Transcription
If you're a fan of Apple products, this
is an incredible week. And even if
you're not, chances are something that
was just announced in the last 3 days is
for you. Apple just announced over five
products this week, but there is a
headline within this that everyone's
missing. I think a lot of the headlines
point to the fact that prices now start
at $600, that the specs are now really
high, that you can run OpenClaw on a
laptop from anywhere in the world at a
pretty high rate of performance with
models that actually run locally on the
device. These are all very cool things,
but one of the the things that people
are missing is the AI angle to all these
releases and how Apple is quietly
becoming one of the biggest players in
the AI space, even though they haven't
actually spent any money on building AI
models or scaling their infrastructure.
This is probably the most bullish I've
been on Apple in the AI race. Um, and
the funniest part is that they've made
no mention of an AI device, but that's
exactly what they released. You
mentioned five devices. Uh, we've got
what's it? a MacBook Pro, there's a new
laptop, um, and a specialized chip. Um,
I've got my turtleneck on today, Josh,
in honor of Steve Jobs.
>> Steve Jobs.
>> Um, for those of you who are new, uh, to
our Apple, um, we have the number one
fan of Apple on the show. That is Josh.
It is his Super Bowl today. And we're
going to get into the weeds about why
Apple just released the top new AI
device. Okay, so let's first get into
what they actually released because
there's quite a few things. They
released the MacBook Pro. They released
a MacBook Air. A brand new MacBook named
the MacBook Neo, which starts at a
surprising price point of $600. This is
important. Remember that. They released
the Studio Display and Studio Display
XDR. Pause right there because these
Studio Displays are awesome. The
previous XDR display used to cost
$6,000. This new one costs half that and
has way better specs across the board.
So, I will be trying to purchase one of
those bad boys. And then finally, they
released the iPad Air and the iPhone
17e. Those two devices are also priced
at $600. So for the first time, there
are three entry-level Apple devices
priced at 600 bucks. And this is
important and this is noteworthy. What's
also important and noteworthy that
wasn't mentioned as much is the chip
architecture that lives within these
devices, particularly the new MacBook
Pro and the MacBook Air. Now, Apple
created their vertically integrated
silicon back with the M1 chip, the M
series chips, and they are now on the
fifth iteration. But this fifth
iteration is pretty amazing. And I think
that's the product that a lot of people
are sleeping on today is not only now do
they have the MacBook Neo, the iPhone
17, and the iPad Air that are capable of
running Apple Intelligence locally for
$600, but now they have these chips that
are capable of running actually large
language models locally on a MacBook.
And this is the first time ever. I think
this is the most excited I've been about
what's inside an Apple product versus
what's actually outside. I'm I'm usually
a display guy. I'm usually an iOS app
guy. I'm like, "Wow, this experience is
amazing." But these chips are actually
insane. So, let me give you the the
rundown of the headlines. The AI compute
processing power of an M5 chip is around
4x larger than the previous generation
of M4. It's 8x larger than the M1. So,
the first in this entire series. Now you
can do a bunch of AI prompts, toolings,
apps, um, and system integrations on
your laptop, and it just feels buttery
smooth. In fact, it's just super quick.
And the reason why this makes me uh
really excited is now you can
conceivably host and run AI models on
your own local device. That means you
can give it access to private data
without handing that over to the likes
of OpenAI or Anthropic. and you can
create a more personalized AI experience
without having to hand over all that uh
private data. Um, but there's a a really
unique architecture around how these
chips are made. Right. Before we get
into the novel architecture, I just want
to double down on something you said,
EJ, which is a testament to how fast
this is relative to previous hardware.
