Did you know that where you live might significantly
predict how much you use artificial intelligence?
Yeah, it's kind of surprising. And maybe even
more surprisingly, who's really winning the global
AI race? Well, it might just challenge what you
think. Or imagine this, typing out messages easily
just by thinking them. Wow. It's not science
fiction anymore. It's actually happening. Today,
we're looking at a really fascinating exploration
of the very latest in AI. From all angles. Exactly.
Yeah. From the uneven global landscape of adoption.
Yeah. All the way to this kind of mind -bending,
brain -like computing that could totally redefine
our tech future. Yeah, some big shifts potentially.
Lots to unpack there. Our mission, like always,
is to pull out the most important nuggets, give
you a shortcut to being really well -informed
without all that info overload. Let's do it.
So let's dive in. OK, we're kicking off with
some really compelling data. This isn't just
theory or predictions. Real world stuff. Anthropic.
You know, the team behind the AI model, Claude,
they just put out this massive usage report.
It's based on over a million anonymized conversations
from just August this year. So very recent data.
Exactly. Yeah. This is what's actually happening.
Who's using AI right now and how? And the findings?
Well, they're pretty stark. The landscape is
anything but uniform. Super uneven, actually.
How so? If you look at the U .S., you've got
these power users really clustered in places
like California, D .C., Utah. Usual tech hubs,
maybe? Sort of, yeah. But then many southern
and plains states noticeably lagging behind.
Okay. And it's not just a U .S. thing. Globally,
the differences are even bigger. Countries like
Israel, Singapore, Canada. They're way ahead
in adopting AI. Way ahead. But then nations like
India, Nigeria, and frankly, most lower income
countries are trailing significantly behind.
So it's definitely not a uniform way of washing
over everyone. Not at all. It's a fascinating
picture, isn't it? Yeah. And this data really
matters because, well, where AI is heavily used
today kind of previews. which tasks, maybe even
jobs, it might start to augment or replace tomorrow.
Yeah, it's a leading indicator. And this feeds
directly into that whole productivity gap discussion,
right? That growing difference in output between
people or companies using AI effectively and
those who aren't. Absolutely. And what's really
striking, maybe even counterintuitive, is that
high skill workers seem to be benefiting the
most right now. Not necessarily leveling the
field then. Not yet, it seems. They're using
AI to fill knowledge gaps faster, speed up decisions,
basically multiply their output. So instead of
closing the gap, it's actually widening it. It's
amplifying the advantages for those already kind
of ahead. That's quite a finding. Not the narrative
we often hear. And I do appreciate Anthropic
being transparent here. They didn't just publish
the findings. They actually open sourced the
data set. Oh, that's great for researchers. Yeah.
And they introduced something called an AI usage
index, basically a tool to track how AI spreads
over time in different places. That'll be useful
for policymakers, too, I bet. Definitely. Provides
some real data to work with. So thinking about
this really uneven global adoption, what does
that tell us about AI's immediate impact on different
economies? Well, it strongly suggests AI will
probably deepen existing divides before it starts
leveling things out. Yeah, that's a sobering
thought, the whole divide thing. But while those
big trends play out, let's pivot. Let's look
at the sheer speed of innovation happening right
now. Okay, some rapid fire stuff. Exactly. Our
Today in AI segment, get ready for some pretty
wild things. First up, a founder actually built
a $100 media brand completely solo. Solo? How?
Using an AI agent. Now, an AI agent, just so
we're clear, is basically software that acts
on its own to do tasks. Right, autonomously.
This one scrapes news, writes content, makes
videos, even posts everything. That's incredible.
One person doing the work of a small team. Pretty
much. It just completely changes the game for
entrepreneurs, you know. It really does. Lowers
that barrier to entry significantly. What else
is catching your eye? Okay, then there's this.
Almost telepathic wearable. Uh -oh, sci -fi alert.
Feels like it. It's being called the world's
first wearable that lets you speak without moving
your mouth. Wait, what? or type messages literally
at the speed of thought, beat. Whoa. Just imagine
the possibilities there, especially for communication
accessibility. It's a huge leap, right? And yeah,
early access is already open for it. That feels
like something straight out of a movie. Okay.
Bypassing traditional input methods entirely.
Totally. You wonder about the learning curve,
the practicalities. Right. But the potential
is just massive. Yeah. The rollout will be fascinating.
And for creators, VE'd just launched Fabric 1
.0. VE, the video platform. Yep. It's an AI talking
video model. It can make these emotional one
-minute videos. Apparently seven times faster
just from a single photo. From one photo. How
realistic does it look? Surprisingly realistic.
It's really blurring those lines. Also, gamma
that AI presentation tool. Oh, yeah. Heard a
lot about them. They just hit $50 million in
annual recurring revenue. In under two years.
