Welcome to the AI Chat Podcast. I'm your host,
Jaden Schaefer. Every day I cover cutting -edge
AI news and talk with the leaders behind it,
breaking down what it means for your life and
business. Anthropic is building their own custom
silicone team to design their own AI chips, and
AMD has just unveiled something called the Helios
Rack system. Their goal is to challenge NVIDIA
head -on in AI data centers. Anthropic is upgrading
Claude's voice mode. It's going to be now running
on Opus and Sonnet. And Google Cloud Revenue
jumped 82 % to $24 .8 billion. If anyone has
been following Google for the last few weeks
when they've released how much their AI spending
is and their stock took a massive hit, well,
evidently, this is the reason why they announced
that. OpenAI and Anthropic are both lobbying
Washington to curb Chinese openweight AI. We've
talked about this a lot on the podcast, but this
is kind of the latest news on the lobbying front.
If you want to get a deep dive on these and a
dozen more stories every single day, I'd love
for you to check out AIChatDaily .com. That's
my own sister website, news site that is partnered
with this podcast. It's essentially like a show
notes, but it also goes deeper and has extra
stories I don't cover in here. There's dozens
of stories. every single day on all the latest
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AI news stories straight into your inbox to keep
you up to date with everything happening in AI.
And you get some really quick breakdowns of all
of the facts so that you understand what's going
on. The website is AIChatDaily .com. The first
story I wanted to talk about is the fact that
Anthropic is building their own AI chip design
team, and it's going to be for creating custom
hardware for Claude. It's the same thing that
OpenAI, Google, and Meta, they're all doing it
right now. And the big reason is everyone wants
to get off of NVIDIA. These companies are incredibly
dependent on NVIDIA. NVIDIA basically has quotas
and they dole out their GPUs and their chips,
and they only give a certain amount to different
companies, and nobody wants to feel bottlenecked
by one player that they're obviously spending.
a ton of money on. So everyone's building their
own chips. Right now, they're also scouting Samsung
as a manufacturing partner, which is ending Anthropic
status as the basically the last major AI lab
without a public silicone program. They're like,
all right, it's time to get serious on that one.
Anthropic currently relies on a bunch of different
suppliers. So there's AWS, Google, NVIDIA, AMD,
all of them give them compute. But of course,
that means that they don't get to control the
pricing allocation. or any of the roadmap timing.
OpenAI shipped their Broadcom designed chip,
which is called Jalapeno. It's an inference chip,
and that was in June of this year. Google now
runs their own TPUs. Meta is building MTIA accelerators.
And Anthropic basically was the only one that
wasn't working on this. Custom silicone typically
takes between 18 to 24 months to design, and
it's going to cost hundreds of millions of dollars
per chip version. But every single efficiency
gain that they can get on this compounds across...
billions of dollars that Anthropic is using for
these Claude API calls. So I think this is something
that is kind of a play on margin. It's not a
shortcut. This is going to take a long time.
Anthropic can tune memory and math formats to
Claude's exact workloads in a way that no off
-the -shelf GPU can really match. But they're
also betting on a two -year runway before any
of that investment is going to get paid back.
So this isn't something that's very quick, but
over the long run, this might be a good play
for them. After announcing a strategic partner,
with in Anthropic. AMD has just unveiled Helios,
which is a rack system for AI data centers, and
they're saying that this is basically a direct
competitor to NVIDIA's products that they have
right now. Microsoft, OpenAI, Meta, Oracle, and
Anthropic have all committed to deploying it
at a gigawatt scale, and it's going to be starting
shipments later this year. Anthropic and AMD
both announced a strategic partnership to deploy
up to two gigawatts of GPUs on Helios, which
is, you know, the exact same scale of Nvidia's
largest AI training cluster. So they're, you
know, they're really being quite competitive
in the market. AMD also introduced Venice X,
which is a data center CPU designed to pair with
Helios. And that's going to be launching in 2027.
And it's going to compete on kind of this full
stack alternative to a lot of the different competitors
that are out there. The CEO, Lisa Su, projected
the AI accelerator market will reach 1 .4 trillion.
by 2030, approaching the size of today's entire
semiconductor industry. So, you know, this one
segment of the market she's saying is going to
be as big as the entire semiconductor industry.