One of the fun facts that I love is that
um previously when Meta was releasing
the Lama models, the $70 billion model,
that required something like $40,000
worth of GPU clusters to run 18 months
ago. And now you can run that on this
new M5 chip. And that brings us back to
the novel breakthrough that enables this
to happen, which is the post that we're
seeing on screen. They basically took
what other companies were calling the
chiplet architecture and built their own
version of it where you take the CPU and
you take the GPU. Two of these things
are both very important to processing
AI, and they fuse them together into a
singular chip. And what's interesting
about this is the CPU part of the chip
is the same on every single version of
the chip. There's the M5 chip, there's
the M5 Pro, and there's the M5 Max. All
of those have the exact same CPU. The
only difference is the amount of GPUs
that they bolt on. So, the Pro gets 20
cores, the Max gets 40 cores. And you
could think of it like these Lego blocks
for Apple silicon. And this is
noteworthy because you can scale this a
really long way. What we know about AI
models in general is that GPUs are how
you scale these things and the CPU is
kind of used as the orchestration layer.
So, this allows these new chips to be
modular in the sense that they can just
kind of stack GPUs more and more and
more. And I assume this is the
architecture that we're going to see
with the Ultra chip that's probably
coming out later this year that's going
to be able to run some serious AI models
locally on this device. And it's a
really novel way of architecting these M
series chips that Apple's kind of
doubled down on. And I I think we're
going to see some really amazing
improvements from it. What I like about
the modular approach is um it doesn't
seem to come at the cost of the size of
the device. Like these things are still
getting smaller and sleeker and thinner
every single year and generation. So
that makes me like, you know, super
excited about like how uh much further
we can take these devices. The other
thing is I watched a really unique video
this week where some random dude hacked
into Apple's I think it was their M4
chip. I don't know if you saw this,
Josh.
This is so cool.
>> Yeah, they they converted it into an AI
transformer. So, what that transformer
was capable of doing was training,
inferencing, or fine-tuning an AI model
right there on his Apple MacBook. And
what he found out was the uh inference
and training costs were 80 times more
efficient than an Nvidia GPU, an A100.
Now, that's from some lone person
hacking into this. And Apple's obviously
not necessarily seen this example, but
they're aware that they have the most
bleeding edge chips. There is no
consumer tech hardware device that has
more premium components um making it up
than Apple's stuff. Like their supply
chain is just insane. So, I'm really
excited about that. The other thing is
what this unlocks is, in my opinion, um
what I'm calling a new era of
personalized intelligence. I think one
of the main challenges that AI has faced
today is that we're relying too much on
model labs which kind of results in a
more fractured experience. Like the
model doesn't know who we are. It keeps
asking us to tell us about ourselves.
And with this new chip architecture, you
can have a more persistent AI agent that
understands who you are, that is more
useful, that is there right with you in
the weeds as you're doing stuff on the
internet or on your computer. And that's
really bullish for me. I can't help but
imagine what it would look like if Apple
decided to really scale the
manufacturing production of these chips
and turn them on for AI training similar
to what Google did with their TPUs and
kind of have their specific hardware
accelerated version of these GPUs. I
feel like that would be a huge business
opportunity. But clearly they are not
taking advantage of this position
they're in because previously on an
episode a few weeks ago we spoke about
capex how much money these companies are
spending on scaling AI infrastructure.
This includes data centers. This
includes GPU powering the data centers.
All of the employees that are required
to make this happen. And the numbers
were staggeringly large. I mean between
what is this? Amazon, Google, Microsoft,
Meta, we have over $630 billion of
spend.
>> But Apple is only at 1.4, which is
actually down 19% year-over-year.
>> You see this bunch down here, Josh?
That's
>> it's like so sad and depressing. And
they're spending no money on scaling
this. And you have to ask like why what
is going on here? Um because clearly
they're in a position where they can win
if they double down on these things that
they're working are working well, but
they're just not doing it. And I wonder
if you have any takes on this of what
you think like what are these other
companies doing and why is Apple not
participating? So there's an optimist
take on this story and then there's a
pessimist take. The pessimist take is
Apple was asleep at the wheel and they
were not focused on AI. They completely
missed that rush and they fell behind
creating one of the leading intelligence
models when they are the most valuable
company. So Google, Microsoft, Amazon
and all these companies that you're
seeing on the screen here got way ahead.
Now the optimist take is this was all
planned because Apple's decision was
never to partake in the AI model race.
