Special Report: 3 AI Stocks To Own Now

Is AI a bubble? 

It’s tough to get a straight answer. Wall Street is probably happy to let individual investors think AI stocks are a bubble…

That way you stay on the sidelines and watch these AI stocks move higher and higher until you can’t stand it anymore…

Because Wall Street knows that the so-called “fear of missing out” (FOMO) will eventually wear you down. And that when the average investor succumbs to FOMO and starts buying in, that’s a good sign that it’s time for them to get out.

These tech CEOs, hedge fund managers, and investment bankers – they’re part of the same club. They went to the same boarding schools, sit at the same tables at $ 5,000-a-plate fundraisers and they all have each other on speed dial.

So you can bet your boots they knew Nvidia (NASDAQ: NVDA) would be crushing earnings estimates over the last year. 

Maybe they didn’t have the inside earnings scoop down to the exact penny. And they probably don’t have a copy of the spreadsheet from the CFO tucked in a drawer…

But they knew.

And they also knew the stock price would surge…

So, the purpose of this Special Report is to explore the AI investment opportunity for individual investors. Because there are still homerun stocks that can make you money…

AI First Wave: Infrastructure 

Artificial Intelligence (AI) is virtually synonymous with the “Big Data” you’ve heard about for years. AI simply refers to computer programs that can “read” through massive amounts of data, interpret it, and generate meaningful conclusions, suggestions, or content in the blink of an eye.

There are, according to expert AI analyst Dan Ives, 4 waves of this AI adoption. They are: 

* First and current wave: Cloud, hyperscalers, and AI startups infrastructure build.

* Second wave: Enterprise generative applications (aka Copilot)

* Third wave: The largest wave, heavy industries that benefit from generative AI.

* Fourth wave: Sovereign AI. Countries that want AI for their intelligence and culture.

Ives goes on to say that we are 25% through the first infrastructure wave. 

That is, upgrading data centers like Amazon Web Services Microsoft’s Azure, and all the other data centers out there so they can handle the stupid amount of data that’s coming down the pike. 

Nvidia’s powerful Graphic Processor Units (GPU) are the very best at handling AI. That’s why demand for its chips – especially the H100 model – is so strong. AMD (NYSE: AMD) shares are surging higher for the same reason. 

Nvidia outsources its chip manufacturing to Taiwan Semiconductor (NYSE: TSM). And Taiwan Semi’s capacity is maxed out. It’s expanding capacity as fast as it can to meet demand. Nvidia is reportedly turning to Intel for help with production expansion.

Data center servers are another important aspect of AI infrastructure. The AI server market itself generated $30 billion in revenue in 2023. Foxconn Chairman Liu Yangwei says that the AI server market will hit $150 billion in 2027. 

Super Micro Computer (NASDAQ: SMIC) has attracted a lot of attention as one of the primary assembling the Nvidia-powered servers that are transforming data centers like Amazon Web Services and Microsoft’s Azure. 

Now, we’ve seen infrastructure builds like this before — railroads, telegraph, broadcast networks, long-distance telephone, the internet, mobile networks…

Pay attention to those historical precedents. Because every time, there were winners and there were losers. Every time, some investments paid off, others didn’t… 

And every time, unimaginable capabilities emerged. Every time, we’ve looked back and wondered how people ever get along without this?   

AI Second Wave: Applications

Of course, AI applications are already being built and used. Microsoft has invested $13 billion to get exclusive use of the ChatGPT application. 

Meta (NASDAQ: META) CEO Mark Zuckerberg boasts that he will have 350,000 of Nvidia’s best chip, the H100 at $30,000 each, by the end of this year. Throw in chips from other companies, like AMD (NYSE: AMD, and it’s estimated Meta will own 600,000 GPUs (graphic processor units, the kind of chip ideal for AI).

What’s he gonna do with all those chips? 

Meta is a really interesting case. Because the company won’t use Azure or AWS – it’s building its own AI-worthy data centers. Plus, Facebook, Instagram, and WhatsApp give Meta a massive base of potential users for the AI applications it rolls out. 

What’s Meta gonna do with all those chips? Probably make a lot of money…

And it’s likely that AI will start showing up as a money-maker for non-tech companies pretty soon…

Microsoft says that half of the companies in the Fortune 500 are Azure AI customers (Azure AI is Microsoft’s cloud hosting business, with the addition of AI applications). 

“Regular” economy stocks like CarMax (NYSE: KMX) and Coca-cola (NYSE: KO) have started dabbling with AI, using it for some customer service and marketing. 

Last year, Coca-cola used Azure AI to help formulate a new version of Coke called Y3000. The new formulation was mostly a gimmick, the company asked people to describe what they think Coke might taste like in the year 3000 and then used AI to create it. 