This is the first time that AMD has landed all
five major frontier AI labs on a single rack
platform. They have everyone signed up for it.
I think this is showing that they're really like
a strong contender for a quote unquote second
place option for a lot of these massive AI infrastructure
buildouts that are coming up. The scale of all
of these different deals. that they've done with
these five hyperscalers. I think they're all
measured in gigawatts, and I think that shows
that the hyperscalers are, all of them are ready
to diversify away from NVIDIA's almost complete
dominance. So it looks like we're having a real
second player in the market, and AMD is gonna
get some serious market share. Does that, you
know, is that like super bad for NVIDIA? I think
their market is just gonna keep growing like
crazy, but there are other competitors now. Anthropic
is upgrading Claude's voice mode. It's now gonna
work with their most powerful models, Opus and
Sonnet. So I think in the past, it was only working
with Haiku. And I will say one thing that I actually
did appreciate about this was I've been going
back and forth between OpenAI and Anthropic as
far as using like Cloud Cowork and ChatGPT work.
And I did find that ChatGPT work after they did
their upgrade and everything's running on Sol
5 .6 extra high. When I go and ask it to complete
a project for me and I'm doing the voice mode
on it, it takes a while for it to kind of transcribe
and write it all down. And it's actually kind
of annoying. the the leg it's a few second leg
and i noticed that it doesn't always happen but
when you have uh soul 5 .6 extra high on it does
and so i actually appreciated that um anthropic
when i was using claude it was like instantaneous
transcription of what i was doing it was all
on haiku now is it perfect is it the is it the
best like there's a couple things that i might
mess up but it was instantaneous and super fast
well they're going to upgrade it because evidently
they think that it needs to be a little bit higher
quality so now they're putting it on opus and
sonnet i hope they don't sacrifice too much the
speed because honestly, that was my favorite
thing. They're going to be able to they're allowing
you to plug that directly into Gmail, Google
Calendar, Slack, Canva, Notion. So you can now
tell Claude by voice to do your emails. I mean,
everything else that you've probably been doing.
I even have like a literal I have this device
from OpenAI. It's like a little keyboard. It
is, I think, built with work louder. And it literally
just has a microphone button that I push. So
I this is the way I've been working a lot lately
is just talk. to these models and having them
go and complete tasks for me instead of typing
it out. I think that's what a lot of people are
doing. There's a lot of software like Whisperflow
that's out right now that does that kind of stuff.
So a lot of different options, but Claude obviously
decided they wanted to put a big upgrade here.
Voice mode is now going to default to whatever
Claude model you last used in text chat. So a
Sonnet workflow is automatically going to have
that for the audio, which is kind of what OpenAI
is doing right now. And I'm not going to lie.
That's actually. annoying to me. I wish you could
choose the audio. Honestly, what I find is when
it does the transcription and when it types it
out, I would actually rather a faster, worse
model because you can like many times I'm literally
using Apple's like voice to text, which is really
ghetto, not very good. And when I when I do it,
there's like a bunch of typos, but Claude understands
and it literally fixes it and does everything
the way I want. So I find that Claude is very
good at getting the meaning out. I'd rather just
have the underlying model better and having.
the voice transcription faster because I absolutely
hate talking and then waiting five seconds for
it to type out before I can hit send. But I mean,
that's just me being impatient. So I guess the
quality improvement is probably good, but I wish
they would let you choose in the settings what
model was powering your voice. Free users are
going to keep getting haiku. So maybe I got to
go switch to being just a free user. Just kidding.
