So is AI actually coming for your job? Or maybe
is it creating totally new ones, things we can't
even picture yet? And what happens when the internet
itself, you know, the global network we rely
on starts to kind of break apart? Beep. Welcome
to the Deep Dive. Today we're digging into a
really fascinating set of sources, mainly a recent
newsletter that caught our eye. Our goal here
is simple. Give you the essential insights, a
shortcut really, to understanding the big AI
trends shaping things right now. We'll cut through
the noise, connect the dots for you, and get
you up to speed without the usual information
overload. Exactly. And for this deep dive, we're
starting with Goldman Sachs. They've got this...
surprisingly nuanced view on AI and jobs. Then
we'll jump into some really cool and maybe slightly
weird AI highlights. Think AI influencers going
viral, leaked prompts, that sort of thing. And
finally, we'll tie it all together. Look at the
bigger picture, the geopolitics of AI, and yeah,
even where it's completely blocked. It's quite
a landscape. Okay, yeah, let's unpack that first
part. For months, all the talk has been about
this AI jobpocalypse, right? Like massive unemployment
is just around the corner. But this Goldman Sachs
research, it paints a much more, well, Subtle
picture. It isn't just yes or no on jobs. It's
more like, yes, some jobs change or go away,
but only for a bit. new ones get created. Right.
And what's really interesting is how they lean
on history. They're saying, look, roles will
shift. Yeah, definitely. Productivity will probably
spike. But crucially, new kinds of work will
pop up. It's basically a pattern we've seen before.
Think steam engines, you know, or the Internet
itself. History shows like 60 percent of the
jobs people have today didn't even exist back
in 1940. Technology keeps doing this, gets rid
of old roles, invents new ones. So how big is
this disruption then? What are the actual numbers?
Well, Goldman Sachs estimates for the U .S. maybe
a 6 % to 7 % risk of jobs being displaced if
AI fully scales up everywhere. But right now,
today, it's closer to 2 .5 % risk just based
on current AI getting used a bit more. And they
only predict about a 0 .5 % temporary rise in
unemployment during this shift. They call it
frictional short -term stuff. They figured it
should sort itself out in about two years. So,
yeah, maybe not quite the catastrophe some headlines
suggest. And that leads to the big question,
right? Which jobs? Who's most affected? Goldman
points to roles with lots of repetitive tasks,
information processing. Think programmers, accountants,
admin assistants, a lot of customer support roles,
high exposure there. On the other side, low exposure
jobs. Those tend to need complex physical skills
or really nuanced human judgment. So air traffic
controllers, radiologists, pharmacists, even
CEOs, actually. AI can help them, sure, but it
can't really replace that core strategic thinking
or human touch. Not yet. And despite all the
chatter, you know, the actual use of generative
AI in companies is still, well, it's pretty low.
The research says only about 9 .3 % of U .S.
firms are really running it in production right
now. But even with that, we are seeing an early
impact. Unemployment for people in their 20s
and 30s in those AI exposed jobs, it's ticked
up about three points this year in 2025. So while
full adoption isn't here, the initial waves are
definitely making ripples. Yeah. And if you zoom
out, Goldman's basically saying AI is a big disturbance,
a market shift. And what happens in big shifts?
The small, agile ones move fast. They find the
new opportunities first. That's the opening.
So the key thing here, maybe the big takeaway
for you listening, is that your job title isn't
everything anymore. It's really about the results
you deliver, the value you create. OK, so digging
a bit deeper than just adapt. Yeah. What's the
core message for navigating this job evolution?
How do you actually thrive? Focus on delivering
tangible value, specific outcomes. Don't just
define yourself by a static role. Adaptability
plus demonstrated results. That's key. All right.
Let's shift gears from the big economic view.
Let's get into some of the specific, sometimes
kind of wild things happening in AI right now.
This is where it gets. really fascinating on
the ground level oh yeah some really wild examples
like uh olivia moore creating that 100 ai influencer
i mean it got 500 followers and a viral video
in just a week and she spent what less than 10
minutes a day on it with just three tools it's
kind of mind -bending makes you wonder about
the future of online identity right and then
on the more technical side you had this ai builder
testing eight different ai agents same setup
for all of them some just crushed it performed
amazingly well others completely bombed it really
shows you the huge range in capabilities right
now. It's not all created equal. And our sources
also mentioned an engineer, Avi, who broke down
MCP. That's Multimodal Conversational Pathways.
Basically letting AI handle text, images, audio,
all in one chat smoothly. He used these really
clear visuals. Made a super complex but important
idea easy to grasp. That's a real skill. OpenAI,
no surprise, they've been busy, apparently quietly
talking to journalists, maybe gearing up for
an IPO. And they weren't just talking current
stuff. They were teasing some really big ambitions,
like an AI -powered browser, maybe a social app,
and even, get this, a potential brain chip interface.
Whoa, okay, hold on. Scaling to a billion queries
is one thing, but connecting directly to a brain
chip? That's a fundamental change in how humans
and computers interact. Yeah. Wow. Two sex islands.
