If you put $10,000 in Apple stock at the

start of the smartphone era, you'd have

over $600,000

today. If you invested that money in

Nvidia [music] when Chat GPT came out

just over 3 years ago, you'd already

have over a hundred grand. My name is

Alex and I spent 8 years [music] as an

electrical engineer and AI researcher at

MIT, which helped me find great stocks

like Nvidia, Micron, and TSMC years

before the rest of the market. And in

this video, I'll show you my top 10

stocks to get rich without getting

lucky. Your time is valuable, so let's

get right into it. Late last year, I

made a video on my top 10 stocks for

2026. But since then, this channel has

grown by close to 100,000 subscribers,

and I've gotten a lot of questions on

which stocks I'm buying, especially with

all the craziness going on in the market

right now. I'm not here to hold you

hostage. So, here's the fullest of

stocks up front. How they're performing

so far this year and their returns

versus the S&P 500 since the whole point

is to get rich without getting lucky.

And that's exactly what's happening with

most of my stocks beating the broader

market by double digits. But it's not

just about picking the right stocks.

It's about how this whole list works

together to be a portfolio that's better

than the sum of its parts. And I'll

explain that as we go along. Also,

accountability is important to me. So, I

have a few simple rules for this list.

Once I pick the stocks, I can't add or

remove them for the entire year. That

way, if I pick a bunch of losers, I

can't just take them off the list and

pretend like it never happened. I also

can't add any winners after they've

already run up. Every stock stays locked

in for the whole year. And I only change

the order based on earnings and the

news. That forces me to make reasonable

predictions about where the stock market

could be headed next. I should also

mention that I'm not a financial

adviser. My AI and engineering

background help me understand the

science behind the stocks, not just

their financials. That's why I only

invest inside my circle of competence.

And I always buy and hold for the long

term, which usually means 3 to 5 years.

But why these stocks specifically? And

are they still good investments today?

Well, that's the point of the rest of

this video. So, let's jump right into

the list. The longer I invest, the more

I believe that every great portfolio

starts with a fund. When I put my money

in the market every month, I put it in

an ETF instead of keeping it in cash.

That way, it grows faster than inflation

and it stays relatively safe since the

funds I pick tend to be well

diversified. Most investors choose a

fund that tracks the S&P 500, like SPY.

But like I've been showing you for years

now, it's actually very simple to beat

the S&P 500. I'm not saying that it's

easy, but it is simple. For example,

just buying the NASDAQ 100 would

outperform the S&P 500 over every single

time frame. But the NASDAQ 100 has a few

issues that might make it the wrong

foundation for a portfolio that's

focused on AI and the chips that power

it. First, it holds stocks that don't

fit the AI theme at all, like Walmart,

Costco, T-Mobile, and Pepsi. Since it

only holds 100 stocks in total, these

companies can really affect the fund's

long-term performance. Second, the

NASDAQ recently changed the rules to let

stocks into the index just 15 trading

days after they go public, while the old

weight was anywhere from 3 months to a

year. SpaceX is eligible to join the

index as early as July 7th, while

companies like OpenAI and Anthropic are

both expected to go public and enter the

index later this fall. All three

companies have valuations measured in

the trillions of dollars, and all three

companies are still unprofitable today.

That's why I've been moving my money

into a fund that lets me have my cake

and eat it, too. Vanguard's information

technology ETF, ticker symbol VGT. VGT

holds over 300 companies, which puts it

right between the NASDAQ 100 and the S&P

500 in terms of diversification. And it

isn't afraid to let its winners ride.

Just Nvidia, Apple, and Microsoft make

up more than 40% of the fund by weight

with other great companies like

Broadcom, Micron, AMD, and Lamb Research

also in the top 10. On top of that, this

fund tracks a completely different index

called the MSCI, USMI information

technology index, which only holds US

stocks in the information technology

sector. Over 80% of the stocks in VGT

focus on hardware, semiconductors,

system software, and applications while

skipping companies like Walmart, Pepsi,

and even the trillion dollar IPOs since

they're not classified as information

technology companies to begin with. And

it even has lower fees than SPY and

Triple Q. So, I'm saving money while

outperforming both indexes by pretty

large margins. That's why VGT is the

foundation for my list of stocks to get

rich without getting lucky. Surprising

no one, the top stock on my list is

Nvidia since they're at the very center

of the entire AI revolution. They make

the chips that every AI model trains on

and have the CUDA software ecosystem

that no competitor can crack. But here's

something that might surprise you.

