08 05 26 *INTERVIEW* David Trainer CEO of New Constructs, joins us to talk about AI investing and capex, and where true value will be created in AI

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Episode Transcript

Speaker 1 (00:00):
All right, good morning, Happy Wednesday, and Ross, thanks for
being here. AI is obviously a huge thing. It's starting
to change the World's going to change the world a
lot more over time, and a lot of folks are
wondering how to make money investing in this, and also
as businesses are wondering how to invest their own money

(00:21):
and how to use AI. There are so many different
angles on this. David Trainor joins us. David is CEO
of New Constructs Investment Research, and he.

Speaker 2 (00:32):
Thinks about this stuff a lot. He partnered with Google
Cloud to create.

Speaker 1 (00:36):
Something called finn Sights AI, and we'll get to that
in a bit as well.

Speaker 2 (00:41):
And so, David, my my professional.

Speaker 1 (00:43):
Background before radio was as a financial markets trader and investor,
and so I'm very used to seeing trends and bubbles
and all this stuff. It's it's been very interesting to
see in not just technology stocks, but even stocks like Caterpillar,
where folks are thinking, like, oh, they're going to make

(01:05):
so much money because of AI. And it's mostly been
a rocket ship, but lately there's been a huge correction
and that one headge fund blew up and blew out.
So how are you I'm gonna ask you a very
broad question, how were you thinking about where in the
longer run money is really going to be made in
this broad world that we're calling AI.

Speaker 2 (01:26):
I think the answer to that question ross is the
same during every one of these hype cycles, and the
answer is where people aren't looking, Because where people are
paying attention, everything's already been bid up to your point,
we're going as far downstream as Caterpillar and have been
for a while. And so I think the place that
people aren't looking, what people are missing and what the

(01:47):
big AI companies don't want you to think about, and
that's part of why it's missing is the data, the
underlying data. And we hear this reference then Alex Karp
at Pallenteer when he's talking about what a rip off
it is for these big companies to pay the frontier
models so much money for tokens while giving away the

(02:08):
proprietary data. Every entity, every person, every individual for that matter,
right has a as a as a personal signature that
is unique to them, and AI, we know, has already
been out there hoovering up everything that's free. Part of
the hypocrisy of the frontier models is like, oh, you know,
the Chinese models are stealing the data. No, no, they're not.

(02:29):
You've been stealing the data. They've all been stealing data.
They've all been using the internet. The problem with using
the Internet, though, is it's what everyone else has. It's commoditized.
Larry Ellison said this late last year in one of
the Oracle conference calls. They're all using the same data,
so results are all really similar. Output is similar. That's

(02:51):
why these Chinese models can catch up. One thing nobody's
talking about is the proprietary data. Now. Alex carpe I
said he does talk about it indirectly because their model
is very different. They go into a company and they say,
we're going to build this whole thing private to you. Right.
Jamath on the All in One episode talks about the

(03:12):
stack and he talks about the harness layer. This is new,
this is a new vocabulary. Really. The harness layer is
one that goes in and says, I'm going to harness
all that data and value that use a company have
and build AI on that. Because companies exist and individuals
exist because of their individuality, they're doing something special. Unique

(03:33):
successful businesses do a lot of successful or unique things,
and they've got unique data around that. Now, data is
a very broad word.

Speaker 3 (03:40):
For processes and culture and best practices. This is all
considered data for an AI, and that's sort of I
think the travesty of a lot of these frontier models.
They're making a lot of money from companies charging them
for token usage while basically stealing all their data.

Speaker 4 (03:58):
Okay, so David, I don't have the expertise that Ross
has when it comes to the investments. I think I'm
going to leave that question up to him for a second.
But I want to just back up and look at
the space RaSE of AI that we see a little
bit here. You mentioned China and the back and forth
what we're seeing of who can build quicker, who has
the more efficient programs, who can do AI right? Does

(04:21):
anyone have the right answer right now? Is it too
early to tell if China's doing AI right? If we
have it right, if it's something that's different. How are
we going about just something that's growing so quickly that
we might not be able to fully understand how we're
going to conduct a future like in future times?

Speaker 2 (04:39):
You know, the advantage you have, Gina is that you've
got the humility to step back and say I don't
know the answer, and too often, you know, you don't
get paid for that, right, But it's the truth. And
I don't think anybody has the answer right now. We're
trying to figure it out. I mean, there's all kinds
of debate on the internet. I mean this fact that
these Kimmi Mom, Kimmy three Mom, budd and the deep

(05:00):
Seek models now are are putting up numbers because we've
got independent judges on the efficacy of the AI model,
which is great, they're putting up numbers now that called
into question everything we thought just a couple of weeks ago,
which is that anthropic and open AI were the best
and the greatest and nothing could touch them. And so
our mental models are changing quickly. And that's the nature

(05:22):
of technology. This is a very competitive landscape. And the
competition is not just in the technology, it's it's in
the narrative. Because he who wins the narrative often wins
the money. So and Elon Musk is a great example, right,
He's had a narrative around a lot of things without
having to do much. But the guys like the richest

(05:42):
person in the world.

