Okay, imagine this. An AI. Super smart. Smart
enough to win a math Olympiad. Yeah. But it also
internally triggers warnings. Yeah. For potentially
helping make, you know, bioweapons, chem stuff,
maybe even nuclear weapons. Yeah, exactly. That's
Google's new DeepThink. And a version of it is
kind of right there on your phone. Wild stuff.
Welcome to the Deep Dive. Today, yeah, we're
going to unpack a whole stack of insights from
AI revolution, Google's deep think and industry
shifts and related AI news that's been popping
up. Our mission really is just to cut through
all the noise, find the surprising bits, the
important facts, and help you get a real handle
on where AI is heading quickly, clearly. We'll
look at Google's new AI brain, this DeepThink,
how other companies are racing like mad to build
even smarter systems. And definitely what all
this rapid change might mean for, you know, your
job, your future. It's going to be a proper deep
dive. All right, let's start with that first
big piece, Google's deep think. They didn't exactly
shout about this launch, did they? No, it was
kind of quiet. But make no mistake, this isn't
just like another chatbot update. Right. This
is a version, a variant of the AI model that
actually got a gold medal at this year's International
Math Olympiad, the IMO. Yeah, think about that.
The absolute smartest high school math kids on
the planet. And an AI comes along and, well,
wins gold. And a version of that same AI. Yeah.
It performs at a bronze medal level, but it's
right inside the Gemini app. Yep, right there.
Better than most high school math geniuses. Running
on your phone, it's accessible power. Something
different. What I find really interesting is
how it actually solves problems. Google calls
it a... parallel thinking techniques. Instead
of just going down one path step by step. It
like explores loads of different ways to tackle
the problem all at once. Exactly. Like a super
fast, really efficient brainstorm, trying out
all these angles super quick, then locking in
the best one. But OK, let's manage expectations.
It's not about to replace a research physicist
just yet. Softly. No, no, not quite yet. That
full gold medal power that's still very much
kept in the lab under wraps. So the version in
Gemini is constrained. Right. It's powerful for
what it is, accessible, but it's not the full
unlocked potential. Oh, and yeah, the access.
Ah, the price tag. Yep. Only for AI Ultra subscribers
right now. And that costs, wait for it, about
$250 a month. Wow. Okay. Yeah. Really? Kind of
shows you who they think the early adopters are,
doesn't it? Or where the initial value lies.
So if we boil it down, what's the main thing
to understand about DeepThink's power level that
we can actually access right now? It's Olympia
-level math smarts, accessible on your phone,
but definitely not its full research power. Okay,
now this next part. This is where it gets really
interesting and maybe a little concerning. Mm
-hmm. The internal red flags at Google. Yeah.
This AI deep think it actually triggered their
own internal safety alerts. Right. Google themselves
said it might have reached a, quote, critical
capability level. That's their term. Yeah, their
term. Yeah. For potentially helping bad actors
with, like you said, biochem or even nuclear
weapons knowledge. OK, so they're not saying
it can do that. No, not that it crossed the line,
but it got close enough that, boom, they added
extra monitoring, tighter safety rules. Right.
Two sec silence. Whoa. I mean, just imagine scaling
that. An AI that capable, potentially doing a
billion queries a day. Yeah, that raises huge
questions about how fast this is all moving and
the responsibility that comes with it. And it's
not like Google's alone in this. This isn't happening
in some, you know, quiet corner. No, it's a full
-on sprint out there. ByteDance, they just launched
SeedProver. That's a silver medal IMO math model.
And the key difference. It's open source. The
code is out there. Big deal. Meanwhile, OpenAI,
they're expected to drop their own gold medal
math AI pretty soon. But this time, Google got
there first. They shipped. It's at the new bar.
It is absolutely a sprint. Everyone wants that
title, right? The smartest AI. The bragging rights
are huge. But so are the risks. And it's not
just math, is it? There's so much else happening.
Google, DeepMind and Kaggle, they've launched
this Kaggle game arena. Oh, yeah. What's that?
It's basically where AI models, GPT, Claude,
Gemini. Even Grok will compete against each other
in strategy games. Kicks off August 5th. Huh.