Nvidia stock is currently trading at a

price to earnings ratio of 31. The last

time it was this cheap was 7 years ago

when it was just $4 per share after

accounting for stock splits. Said

another way, Nvidia stock is cheaper now

than at any point in the entire AI

revolution or in the 3 years before chat

GPT even came out. Talk about a great

way to get rich without getting lucky.

According to Market US, the global

artificial intelligence market is

expected to almost 19x in size over the

next nine years, which is a compound

annual growth rate of 38.5%

through 2034. But many of the companies

building next generation AI applications

are not publicly traded. Think about the

'9s and early 2000s. Companies like

Amazon and Google went public very early

in their growth cycle, but today they're

waiting an average of 10 years or longer

to go public. That means investors like

us can miss out on most of the returns

from the next Amazon, the next Google,

the next Nvidia. That's where VCX comes

in. The sponsor of this video, VCX is

the public ticker for private tech.

Venture capital is usually only for the

ultra wealthy, but VCX by Fundrise gives

everyday investors access to some of the

top private preIPO companies on Earth.

They have an impressive track record

already investing over $500 million in

some of the largest most in demand AI

infrastructure and space launch

companies. So if you want access to some

of the best late stage companies before

they IPO, check out VCX by Fundrise with

my link below today. All right. The

reason I spend so much time going to AI

conferences and interviewing industry

experts all over the world is to

understand how long Nvidia can defend

their massive market share. In my

opinion, this is still the single most

important question in the stock market

today because Wall Street analysts keep

thinking that Nvidia's growth will slow

down and the AI revolution will slow

down with it. We hear the same narrative

every single quarter. The biggest

company on Earth simply can't keep

growing at this pace. And that's true.

Nvidia hasn't been growing at a steady

pace at all. It's actually been

accelerating. Nvidia's revenues grew

year-over-year by 55%, 62%, 73%, and 85%

over the last four quarters. Like I've

been saying for years now, Nvidia will

not get disrupted by another GPU maker

since their hardware and software

ecosystems are already so entrenched.

