ChatGPT once looked pretty much invincible, didn't
it? But now it finds itself, well, surrounded.
It's this surprising, really intense shift happening
right now in the AI landscape. We're talking
new challengers, global power plays, and the
real AI war. you know often unfolding right there
on your phone screen welcome to the deep dive
we're here to unpack the latest insights from
your sources yeah and today yeah we're plunging
into this ai frontier looking where the industry
stands maybe where it's heading and it is moving
fast we'll uh explore the intense competition
you know from the tech giants we all know to
these um stealthy startups you might not have
even heard of yet And we'll also dig into some
truly unexpected real world applications. And
this is crucial, I think, advancements in AI
safety and reliability. It's such a dynamic space.
Lots to consider. So, OK, what does this all
mean for you listening? We'll map out the current
state of play, see how AI is truly evolving beyond
just those few big names and what innovations
might be coming next. So let's unpack this first
part. The A16's report, that's Andreessen Horowitz,
the VC firm, their latest report is, well, it's
a bit of a game changer. It shows ChatGPT's dominant
lead, which, you know, once felt kind of insurmountable,
it's actually shrinking. It is. The competition
is catching up and fast. What's truly fascinating
here, I think, is just how quickly this landscape
can shift. Like you blink and things look different.
Gemini, for example. It's not just a player anymore.
It's now the number two AI app on mobile. Number
two. Wow. And it's captured, get this, 90 % of
the Android market. 90! Think about that penetration.
It's not just a big slice. It's like practically
the whole pie on Android. Right. And Grok, you
know, from x .ai. That isn't just some niche
thing either. No. It's quickly become a top five
web AI tool and number 23 on mobile with, what,
over 20 million users already? Yeah, that's exploding
growth. I mean, it's fueled by that integration
into X, right? Access to real -time info. Exactly.
It really shows the power of platform integration.
Meanwhile, you see Claude, Anthropix AI, it's
maintaining steady web growth. Solid performer
there. Okay. But surprisingly, it's flat on mobile.
Just hasn't taken off the same way. Interesting.
And then there's Perplexity AI, kind of. quietly,
almost stealthily climbing in both web and mobile.
Ah, yeah, perplexity. Yeah, they're building
a strong user base by focusing on answer accuracy
and showing their sources. And then there's this
global element, which is maybe surprising to
some. Oh, yeah. This isn't just a Silicon Valley
game anymore, is it? 22 of the top 50 mobile
AI apps from China now. 22. That's almost half.
Dubao from ByteDance, for instance, already number
four on mobile. Quark from Alibaba is number
nine on the web. It really signals a truly global
arms race in AI. You've got diverse players bringing
different strengths, different approaches. Exactly.
And we're also seeing new kind of intriguing
players pop up, like Lovable and Replit, making
their first appearance on these lists. Lovable,
that's the vibe coding startup. Yeah, helping
users create code based on like emotional cues
or aesthetics, making coding more intuitive.
And Replit's the collaborative code editor with
AI built in. Right, speeding up development.
And others like PixAI and AI Mirror, focusing
on images. They feel like they're right on the
edge of breaking through, you know? Mainstream
adoption feels... close for them so okay thinking
about all this competition especially on mobile
yeah what does that intense focus really signify
for like how we'll interact with AI day to day
well I think it shows that ubiquitous you know
personalized AI it's rapidly becoming just an
indispensable part of our daily digital lives
mm -hmm yeah makes sense and if we connect this
to the bigger picture AI isn't just for chatbots
anymore or just generating text and images. Its
reliability is being seriously tested now in
really critical real world areas. The Washington
Post, for instance, ran this huge test. Oh, yeah,
I saw that. 900 answers across nine major AI
tools just to see what actually works, you know,
not just in theory, but under pressure. That's
a genuine stress test way beyond the usual benchmarks.
And speaking of real world impact, remember PJ
Ace's viral AI ad for Kelshi? Oh, yeah. That
was impressive. Well, he did it again, crafted
another super realistic video, this time for
David Beckham's company, IM8. Wow. These aren't
just clever tricks anymore. They're showing AI's
ability to create stuff that looks almost exactly
like live action video. It's transforming content
production. And what's maybe equally remarkable
is the collaboration that's starting to happen
between these competitors. Like Anthropic and
OpenAI? Exactly. They just audited each other's
AI models for safety risks. That's a first of
its kind move in this industry. That is significant.