Like an AI Olympics for strategy. That's actually
pretty cool. Yeah. A way to benchmark how they
handle complex changing situations beyond just,
you know, text. Pushing them in different ways.
But, you know, it's not all just impressive demos
and competitions. There's friction, too. Perplexity
AI. Ah, the search engine thing. Right. They're
being accused of some. Let's call it sneaky scraping.
Making millions of requests daily, even from
sites that specifically block bots like theirs.
And Cloudflare called them out? Cloudflare delisted
them. But Perplexity is apparently just refusing
to accept that action. Sticking to their guns.
Wow. Yeah, that's quite a stance, isn't it? It
really highlights that tension. AI needs data.
But what about website rules? Ethics .ip. Big
questions there. And on the creative front, XAI.
Oh yeah, Grok Imagine. Dropped officially. Turns
simple text or even an image into a 15 second
video. With audio. Just like that. Text to video.
Pretty much. Imagine whipping up quick explainers
or social clips. The speed of progress in generative
AI is just wild. From words to a mini movie.
And then there's the classic tech rivalry. Google
took a direct shot at Apple. Oh! How so? With
a Pixel 10 ad. Yeah. Basically mocking the fact
that Apple's big Siri AI update is still, you
know, coming soon. Ah, playing the we have it
now card. Yep. The ad pretty much says, if Apple's
still coming soon, maybe you should just change
your phone. Ouch. Yeah. Classic competitive spirit.
The gloves are definitely off. So, okay. We've
got these super smart AIs, rapid progress, intense
competition, internal safety flags, data scraping
rows. When AI gets this smart this fast. What's
the core challenge everyone's grappling with?
It's balancing that incredibly fast innovation
push with critical safety needs and figuring
out the ethical lines as you go. Right. Let's
maybe shift gears slightly to how AI is actually
becoming more practical, more accessible day
to day. They're known for quantum computing,
right? They just launched an AI toolkit. It's
already usable. Quantum AI, that's pretty cutting
edge. Yeah, and they have a working demo already,
generating images using quantum principles somehow.
They're going to present it all at the AI Research
Summit next year. Wow. Connecting quantum research
to something tangible like image generation,
that's a big step. Using quantum mechanics for
faster AI calculations. Neat. And the money flowing
in. It's huge. Observe Inc., for instance. They
just raised $156 million. For what exactly? For
their AI observability platform. Basically AI
watching other AI systems. Ah, okay. Like quality
control for AI? Sort of. Helps companies see
how their AI is doing, fix problems. And get
this, they're processing over 150 petabytes of
data every month with help from OpenAI. 150 petabytes.
That's just... astronomical, shows you the scale
these systems operate at. And yeah, observability
is crucial if you're deploying complex AI. You've
got to know what it's doing. And it's not just
big companies and huge investments. We're seeing
guides pop up for building no -code AI. Meaning
you don't have to be a programmer? Exactly. Like
there's a guide on building a rack system. Using
tools like NAN and Supabase, anyone can try it.
Right. R -drying, retrieval augmented generation.
That's a really useful technique. Explain that.
It's basically where the AI doesn't just rely
on its general training data. It combines that
with specific documents you give it. So like
you could ask it about your company's vacation
policy and it pulls the answer directly from
your actual policy document. Much better answers.
Very practical. We're also seeing specific business
strategies emerge like this value first AI lead
strategy. Fiverr and Upwork are apparently using
it. How does that work? Seems like using AI to
find and connect with customers who already know
exactly what service they need. High intent,
kind of pre -sold leads. Smart. Using AI for
better targeting. And if you're thinking about
skills, there's even a guide out there. Seven
AI skills to make you rich in 2025. Covers AI
design, development strategy. It works. Yeah,
the message there seems to be. Don't just learn
about AI. Learn how to use AI to solve actual
business problems. That's where the value and
the money is. Think of AI as your super -powered
assistant. And the tools themselves. They're
getting so specific and powerful. SciSpace AI
automates research tasks for academics, like
150 different tools. Wow. Furbyte helps writers
get publish -ready content faster. Tregno builds
entire SEO strategies. Gulpo creates AI videos
like explainers. It's amazing how specialized
they're becoming, each one tackling a really
specific pain point, automating stuff that used
to take humans ages. Right. It means you can
potentially do more, faster, maybe even better
quality in some cases. Absolutely. More leverage.
