Nvidia
may
have
enjoyed
a
red-hot
run
on
the
back
of
the
artificial
intelligence
craze,
but
many
other
tech
stocks
have
also
benefited.
As
with
any
investing
theme,
diversification
is
needed.
Veteran
tech
investor
Paul
Meeks
told
CNBC
Pro
that
even
if
Nvidia
is
a
“great
story,”
it’s
“too
risky
to
be
in
just
one”
when
it
comes
to
AI.
Tech
giants
and
semiconductor
stocks
have
captured
the
attention
of
investors,
given
that
chips
and
other
systems
are
needed
for
the
infrastructure
expansion
of
the
initial
AI
phase.
CNBC
Pro
speaks
to
fund
managers
to
find
out
the
best
alternatives
to
Nvidia
that
investors
can
consider.
Semiconductors
Jordan
Cvetanovski,
portfolio
manager
at
Sydney-based
Pella
Funds
Management,
named
Taiwan’s
TSMC
and
Dutch
firm
ASML
as
two
stocks
to
buy.
Both
are
listed
in
the
United
States.
Cvetanovski,
who
manages
the
Pella
Global
Generations
Fund,
says
TSMC
is
a
good
way
to
play
growth
in
tech
and
AI
in
particular.
“TSMC
is
arguably
one
of
the
cheapest
technology
companies
out
there.
We
don’t
have
to
believe
in
huge
growth
numbers
to
justify
their
valuation,”
he
said.
“We
think
it’s
a
wonderful
business,
100%
dominant
basically
and
they’ll
continue
to
be
dominant.”
ASML
will
also
continue
to
benefit
“because
without
ASML
there’s
no
TSMC,
without
TSMC
there’s
no
Nvidia,”
Cvetanovski
said.
ASML
has
a
monopoly
on
EUV
lithography
machines,
which
are
needed
to
make
advanced
processor
chips.
All
three
stocks
are
interdependent:
The
U.S.
chipmaker
depends
on
TSMC
to
manufacture
its
graphics
processing
units.
TSMC,
in
turn,
uses machines
made
by
ASML to
make
the
most
advanced
semiconductors.
Cvetanovski
believes
that
Nvidia
will
continue
to
dominate
the
chip
industry
despite
competition
from
players
such
as
Advanced
Micro
Devices
.
Ray
Wang,
principal
analyst
and
founder
of
Constellation
Research,
also
named
TSMC,
saying
that
it
“always
wins.”
He
also
believes
that
AMD
will
“come
close.”
A
data
center
play
Data
centers
are
also
set
to
benefit
from
AI,
the
applications
of
which
are
very
power-intensive.
Cvetanovski
named
Vertiv
as
a
beneficiary.
“AI
requires
…
more
data
centers,
all
this
demand
will
require
more
data
centers,
more
sophisticated
cooling
systems
and
all
kinds
of
other
things
that
go
with
AI
investing,”
he
said.
Vertiv
is
experiencing
growth
of
10%
to
12%
and
more
growth
“is
still
not
a
huge
hurdle
for
them
over
the
next
three
to
five
years,”
Cvetanovski
said.
Super
Micro
Computer
Meeks,
who
is
co-chief
investment
officer
at
Harvest
Portfolio
Management,
says
Super
Micro
Computer
is
his
favorite
alternative
AI
stock
to
play
right
now.
As
AI
is
still
in
the
infrastructure
buildout
phase,
AI
products
are
set
to
come
only
in
2025
or
2026,
he
said.
“So
with
that
thesis
Super
Micro
makes
customized
servers
that
are
used
by
AI
customers,
so
it
uses
Nvidia’s
chips
in
their
servers
and
as
[Super
Micro]
sells
their
servers
to
folks
like
Microsoft,
and
then
they
put
them
in
a
data
center.
And
so
Super
Micro
has
done
a
pretty
good
job
of
transitioning
its
focus
to
AI
customers.”
The
stock
has
risen
astronomically
since
last
year
,
but
Meeks
continues
to
believe
that
it
and
Nvidia
will
continue
to
beat
earnings
estimates.
“And
as
long
as
they
continue
to
beat
the
analyst
numbers,
you
know,
the
stock
should
rise
…
Because
Wall
Street
is
…
what
you
do
versus
the
expectation,”
he
told
CNBC
Pro
last
week.
Big
Tech
Investors
should
also
own
Big
Tech
stocks
that
are
building
their
AI
businesses,
such
as
Amazon,
Alphabet
,
Meta
and
Microsoft
,
according
to
Meeks.
Those
would
be
the
main
infrastructure
plays,
as
cloud
data
centers
—
which
these
tech
giants
have
—
will
be
needed
to
train
and
run
AI
models,
he
said.
Meeks
compared
the
current
stage
to
the
formation
of
the
internet.
“The
guys
that
made
all
the
early
money
were
companies
like
Cisco
because
they
provided
the
networking
for
the
internet.
At
that
time
in
the
late
90s,
America’s
largest
market
cap
was
Cisco
because
it
was
doing
the
plumbing
of
the
internet.”
Many
investors
want
new
exciting
ideas
to
buy
into
but
in
this
case,
the
“strong
gets
stronger,”
he
said.
“You
want
to
be
with
the
established
companies
because
they
will
benefit
the
most
from
AI
because
they
can
spend
the
money,”
he
said,
adding
that
building
AI
infrastructure
is
extremely
expensive.
The
next
Nvidia?
Wang
of
Constellation
Research
didn’t
only
name
tech
giants
like
AMD,
Amazon
and
Meta
—
he
also
named
some
startups.
The
next
Nvidia
could
be
a
few
companies
that
are
specialized
in
the
tensor
processing
unit
space
that
Google
pioneered,
he
said.
These
are
AI
accelerator
application-specific
integrated
circuits
developed
by
Google
for
neural
network
machine
learning,
using
Google’s
own
TensorFlow
software,
he
explained.
One
name
he
highlighted
is
OpenAI
CEO
Sam
Altman’s
TPU
startup,
Tigris.
He
also
named
Groq,
a
Google-funded
startup
developing
custom
AI
chips
for
running
models.