It definitely makes you think about... the guardrails
needed, doesn't it? Because it's not all sleek
progress like those leaked Grok prompts. Exactly.
Not all smooth sailing. Those leaked internal
prompts for Grok stuff like crazy conspiracist
or unhinged comedian, they were designed to push
the AI towards really controversial stuff, even
the insane sex shock humor. It's a raw look at
prompt engineering. It shows how sensitive these
models are. You nudge the prompt a little and
the output can go way off track. We call it prompt
drift, honestly. I still wrestle with prompt
drift. myself sometimes. Tiny tweaks can lead
to wildly different unexpected results. These
leaks just really hammer home how much careful
setup and oversight is still needed. Right. But
on a more constructive note, funding is still
flowing. The Allen Institute for AI, they just
secured a huge round, $152 million. Big chunks
came from the NSF and NVIDIA. And the focus,
building open source AI models specifically for
science and medicine, that could genuinely speed
up discoveries, which is pretty exciting. So
we've got AI influencers, tricky prompts, brain
chips, open source science. What's the single
thread tying these diverse, almost opposing things
together? It's the sheer speed and breadth. Incredible
innovation is happening, but it's bumping right
up against serious ethical questions often faster
than we can answer them. Sponsor. All right,
let's pivot again. Time for some quick -fire
updates from across the AI world, and then we
need to talk about this growing digital divide.
It's important. Okay, quick hits. Meta apparently
planned its fourth AI division shakeup just this
year, 2025. Shows you how fast even the giants
are scrambling to adapt, right? It's constant
change. OpenAI launched GPT -GO in India. Big
move. Ten times higher usage limits. Clearly
trying to expand access and, you know, get into
huge markets. We also saw Stanford HAI. and Google
DeepMind teaming up for an AI challenge. More
blending of academia and industry trying to crack
big problems. And for practical tools, Perplexity
Finance can now give you live transcripts from
earnings calls. Super useful for anyone tracking
stocks. But it's not all just tools and restructuring.
There are real concerns cropping up. Like in
Texas, they've accused meta and character AI
of, well, basically misleading people, presenting
their AI chatbots as mental health resources.
That raises some pretty serious ethical alarms,
you know. About responsibility. Yeah, it really
does. And that brings us to something pretty
stark. If AI is everywhere, why is it banned
in some places? Our sources show that chat GPT
is blocked or just plain unavailable in 20 countries
right now in 2025. Yeah, this is where the geopolitics
gets really visible. places like Cyber News and
OpenAI itself shows 18 of those bands are government
blocks. Why? Usually censorship, political control,
maybe security fears about data going overseas.
Then there are two others, Hong Kong and Belarus,
where OpenAI just doesn't offer the service.
Probably complicated business or legal reasons
there. It's not just tech, it's policy. Right.
And it's interesting, in places like China or
Iran, they aren't just blocking tools like ChatGPT,
these foreign large language models, or LLMs.
They're actively pushing their own domestic AI.
like quen or deep seek and the key difference
those are much easier for the governments to
Well, monitoring control. Exactly. This is becoming
a massive geopolitical thing. Access to these
advanced AI tools. It's turning into a strategic
advantage like oil or microchips used to be.
We're basically watching the Internet split in
real time. You've got one version, sort of the
U .S. model, aiming for more openness and another
version that's much more locked down, controlled.
China is a prime example. They're not just blocking.
They're racing to build their own powerful AI
to compete and maintain control. It really feels
like a new kind of. digital iron curtain coming
down. So putting these rapid updates together
with the bands, how does this shape our view
of where AI is headed globally? It shows AI's
future is complex. It's going to be defined by
both explosive innovation and these growing global
governance headaches and divides, a real tension
there. So let's bring it all together. We've
covered the job market shifts, the sometimes
chaotic pace of development, the ethical questions,
this emerging global divide. What's the big idea,
the main thing, you? Our listener should take
away from this deep dive today. I think it's
that AI isn't just one thing. It's this whole
dynamic system full of opportunity. Yeah, but
also real challenges. The key takeaway maybe
is that succeeding now really depends on your
awareness. Understanding the tech is part of
it, sure. But you also need to grasp its economic
ripples, its social impact, and these geopolitical
games being played. It really demands you stay
curious, stay learning, and don't just sit back
passively. We really hope this discussion has
given you a clearer, maybe more nuanced view
of AI's broad impact on work, on innovation and
on these global splits. It's worth thinking about
how your own skills, your own perspective might
need to adapt in this environment. New resources
are always popping up for learning, building
or just automating things better. So keep exploring.
Yeah. And as you think about all this, maybe
consider this. How much does today's AI scene
feel like the early Internet? You know, that
mix of huge promise, total chaos, unexpected
winners and losers, and these strange divides
appearing. What does that parallel suggest about
the next 10 years of AI? And maybe more importantly,
where do you want to position yourself in that
future? Thanks for joining us for this deep dive
into the complex world of AI. We'll be back soon
with more insights. Out Hero Music.