Speaker 1 (05:43):
We're talking with David Train, our CEO of New constructs
the website new constructs dot com, and he has partnered
with Google Cloud to create an AI investing agent called
fin sites Ai.

Speaker 2 (05:55):
That's interesting as well.

Speaker 1 (05:56):
Again, you can check out new constructs dot com. What so,
let me switch this a little bit now to individual
investor kind of questions. A lot of people have been
jumping into this stuff, chasing this stuff right, And I'm
sure there's plenty of people who bought Nvidia at thirty
and I'm sure there's also people who bought it higher

(06:18):
than this, right, and a lot of people. You know,
when I was a professional trader, the people we used
to call somewhat disparagingly the public, you know, would get
in late and lose money. Even though the company's fye,
it doesn't mean the stock's okay. So when you're thinking
about and talking with individual investors who are maybe not

(06:38):
at your level of sophistication, how do you tell them
to think about how to try to make money in
AI without without being you know, the last person into
the bubble.

Speaker 2 (06:54):
Ross I love that you asked that question because it's
so overlooked. People don't want to always understand that there's,
to your point, a distinction between a good company and
a good stock. You can have a really profitable business
in VideA is a great example, but is it is
it a good stock? And the answer to that question is, well,

(07:14):
what does the stock price imply about its future cash flows?
Because coming back to first principles, not to sound nerdy,
but the basic about valuation is the value of the
asset is the present value. The cash flow is available
to the owner. That's why you buy it. That's the
purpose of a security. So if you take the stock
price and reverse engineer what the cash flows have to be,

(07:36):
you can get a sense of like, well, how expensive
is it really in a way that goes well beyond multiples.
And that's that's there's a technique called reverse just kind
of cash flow modeling. It's philosophy called expectations investing. These
things have been around for shoots since I was on
Wall Street back during the tech bubble. But you don't
see these concepts proliferated because they are not conducive to

(07:56):
selling stock. And things that are not conducive to selling
stock don't make one all street moneyf it doesn't wake
Wall Street money, it doesn't talk about it.

Speaker 1 (08:03):
I sat, I saw a great note the other day.
We're just about out of time here. I saw a
great note the other day. It was entitled the the
public is the Exit, which was always kind of true
in an IPO, but it's much more true now than
it ever has been in the past, because a lot
of the companies that are going public have raised so
much money in the private markets. It used to be

(08:25):
that when you would go raise money in the public markets,
it would massively dwarf all of the money you ever
raised in the past. Now it may be dwarfs it
a little, but you've still got people with billions and
billions of dollars to stock to sell, of stock to
sell in SpaceX, orientthropic or whatever's coming next. And so
the public needs to be really careful not to get
sucked into this thing of thinking they've been they've won

(08:47):
to they've won the lottery by being given the chance
to buy stock in an IPO.

Speaker 2 (08:54):
One hundred percent. You know, back during the tech bubble,
it was purposely set up that there was very limited
supply for the publican investors, which created an automatic and
balance that caused all that IPO popping we saw back then. Yeah,
we still see that happen some today, and you got
to remember, I mean, Wall Street is the same Wall
Street that try to sell people we work for forty
five billion dollars. Yeah, that was a zero. Yeah, so really,

(09:15):
buyer beware beyond me. Another busted business model, Peloton. These
are all hyped up in a big way, and we
are in a big hype cycle right now. I think
pretty much everyone agrees like this is a hype cycle.
Everybody's thinking a lot of the same things. We've seen
more train dollar companies come up, come about than ever before,
and not everybody's going to be a winner.

Speaker 1 (09:35):
David Trainer's very very interesting finance related website is new
constructs dot com and if you go over there where
it's a solutions check out fin sits dot AI. An
interesting way to add potentially little AI value to how
you think about and how you go about your investing.
New Constructs dot com. David Trainer is the CEO. Thanks

(09:57):
for your time, interesting conversation, appreciate it.

Speaker 2 (10:00):
Thank you. It was great to be with you guys.

Speaker 3 (10:01):
Yeah.

Speaker 2 (10:02):
Likewise, all right, that was that was really cool.

Speaker 1 (10:05):
Gene. I have a feeling that guy. I could talk
with that guy for hours and hours an hour, like
he knows a lot. He knows a lot more than
I do.

Speaker 4 (10:10):
Definitely nerding out. That's been over my head at times,
which is which is a good thing.

Speaker 2 (10:18):
I learn a lot