So looking at all this practical stuff, the tools,
the investment, the no -code movement, what's
the big takeaway? How is AI evolving for... you
know, us regular users or businesses. I'd say
AI is becoming way more specialized, definitely
more accessible, and it's getting woven really
deep into workflows everywhere. Okay. Now for
the topic that probably touches everyone listening,
jobs. The big one. We looked at these charts,
fastest shrinking jobs versus safest jobs from
AI 2025, 2030. And honestly. The picture is pretty
stark. Yeah, it's clear. If your job is mostly
repetitive tasks, administrative stuff, it's
at risk. High risk. But if it involves a lot
of human interaction, complex problem solving
in the real world, emotional intelligence, it
seems much safer. For now, at least. Definitely.
Anything clerical, just moving data around, stuff
tied to old systems that's being automated fast.
Bots, self -checkouts, predictive software, they're
taking over those roles. It's a fundamental shift.
But like you said, it's not all doom and gloom.
Not every job is on the chopping block. No, thankfully
not. Jobs needing real -time judgment, empathy,
creativity, fixing physical things. Think therapists,
electricians, artists, good manager. They're
still very much needed. Right. Those uniquely
human skills. But, and it's a big but. Don't
get too comfortable thinking AI can't handle
complexity. Remember the McDonald's AI drive
-thru fail? Kept adding bacon to everything.
Slightly amused. I do remember that. Hilarious.
Or, less hilariously, Amazon's Just Walk Out
tech, the cashierless stores. Turns out, behind
the scenes, there were reportedly like a thousand
people in India watching feeds to make sure the
charges were right. So a lot of the shiny AI
automation we see still have a whole lot of humans
behind the curtain, kind of like the Wizard of
Oz. Pretty much. It's not always as automated
as it looks. It reminds me, you know, I still
wrestle sometimes with prompt drift myself. Yeah.
When you're having a long chat with an AI and
it kind of forgets the original point or instruction.
Oh, yeah. It makes me wonder how these more complex
jobs, the ones needing sustained focus and context,
how they'll really evolve as AI gets better,
but maybe still imperfect for everyone. Yeah,
it's basically sorting jobs into two piles, isn't
it? The easy to automate pile and the hard to
automate pile. And you definitely want to be
in the second pile. Absolutely. Which means doubling
down on those human skills. Creativity, critical
thinking, collaboration, empathy, adapting is
key. And doing it quickly. So bottom line for
people listening, how should we really think
about our careers, our skills in this this AI
driven world that's changing so fast? Foken hard
on those uniquely human, non -repetitive skills
and be ready, really ready to adapt and learn
how to work with these new AI tools. Sponsor.
OK, that was a lot. So let's try to pull the
big threads together. What does all this really
mean? We've seen AI pushing boundaries like crazy.
Google's DeepThink is a prime example, incredible
power, Olympiad level smarts, but also these
serious safety questions popping up internally.
Yeah. And the race to build the next big AI model.
It's incredibly intense, super dynamic, super
competitive. New stuff is landing constantly,
almost redefining state of the art week by week.
We also saw how AI isn't just lab experiments
anymore. It's becoming really practical, specialized.
New tools, new strategies are changing how businesses
work, how individuals create and research. More
accessible, more integrated. And crucially, all
of this is shaking up the job market big time.
It's speeding up that shift away from repetitive
tasks towards roles that really need those human
skills, the ones AI can't easily replicate yet.
So this whole deep dive today really shows technology
is moving at lightning speed. But it's forcing
us, all of us, to wrestle with some really complex
ethical questions, rethink data, privacy, and
fundamentally rethink our relationship with work
itself. So turning it over to you listening,
what stood out most to you from all this? How
do you see these AI shifts impacting your world,
your job, even just, you know, your day to day
life? Yeah, we really encourage you to maybe
dig a bit deeper into some of these areas because
the pace of change is, well, it's kind of astonishing.
It really is. Thank you for joining us for this
deep dive. Until next time, keep digging into
what's truly interesting. Otiro Music.