect revenue to grow 7% YoY to $30.84 billion.

Source: SEEKING ALPHA

The operating income declined by (15%) YoY to $7.2 billion as total expenses rose 10% YoY. The operating margin was 25% compared to 31% in the same period last year. The net income declined by (24%) YoY to $5.7 billion, resulting in EPS of $2.20 compared to $2.72 in the same period last year.

Source: YCHARTS

The company recorded $1.14 billion in restructuring charges related to layoffs, facilities consolidation, and data center. Excluding these charges, the operating margin would be 4% higher and EPS would be $0.44 higher.

Amazon: AWS is Slowing

The company’s revenue grew by 9.4% and 11% YoY in constant currency to $127.4 billion. Analyst consensus is for growth of 8.2% next quarter.

Source: SEEKING ALPHA

The operating margin was 3.8% compared to 3.2% in the same period last year. Net Income was $3.2 billion or $0.31 per share compared to a net loss of ($3.8) billion or ($0.38) per share in the same period last year.

The net income included a pre-tax valuation loss of ($0.5) billion from the investment in Rivian Automobile compared to a pre-tax valuation loss of ($7.6) billion in the same period last year.

Source: YCHARTS

AWS revenue grew by 16% YoY to $21.4 billion. This is lower than the 20% growth in the December quarter and a remarkable slowdown from the 37% in the same period last year.

Management discussed in the earnings call that April AWS revenue growth further decelerated to 11%. This is due to the ongoing tough macro environment, causing customers to optimize their cloud spending in the recent quarter.

The company’s CEO, Andy Jassy, also highlighted cautiousness in the enterprise customers. “In AWS, what we’re seeing is enterprises continue to be cautious in their spending in this uncertain time. Customers are looking for ways to save money however they can right now. They tell us that most of it is cost optimizing versus cost cutting, which is an interesting distinction because they say they’re cost optimizing to reallocate those resources on new customer experiences.”cost optimizing versus cost cutting, which is an interesting distinction because they say they’re cost optimizing to reallocate those resources on new customer experiences.”

Notably, despite the market rewarding Microsoft’s report, cost optimization is not isolated to one hyperscaler and investors can expect to see more evidence of optimizations in future reports.

Apple: More Buybacks to Appease the Street

Apple’s revenue declined by (2.5%) YoY to $94.84 billion. Management commented that they expect YoY performance to be similar to the March quarter. Analysts expect revenue to decline (1.7%) YoY to $81.53 billion in the next quarter following these comments.

Source: SEEKING ALPHA

iPhone sales grew by 1.5% YoY to $51.3 billion. Mac revenue declined by (31%) YoY to $7.2 billion. iPad revenue declined by (13%) YoY to $6.7 billion. Wearables, home and accessories revenue was flat, and the services segment revenue grew by 5.5% YoY to $20.9 billion.

The operating margin was 29.9% compared to 30.8% in the same period last year. The operating expenses of $13.66 billion were lower than management guidance of $13.7 billion to $13.9 billion, which the market saw as a positive.

Net income declined by (3.4%) YoY to $24.2 billion with a net profit margin of 25.5% compared to 25.7% in the same period last year. EPS came in at $1.52 and remained unchanged from the same period last year.

Source: YCHARTS

Apple returned $23 billion to the shareholders through dividends and equivalents of $3.7 billion and $19.1 billion in share repurchases. The board also authorized an additional $90 billion share repurchase and increased the quarterly dividend by 4% to $0.24 per share.

Analyst Comments:

Deutsche Bank analyst Benjamin Black raised the firm's price target on Alphabet to $125 from $120 and kept a Buy rating on the shares. He noted, “The company reported solid Q1 results with the biggest takeaway being the stabilizing growth trends at Search and YouTube, which beat Street expectations.”stabilizing growth trends at Search and YouTube, which beat Street expectations.”

Wedbush Securities analyst Dan Ives said in a research note. "It's clear that in Redmond's enterprise backyard the company is gaining more market share on the cloud front with many enterprises making this transformational shift on the shoulders of Microsoft,"gaining more market share on the cloud front with many enterprises making this transformational shift on the shoulders of Microsoft," He further said, "Cloud growth and the overall outlook for the June quarter was solid and much better than feared given recent noise in the market and will be music to the ears of investors this morning digesting results."Cloud growth and the overall outlook for the June quarter was solid and much better than feared given recent noise in the market and will be music to the ears of investors this morning digesting results."