Apple's plan was to own the distribution
and operating system layer of AI, which
is hint hint what they did with cell
phones and the app store and iOS. And
they're doing exactly the same thing on
AI. So you could actually look at it as
Apple was so smart not wasting hundreds
of billions of dollars of their
hard-earned cash and instead pays Google
a billion dollars to rent Gemini and
then builds a an ecosystem right on top
of it. It's kind of genius if you think
about it. This is like the ghost of
Steve Jobs hand like looking over the
company. And actually, if you scroll up
on this post a little bit, it's it's
kind of me making fun of Apple and how
they've kind of accidentally stumbled
upon this miracle. And I would believe
the optimist case if in fact they didn't
totally fumble WWDC 2 years ago. Um,
there was a very clear intention to
deploy Apple intelligence throughout the
suite of hardware and to place
themselves into this AI race. It just
failed completely and catastrophically.
And had that not have happened, I think
I could have believed this optimist take
where they really are just being slow
and calculated. But I think this was an
accident. They just so happened to
create the best hardware in the world.
And it just so happens that all the AI
models need to run on hardware just like
this. It's kind of like Nvidia. Like
Nvidia accidentally became the most
important company in the world. And it
required a lot of execution along the
way and they deserve every bit of that.
but they were in a unique position to do
so. And I haven't seen any signs of
Apple doubling down to do so on the
software side at least. It's only been
on the hardware side and it's only
because this has been the trajectory
since 2021 when they first launched the
M1 chip. But it is interesting. I mean,
if we look at this chart um down to the
bottom of this post here, it shows the
increase in capex from everyone is going
straight vertical and Apple's spending
none. And yet the Mac minis are sold out
everywhere. You cannot buy one because
everyone's running OpenClaw on it. The
Mac Studios are running local models on
everybody's machines. The new MacBook
Pros are incredible. They're going to be
running models. I mean, there's just
everything is sold out. Everything is
backlogged. They can't make enough
hardware to support this. And something
is happening here. Like the market
forces are at play and they are saying,
"Apple, you are making great hardware.
Like, please do more of this." I I was
joking with some friends the other day
that um the only real threat to Nvidia's
hardware mode is Apple with their Mac
minis and with their laptops because
they're the second largest most valuable
company that comes behind them for a
reason because they're selling out all
their hardware. People can't get enough
of it. But consumers in particular use
it to run the AI models. Um on the
software side of things, listen, it's
not clear just yet, but I do think Apple
gets ahead for two main reasons. Number
one, they have like the largest
distribution ever. I believe it's 2.5 to
3 billion active Apple devices currently
in the world right now. It's it's
insane, right? So, if they wanted to,
they could switch on bleeding edge AI
via Google's Gemini or their own
fine-tuned version of that model to 2.5
to 3 billion people tomorrow, right? So,
uh they instantly become the most u or
the largest consumer mode for AI
immediately. But they're taking their
time. I believe they're building
something uh much more curated and
better than what we have today. Now, the
pessimist will say h they're slow.
They've been slacking and I would
probably agree with you. But hey,
they're the second most valuable company
in the world. They can take that time to
to wait and build something interesting.
That being said, um all these releases
are super cool, Josh. But there's one
thing that's nagging me at the back of
my head, which is uh Siri AI has been
delayed again. I do not know when I'm
going to get this, but it's already been
delayed what, a year and a half at this
point. This is, of course, Apple's
personal AI assistant, which is probably
going to be the conduit and the main
spokesman for all their Apple software
stuff. So, until I see that released,
I'm not going to believe that it's
actually happening. Yeah, I mean, the
the software part again, they they just
fumbled so hard. There's no denying it.