Is AI a Bubble?

So back to the question: is AI a bubble? The quick answer is: not yet. 

Because there’s not really a very big difference between an “emerging investment trend” and a “bubble.” An emerging investment trend occurs when some new product or innovation spurs investment by companies to take advantage of the innovation, which in turn spurs investors to buy stock, with the expectation that revenue and profits will grow. 

A bubble occurs when those expectations become unrealistic. 

For instance, we might not think that something as grounded in reality as oil production had bubble potential, but it did. When Saudi Arabia flooded the market with oil in 2014-2015, the Shale Oil bubble popped. Oil prices cratered, huge sums spent on leases became unsustainable, over 100 U.S. oil companies went bankrupt…

It was unrealistic expectations for oil prices that made the Shale Revolution a bubble. 

At some point, price will be the thing that exposes unrealistic expectations for AI. The point is, once a company like Coca-cola is paying for Azure AI (or the Amazon Web Services equivalent) the ways they can use it for various marketing ideas is limitless. 

Tech companies have their AI strategies in place. Fortune 500 companies are experimenting with their AI strategies right now. As an investor, do you have an AI plan? If not, you should. And soon. AI is not going to wait…

The uses will expand, and companies will see productivity gains and improved profit margins. The stock market will go higher. Then at some point, the payoff of AI will fade. Companies will cut AI spending to maintain profit margins…

That’s when we’ll find out there were some unrealistic expectations for AI… and it’s most likely a few years from now. 

3 AI Stocks to Own Now

Snowflake (NASDAQ: SNOW)

That said, one must interpret all that data in a way that is useful.  The number one company that manages data is Snowflake Inc.

Here is the company blurb from Yahoo!

“Snowflake Inc. provides a cloud-based data platform for various organizations in the United States and internationally. Its platform offers Data Cloud, which enables customers to consolidate data into a single source of truth to drive meaningful business insights, build data-driven applications, and share data and data products. The company was formerly known as Snowflake Computing, Inc. and changed its name to Snowflake Inc. in April 2019. Snowflake Inc. was incorporated in 2012 and is based in Bozeman, Montana.”

Big Data is Big Business

Gartner Market Research is the gold standard for software reviews.  If you make the top right of the Gartner quadrant it means that CIOs and other IT professionals can go to their board and say look, Snowflake is the best of breed.  It is well worth the millions of dollars it will cost to get it.

Snowflake is in the top right quadrant with the big boys and is the only pure-play you can buy.  

3 AI report Image 1

Right now Gartner is saying that cloud application spending will surpass traditional IT spending for the first time this year.

They write: “Spending for cloud applications (Software as a Service) will reach $244 billion this year, up nearly 19 percent from 2023, and by 2028 70 percent of IT workloads will run in cloud environments.

Businesses and organizations are rapidly adopting cloud software of all types including ERP and CRM software, collaboration and communications systems, data management and analytics platforms, and AI and application development tools.”

Snowflake is a data warehousing company.  The company provides cloud-based data analytics and storage. 

The company went public in September 2020 and saw its share price go from $120 to $385 in just a few months.  In the latest quarter, Snowflake made $734.2 million in revenue, up 32% year over year.  Granted, this growth has slowed from the 100% plus of a few years ago but it is solid repeat customers who are paying up.

At the end of the quarter, Snowflake had 436 customers who spent at least $1 million with the company in the trailing 12 months. That’s a jump of 52% from the same quarter last year.  

Big customers with big spending tend to stick around.  Furthermore, Snowflake benefits from scale.  Its product margin was 78.3% in the third quarter, an increase from 74.6% the previous year.

Those are huge margins, the type Apple (AAPL) used to get back in the day.

Don’t get me wrong.  Even at half-off its all all-time high, Snowflake isn’t cheap.  They have yet to turn a profit, though they project $10 billion in revenue by 2029.

What you are buying is growth and the AI story.  Snowflake projects that it can grow at 30% a year for the next five years.  They will likely do better.  As interest rates come down and companies have to answer the AI question they will spend more on data management.

Why You Should Buy Now

I want to own a part of the AI story behind Microsoft and Amazon whose AI segments won’t move the needle like they will with Snowflake.  

And this three-year chart provided the catalyst to buy:

3 AI Image 2

Snowflake went public in 2020, hit a double top, and then got cut in half.  The last two years it has been consolidating.  This chart pattern is known as a “coiled spring” pattern.  It just broke out and everything being equal you want to buy the breakout on companies you like.

The rule of thumb tells us that it will go higher as much as it went sideways.  That would put it at about $450 a share though it would have to get through that double top at $400 first.  

Snowflake just sold off after reporting earnings, even though the company beat on both top and bottom lines.  In fact, they reported a great quarter.  

