Imagine building the brain for a powerful AI
model. Not over months, but maybe in just a couple
of hours. Right. And doing it with something
like, what, 200 ,000 graphics cards? That sounds
like sci -fi, but it's actually happening now.
Welcome to the Deep Dive. Today, we're going
to unpack a really fascinating set of sources.
They focus on this rapidly accelerating world
of AI, specifically the intense battle that's
going on, sometimes behind the scenes, for computing
power. Yeah, and our mission today is to explore
what some people are calling the GPU arms race.
We want to understand what it means for big tech,
for everyone else. And then we'll dive into some
of the latest kind of surprising AI developments
that are popping up and shaping things. We'll
try to highlight what's really important here,
maybe how these shifts could impact you as you,
you know. navigate this incredibly fast -moving
landscape. So let's dig in. Okay, let's unpack
this first part. The core idea seems pretty straightforward,
actually. Training the biggest, most advanced
AI models. It now depends almost entirely on
who controls the most computing power. Simple
as that. It really is a new kind of arms race,
isn't it? But instead of weapons, it's silicon
and, well, massive amounts of energy. Exactly.
And the biggest player kind of stepping out into
the light right now, that seems to be XAI's Colossus
supercomputer. It's being called the Undisputed
Heavyweight, packing, get this, 200 ,000 H100
equivalent GPUs, graphics processing units. 100
,000. It's hard to even picture that. It's truly
massive. And what's really fascinating, maybe
even mind -bending, is this machine can apparently
train a model like GPT -3 in under two hours.
Under two hours, not weeks. Nope, not weeks or
days, hours. Beat, whoa. Yeah. I mean, just imagine
scaling that kind of training capacity. Think
about applying it to like a billion search queries
or way more complex tasks. It's kind of staggering.
That speed changes the whole development cycle.
Completely. It allows for super rapid iteration
experimentation, just fundamentally changes the
pace of AI progress. And it's not just XAI, right?
Other big tech players are scaling up incredibly
fast, too. We're seeing Meta, Microsoft, and
OpenAI, Oracle. They're all running these huge
clusters, 65 ,000 to maybe 100 ,000 GPUs. And
Tesla's definitely in the game, too, 50 ,000
GPUs for their Cortex Phase 1 project. And it's
interesting. Most of these top 10 players, the
ones we know about anyway, are based in the U
.S. Right. But, you know, what's really noticeable
is who's not on that public list. Google and
Amazon. Yeah, that's a good point. They're obviously
dominant forces in AI model development. Totally.
But they're suspiciously quiet about their own
supercomputer specs, given their history, their
investments. It feels highly likely they're building
huge clusters, too. Just maybe. In stealth mode.
Or guarding trade secrets very closely. It suggests
this foundational AI infrastructure is seen as
deeply strategic, which brings up a really important
question, especially when you look at the money
involved. The sources say the cost of building
and running these massive GPU clusters, it's
doubling every 13 months. Doubling every 13 months.
Wow. That's not just a big expense. That's an
accelerating financial strain, even for the biggest
companies out there. Even for them. And the sources
really emphasize this point. Whoever controls
these chips, this compute, they essentially control
the next wave of AI. Yeah, it's like the new
strategic resource, like oil refineries or maybe
fiber optic cables. These GPU clusters are that
critical infrastructure now. And that's probably
why you see national labs like Lawrence Livermore
also scaling up their own compute power pretty
rapidly. They see the strategic importance, too.
So thinking about these crazy costs and this
intense competition, what does this whole escalating
GPU arms race really mean for, say, smaller AI
innovators or startups just trying to get going?
Yeah, that's the big worry, isn't it? Is it creating
this kind of AI oligarchy? That's exactly the
concern. I mean, this rising barrier to entry.
It kind of implies that only the players with
the deepest pockets can really afford to train
and deploy these cutting edge frontier models.