And there's going to be paid users that get the
Opus and Sonnet and all of the rest of it. They
have a lot of different languages supported on
this, by the way, English, French, German, Hindi,
Japanese. korean spanish um and it you know of
course auto detects it so that's fantastic Google
Cloud revenue is up 82 % to $24 .8 billion last
quarter. That absolutely crushed the expectations
that Wall Street had. I think it's proving that
the company's huge AI spending is actually paying
off. The $514 billion backlog of signed customer
contracts, I think is showing that there is a
huge demand for AI infrastructure and service
is real and it's locked in for years. So a lot
of these deals that Google Cloud's doing, it's
not just for this year or for this month. month,
but these are multi -year deals. Cloud growth
is accelerating really fast. It's up from 63
% last quarter to 82 % this quarter. It's mostly
driven by a lot of different companies renting
compute power and buying pre -built AI products
from them. Gemini reached 950 million monthly
active users. That's up from 750 two quarters
ago. So the usage of their own products is accelerating,
but also the amount of companies signing deals
to power their AI on their infrastructure is
also increasing. seen. And Alphabet posted 112
.1 billion in quarterly profit. That's almost
four times the 28 .1 billion from the same quarter
last year. That is wild. 112 billion. up to 21
billion just one year later that's absolutely
insane google's 180 billion to 190 billion dollars
in annual spending on data centers and chips
is now um you know it's something that kind of
crashed their stock a couple weeks ago when it
came out and everyone was like oh my gosh google's
overspending but i think this is showing there
is serious demand the demand is accelerating
like crazy um they know they're going to get
that money back and so i think they expect that
2027 is going to be when this massive build out
starts turning into some real cash generation.
But in order to get that money, like they have
to spend, they got to spend the money to make
the money, but they can see a lot of demand.
So evidently they're going all in. OpenAI and
Anthropic are both lobbying US regulators to
restrict Chinese openweight AI models like Moonshot's
Kimi. You know, K3 came out a while ago and it
was all the rage. And then we have the latest
Quen model came out a few days ago. What they're
saying here is that there are national security
concerns. They, of course, are saying this at
a time when it would be quite convenient. It
would push these companies towards, you know,
being the winners in this space. No one could
really dethrone them. None of these open source
models could go scorched earth on them. Opening
eyes, Dean Ball argued the U .S. should create
regulatory fear uncertainty and doubt around
open weight models to weaken their competitive
position um and then he kind of walked that argument
back but that was like his first thing we've
heard this in crypto a lot back in the day the
fud um that he's you know openly saying that
they should create some fud and he's like no
no actually it's serious it's not it's not just
fud for for fud's sake Kimmy's launch at the
end of last month, I think a lot of people were
panicking. There was a viral demo showing it
generating a macOS -like UI mockup in 30 minutes.
I think a lot of the hype faded after that. A
lot of these demos are like, oh my gosh, look
at this crazy, incredible thing. And then once
it actually comes out and people actually play
with it, they're like, okay, it's not as crazy
as it seems, which is why I'm actually a little
skeptical. I mean, whatever, you can say I'm
dumb, but it's why I'm a little skeptical of
like, uh anthropic always hyping up their models
to an insane degree only giving them to enterprises
not to the regular people and saying look it
can do all these crazy things I don't know, it
makes me skeptical when they won't give it to
you, but maybe it's truly dangerous. I don't
know. This is the second time that we've had
in the last under a year, basically, where we've
had this kind of cycle where there's a huge cheaper
model that comes out and it's super capable.
DeepSeek had something that kind of was along
these lines. And then afterwards, there's a bunch
of policy restrictions that people were calling
for after it came out. So I think we're seeing
basically the same pattern play out over and
over again. Chinese labs are going to ship like
a super cheap open. model. It's going to be really
competitive in the benchmarks. A lot of the American
executives are going to start warning about security
and regulation and we need to have restrictions.
And of course, the people that are really winning
are those big closed model companies, OpenAI,
Anthropic, etc. So I think whether those security
concerns are legitimate or not, it doesn't change
the fact that all of the people asking for these
policy changes happen to be the people that are
going to be winning from it. So I am a little
bit skeptical of it, if I'm being honest. And
I actually think open weight models are fantastic
for innovation. And like for my own company,
being able to use a model that's 90, you know,
90 % cheaper, 90 times cheaper than an open or
than a closed source model, if it can do some
of the same tasks that we needed to get down
on a repeated basis. To me, that makes a lot
of sense. But There's a lot to debate on this
topic for sure. Guys, thank you so much for tuning
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