And there's no signs that they are going
to recover. I think the most bullish
thing they've done recently in terms of
software is just license out their AI to
Gemini. Clearly, Google can do an
amazing job and for a billion dollars a
year, Apple's getting access to Gemini
models and they're going to integrate
locally into perhaps not locally, but
they'll integrate them into all these
mobile devices. And that takes us to
this new weird place where like there is
a potential to shift the current market
forces based on this distribution that
you just mentioned that Apple has of
multiple billions of products already in
people's hands that are AI capable. And
this this is noteworthy. I mean, what
we're seeing with OpenClaw in
particular, it it kind of set the stage
for what how strong of a preference
people have to running these models on
actual hardware that they feel that they
own. A lot of people bought OpenCore,
not because they needed the compute to
run the models. That's not true. You
could do this on a $5 virtual private
server. They used it because it
connected with the ecosystem that Apple
provides. They used it because it can
query through their iMes
and it could FaceTime and it can use the
Apple suite of software. And that is a
really big deal. And that gets into this
this AI edge compute bullcase, which is
the idea that everyone needs GPT 6 7 8 9
10 served from OpenAI's cloud servers
might not be true for the majority of
the users that actually just want AI to
help them like figure out their grocery
store order and summarize their emails
for them. And there is a limit to the
intelligence that the average user will
actually need access to. And it would
seem as if a lot of these current models
have reached that threshold. Not
everyone needs to go cure cancer or
solve novel physics. And with that
understanding, we're at a moment now
where Apple's hardware, particularly
this new hardware, is able to run all of
these models that are capable of these
average use cases locally on device. And
that's a lot of users that will be using
this. And it may actually be like one of
the largest bare cases against companies
like OpenAI, like Anthropic, who rely so
heavily on customers paying money and
using the API fees because these local
models are becoming so highly
intelligent, so capable, and so small
that they could just run on an iPhone.
Yeah, I actually wrote about this at
length in um the essay that we just
dropped in our Substack. If you're not
subscribed, definitely go check that
out. It's in my opinion a banger and it
goes through everything that Josh just
covered. My thinking about models has
evolved pretty drastically over the last
month in the light of openclaw because
what I initially thought was openclaw
was just a bunch of open-source
techheavy developers that were just kind
of toying around and messing around with
something quite dangerous and then what
I actually learned was that the reason
why they were doing it was because it
led to a better AI experience overall.
And when you and I have tried out open
clone we have a bunch of episodes that
demonstrate this. we have just had a
much better experience like the AI
actually remembers you but can do so
many things for you and I think that's
where people are eventually going to
settle particularly consumers like yeah
okay we can talk to chat GBT but like I
wanted to now do stuff for that it's
much harder to do that if your AI
provider is open AI with their own
servers versus having an AI model
locally on your device so I do think
there's a larger trend which is going to
be around edge compute and local AI
devices and local AI models running on
your phone and on your laptop which will
lead to a more personalized experience.
I'm excited to see uh people take
privacy more seriously at this point
with openclaw. Some of the worst
examples of it was the agent would steal
your credit card info and spend it on
some random stuff or would go rogue and
burn up all your compute tokens. You
have more control and access over that
if you go through an Apple device that
might kind of give you a semi-private
experience that you don't have to expose
all that kind of data. If this trend
becomes true, then it completely uh
threatens Anthropic and OpenAI's mode
which have relied heavily on
subscriptions. Why would you pay $200 a
month on a claude subscription? I'm just
playing this the antagonist here if you
could get Frontier Intelligence for a
much smaller model that fits on your
mobile phone device that's a Quen model
that got released this week. Um, and
that can work with all your personalized
data. Why wouldn't you just do that?
It's a it's a no-brainer and I
understand the thesis behind it and I
think that's what Apple's going after.
>> Well, now we have to ask the question
are they capable of doing this and who
is going to get them to this place and
to do so uh we have to look at the
leadership. We have to go to the seed
suite first and that is thanks to poly
market who has prediction markets on who
is actually going to be responsible for
running the ship after Tim Cook leaves.
So, it's been widely rumored that Tim
Cook is going to be stepping down from
Apple to as CEO capacity sometime this
year. He's been there for a long time.