It'll take a fundamentally different

kind of AI accelerator to chip away at

their customer base one workload at a

time. That's why Broadcom and Google are

also very high on my list. While Nvidia

sells infrastructure for a broad range

of AI applications, their biggest

customers don't want to rely on them

forever. They want specialized chips for

the workloads that they run billions of

times per day. That shift from

generalpurpose GPUs towards custom chips

optimized for specific applications is

the single most important thing that

investors need to watch. Google has

their own AI chip called the tensor

processing unit or TPU. And today it

runs more AI compute than any other

company on Earth. Google is the only

company that owns its entire stack. The

chips, the data centers, the cloud, the

Gemini models, and products and services

used by billions of people around the

world. Google Cloud is now making over

$80 billion a year in revenue. They have

a backlog of almost half a trillion

dollars, and it's growing almost as fast

as Amazon Web Services and Microsoft

Azure put together. As if that wasn't

enough, Google recently started selling

their TPUs to outside customers,

including a deal to sell up to a million

chips to Anthropic, which would be well

over a gawatt of new compute capacity

coming online this year alone. Think

about how confident you have to be to

sell a million of your best AI chips to

the company building the biggest

competitor to your own AI. Google is so

far ahead thanks to their full stack

strategy that they can arm their own

rivals with their best chips and still

win big. But while Google builds custom

chips for themselves, Broadcom builds

them for everybody else, including

Google, Meta, OpenAI, and Anthropic,

making them one of Nvidia's biggest

direct competitors. Broadcom's AI chip

revenue hit 10.8 8 billion last quarter,

which is up 143% year-over-year. And now

they're guiding for over a hundred

billion in AI chip revenue by the end of

2027. Whether the market shifts towards

Nvidia's GPUs, Google's TPUs, or custom

chips made by Broadcom, I win because I

hold all three. And all three companies

have two big things in common. First,

regardless of who designs the chip, it's

built by Taiwan Semiconductor, ticker

symbol TSM. TSMC builds over 90% of all

advanced chips on Earth and around 70%

of the world's chips by revenue. They're

the only company that can make advanced

chips for every side of the chip war at

scale. They make GPUs for Nvidia and for

AMD. They make smartphone processors for

Apple and for Samsung. They make custom

AI chips for Amazon and Microsoft and

Google. TSMC is so far ahead of every

other foundry that they can simply set

the price and customers have to pay

because there's nowhere else for them to

even go. That's why TSMC is always on my

list of stocks to get rich without

getting lucky. The other thing all these

companies have in common is they all

rely on other companies for memory. AI

chips are only as fast as the memory

that supports them. Today, one of the

biggest bottleneck of the entire AI

buildout is high bandwidth memory. Only

three companies on Earth even make it,

and Micron is the only one based in the

United States. Micron's memory is

already pre-sold through the end of

2027, and the memory shortage is

expected to get worse before it gets

better as AI demand keeps increasing.

That's why AI companies are signing

multi-year contracts and prepaying for

chips that aren't even built yet. Memory

is no longer a cyclical commodity.

Micron has a lot of pricing power for

memory chips and AI companies can either

pay up or fall behind. Micron is about

to report earnings right as I'm

recording this. So, let me know in the

comments if you want me to make a deep

dive video on them once we have the

latest numbers. Regardless, while Wall

Street analysts argue over which chip is

faster, TSMC and Micron are getting paid

no matter what. That's another way that

all the stocks on my list work together.

And if you feel I've earned it so far,

consider hitting the like button and

subscribing to the channel. That really

helps me out and it lets me know to make

more content like this. Thanks. Now,

let's keep moving down this list. Every

AI data center also needs power and

cooling. A single Nvidia rack today

pulls around 120 kW. That's around 10

times more than a traditional server

rack. And the Vera Rubin racks that are

currently shipping take over 200 kW of

power. And the power requirements will

keep going up with each new generation.

The old way of wiring data centers

simply can't carry that much current.

Copper starts to melt. So, Nvidia

partnered with Verdive, ticker symbol

VRT, to redesign the entire power

architecture from the ground up. This

redesign moves data centers to 800 volts

of DC power, the same standard that

Nvidia is building to eventually support

1 megawatt racks. And Verdive

co-developed it. Here's why that matters

for investors. Most vendors sell one

piece of the puzzle. either the power or

the cooling, but Verdive sells them both

as a single end-to-end architecture from

the grid to the chip, all optimized to

work together. Companies like Schneider,

Eaton, and Delta are racing to the same

800vt standard. But only Verdiv and

Schneder deliver the full power and

cooling stack as a single system. But

power is only half the problem. A rack

that draws 600 kW builds up a lot of

heat, way more than air cooling can

handle. These racks need direct to chip

liquid cooling and Verdive builds that

too. Every gigawatt scale AI factory

being built right now needs what Vertive

is selling and their backlog shows it.

With orders growing by 250%

year-over-year, which is the fastest

growth in Vertive's history. Before

anyone can order Vertive Systems though,

they need the grid connected power to

run it in the first place. And that's

where IN comes in. Iron has over 4.5

gawatts of secured power across Texas,

Oklahoma, Canada, and Spain. And they're

using that power for AI data centers.

Nvidia itself has a 5-year, $3.4 billion

cloud contract to run their own internal

workloads on Iron's infrastructure. And

as part of that deal, Nvidia took a

warrant to buy $30 million shares of

Iron stock for $70 per share. That only

pays off if Iron trades well above that

price over the next few years. Iron is

currently $49 per share, which implies a

40% upside just to hit Nvidia's strike

price on this stock. Microsoft also

signed a 5-year $9.7 billion deal for

Iron's capacity, and they prepaid for

20% of it upfront. In fact, Iron's $3.4

billion annual recurring revenue target

only uses about 10% of the power that

they already have secured. That means

that they can support 10 times that

number once all their AI infrastructure

is constructed, up and running. And

that's why the stock is so volatile.