Yeah. It signals maybe a maturing approach to
development where safety isn't just internal.
It's a shared, auditable thing. Building collective
trust, maybe. It absolutely shows a maturing
industry. I agree. And then in education, Anthropic
analyzed, what, 74 ,000 educator chats with Claude?
74 ,000. Yeah. That wasn't just a survey. It
was a deep dive into how professors are kind
of. quietly but significantly adapting to AI
in higher ed. Integrating it into teaching, curriculum,
often behind the scenes. And on a totally different
scale, Google DeepMind's experimental weather
AI. It just... nailed its first real -world test.
Oh, the hurricane prediction. Yeah, predicted
Hurricane Erin's path more accurately than the
traditional methods by, you know, analyzing vast
amounts of atmospheric data, spotting patterns
maybe missed before. I mean, imagine scaling
that. Right. Predicting extreme weather precisely.
With that accuracy, it could literally save so
many lives. Think about disaster preparedness.
Yeah, the global impact is huge. Indeed. And
on the funding side, we're seeing massive investments
in these practical applications, too. Field AI
just raised $405 million. Wow, $405 million.
What's our goal? Get this. Build one universal
robot brain. One brain that works across all
robot types. Ambitious. Very. They're physics
-based AI. It understands real -world forces,
movement. It's already reducing risk in energy
delivery construction. Okay, so when we look
across all these different uses, weather, robotics,
safety audits, what's the common thread here
about... AI's readiness for, you know, real impact?
I'd say AI is really proving its diverse utility
now and it's increasing reliability across a
whole bunch of critical sectors. Here's where
it gets really interesting, I think, for people
wanting to actually use AI themselves. Can GPC5,
you know, one of the newer models, actually create
profitable trading strategies? Ah, the million
dollar question. Yeah. Or maybe billion dollar.
Right. A review on TradingView put it through
a pretty brutal test, real market data. So we're
asking where does it shine and where does it
completely fall flat in finance? Well, this brings
up such an important question. How do you even
tell an AI what you want it to do, especially
when money is involved? Yeah, the prompt matters.
Exactly. That's prompt engineering. It's the
art, maybe the science, of crafting really precise,
clear instructions, like writing a super detailed
recipe for a chef, you know. Good analogy. It's
becoming absolutely key to making money with
AI, to consistently getting something valuable
out of it. I have to admit, I still wrestle with
prompt drift myself sometimes, you know, getting
exactly what I need consistently. It's a learning
curve for everyone, I think, even us. Oh, for
sure. But for those looking to start, there's
actually a seven -day AI business launch plan
out there now. A full roadmap. Yeah, complete
step -by -step from just an idea to a launch
company. Covers market research, deployment,
the whole thing. We're also seeing these highly
specialized AI tools emerge, redefining what's
possible for creators. For example, Gemini 2
.5 Flash Image. The image generator. Yeah, it
creates images with incredible detail, down to
like what they call a nano -banana. A nano -banana.
Right. This is a SOTA image model, state -of
-the -art. The absolute cutting edge allows for
hyper -detailed product stuff or, you know, microscopic
scientific images. Then there's Codex, which
is pretty amazing too. Builds web apps in minutes.
For free. Using like 27 different AI models,
right? Yeah, handling different parts of development.
And one part turns content into interactive chat
pages. No code needed at all. Wow. And Screenshot
Reports creates branded reports just from screenshots,
streamlining something that's usually pretty
tedious. Okay, so thinking about all these tools,
prompt engineering, no code builders, specialized
models, what's the fundamental shift happening
for creators and entrepreneurs here? I think
AI is really democratizing innovation. It's allowing
pretty much anyone to build and create, often
with absolutely no code required. So, okay, how
do we make AI feel more human, more relatable
when we interact with it? There's this viral
system prompt for ChatGPT going around. Oh, yeah.
What does it do? It basically teaches the AI
to speak more like a real person, injects conversational
nuances, idioms, even a bit of personality. Makes
it feel less robotic. Huh. Interesting. Like
giving a conversational coaching. Exactly. And
on the video side, things are moving fast too.