He's had an incredibly successful run,
but it seems as if the Apple seuite is
kind of grooming the next person. And
according to Poly Market, John Turnis is
going to be that guy. And this is
exciting because John Turnis is the VP
of I believe engineering hardware at
Apple. He's a hardware guy. He's the
person that has helped design, develop,
and lead these devices. and Poly Market
has him at what over 50% chance of
running the company. So if he does
actually become CEO, is there a world in
which he can push this company forward
in the sense that they can really double
down on this edge AI compute thing? They
could get these models running on all
the devices maybe. I think that would be
a really fun opportunity to see. Um, and
we really need a shakeup. Like Apple's
been so slow. They've been so boring for
so long that this would make a really
big difference. And also, there's
another market that shows the future
products that they're planning to
launch. And there's one that I think
surprises a lot of people, which is a
foldable phone before 2027 at an 84%
chance. So, by September of this year,
you will be able to buy a folding
iPhone, which seems a little bizarre.
Um, but according to Poly Market, this
is true. Thank you to Poly Market for
supporting and sponsoring this section
of the episode. And yeah, I think it's
just a testament as always to how Apple
is slow, but they are figuring it out.
And man, if they can get this foldable
iPhone that turns into an iPad, runs
models locally on your phone, it's gonna
be pretty cool. So, feeling bullish on
Apple in general. I mean, what do you
think this means for the valuation of
the company, EJ? Like, Apple as a stock,
is this are we still being theoretical
hypothetical or does this convert to
actual revenue dollars? Uh, I think it
eventually converts to revenue dollars,
but they're going to need to deliver on,
well, they delivered on the hardware
side, they need to deliver on the
software side. And that's typically
where Apple has really dominated the
consumer market. Yes, they built an
amazing iPhone, but they also uh killed
it with creating the best perfected app
that you can use on your phone and that
entire ecosystem for developers and
consumers on either side. So, they need
to pull off the same thing for AI. And
the challenge that they're going to face
is it's not the same as the internet
that we know today. It's going to be a
new operating system. You and I have
discussed multiple things on this show
before. We've discussed Plexity
releasing a new personal computer and
then OpenAI releasing an AI web browser
and all these random products um that
you and I don't really use anymore. It's
used for very niche things. And what
those attempts are getting at is trying
to rebuild an operating system around
this new weird technology that kind of
feels like magic, but is also kind of
dangerous. Um, and so Apple is the
company that's currently being presented
to solve that problem. My bet is they're
going to nail it. Um, at least within
the next kind of 2 to 3 years for two
reasons. One, they have the largest
distribution. I was mentioning earlier,
3 billion active devices. So it's easy
for them to kind of turn that on. Their
biggest threat actually might be Google,
but Google doesn't really have the best
experience of creating consumer
hardware, aka Google Glass. Uh there's
actually a new version of that coming
out in a few months time, but yeah, I
think Apple has the best shot of it.
Valuation wise, I actually think it's up
from here and they're currently valued
at what, like just under $4 billion or
just over four uh 4 billion 4 trillion.
Um and I think they're going to see
their kind of uh Nvidia type rise now.
Um, it wouldn't surprise me if they
actually compete uh with Nvidia for the
top spot once once consumer AI takes
off.
>> So, in summary, there is a lot of cool
new hardware that just came down the
pipe this week. There is probably
something for everyone. And the
noteworthy thing is this new kind of AI
angle that they're taking. They have the
accessible devices starting at $600.
They have the high-end devices like
these new MacBook Pros that go up to 7
$8,000, but that are capable of running
these really powerful, impressive local
models on them. Is that going to be
enough to actually start to detract away
from the market shares of these other
players like OpenAI and Anthropic? We
will see. We will be monitoring the
situation as always. But that is the
news as it relates to Apple this week.
It is a huge release in hardware. Are
they accidentally sleepwalking into
success or is this a tactical master
plan? We don't know. Perhaps the new CEO
John Turnis will tell us. But until
then, thank you so much for watching.
like each mentioned, he has a newsletter
about this, about local edge inference
uh that is releasing as you're watching
this episode. It's out. So, you can find
that on our Substack linked in the
description below. Another way that you
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