Kris’ note: He’s pounded the table on this idea since he joined the Legacy Research team last June.
His name is Colin Tedards, and he’s the man behind our flagship tech investing publications, including the Near Future Report.
Your editor first met Colin during the process to bring him onboard. We were impressed by this natural enthusiasm. By his entrepreneurialism.
And by his belief that America offers investors the single best opportunity to profit from technological innovation.
In today’s guest essay, Colin looks deeper inside one of the most important (and controversial) topics, artificial intelligence (AI).
AI isn’t a new story. But the technology that’s behind it is improving and changing all the time. In the essay that follows, Colin will show you where some of those biggest changes are coming from, and what you can do to take part in this booming trend…
The S&P 500 closed up 0.8% to end the day at 4,927.94… the NASDAQ gained 1.1% to close at 15,628.04.
In commodities, West Texas Intermediate crude oil trades at $76.95, down $1.28…
Gold is $2,031 per troy ounce, up $13…
And bitcoin is $43,136, up $1,189 since Friday.
Now, we turn things over to Colin…
If you have $10 billion lying around, Sam Altman would like a word.
Altman is the CEO of OpenAI, the creator of the largest artificial intelligence (“AI”) platform, ChatGPT.
Last November, OpenAI’s board gave him the boot for not focusing on AI. Instead, he was jet-setting in hopes of finding investors to help him build semiconductor plants.
That’s not a small undertaking. Cutting-edge chipmaking plants cost billions of dollars and take years to build out. That’s why Altman was speaking with the likes of SoftBank and Abu Dhabi-based G42.
But Altman was brought back on as CEO of OpenAI. And last week, Bloomberg reported that he’s back on the hunt for billions in funding.
Altman and I both see the sheer demand that AI will have for advanced chips. As an investor, you should be paying attention, too.
Advanced chips are almost impossibly complex. We can count the number of companies that can build these chips with just one hand.
And AI has given the companies that make these chips a near license to print money. Elon Musk even said that he’ll buy as many as can be delivered.
Today, I’m going to share why Altman is on the right path… and how we can profit from it.
Making AI Possible
Cutting-edge chips are truly a marvel of engineering.
The individual chips are made from wafers… And a single wafer is made up of hundreds of smaller chips – the little squares on its surface.
A finished wafer from TSMC
(Source: Taiwan Semiconductor Manufacturing Co., LTD)
Each wafer is made of dozens of layers. And each layer is etched and then sandwiched together.
Billions of transistors are etched onto each chip… And every single one has to work for the highest-end chips.
It’s these high-end chips that are the hardest to make.
But to make better chips, the transistors need to get smaller.
During the 1990s, cutting-edge chips had transistors that were 350 nanometers (nm).
Advanced chips such as Nvidia’s H100 use 3 nm transistors.
The realm of 3 nm plunges us into dimensions that are harder to grasp. A single strand of hair is 80,000 to 100,000 nanometers wide.
A single silicon atom has a size of about 0.2 nm. So, 3 nm is about the width of 15 silicon atoms lined up, side by side.
As you can imagine, it’s extremely difficult to etch something that small.
But that’s what extreme ultraviolet (EUV) machines are built for…
To start with, the machine blasts particles of molten tin with a laser.
EUV machine firing lasers and droplets of molten tin (Source: CNBC)
This constant stream of tin reacts with the laser and emits EUV rays.
The wavelengths of these rays are so small they’re even absorbed by air. This machine has to operate in a perfect vacuum.
It then uses the world’s flattest mirrors to redirect the EUV light to the wafer.
EUV light being redirected at the wafer using mirrors (Source: CNBC)
The beams of light are held steady, and the wafer is moved to allow the etching to occur.
Each wafer has hundreds of chips. And each chip has billions of transistors.
These machines can make up to 3,000 wafers per day.
Here’s a clip of the entire process…
An EUV machine at work (Source: CNBC)
These EUV machines cost more than $200 million and are the length of a school bus.
The finished product is transported by three 737 airplanes and 20 semi-trucks to their final destination.
And housing these machines is even more expensive. While a basic semiconductor plant making chips for TVs and appliances might cost a few hundred million… a state-of-the-art facility will cost billions and take years to build.
That’s why Altman isn’t wasting any time trying to realize his ambitions for more chip plants.
Can’t Keep Up
Last week, Taiwan Semiconductor Manufacturing Company (TSMC) announced its latest earnings.
I won’t bog you down with the nitty-gritty details… The major takeaway is that demand for these advanced 3 nm chips is through the roof. Here’s a statement from TSMC’s CEO, C.C. Wei
We expect revenue from our 3-nanometer technology to more than triple in 2024… and are confident that our 3-nanometer family will be another large and long-lasting node for TSMC.
AI models need to be supported by more powerful semiconductor hardware, which requires the use of the most advanced semiconductor process technologies.
TSMC is the biggest maker of 3 nm chips. It makes Nvidia’s H100 and AMD’s MI300x – the most advanced chips on the market.
But even it won’t be able to keep up with the demand for AI chips.
According to multiple market research companies, AI chip demand is expected to grow by 40% per year to nearly $300 billion by 2030.
Altman realizes that even market leaders like TSMC can’t keep up with demand. That’s why he’s raising money now to build the manufacturing capacity for 2030.
I’ve curated my top picks for semiconductor makers in my Near Future Report advisory. They’re already up an average of 64%… But it’s not too late to get in.
And if you’re not already subscribed, you can go here to check out my presentation on how to profit from AI.
Editor, The Bleeding Edge
Report Card Reminder
Just a reminder, last Friday we published part one of the first-ever Legacy Research Annual Report Card.
We reviewed the seven entry-level publications we help publish. Grades ranged from an A+ to a D.
To find out which service got what, go here.
If You’re So Good…
Folks will often ask him, “If you’re so good, why don’t you just do it yourself and not tell anyone?”
It’s a common question put to those of us in the financial newsletter industry.
The answer our new expert gives is that he “enjoys helping regular investors make money.”
It’s a story we’ve heard from some of the other experts we work with. Most of them have spent years, often decades, working in private wealth… hedge funds… specialist brokerages.
But at some point in their career, they think to themselves, “I’m helping this guy who’s worth $500 million make another million… what does it matter?”
But if you can help someone worth $250,000 make another $25,000 or $50,000 or $100,000… that does matter.
As for the expert – don’t worry, we’ll reveal him soon – not only does he come to us with a first-class trading background (we shared examples of some of his biggest wins last week), but he’s an entrepreneur with a lot of business sense too.
For instance, in the 1990s he developed a wireless trading system. You can see the framed newspaper spread from the Wall Street Journal below… held by our “mystery” expert during a recent Zoom call with him:
He also built an options trading and training company that he eventually sold to the largest online trading platform for $20 million… he then bought it back from that same firm a few years later for less than a penny on the dollar!
We’ll share more of this expert’s background over the next few days. And if you haven’t figured out who he is already, we hope to be able to reveal his identity next week.
We’re looking forward to him joining us, and we’re looking forward to sharing his experience and knowledge with you.
Today’s top gaining ETFs…
Invesco Dorsey Wright Healthcare Momentum ETF (PTH) +3%
Invesco Dorsey Wright Technology Momentum ETF (PTF) +2.6%
Invesco Dorsey Wright SmallCap Momentum ETF (DWAS) +2.2%
Alpha Architect U.S. Quantitative Momentum ETF (QMOM) +2.1%
First Trust RBA American Industrial RenaissanceTM ETF (AIRR) +2.1%
Today’s biggest losing ETFs…
VanEck ChiNext ETF (CNXT) -4.2%
Invesco China Technology ETF (CQQQ) -3.2%
KraneShares MSCI All China Health Care Index ETF (KURE) -3.1%
KraneShares MSCI China Clean Technology ETF (KGRN) -3%
Global X MSCI China Consumer Discretionary ETF (CHIQ) -2.7%
If you have any questions or comments for our experts here at Legacy Research, we’d love to hear from you.
Write to us at [email protected] and just type “Daily Cut mailbag” in the subject line.
Editor, The Daily Cut