Wow, that's fast growth. And their co -founders
even shared their growth playbook, which is pretty
cool. Nice. Then switching gears to robotics,
Dyna Robotics raised a huge $120 million from
big names like NVIDIA and Amazon. For what specifically?
For their AI -powered robot arms. It's part of
this massive robotics boon, like $12 .1 billion
invested just this year. It's clear the money
and the innovation are just pouring in everywhere,
isn't it? Absolutely exploding. We also saw OpenAI.
And Harvard put out that big report on chat GPT
usage. Yeah, the largest public one ever, I think.
Right. Showing common queries, how people really
use it. And Google, DeepMind's CEO, hinted at
the number one skill needed for this AI world.
What was it? Didn't say explicitly, but the hint
points towards not just using AI, but really
effectively directing it. Judgment, prompt crafting,
that kind of thing. So all these different innovations.
How do they reshape our daily interactions, our
work lives? They're pushing us towards faster,
more intuitive, highly automated ways of doing
things, demands new skills. Building on that,
let's shift focus now to practical applications.
Powerful new tools for automation and... Maybe
more excitingly, creative work. Yeah, where the
rubber meets the road for a lot of us. Exactly.
Okay, so for folks deep into automation, there
are these new NAN workflow guides. NAN. Remind
us what a workflow is in this context. Sure.
An NAN workflow is basically an automated sequence
of tasks. It connects different apps and services
together to do something automatically. Got it.
Like Zapier, but maybe more complex. Yeah, often
more customizable. So there's a guide on evaluating
these workflows using actual test data to optimize
them. No more guesswork. That sounds useful.
Data -driven automation. And for the finance
crowd, there's another guide showing how to build
a no -code NAN workflow to analyze crypto, forex,
stocks. All automatically. Bringing automation
to personal finance analysis. Interesting. Yeah,
bringing precision. You know, honestly, I still
wrestle with prompt drift myself sometimes. Oh,
yeah. Explain it. It's that subtle thing where
the AI's understanding of your instructions kind
of shifts over time, even if you use the same
prompt, keeping it consistent. It's a constant
effort. So crafting those prompts and optimizing
the workflow is key. It's a skill we all need
to keep honing. Definitely. Like trying to get
a puppy to consistently fetch the right stick.
That's a good analogy. It really does highlight
that shift from just using AI to like mastering
the art of directing it precisely. And speaking
of crafting things, Google's apparently got a
new AI image tool that's making pro photo editors
a bit nervous. Oh, yeah. This one's a potential
game changer. It's incredibly powerful. How so?
You can basically go from a simple selfie to
something looking like a polished magazine cover
just by typing commands. Seriously, like make
my hair look better or change the background
to Paris. Pretty much, but much more sophisticated.
It interprets complex text commands to build
and manipulate visuals. High -level editing becomes
super simple. Wow. So it really democratizes
that kind of high -end visual work. Absolutely.
But, you know, also raises questions about traditional
photo editing roles. And we're also seeing a
flood of what we're calling new empowered AI
tools just popping up constantly. Yeah, a whole
ecosystem. Things like admin tools offers over
125 administrative tools. in one place. Handy.
Cliptery, which claims to turn a script straight
into a YouTube video. Script to video, getting
better all the time. Summa AI for generating
personalized LinkedIn posts based on news. Keeping
that feed active. And Prompt Prism, this one
takes your, like... messy ideas and turns them
into detailed prompts for advanced video models
like VO3. So helping with the prompt crafting
itself. Exactly. That's the core of prompt engineering,
right? Crafting those precise instructions to
get the AI to do exactly what you want. So how
do these tools democratize these complex AI capabilities?
How do they empower everyday users? They basically
make sophisticated tasks much more accessible,
even if you don't have deep technical skills.
Okay, let's do a quick run through some AI quick
hits, get a feel for the industry pulse, maybe
the human side of things, too. Sounds good. What's
buzzing? Well, Sam Altman, OpenAI's CEO, admitted
recently he hasn't slept well since GPT first
launched. Wow. Gives you a sense of the pressure,
huh? Totally. The immense stakes involved there.
And speaking of open AI, China's Tencent just
poached one of their prominent researchers. Oh,
ooh, the talent wars continue. Fiercely competitive.
Then, on a lighter note, Gemini had this funny
moment failing to make a seahorse emoji. Made
it seem like it briefly lost its mind. Happens
to the best of us, I guess. Even AI needs a moment.
Right. But then, kind of surprisingly, Gemini
actually overtook ChatGPT as the top iOS app
for a bit. Really? Mostly due to this weirdly
viral banana moment it had. You just can't predict
what captures the public's attention sometimes.