It definitely pushes innovation towards them,
centralizing power. OK, so while that hardware
battle is clearly intense, AI's impact goes way
beyond just the raw compute, right? Let's maybe
pivot a bit now. Look at some broader ways AI
is reshaping things like policy or new creative
tools, even how we interact with tech itself.
Yeah, sounds good. So policy wise, there was
actually a pretty big move recently. The Trump
administration released this really extensive
AI action plan. Action plan. Yeah. And it's not
just some quick memo. It's apparently a huge
checklist over 90 different points, all aimed
at making sure the U .S. stays, you know, an
AI superpower. 90 points. That's comprehensive.
It is. And what's interesting is they apparently
shaped it using feedback from over 10 ,000 public
comments. So lots of different voices went into
it. That's quite a bit of public input. Yeah.
And alongside policy, there's also this push
to maybe democratize the building of AI. Exactly.
Like, look at GitHub Spark. It now lets developers
build and deploy AI apps just using prompts,
like plain English instructions. Just prompts,
not complex code. Right. Which is obviously super
appealing to the, what, 150 million programmers
already on GitHub. It basically turns coding
into more of a conversation. Lowers the barrier
significantly. Totally. And then you see these
incredible creative uses popping up. There's
an AI filmmaker, Lu Huang, who showed 10 really
top tier examples of using JSON. JSON. OK, that's
a data format, right? Makes things easy for chatbots
to read. Yeah, exactly. Using JSON to generate
these stunningly realistic, really polished commercials.
quality is wow it shows ai can handle seriously
complex creative work now that's impressive and
if we connect that to how we interact with technology
meta seems to be taking a pretty bold step Kind
of like Neuralink, but different. They've got
this AI wristband. Yeah, I saw that. It's designed
to decode signals in your wrist nerve signals,
basically to let you control devices with just
tiny little hand gestures, almost invisible ones.
So like minority report, but subtle. Kind of.
It's definitely a big step towards making human
computer interaction much more seamless, more
intuitive, like tech becoming an extension of
your thoughts. Imagine the possibilities there
for accessibility, for just efficiency. For sure.
And speaking of big moves. OpenAI looks like
the next big thing is GPT -5. Expected maybe
early August. GPT -5, okay. What's the word on
that? Is it just a bigger GPT -4? Doesn't sound
like it. It's described more as combining the
powerful tech stuff from the GPT series that
we know with their O -series models, like O3,
which seem more focused on real -time, maybe
multimodal interaction, seeing and hearing. Perhaps.
So not just text, more integrated, more perceptive.
That seems to be the idea. So you won't just
see it as a text model like GPT -4 was initially.
It's expected to be a more. evolved system. Could
change how we interact with AI quite a bit. Okay.
Interesting. And one more on the business side.
Yeah. Legalon. It's an AI legal tech company.
They just raised another $50 million for their
tools. $50 million. What do their tools do? They
help with legal work, specifically contract review.
Apparently they're already used by 7 ,000 organizations.
And get this, they speed up contract review by
85%. 85%. That's... Massive efficiency gain,
right? They already serve like a quarter of Japan's
public companies and they're expanding fast.
So clear, tangible impact in a field that's usually
kind of slow to change. Okay, so with all these
things happening, the policy, the building tools,
the interfaces, the business applications, how
quickly do you really think these new AI tools
could fundamentally change our day -to -day work?
our professional lives? I think very fast, honestly.
Many of these seem designed for immediate practical
use. They slot right into existing workflows,
so the impact could be felt quite quickly. Okay,
let's dive into maybe a few quick hits now. Things
from the AI world that just kind of caught our
eye, sparked some curiosity. And then let's end
with something truly remarkable, connecting AI
to human history. Sounds great. Yeah, a few things
popped out. There was a funny piece. Someone
asked an AI if their job writing humor was at
risk. Kind of meta, right? Chuckles softly. Yeah.