So why did the stock faceplant?  For two reasons, the CEO, Frank Slootman, who has been at the helm for the last five years is moving on to become the chairman.

The stock market hates change and when a CEO, or a CFO leaves a company the immediate thought is that someone is cooking the books.  This reaction is usually wrong as it is in this case.  

The second reason for the selloff is that the company guided forward earnings growth downward.  

But it sounds to me like the old Wall Street game of lower expectations so that the new CEO can beat them handily.  AI is booming right now and Snowflake is right in the center of it.  They are hiring 1,000 people and you’re telling me growth is going to slow from 38% to 27%? 

The drop in the stock price to $180 creates an excellent opportunity.


Intel is turning it around, and quickly. You should pay attention…

Because Nvidia’s primary supplier, Taiwan Semiconductor, doesn’t have enough capacity to make all of the high-end H100 AI chips that Nvidia can sell, Nvidia is bringing Intel into the fold. 

Today’s semiconductor fabrication is still similar to what it was when Intel started back in the 1970s. You make a big silicon wafer, etch a bunch of circuits on it, embed some transistors and then you cut the wafer up into individual chips. Only now, you can etch circuits that are 3 nanometers wide, transistors are so small you can put billions of them on one chip, and the ultimate performance of a GPU like Nvidia’s H100 processor comes down to how you package it all together.

It’s called “advanced packaging” and Intel can actually do it. And because Taiwan Semi is maxed out on its packaging capacity, Intel is taking over as much as 10% of Nvidia’s advanced packaging needs. That’s what you call a foot in the door. And maybe with a little sweet talk, Intel can get some more business from Nvidia, or maybe AMD will take notice of Intel’s packaging capability… 

But that’s not all…

Going Dutch 

The main reason for Intel’s fall from grace came a decade or so ago, when Intel declined to buy next-generation lithography machines from ASML (NASDAQ: AMSL). Lithography is the process by which circuits are etched on silicon wafers. The smaller the circuit, the more you can put on a chip to make them smaller, faster, and energy efficient. 

Taiwan Semiconductor (NYSE: TSM) jumped on the newest generation of ASML lithography machines, got ahead of the current chip cycle, and left Intel in its dust. The two companies diverged in 2020 – Taiwan Semi’s market cap has tripled to $670 billion. Intel’s market cap has fallen ~25%…

It appears that Intel learned something. I understand that Intel is first in line to buy ASML’s newest lithography machines. This gives Intel the opportunity to get a head start on the next chip cycle and actually become competitive with Taiwan Semi. 

Amazon (NASDAQ: AMZN) and Microsoft (NASDAQ: MSFT) eclipsed their Y2K internet bubble highs years ago. Intel came close back in 2020, right before its mistakes became evident.

A year ago, Intel’s earnings were about to get cut in half. But now, earnings for fiscal 2025 (which starts in June) are expected to jump 65%. 

Intel’s turnaround is compelling. A run at those all-time highs up around $73 could be coming this year. 

Symbotic (NASDAQ: SYM) 

There’s a well-established pattern for secondary offerings. First the secondary is announced and the stock price falls. Then the pricing of the secondary is announced and the stock price adjusts to near the offering price. The stock remains at the offering until it is completed, and then the stock often rallies. 

Symbotic provides AI driven software and robotics that automate the unpacking and repacking of pallets at distribution centers. So when a Duke’s mayonnaise truck comes to a distribution center, Symbotic powered robots unload and unpack pallets of mayonnaise, store them and then repack pallets with mayonnaise and other goods with the same ultimate destination, and send them on their way. (Videos of the system in action are pretty impressive https://www.symbotic.com/symbotic-system/how-it-works/).

Symbotic is expected to grow revenue from $1.74 billion in fiscal 2024 (which ends June 1) to $2.48 billion in fiscal 2025. That’s pretty good, it should be turning a $0.53 share profit next year too. 

Right now, 88% of revenue comes from Walmart, (NYSE: WMT), who also owns 11% of the company. Other major customers are Albertsons (NYSE: ACI) and Target (NYSE: TGT). Symbotic has 15 systems up and running, and 37 more in various stages of deployment. Backlog stands at $23 billion.

Last Wednesday, February 21, at 4 pm, Symbotic announced a 10 million share stock offering. Four hours later, at 8 pm, another press release revealed the pricing: $40.50 a share.  

That’s as quick a turnaround from announcing a secondary to pricing one as I’ve ever seen. The stock closed at $39.68 the next day, which was Thursday, February 22. It closed at $40.40 on Friday, February 23.

Over the last year, Symbotic has traded as low as $14 and as high as $64. $40 looks like a good entry point. 

Brit Ryle,

Senior Analyst, Outsider Club

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