The Internet is strange. Tell me about it. And
for the developers out there, OpenAI upgraded
GPT -5 codecs. That coding model. Yeah. Enhanced
capabilities for writing code, debugging, all
that jazz. So continuous progress under the hood.
Looking at these little snippets, what do they
reveal about? the human side of AI development
beyond just the tech. They really show both the
intense pressures and the sometimes unexpected,
almost quirky challenges in this whole AI race.
Okay, now here's where things get, I think, really
interesting. Potentially paradigm shifting. We've
talked a lot about current AI models, the ones
most people know, but there's this fascinating
AI view coming out of China. Spiking Brain 1
.0. Ah, yes, this is huge. And it seems to directly
challenge the whole NVIDIA stack dominance we
see everywhere else. It absolutely does. This
could be a monumental development, seriously.
Chinese researchers unveiled this completely
new neural -inspired AI system. Neural -inspired,
meaning? Right. It literally mimics how our actual
brains process information. And here's the kicker.
Okay. It runs entirely on Chinese Medic X chips.
Zero reliance on NVIDIA hardware. None. Wow.
So completely independent silicon. Exactly. That's
not just an engineering achievement. It's a massive
strategic play for technological sovereignty.
So how is it fundamentally different? How does
it work compared to, say, GBT -4 or Gemini. OK,
so most current models work token by token, right?
They process information sequentially, like reading
word by word. Right, piece by piece. Spiking
brain 1 .0 doesn't activate the whole model for
every token. Instead, it mimics how neurons in
our brain fire selectively. Only the needed parts
activate. Ah, like only using the relevant brain
cells for a specific thought. Precisely. It's
called a neuromorphic approach, computing inspired
directly by brain structure and function. And
they've already trained pretty big models, 7
billion and 76 billion parameters, using this
architecture. That's impressive scale for such
a different approach. It's not just a lab experiment,
then. Definitely not. And the efficiency gains
are just staggering. How efficient are we talking?
Get this. It used less than 2 % of the training
data standard models need, but it matched their
performance on core language tasks. Less than
2%. That's incredible. And it was stable. Ran
for weeks without crashing. But here's the real
headline number. Go on. On a massive 4 million
token prompt. That's a huge amount of text. It
ran 100 times faster than traditional models.
100 times faster. 100 times. Whoa. Just imagine
scaling that kind of efficiency. It's like stacking
Lego blocks of data compared to, I don't know,
building with bricks. It completely changes the
economics and speed of AI. 100Xs. That's almost
hard to comprehend in this field. Yeah. That's
a generational leap, not an incremental one.
And I heard there's a public version people can
try. Yes. Incredibly, they released a public.
version called shunxi it's free to test online
and it runs on fully hosted on those chinese
medic x chips it's a direct real world demonstration
look we can do this entirely without us tech
that's a powerful statement It really is. It
feels like maybe the mouse moment for brain -like
computing, the very beginning of something potentially
huge. And it makes you ask, where are Meta's
or OpenAI's neuromorphic projects? You have to
assume they're working on something similar,
right? So how might this kind of brain -like
computing, like spiking brain 1 .0, fundamentally
alter the AI development landscape and maybe
global tech power? It really promises vastly
more efficient, maybe even self -sustaining AI
that could dramatically shift the geopolitical
tech balance. Sponsor. Mid -roll sponsor read.
So as we wrap up this deep dive, it seems abundantly
clear AI is transforming things incredibly rapidly.
But it's crucial to see it's not a uniform way
washing over everyone equally. Definitely not.
We've seen these stark divides in global adoption.
It highlights who's benefiting most right now
and worryingly where existing gaps might actually
be getting wider. The productivity gap issue.
Exactly. Yet at the same time, there's this absolute
explosion of innovation. Across everything from
personal tools, letting one person build a media
empire. Yeah, the solo founder example. To entirely
new computing architectures like China's spiking
brain 1 .0, challenging the very foundations
of how we've been building AI. It's a fascinating
contrast. It really is. The global AI race clearly
isn't just about features anymore. It's about
fundamental approaches, efficiency, and increasingly
national technological sovereignty. It's complex,
dynamic, and just moving incredibly fast. The
pace really is immense, isn't it? We're seeing
breakthroughs almost daily that make you rethink
what's even possible. Forces you to constantly
recalibrate. Constantly. And it makes you wonder,
right, if AI can mimic our own brain's processes
this efficiently, what new insights might that
give us into human intelligence itself? That's
a deep question. What comes next? When we really
understand how to build intelligence inspired
by biology, not just simulate it. Lots to think
about. Indeed. Thanks for diving deep with us
today on Tiro Music.