Building data centers costs money that I

doesn't have yet. So, they'll need to

keep raising capital to close that gap.

That's a real risk. But it's the same

kind of spending that we're seeing from

AI companies across the board. What

makes Iron special though is they have

by far the most secured power for their

size. And that's exactly why I own it.

All right. So far, we've covered my top

stocks for AI chips and the

infrastructure built around them.

Software sits on top of that

infrastructure, which is why I saved it

for last. Let's start with Meta

Platforms. Meta currently trades at

around 20 times earnings, which is the

lowest multiple in the entire

Magnificent 7. It's cheap because

they're spending between 125 and $145

billion in capex this year alone, which

is close to double what they spent in

2025. But here's the thing. Their family

of apps have over 3.5 billion daily

active users across Facebook, Instagram,

Messenger, and WhatsApp. So, they need

to spend aggressively on AI

infrastructure if they want to serve AI

to almost half the people on the planet.

And while Wall Street analysts see Meta

spending as a risk, they're already

proving that it's worth it. Ad

impressions are up 19%, the average

price per ad is up by 12%, and their

revenues are up by 33% all

yearover-year. So, as the stock keeps

dropping, I'll keep dollar cost

averaging in to this global growth

machine. And we can't talk about growth

machines without talking about

Palanteer, which has been on my list for

3 years in a row now. Palanteer's

revenue grew by 85% year-over-year, and

they raised their fullear guidance to

7.6 billion, which would imply another

71% growth. They also guided for $3.2 2

billion in US commercial revenue, which

would be up 120% year-over-year. So,

this is a profitable pure play AI

software company that's almost doubling

in size every single year. And I expect

that growth to continue because the

global market for AI and software is

expected to almost 7x in size over the

next 7 years, which would be a 32%

compound annual growth rate from now

through 2033. That's about twice the

growth rate of the S&P 500 for 7 years

straight. And Palanteer is positioned to

take a meaningful slice of that growth

with its AI software platforms. This is

what I mean by getting rich without

getting lucky. But we can't talk about

data without talking about security.

Every dollar spent on AI infrastructure,

models, software, or services is a

dollar that's vulnerable to new kinds of

cyber attacks. So cyber security is not

an option. It's just the cost of doing

business. That's why I've been investing

in Crowdstrike, ticker symbol CRWD. The

big reason I like CrowdStrike is their

Falcon platform, which has three parts.

A library of cloud-based modules to do

things like anti virus scans, firewall

management, and protecting against

malware. They have a proprietary threat

graph that tracks the connections

between people, their devices, and the

networks they have access to. Kind of

like Palanteer's ontologies, but

specifically for enterprise networks.

Then they can compare the actual network

traffic against that graph and deal with

any differences as they come up. And

they do that with the Falcon agent,

which is the third part of their

platform. This Falcon agent is a tiny

piece of software that runs on every

device to send data back to CrowdStrike,

so they know when it's time to run the

different cloud modules and update their

threat graph. The global cloud security

market is expected to more than triple

in size over the next 6 years, and

that's before accounting for AI enabled

cyber threats. So, I expect the cyber

security industry to grow even faster

than that with CrowdStrike in a great

position to capture a lot of that

growth. Like I mentioned earlier, I've

been traveling to many different AI

conferences. So, I haven't been doing a

good job keeping up with this list, but

after 6 months, I still feel great about

the whole thing, the stocks, the order,

and the list's overall performance. And

now that conference season is over, I'll

be covering these stocks a lot more

going forward. So, let me know if you

want me to make an updated deep dive

video on any one of them. And if you

want to see what else I'm buying to get

rich without getting lucky, check out

this video next. Either way, thanks for

watching and until next time, this is

Tickerol U. My name is Alex, reminding

you that the best investment you can

make is in you.