BMO analyst Keith Bachman upgraded Microsoft (MSFT) shares to outperform. He stated that he now has "higher conviction" that any headwinds to Azure are likely to moderate by the end of the year, while opportunities in artificial intelligence can help the longer-term. "While the stock is not inexpensive, we think the durable growth opportunities warrant a premium valuation."

RBC Capital analyst Brad Erickson raised the firm's price target on Meta Platforms to $285 from $225 and kept an Outperform rating on the shares. Brad said, “The company's Q1 results were better-than-feared and the simple three-fold bull case – dominating engagement vs. competition, restoring lost signal post-IDFA, and cutting costs – is increasingly coming into view.” RBC believes that further upside is still achievable for Meta on engagement share gains and the ongoing conversion improvement eventually leading to incremental spend.

Citi analyst Ronald Josey raised the firm's price target on Meta Platforms to $315 from $260 and kept a Buy rating on the shares. “With engagement rising, newer advertising products attracting incremental spend, and a more streamlined organization, Meta's momentum in Q1 can continue.”“With engagement rising, newer advertising products attracting incremental spend, and a more streamlined organization, Meta's momentum in Q1 can continue.” the analyst tells investors in a research note.

Conclusion:

We have Buy levels we are targeting for FAAMG stocks, which we share with our premium research members each week as the stocks progress. We believe our target buy levels will set us up for gains in FAAMG stocks when the next bull cycle begins. We provide in depth macro and individual stock analysis so that readers can better understand why we buy/sell. In this market, we frequently take gains.

Right now, we do not believe FAAMG stocks are in a buy zone. Instead, some are trading higher than their 5-year median on valuations despite a weaker macro backdrop and fundamental weakness. The market is front-running the anticipated revenue rebound. Most of this rebound is based off low comps, and there could be soft growth in the future for some of these names.

You can learn more here including information on our next webinar, this Thursday at 4:30 pm Eastern, where we review our positions live.

Equity Analyst Royston Roche contributed to this article.

AI is Not a Buzzword for Nvidia

Why the Market is Bulled Up on Nvidia

The H100 is a Turning Point from Hardware to Software

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

What to Expect in the Upcoming Earnings:

Where Nvidia’s Price Will Go Next:

Conclusion:

Recommended Reading:

Earnings Call:

Conclusion:

Recommended Readings:

Earnings Call:

Conclusion:

Recommended Readings:

Fiscal Q1 Earnings Consensus:

Additional Notes:

The H100 is a Turning Point from Hardware to Software

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

What Levels We Plan to Buy Again

Recommended Reading:

Fiscal Q1 Earnings Consensus:

Additional Notes:

The H100 is a Turning Point from Hardware to Software

Nvidia’s TAM of $600 Billion is Easily and Quickly Achievable

What Levels We Plan to Buy Again

Recommended Reading:

Liquid Cooling

AI Development Platforms

Financials:

Supply Chain Issues

Risks:

Valuation:

Conclusion:

Recommended Reading:

Google drops the waitlist for Bard and announces new features

Background on Google’s Bard:

Google launches new Large Language Model, PaLM2

Google Unveils its new AI-powered Search

Google launches new Large Language Model, PaLM2

Google Cloud announces new A3 supercomputer VMs built to power LLMs

Conclusion:

Recommended Reading:

Google drops the waitlist for Bard and announces new features

Background on Google’s Bard:

Google launches new Large Language Model, PaLM2

Google Unveils its new AI-powered Search

Google launches new Large Language Model, PaLM2

Google Cloud announces new A3 supercomputer VMs built to power LLMs

Conclusion:

Recommended Reading:

Shopify Over the Past Year:

Shopify Fulfillment Network

Reduction in Capex Costs and 20% Headcount Cuts

Merchant Solutions Versus Subscription Solutions

More on Q1 Earnings Results

Will Margins Continue to Improve After Logistics is Sold Off?

Valuation:

Conclusion:

Recommended Reading:

FAAMG Stocks Trading at Precarious Valuations

FAAMG Earnings Overview:

Alphabet: Search is Resilient

Microsoft: Top Line and Bottom Line Beat

Meta: Back to Positive Growth

Amazon: AWS is Slowing

Apple: More Buybacks to Appease the Street

Analyst Comments:

Conclusion:

Recommended Reading: