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00:00 Episode Overview
02:00 The Market Recovery
14:00 Netflix Earnings
15:30 Amazon Buys Satellite Company
16:28 Analysts Turn Bullish On Meta
27:00 Jensen Says Amazon Is Lying
37:00 Fail Of The Week: Allbirds Goes to AI
39:45 New Qualtrim Feature
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The stock market is racing back up to all time highs.
The S&P 500 has basically entirely recovered.
And it's done so in just a couple of weeks.
From March 30th to today, the S&P 500 is up 11%, it continues racing upwards.
The QQQs up even more, currently up around 14%.
My portfolio and stocks are racing up as well.
We've erased all the losses for this year, and the future looks bright.
Now we're going to be going through why the market is recovering.
Why stocks are going up, even though the straight of her moves is closed.
Even though we're still in Iran, things aren't settled.
It's still just as bad as it was before or possibly even worse.
So why is the market ignoring this? We'll be discussing it.
We'll also be going over which companies I bought during this dip.
We'll be looking at all my biggest buys going back throughout this year,
as well as which companies I still believe there's value to be had.
Which companies I think overall are the best buys today.
We'll also be looking at a Tom Lee update.
We have his thoughts on this market recovery.
Why he thinks it's a better time now than ever to invest.
Amazon just purchased global star for $11.6 billion.
And we have the analysts finally catching up with meta.
They're starting to become bullish.
They're starting to turn the negative sentiment to the positive.
We'll be going through a Deutsche Bank write up on meta.
Now we also have Jensen acting as a wartime CEO.
He's going on the offensive.
He recently went on an interview where he challenged Google.
And he challenged Amazon directly.
He says, prove it.
Prove it that your stuff saves so much money.
He also went in a battle trying to justify why Nvidia should be able to sell to China.
This got a little bit tense in this interview.
We'll be looking over this, as well as we'll be looking at the disagreement
between Jensen and Andy Jassy.
Jassy says that they're very efficient,
and that training will eventually replace a lot of Nvidia.
And Jensen says not so fast.
He claims it's all false.
He basically calls Jassy a liar and says to prove it.
So we'll be going point by point through some of this interview.
In fact, checking of who's right and who's wrong.
And then for the fail of the week, we have the story of all birds, a shoe company.
They sold off their shoe business and they pivoted into AI and the stock went up like 700%.
Is this evidence that we're in a bubble or is it a 200 IQ move?
We'll be discussing.
And then finally, after all of that, I want to show you something that I've been working on.
It's recently released and it's called Qualtrum Studio.
It's basically a Netflix for investors.
This is all exclusive content on Qualtrum and I basically built a Netflix.
I'll show you what this is, how we built it, and the reason that we did it.
Give you a little bit of behind the scenes.
So we have a jam-packed episode to get into.
Let's go ahead and get started.
Now starting off, we get into the recovery this year.
We've had an incredible rebound with the S&P 500 going up big since March 30th.
It's basically been straight up, same with the QQQ.
Now, one interesting thing about this is we've seen this massive recovery,
but software stocks don't seem to be having the same luck.
If we look at software, it paints a different picture.
Software is down much more than the average of the market.
And this is shown in the software ETFs.
This also includes Microsoft, which is a bigger kind of mixed software company.
This would look even worse if it was purely software,
like the Adobe's and the Salesforce type of companies.
But regardless, it's down 30%.
This year, it's had no such recovery.
It's still down 18% year to date.
So while the S&P 500 is at all-time highs,
while the QQQ is at all-time highs, software remains in the gutter.
It is still sold off, and it's not seeing this sharp of a recovery, at least not yet.
And I believe the reason for that is the characterization of this cell-off and of the different risks.
For example, one of the reasons that I remained bullish throughout this year,
even through the Iran conflict, even as bad as that looked,
with oil prices going higher, with the US getting involved with another war,
with the potential for it spiraling out of control.
And every single concern that comes along with any type of conflict,
I remained bullish specifically because of the nature of the threat.
As an investor, you have to look past the headline news.
CNN and the New York Times and any type of mainstream media
will always try to make everything seem as scary as possible.
And although war is threatening and scary, it's not fun.
I wish there were no wars.
As an investor, I have to look at the relative risk to my investments.
When I looked at the Iran war, the risk is almost certainly temporary.
Now, it can be a long temporary.
It could affect oil prices, which can affect the economy.
It can affect sentiment, which can affect pricing of companies.
But all of that is inherently temporary.
War with Iran is not going to change Amazon.
It's not going to change meta.
These companies are not pivoting their businesses because of Iran.
They're just not doing anything differently.
They're operating as normal, generating cash flows.
Sure, oil goes up and down a little bit.
But overall, the businesses that I invest in
are not fundamentally changed at all.
Any type of outcome from an Iran war is inherently temporary.
They won't be top of mind in 10 years.
Most of us will look back and will be focused on other things.
This will be something in the past.
So when I looked at the war with Iran, I kept believing
that this is a buying opportunity, even as small as it is.
Now, this was never the biggest dip.
We're only down 9%.
But this is why I made videos during this time period to buy the dip.
Was because I did not believe that this was an intrinsic problem for companies.
I did not believe it would fundamentally change the investments that I invest in.
Wars typically don't do that.
Even bad ones.
Even ones much worse than the war with Iran.
So looking at this, I assessed it to be temporary, even if it's a long temporary.
Then we get to the other side of the story.
We look at software stocks.
Software is in a much bigger sell-off,
and I've had a much more careful, cautious tone around software.
Now, artificial intelligence in terms of just human nature
is likely not as scary as a war.
War is probably scarier than AI.
I don't know, maybe it's not,
but it seems like war is a more pressing, scary thing in the news
than new technology.
But in terms of investment risk,
the risk of artificial intelligence
changing a business model of a company
is significantly higher than a war,
significantly more disruptive.
And there is far greater chance that AI will fundamentally change
the business models of many software companies.
In fact, I believe there's a much higher probability,
a very good chance that artificial intelligence
will permanently damage the earnings of many software companies.
That is why when I look at IGV,
the sell-off, I believe, is far more extensive.
It's a far deeper sell-off.
And I believe it's going to take a lot longer to recover.
Now, eventually it could recover,
especially if software companies prove to be very profitable
and robust against AI,
especially if they're able to leverage AI
and use it further, they're good.
But overall, the risk is there.
AI presents a fundamental intrinsic risk
to the business model of every company.
So in terms of risk factors to investors,
I believe that the war with Iran has always been a lesser risk
by far than the software risk from AI.
They present fundamentally different pressures on companies
and one of them is short-term, one of them is long-term.
When I look at this with my portfolio,
I've had far greater respect
for the potential damage of artificial intelligence
than I have of any type of conflict around the world.
For example, looking at the stocks that I own,
I own very few software stocks.
There's very few that I could characterize as software.
In fact, one of the only companies that I own
that software is into it,
and it's one of the only investments I have
that's actively doing very poor.
Most companies that I'm invested in
are doing much better than this one.
But with the huge majority of my portfolio,
position in the companies that I believe are AI proof,
I feel very bullish going forward.
Now, looking at my recent purchases,
we'll go through just a couple.
I can highlight a few of them here.
Now, on February 17th, I bought $11,000 of S&P global,
so this stock was falling a little bit,
not a ton, but it was falling a little bit.
I bought it at $415.
I bought more of it at around the same price,
another $6,000 worth at $412.
Now, looking at it today, it went from $415 to $438,
which is a nice little move up, but it's not much.
So this is a good buy, I guess it's in the green,
but it's not a crazy one.
In March 13th, I bought $3,300 worth of meta
at a share price of $6,13.
Now, we look at meta today, we can bring meta.
Meta is currently at $676.
So this is another one that's in the green a little bit,
50, 60 bucks, nothing big.
We look at meta again, and I bought another $4,000 of it.
This time at March 27th, at $536.
So this was a good buy.
I should have bought more meta when it went down to this price,
but it's hard, I only have so much cash on hand
at one given time.
Regardless, buying $4,000 at $536 was one of the better buys this year.
We look at Netflix.
In January 26th, I bought $5,000 worth of Netflix at $85.
Now, what is Netflix trading at today?
It's gotta be much higher than that.
I believe Netflix is well above $100.
Yeah, it's up now to 110.
So obviously, a lot of people were very bearish on Netflix.
They're like, oh no, the stock is gonna be wrapped up
with this HBO merger for the next three years in the DOJ.
The earnings reports are gonna be a mess.
It really dissuaded investors.
I didn't care about that.
I thought that they'd do great with HBO.
Honestly, I would have been fine with the merger.
But regardless, I bought more of the stock when it dipped down
and this wasn't the exact bottom.
In fact, Netflix continued to go down into the 70s.
So I did not time the bottom on this buy.
I didn't even get really close to the bottom,
but I bought it really low and Netflix is up substantially.
The last one that I'll show here is Duolingo.
I bought $5,000 worth of this one, February 10th
at a share price of $1.21.
So this one, I actually believe,
is underneath my buy in price.
Let's go ahead and take a look at it.
So I bought it at $1.21 and Duolingo's at $103.
So it's gone down even from that price.
I'm a little bit in the red on that buy.
Duolingo has not been a good stock for me.
It's just basically only gone down since buying it.
It's like one of the worst performed or time stocks
that I've ever bought.
Luckily, I bought a small position.
I started off with a two and a half percent position.
It went down from there.
Currently, it's down around 70%.
I bought more and more of it as it's gone down,
but overall, I'm still in the red on this one.
But I'm still holding out on Duolingo.
I like what I see with the fundamentals
and we'll see if this one turns around.
The portfolios overall are up huge
in just the past couple of weeks.
I still like meta right now,
even more than when I first bought it.
I'm still extremely bullish on the company.
I think that one's gonna be a big win or over time.
In the story fund, we also have this racing backup
to all time highs.
In fact, the story fund has never been bigger
than it is today.
It's also up around 6% year to date.
So overall, between the two portfolios,
we're moving back into the green in 2026.
And this is because basically every stock in this
has had a massive recovery.
Microsoft is moving up big time.
The stock is down to historically low valuations.
It's a great company.
It's Microsoft.
So we can expect that one to move up.
Google has just been in maintenance mode.
So I don't mind that.
It's gone up so much last year
that Google just remains where it is today.
Netflix had the big recovery and Amazon
has moved up dramatically.
Looking at Amazon, we can see that this stocks somehow
it just snuck its way up to 250.
Like it's at 248.85 right now.
So Amazon was just at $200 per share seemingly yesterday.
Now it's back up at 250.
I believe that Amazon today could easily
deserve to trade at 300.
I don't think that would be extreme at all.
I think that'd be warranted
given the potential of this company.
As the story continues on,
we'll see more and more investors get bullish for this one.
One person that I like, I like his interviews
and I like his thought process
because he doesn't try to instill fear in the investor
is Tom Lee.
Tom Lee provides an argument of why he believes
that stocks today are better positioned for gains
than they were proceeding the war.
I know this is gonna sound counter to what other,
what the viewers might think,
but I think the stock market is in a better position today
than earlier this year when it made it's all time high.
Because one, we're now seeing that the US stock market
can handle a surge in oil while it hurts other countries.
We've seen earnings go up,
so we now feel comfortable that the war
is actually stimulating the economy.
And the third is, I know I've talked before
about inflation shocks,
but we've been looking back at the history of oil spikes
and the impact on core is less than we thought.
So I think there may be less of an inflation shock coming.
So I think stocks can go back to that 7,300,
which is our base case for this year
and our three-phase market
before we might see a larger drawdown.
The argument that Tom is making here is a simple one.
It's basically that the devil you know
is better than the devil you don't.
Meaning that when investors first look at something
that's new, it's unpredictable and it's scarier.
It's unknown.
When we start to actually get into something,
we know it, we can see the reaction,
we become more acclimated to it.
The news headlines don't hit quite as hard as they used to.
Investors just become a little bit less concerned.
Overall, I agree with his assessment.
It's a strong argument.
I think there is reason to believe
the market could be much higher this year,
especially because earnings continue to grow.
Now, moving forward, there are a couple companies
that just reported earnings,
ASML being one of them.
Just a look at what happened in Q1 of 2026.
We can look at the Qualtron brief.
ASML reported net sales about 8.8 billion euros
in the income of roughly 2.8 billion euros.
Beating profit and sales expectations
on strong AI-driven demand for EUV and immersion tools.
Management raised its 2026 revenue guidance
to approximately 36 to 40 billion.
So they raised it up to billion euros worth.
Revenue guidance is being raised.
What they gross margin outlook of 51 to 53%,
signaling confidence in sustained AI in advance,
node investment despite macro and export headwinds.
ASML trades at a 35 Ford PE,
a less than 2% free cash flow yield.
It's just simply more expensive today.
A lot of the bright future is being priced in.
And for me, that moves this stock from a buy to a hold.
Now, another stock that's reporting earnings today,
later today, is Netflix.
The stock is currently at $109.
Now, I can't possibly guess
what direction Netflix will trade after earnings.
So if we're gonna be one of the people
that looks at the stock price five seconds
after the report earnings to see if the ticker goes up or down,
I can't tell you what direction it's gonna go.
But I can with the level of confidence make the prediction
that I believe Netflix will be substantially higher
over the next five years.
The combination of more subscribers,
more price increases, more engagement,
and investing more in content
so that their value proposition remains really good
during all of this makes for an incredibly strong business
model that others have a difficult
if not impossible time copying.
Another thing I'll mention is when we look at the top free apps
from the Apple App Store,
the Netflix game controller has been,
like in the top 10, top 15, for quite some time,
it's been bouncing around here day after day,
competing with apps like Chatchy BT.
With tax filing, we have turbo tax as a top one,
but Netflix game controller was number one for some time
beating out the top AI apps.
I remain incredibly bullish on Netflix.
I'll buy any dip that I see with this company.
Now, moving on, we get to news of Amazon
just to update with this company.
They recently agreed to buy global star.
This is an $11.6 billion deal.
Now, what is this for?
Well, the transaction will give Amazon's nascent,
Leo satellite internet business a boost
as it buys to compete with Elon Musk's SpaceX.
All of this effort is to build Amazon's SpaceX competitor
to make it so that they can offer satellite internet.
We have SpaceX that big leader was Starlink
and Elon Musk has enjoyed Starlink
with basically no competition.
It is right now a monopoly,
but Amazon is changing that
and they're doing it through brute force.
Amazon stock also went up after announcing this acquisition,
which is rare.
Typically, when a big company acquires a smaller one,
the bigger one trades down,
in this case, investors are actually bullish
on this acquisition, which I believe is right.
Now, at a recent episode, I just highlighted
that my two big bets for 2026 are Amazon and Meta.
We also have investors now turning more bullish
in the sentiments improving for Meta.
This is a write up from Deutsche Bank analysts
and I wanna go through some of it.
This write up is overall a bullish thesis on Meta
that outlines a number of catalysts
of why they believe this stock will move up this year.
And they start off with one of the primary catalysts
which they believe is that Meta
typically overestates how much their expenses will be
and it's usually reported in Q1.
They say in fact, over the last four years,
Meta has lowered its expense outlook three times in Q1,
including Q1 2025 earnings.
As such, we believe this incremental spend
was already contemplated in Meta's
topics and topics outlook.
So the first thing that they're outlining is that
the expenses have already been priced into the stock
and they believe that Meta will come out and say,
actually these expenses aren't quite as bad as they look.
We're gonna guide down with our expenses.
Anytime that Meta guides down with their expenses,
the stock goes up.
Investors believe that that means more efficiency,
higher margins, more cash flow.
They continue on and shift the argument
for Meta's rise now to Mew Spark,
which is Meta's new AI model.
We can see it again right here.
Currently number five in the App Store.
That's right there next to Gemini and Chatchy BT.
Meta also recently released Mew Spark,
the first foundational model coming
from the revamped Meta super intelligence lab,
which we think is geared towards
supporting Meta's core business and Meta AI assistant.
It has been engineered from the ground up
as a natively multi-model reasoning engine
designed to seamlessly integrate visual data
with text and tools.
This differs from some existing models
that have had multi-model capabilities added on.
So basically, Meta's model was built
from the ground up multi-model.
Some other models are built for different reasons
and then they kind of patch together
different aspects of it to make it multi-model
after the fact.
And they believe that Meta's architecture
is actually better for their needs.
A key innovation is the contemplating mode,
which utilizes multi-agent systems
to tackle complex problems in parallel,
aiming for deeper analysis without significant latency.
And even as importantly,
per Meta, Mew Spark has been architected for efficiency.
It uses an order of magnitude less compute resources,
which is critical in an environment
with severe chip shortages for deployment
in smaller form factors.
They talk about the contemplative mode.
This is actually something that I saw new
with Meta, I've never really seen this before.
Basically, you query something
that's more deep, a thoughtful thing.
And usually what happens, if it's in Gemini,
it'll just have the one thing spin through
and kind of explain what it's doing.
With Meta, it does that,
but it's like six different models all running
or the model running six different times in parallel.
All of them are factoring through this reasoning
and then it synthesizes the outcome
from all six of these.
Based on the reports from independent benchmarks,
we believe this new model may not have entirely leapfrogged
the top tier, but it still is highly competitive,
particularly in visual analysis reasoning
and healthcare applications.
Now, they continue on talking about how,
not only this justifies part of the reality lab spend,
but also how careful Meta is in having this tailor made
for all their future applications.
They say Mew Spark is a potential software unlock
that reality labs needed to justify its large cash burn
because the model is highly efficient, natively multi-model.
It appears that it is tailor made for edge devices
like Rayban, Meta Smart Classes and Future AR headsets.
When an AI process is visual and auditory inputs
simultaneously and natively,
it drastically reduces latency.
This means that the glasses can see
what the user sees in real time,
overlaying visual objects in real environment,
translating live texts or offering contextual advice
without the lag that ruins the AR illusion.
Basically, if Meta didn't build this themselves
and they relied on some other third party model
that's a taped together multi-model,
then they wouldn't be able to use this
in their own products without latency.
So having their own model,
purpose-built makes it so that the whole ecosystem works.
Now, you have this also, I think, contrasting with Apple.
Apple doesn't have their own tailor-made model.
They're working on different ways
to try to bring down latency,
but Apple will be by far the biggest competitor
with Meta with the Rayban Smart Classes.
We know that Apple's working on smart glasses.
Apple has the ecosystem.
They have the App Store.
They have the iPhone and everybody's pocket.
They can do a lot of things that Meta can't do,
but with Meta's massive investment
in owning their whole stack of AI,
this is actually giving them somewhat of an advantage
in some areas even to compete with Apple in hardware.
And this is why a lot of investors are saying
it's a good thing because Apple's saving cash
on not investing in their own AI models,
where I believe it's actually a risk for the company.
Apple could be giving up significant technological advantages
by being unwilling to invest in AI
at the same level that Meta is.
But we'll see how that turns out right now.
I think that Meta's making good ground.
In healthcare and wellness,
Meta collaborated with over 1000 physicians
to curate training data,
enabling Mew Spark to provide more accurate
and interactive health insights
and generate nutritional content,
explain muscle groups activated during exercises,
and generate interactive health displays.
Dispositions Mew Spark is a daily wellness companion,
moving beyond generic chatbot responses.
While it is not a substitute for professional medical advice,
its ability to interpret images and charts
could provide more tailored guidance
than text-only models.
By positioning Mew Spark is a daily wellness companion,
likely by integrating wearables,
Meta could create a sticky, high-frequency use case.
This strategy could yield ecosystem retention
while collecting high-intent data.
Diet, fitness, and health goals
that would ultimately prove to be valuable
targeting for advertisers.
This puts them in competition with both Amazon,
which I believe is trying to push into healthcare
with more of a pharmaceutical approach,
but it also pushes them against Apple.
Apple is trying to become a healthcare company
with the watch, with the glasses,
but they do not have the model that Meta has.
This is why I believe that this investment,
the $100 billion plus into CapEx
could be well worth it for Meta.
It opens up entirely new business lines,
new technology that you can't deal without it.
In terms of shopping,
Mew Spark is set to power a new shopping mode
that leverages Meta's vast ecosystem
of creator content on Instagram and threads.
The AI can provide personalized product recommendations
based on a user's interest and the content they engage with.
Effectively turning social media posts
into shoppable interactions.
By natively integrating AI into discovery phase,
we think Meta is compressing the funnel
between inspiration, seeing a creator's outfit,
and the ultimate transaction, buying the item.
If this scales, it should materially boost conversion rates,
allowing Meta to charge a premium
for AI-assisted ad placement,
and keeping users inside the Meta ecosystem,
rather than defecting to Google search or Amazon.
Keep in mind, Meta has 3.58 billion daily active users.
They have the entire customer base
half the world using their product already.
So they don't need more new customers,
they just need to be able to vertically integrate it,
make the shopping experience more seamless, remove friction,
and they're highlighting a specific way
that Mew Spark, this new model can do that.
With the focus on supporting the internal operations,
it is not surprising giving Meta has said it believes
that returns from the upcoming models
will primarily come from the consumer experiences they build,
such as making content more engaging
across their family vaps.
So in terms of monetization and how this factors in
with the business, it is likely that Meta AI
will have a pro mode that the more wealthy consumers of Meta
can pay for to have an advanced AI as their daily driver.
But I don't believe that that's even close
to the main way they're monetizing this.
They're going to monetize it by integrating it
into all of their ecosystem,
making it so that all of their distribution,
all of their touch points work better.
They already have the biggest audience in the world,
now they just need to leverage it.
There's also a number of other advantages
that they outline here,
commoditizing the base, monetizing the frontier.
By open sourcing Lama, Meta commoditized
the foundational layer of AI, creating a wide ecosystem
of developers and applications built on its technology.
With Mew Spark, Meta can now offer premium,
cutting-edge features and capabilities as a paid service,
potentially through APIs or subscriptions,
creating new revenue streams beyond advertising.
In the competitive advantage, keeping the architecture
of its most advanced model close prevents competitors
from easily replicating its innovations,
particularly the multi-agent contemplating mode.
This is crucial in the highly competitive
frontier model landscape in our view.
Enterprise and high value applications.
A closed model allows Meta to offer more controlled,
reliable, and secure solutions for enterprise clients,
particularly in regulated industries like healthcare.
This approach is similar to that of competitors
like OpenAI or Anthropic.
In our view, as we've highlighted before,
the big picture here is that one,
Meta made the necessary investments
to support continued user engagement growth at scale.
Two, that has created the most durable advertising platform
across the group, and three, is leaning in
to foundational AI model training work,
which is unlocking new vertically integrated opportunities
across large total dressable markets,
including business messaging.
Meta AI, potentially searchable advertising,
scaled wearables, with 2026 even shaping up to be a year
of ramped product releases, including an array
of new AI model launches.
As such, notwithstanding the broader market pullback,
we think the dip creates a buying opportunity.
This stock is a high-quality compounding machine.
It has an ever-growing mode.
It is on the forefront of a lot of technologies,
and it's being driven by Mark Zuckerberg
that is aware of the concerns
but willing to make the hard investments
to have the biggest payoff.
The market still looks at this as a company
that will have low returns when that's already proven wrong.
So while Meta trades at the low 20s PE ratio,
it should be trading up there at the high 20s.
We should see continued multiple expansion
from this stock going forward,
not to mention the rapid earnings growth.
They believe the stock today should trade at a 27 PE,
at a price of 920.
Meta currently trades at 670.
So there is a significant gap
of where this one could continue to go.
I think it will.
Now, moving on, we get to an interview
with Jensen getting a little upset.
Now, he's not upset with the interview he heard.
Warcush Patel is interviewing Jensen
but they're not really upset at each other
but the interview does get a little testy.
Jensen doesn't like the subject
and I don't think he likes the questions at all.
In fact, he's asked about why Nvidia
should be allowed to sell its chips to China?
When they're an economic and adversarial country,
why should we be selling to them
to give them some type of advantage?
And he really does not like the comparisons being made here.
The claim here is, Darryl had this quote where he said,
it's like Boeing bragging that we're selling
North Korea nukes but the missile casings
are made by Boeing and that's somehow enabling
the US technology stack.
Like, fundamentally, you're giving them this
given ability.
I'm comparing AI to anything that you just mentioned
as lunacy.
But AI similar to Enrich uranium, right?
And then it can have positive uses.
It can have negative uses.
We still don't want to send Enrich uranium
to other countries.
Now, I get the argument that he's trying to make here.
AI is an incredibly powerful tool.
It's unlike anything we've ever seen.
People say it's the biggest technological innovation
since electricity, right?
So that makes sense.
But I think what the mistake that the interviewer here makes
is he goes to such an extreme, he compares it
to nuclear weapons, which those don't really
have that much of a positive, like,
there's no upside with nukes.
There's only death and destruction.
I would have used a more relatable technology,
one like Palantir, that has many applications.
It can help businesses become more efficient.
It can help with logistics.
And it can help with war.
Would we want to hand Palantir technology over to China?
I doubt it.
And that argument is very sound.
But here is how Jensen reacts.
And again, I think he's already extremely bothered
by the example of comparing it to nukes.
Enrich, the analogy is Enrich uranium is like a thing.
Because it's a lousy analogy.
It's a illogical analogy.
But if that compute can run a model,
they can do zero-day exploits against all American software.
How is that not a weapon?
First of all, the way to solve that problem
is to have dialogues with the researchers,
the dialogues with China and dialogues with all the countries,
to make sure that people don't use technology in that way.
That's a dialogue that has to happen.
I just have to call this out.
That's one of the most naive things that I've heard.
We're going to have a dialogue with China, a dialogue.
We're just going to talk really nice to them,
and then they'll do what we want.
And they won't harm us.
They won't do anything that we don't want them to do
if we have a good dialogue.
How does that work with Russia?
Do we just have a dialogue with Russia and say,
hey, Putin, can you stop doing this?
Can you behave please?
Dialogue is always nice, but we don't
need to have that dialogue if they don't
have the same technology as us.
If we don't hand them over powerful technology.
So I don't really buy this reasoning at all.
I think this is very motivated reasoning from Jensen,
who wants his business to be able to have more revenue
and open up a new market.
AI industry matters across every single layer.
And we want United States to win at every single layer,
including the chip layer, and conceding the entire market
is not going to allow United States
to win the technology race long-term in the chip layer
in the computing stack.
That is just a fact.
Jensen is making the argument that the only way
we can win the long-term in China
is by selling them chips today.
But history doesn't really support that assertion.
Typically, when we sell high-end technology to China,
they use it as a crutch to enable them
and a catalyst to grow until their own industries
can replicate the same technology that we're selling them.
Companies in China like Huawei
are not going to back off of chip development
because Nvidia's selling in China.
They're not going to say, oh, and videos here
we're no longer going to develop chips.
It's very difficult that there's
any benefits to us to selling them in China
other than Nvidia's revenue.
Tesla sold extremely good electric vehicles
to China for a long time.
iPhone's are sold in China, extremely good.
They didn't cost them lock-in.
China will still make their version of EVs
and they're dominating their smartphone's dominating.
When you started the conversation today,
you would acknowledge it and you acknowledged
that Nvidia's position is very different.
Use words like moat.
The single most important thing to our company
is our richness of our ecosystem, which is about developers.
50% of the AI developers are in China.
We don't want to, we shouldn't,
the United States should not give that up.
Okay, I'm going to be honest here.
This is another ridiculous statement by Jensen.
He's asserting that the reason that Nvidia's different
than companies like Tesla or Apple
is because Nvidia is a five-layer moat.
It's an ecosystem and Apple isn't.
Apple doesn't have an ecosystem.
Apple doesn't have a moat.
Are we really going to argue that?
Apple has likely one of the most impenetrable moats
of any company on planet Earth.
Yet China went right around them,
built their own phones, built their own ecosystem
like there was no problem.
China will build their own chip tech stack,
whether Nvidia, whether Jensen likes it or not.
I just think that this is a crazy statement.
Even Tesla was talked about as having a big ecosystem
because of their vertical integration,
because of the design of their vehicles,
because of their batteries
and how everything was built and so on.
And now China's crushing Tesla and China.
Now we also have a part of this interview
where Jensen goes directly against the words of Andy Jassy.
Nobody can demonstrate to me
that any single platform in the world today
has better performance TCO ratio, not one company.
And in fact, the benchmarks are out there.
Dylan's inference max is sitting out there
for everybody to use.
And not one TPU won't come, training won't come.
I encourage them to use inference max
and demonstrate their incredible inference cost.
It's really, really hard.
Not nobody wants to show up.
You say improve it.
You're making these claims, you have to prove it.
ML purf, I would welcome Tranium to demonstrate
their 40% that they claim all the time.
I would love to hear them demonstrate
the cost advantage of TPUs.
It makes no sense in my mind.
It makes absolutely zero sense.
On first principles, it makes no sense.
So Andy Jassy, just in a letter a couple days ago
says that our chip business is on fire
and it's changing our economics.
He says that Nvidia's great,
but people want better cost per compute.
He says that Graviton, which is up to 40% better price performance
than other X86 processors is now used expansively
by 98% of top 1000 EC2 customers.
This seems very precise.
He continues on directly going against
the likes of Sundar Pachai and Andy Jassy
in the claims that they make,
trying to highlight how unique Nvidia is.
Andthropic isn't a unique instance and not a trend.
Without anthropic, why would there be any TPU growth at all?
It's 100% anthropic.
All right, so Jensen's making a lot of statements here
and I have to go through and fact check some of this.
First of all, he's trying to aggressively characterize
anthropic as just a one off event.
It's not a trend.
People aren't using other stuff than Nvidia.
Don't worry, I still hold the market share.
It's all me.
No one else is going anywhere else and anthropic.
Don't pay attention to them.
It's just a one time outlier.
It's an anomaly.
Anthropic just decided to do it
and no one else is gonna follow suit.
Okay, I have to disagree here.
First of all, anthropic is not just some random company
that decided to train on Nvidia competitors.
Anthropic is like the biggest, most compelling AI company today.
They're the ones that are crushing software companies.
They're ones that are moving forward the fastest.
So having anthropic train on Google and on Amazon shows
that literally the best models with the highest impact
in the world can be trained on direct competitors to Nvidia.
Of course, Jensen doesn't like that story.
He doesn't like facing it.
So he's gonna try to aggressively spin the narrative
that you have to use Nvidia if you want to be great in AI.
Even though anthropic is a striking counter example.
Another counter example that I would give is Google
with Gemini.
Gemini is entirely trained on Google's own TPUs.
Gemini Pro, I believe is my favorite model.
I just think it's the best one overall.
Again, trained directly on a competitor to Jensen.
We also have Amazon.
Amazon, of course, trained anthropic.
That was part of it.
Anthropic has been trained on multiple clouds.
But we have him saying that basically Amazon
is not being truthful.
He says that they need to prove
they're 40% better price performance.
Now, I believe there's a little bit of nuance here.
And there's reasons to believe both of them
could be right to some extent.
Jensen is probably saying that in a broad circumstance
with every application, Nvidia has better price performance
than Graviton or Trainiam chips.
Jassy saying that in the application for our clients,
specifically for these use cases,
we can get the price to compute much lower than Nvidia's.
Early on a few years ago, when it seemed like Amazon
and Google weren't as much of a direct competitor
to Nvidia and they were more of just a customer,
he talked about their technology more glowingly.
He said that they have something special going.
But now that they're posing a real competitive threat,
now that they're stealing very large clients
for their own in-house chips,
it seems like Jensen is going in a far more aggressive stance
against them, trying to keep the narrative
that Nvidia's the only game in town.
But I don't believe that's the case anymore.
And I think we're gonna see more and more examples
of large companies and small choosing different sources
besides Nvidia.
We'll have to wait and see.
Now moving on, we get to the fill of the week,
which is this story right here.
For its next act, All Birds makes an unlikely pivot
from shoes to AI.
This is in the Wall Street Journal, it is real.
All Birds, the shoe company is now an AI company.
Now when I saw this headline immediately,
it just dragged me as a fill of the week.
I was gonna highlight how this is obviously a bubble, right?
I was gonna have a little clip.
In fact, I just thought of having the clip
of the big short where Mark Baum is saying,
this is a bubble, he's on the phone.
But then I looked more into the story
and it became rather intriguing.
Actually, it actually changed my opinion
when I looked a little bit deeper.
So let's go ahead and just read into this
and we'll see what's going on with this company.
All Birds said Wednesday that it will change its name
to New Bird AI and will look to capitalize
on the frenzy surrounding artificial intelligence
by buying high end server equipment
with AI chips and renting out access to them.
The move comes just weeks after All Birds,
once valued at $4 billion,
struck a deal to sell off most of its assets for $39 million.
Indeed, the company needed a new name
because it is selling the old one.
Now, the announcement that it was raising $50 million,
so someone from the outside gave them $50 million
to pivot into AI and it sent the stock soaring
from $2.49 up to $17 per share.
So on the surface, this looks like a crazy pivot
from a company that's obviously signs of a bubble.
And it is, it shows that there's a massive frenzy
and a surge for everybody to get into the hot new thing,
which of course is AI and data centers.