And I'll admit it, I still wrestle with prompt
drift myself sometimes, you know, where the AI
kind of slowly forgets what you originally asked
it to do. So, yeah, I get the anxiety. It's a
real thing. We also saw this alert from scientists
sounding a pretty light alarm, actually, saying
AI might soon get smart enough to outsmart our
current safety checks. That's sobering. It definitely
raises some immediate concerns. Yeah. On a lighter,
more practical note, Google's got that new AI
feature, right? Let's you... Virtually try on
clothes you see in search results. Oh, yeah.
The virtual try on. That could be a game changer
for shopping online. Make it way more interactive.
And Google's also rethinking search itself, aren't
they? With this new AI curated web guide. Yeah.
Trying to get more synthesized answers, not just
links. Right. Moving beyond just keywords. We
also saw this really interesting comparison.
Someone gave the exact same complex financial
task to an AI and a human financial planner.
Oh, how'd that turn out? out well it just really
highlighted their different strengths you know
the ai was amazing at crunching the data finding
patterns the human brought in like nuance emotional
understanding strategic thinking about life goals
different approaches fascinating comparison okay
but here's the one that really got me connecting
ai to our past google deep mind quietly released
something called Aeneas. It's fully open source.
And it's pretty groundbreaking. What it does
is it reads, analyzes, and actually reconstructs
ancient Roman texts using images of fragments,
bits of text. Wow. Wait, so you feed it like
a picture of a broken stone tablet with faded
letters. Exactly. Maybe just a blurry photo.
Incomplete inscription. And Aeneas pulls from
this huge database like 176 ,000 ancient writings.
And then it intelligently guesses where it might
be from, when it was likely written, and crucially,
what it used to say. That's incredible. How accurate
is it? The numbers are pretty remarkable. It
gets 72 % accuracy assigning inscriptions to
the correct Roman province. 72%, okay. And it
restores the broken or missing text with 73 %
accuracy. Wow. And maybe just as important, 90
% of the historians who tried it said it significantly
boosted their confidence in their own research
by like 44%. That's a huge endorsement from the
experts themselves. And here's the kicker. It's
totally free and open source. Open source. So
anyone can use it. Adapt it. Yep. Researchers
can download the model, fine tune it for their
specific projects, maybe even adapt it to other
ancient languages. That's amazing. It really
raises this important question, doesn't it? How
AI? through tools like Aeneas could just unlock
vast amounts of human history, stuff that was
basically inaccessible or would take lifetimes
to piece together before. Yeah, definitely. So
thinking about that open source aspect, could
Aeneas or tools built like it potentially unlock
other forgotten historical texts, maybe even
decipher completely lost ancient languages? Oh,
absolutely. I mean, it's open source nature is
practically an invitation for that, applying
it to different scripts, different cultures.
Yeah, it could potentially reveal countless historical
insights we just don't have access to right now.
Sponsor. OK, so let's try to pull this all together.
What does this all mean for you listening right
now? We've seen today that this AI boom It's
not just about clever software. It's deeply tied
into this really high state's global arms race
for raw computing power. And this battle, it's
driving innovation like crazy, but it's also
creating these immense financial pressures, these
strategic pressures. Right. And if we connect
that to the bigger picture, AI isn't just about
the hardware, the compute power. It's rapidly
transforming almost everything from how governments
make policy to how commercials get made, even
down to our fundamental ability to like. preserve
and understand ancient history. It really feels
like a foundational shift happening across so
many different areas. It's redefining what's
even possible. So as you think about all this,
there's maybe a question to mull over, a provocative
thought. As these AI models keep getting bigger
and bigger, demanding more and more resources,
where do you think the physical infrastructure
is actually going to end up? The chips, the massive
amounts of energy needed, these enormous data
centers. where will they physically be built
in the future? Yeah, that's a big question. And
how might that geographical concentration, wherever
it ends up being, how might that shift global
power dynamics in the years ahead? That's definitely
something worth pondering as you, you know, engage
with this AI world unfolding around us. Hopefully
this deep dive gave you some valuable nuggets
to think about. Thank you for joining us on this
deep dive into the latest in AI OTRO music.