Alibaba just updated its video AI, film quality
avatars, they're calling them. Making AI characters
look almost real. Stunningly real, yeah. Almost
indistinguishable from live actors. And Google
Workspace now has a free AI video tool called
Google Vids. Puts easy video creation into more
hands. But AI isn't all positive, right? There
are challenges. It's a pretty stark one. Definitely.
Stanford University recently found AI actually
killed 13 percent of jobs for 22 to 25 year olds,
specifically in coding and support roles. 13
percent. That's significant. It's a stark reminder
of the disruptive power affecting real people,
highlighting that need for workforce adaptation.
And sadly, we've seen a darker side already.
A hacker recently used Claude Anthropics AI to
run a full scale cybercrime operation. Seriously?
God. It hits 17 different organizations. It just
clearly shows the critical need for robust security,
ethical safeguards, preventing these powerful
tools from being weaponized. Which really raises
the question, how do we properly test these incredibly
powerful AI agents, test them in a way that reflects
real world performance? Well, AI2, the Allen
Institute for AI. They just dropped AstaBench.
AstaBench. Okay, what is it? It's a new benchmark
suite. But a really rigorous one. It's built
specifically to test scientific AI agents. Uses
over 2 ,400 real research tasks. Wow, 2 ,400
real tasks. That's way beyond simple chatbot
stuff. Oh, yeah. And AstaBench focuses on what
they call five brutal truths about agent testing.
Okay, like what? Well, first, tasks have to be
real world and genuinely hard. Second, tool use
needs careful control. Third, you've got to track
the cost accuracies and everything if it's bankrupting
you. Fourth, standardization is key for comparing
apples to apples. And fifth, you can't claim
progress unless you know exactly what you've
actually beaten. Really practical fundamental
points. And they tested a lot of agents. 57 agents
across 22 different architectures. Huge sample.
Their own agent, Asta V0, scored 53%. React plus
G5 got 43 .3%. Okay, so still room for improvement.
Definitely. And interestingly, data analysis,
still pretty weak across the board. No one scored
above 34 % there. That's a major area needing
work. And what about GPT -5's impact in those
tests? Also interesting. It actually helped general
agents, like the ones using that React framework
for reasoning and action. But it oddly hurt specialized
ones. which suggests maybe it's tuned specifically
for certain workflows like those React -style
operations. This is definitely the benchmark
to watch if you're building AI for critical fields,
research, medicine, engineering, where trust
and reproducibility are everything. So boiling
it down, what's the biggest takeaway from Ask
the Bench for you and maybe for anyone relying
on AI for really important tasks? I think it's
that rigorous, truly real -world benchmarks are
absolutely essential if we're going to build
trustworthy and reliable AI, period. So if we
try to connect all of this, tie it together,
three things really stand out from today's deep
dive, I think. First, the AI competition is just
incredibly intense now, and it's truly global.
Chad GPT isn't alone at the top anymore. And
that battleground for dominance, it's decisively
shifted to mobile devices. That's where the action
is. Second, AI's practical applications are just
expanding so rapidly. They're touching almost
every part of our lives in really tangible ways
now. From predicting hurricanes, transforming
education, providing these powerful business
tools. It's integrated. It's everywhere. It's
not just niche tech anymore. Exactly. And third,
maybe most importantly, the need for robust testing,
industry -wide safety audits, clear ethical guidelines.
Yeah. It's more critical than ever before. Yeah.
As AI gets more powerful, more deeply integrated
into our lives, we just need smarter ways to
ensure it works reliably, safely, and responsibly
for everyone. So the big question then, as AI
keeps evolving so quickly, how do we make sure
we're building trustworthy, responsible systems?
Systems that actually benefit humanity rather
than introducing new risks. And maybe related.
What's your role in understanding this rapidly
changing landscape? How will you adapt your own
skills, your own expectations as this continues?
We really encourage you to keep exploring, keep
asking questions. This deep dive into your sources
clearly shows the future of AI while it's still
being written. And it's a story we're all a part
of, really. Thank you for joining us on this
deep dive. We'll be back soon with more insights.
Until then, keep digging. Out Hero Music.