And All Birds is taking advantage of that.
But there's more to this story.
If we look at the story of All Birds,
it's a stock that is basically going bankrupt.
The company had a shoe line like many of these companies,
shoe lines, they don't fare well over time.
And of course, sales struggled,
their distribution went south, the shoe line went south.
The stock was down over 91%.
They're in the midst of being an acquisition play,
a company that's basically only worth its brand.
So the leadership of the company also knows that
at this point in time,
the company is a heavy target for a short.
In fact, short interest was somewhere around 18%.
So 18% of shares outstanding are being shorted.
The stock is way down, it continues to go down.
And they think of a way that they can blow away the shorts.
They can do a short squeeze.
And that is with a pivot and a headline to AI.
So the management gets $50 million as a loan.
They use this to invest in AI.
They know it's going to generate massive headlines.
And then they have a massive short squeeze
causing shorts to cover their position.
So that first, I was a little bit disappointed
that this wasn't going to be a massive fail.
I was hoping it would be some humorous thing.
But when I actually looked at the details,
it was a little bit smarter than it seems.
Now finally, I wanted to show you something
that I've been working on just because I think it's cool
and you may like it.
Even if you're not a Qualtrum subscriber,
I think you may appreciate this.
On Qualtrum, you're familiar with this, right?
We have the insights page
and we look at different companies all the time.
But I've added a new page.
When you click on it, it transports you
into an entirely different experience.
All of a sudden, you're in this like nice moody,
themed video-esque page.
It's a lot like Netflix.
We have custom art for each episode.
It has highlighted videos that it cycles through
to show you which ones I think are the most interesting to watch.
And what we've built here is basically
a Netflix for investors.
Now all of this, every single video is exclusive.
These are videos you're not going to find on YouTube.
They just don't exist on YouTube.
These are the ones that we do exclusively
in a lot of cases they're longer format videos.
For example, I just released one here
on Brookfield Corporation.
We have Bruce Flat there who's the CEO, the creator of it.
It goes over a lot of history of Brookfield.
And if we want to play this, we can just hit play.
Then it brings us, look at that.
It brings us right to the video.
Except that is not a YouTube video.
That is our own hosting, our own distribution.
We have figured out the technology
to make this available.
And the cool thing is, is it just works perfectly
in HD.
It'll stream anywhere you have the internet.
It took some time to figure it out.
And it looks almost a little bit like YouTube.
It even has a next up section,
which is algorithmically driven.
It tells you which videos in the exclusive library
you may be interested in based on the one you're watching.
And we do this through a tagging system.
So another cool thing is, before doing this,
everything was just basically dumped into Discord.
So I'd record an exclusive episode.
I would say, hey, Discord members, here's the video.
And you just get a YouTube video with a link.
It would be an unlisted video.
And that didn't really look that cool, first of all.
It just looked pretty plain.
Having a video dumped into Discord is nothing special.
This dresses it up a little bit.
It sets the vibe.
It makes you want to like dive into it more.
Like when I look at this and I see Brookfield Corporation here,
I see Bruce Flat.
It immediately gives me a visual of what to expect.
This is going to be a video about building a big business,
about industry, about a guy that's building a large corporation.
And the image is set the tone.
So instead of just having videos dumped
into Discord with an exclusive membership,
now it feels like this is a real thing.
And that's part of what I wanted to do here.
Another thing is it literally just has
a lot of technological advantages.
For example, there's a search up here.
I can search meta and it instantly
surfaces every video in the library with meta.
And every single ticker is tagged.
So you can put in any ticker and see
all the videos associated with that ticker.
So it also has categorization, it has search capability.
We have each category of like deep dives, portfolio updates,
market updates, AMAs, and so on, all in nice rows and categories,
with the most recent ones being on the left
and then to the oldest on the right.
So there's structure now.
Now people that sign up for Qualtrim
and want to see the video, they have a full library to look at.
Even have these category options up top here.
For example, I can see all the deep dives,
I can see the portfolio updates.
And these will populate more and more
as we get more new episodes on here.
So it brings structure, it brings clarity,
it sets the vibe, I think it's a really cool feature.
Plus we're making sure it has all the same parity
of streaming features as YouTube premium.
So being able to play in the background,
being able to cast your TV, all that good stuff as well.
But that is Qualtrim Studio.
We've built, I built my own Netflix, so to speak.
A much smaller version, a financial Netflix.
But I've always liked Netflix
and I think it's cool to be able to say I've built my own.
That's kind of a cool thing.
So here's a little mini version of financial Netflix
and another thing I'll mention
is this isn't impacting the price at all.
Qualtrim staying the exact same price.
This is just an ad into offer more value and structure
to the exclusive content.
Like always, if you haven't tried out Qualtrim,
you can try it out risk-free.
It comes with a seven day free trial.
I think you'll love it if you try it.
That's all for this episode.
Hope you enjoyed.
See you in the next one.
