Limitless Podcast

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Google launched Gemini 3.0, a groundbreaking AI model with advanced multimodal capabilities for interpreting diverse inputs. 

We highlight its impressive benchmark performance, including a 37.5% on Humanity’s Last Exam, and discuss Google’s proprietary TPU infrastructure and the new tool, Google Anti-Gravity. 

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TIMESTAMPS

0:00 Gemini 3.0
5:34 Game-Changing Features
9:04 Benchmarking Breakthroughs
13:21 Cost and Quality Trade-offs
17:46 Google’s Strategic Advantage
24:51 Predictions for the Future

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RESOURCES

Josh: https://x.com/JoshjKale

Ejaaz: https://x.com/cryptopunk7213

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Not financial or tax advice. See our investment disclosures here:
https://www.bankless.com/disclosures⁠

What is Limitless Podcast?

Exploring the frontiers of Technology and AI

Josh:
If I had a crown in my hands, I would place it on the heads of Google because they have done it again.

Josh:
They have the world's best AI model ever in history by a shockingly large margin.

Josh:
Gemini 3.0 just got released.

Josh:
It's available now to anybody in the world to go use it. And the benchmarks

Josh:
are kind of blowing everyone's expectations out of the water, myself included.

Josh:
And most importantly, it places another data point on the chart that shows we

Josh:
are continuing to ascend up this exponential curve towards AGI.

Josh:
And the roadmap is still intact and we are very quickly moving through it.

Josh:
This, EJs, I was just, I was going through the benchmarks before recording this

Josh:
and I, it's, it's shocking because we live in this world and yet somehow I'm

Josh:
still continually blown away by the progress that's made by these models. So let's get into it.

Josh:
Please walk everyone through, tell me, what did Gemini and the Google team just

Josh:
release with this 3.0 update?

Ejaaz:
People probably think we say the world's best model every week,

Ejaaz:
but this time we really, really mean it.

Ejaaz:
Like they have blown every single other model provider out the water.

Ejaaz:
The things that this thing can do. Well, how about how about I just show you?

Ejaaz:
How about I show you, Josh?

Josh:
Please, let's see some examples.

Ejaaz:
We have a thread here. And Sundar basically says, you can give Gemini 3 anything,

Ejaaz:
images, PDFs, scribbles on a napkin, and it'll create whatever you like.

Ejaaz:
For example, an image becomes a board game.

Ejaaz:
A napkin sketch transforms into a full website.

Ejaaz:
And a diagram could turn into an interactive lesson, right? So there's two examples

Ejaaz:
I want to show you, Josh. I want to get your opinion on this.

Ejaaz:
So number one, there's a short video of someone playing pickleball here and

Ejaaz:
he or she rather uploads it into Gemini and says, hey, can you tell me how well

Ejaaz:
I've done here and how I can improve my game?

Ejaaz:
And it analyzes the entire video.

Ejaaz:
It knows that she's wearing a knee brace. It analyzes her positions,

Ejaaz:
telling her where she can move to better position herself to score the point.

Ejaaz:
That's pretty nuts. But before I get your reaction to that, because Josh,

Ejaaz:
I know you're an athlete. I know you're very competitive when it comes to these

Ejaaz:
things. So this is a tool you could definitely use.

Ejaaz:
The second thing is probably applicable to a lot of listeners on this show.

Ejaaz:
They've embedded Gemini 3 into Google search and into new generative UI experiences.

Ejaaz:
The way I would summarize this is it basically is very intuitive, Josh.

Ejaaz:
It understands what you're asking for without you needing to really kind of explain yourself.

Ejaaz:
The example they're showing on the video here is, can you explain the three body problem to me?

Ejaaz:
And rather than just give you kind of like this simplistic text,

Ejaaz:
which explains the concept, it decides to create a video diagram from scratch

Ejaaz:
to show you a visual depiction of how this works.

Ejaaz:
Right. Give me your reaction in order from one to two. So starting with the sports.

Josh:
Okay, let's go. The first example.

Ejaaz:
Yes, sir.

Josh:
So this is really cool, the napkin example, where you can scribble something

Josh:
down on a piece of paper, it'll generate it in the real world.

Josh:
What all these examples are kind of showing me is what we always talk about

Josh:
with Google, where it has this awareness of physics, reality,

Josh:
and visuals and understanding what it's seeing.

Josh:
And all three of these examples are leaning into that. So it leads me to believe

Josh:
Gemini really is a multimodal first model, where it's meant to ingest,

Josh:
meant to understand the world around us. This example of the chessboard and

Josh:
the napkin is amazing because a lot of people oftentimes have sketches.

Josh:
You just draw it down on paper and it intuitively understands it.

Josh:
But the one that was most surprising to me is the video example.

Josh:
Because as far as I'm concerned.

Josh:
As far as I'm aware, there has never been a model that can ingest video and

Josh:
understand the video that it sees. And if it does exist, I've never tried it before.

Josh:
So the idea that you can, I mean, I play baseball growing up.

Josh:
I, if I could take a video of myself swinging and get a corrective coach to

Josh:
walk me through exactly what was wrong.

Josh:
A lot of people play golf. I'm sure who are watching this.

Josh:
If you could have a phone recording of you playing golf and it can actually

Josh:
critique it and then critique me as if you are a tiger woods,

Josh:
critique me as if you are whoever else is good that plays golf.

Josh:
I don't know, Rory McIlroy, whatever they are, but like critique Critique me

Josh:
as if you are an expert who is really good at golf and can give me some feedback

Josh:
on how I can better my swing.

Josh:
And what this offers in this one just narrow case example is now you have this

Josh:
personal tutor that can do anything. If you're dancing, if you're doing anything

Josh:
physical, if you're whatever it is, it can evaluate things for you.

Josh:
Even if you have a video, a podcast, EJS, we uploaded to Gemini 3.0,

Josh:
it could critique us. What did we do well? What did we not?

Josh:
What did the visuals look like? How can we improve them? And that awareness

Josh:
of video is like really cool.

Ejaaz:
Yeah, I just want to say, I think the closest we got to this was with GPT,

Ejaaz:
where you can upload an image, like what's under my car bonnet and say,

Ejaaz:
hey, what's wrong? My car stopped working.

Ejaaz:
And it can kind of like identify the point that you need to kind of like change,

Ejaaz:
change the oil, blah, blah, blah.

Ejaaz:
But that's just a static image. To go from that to live video and for it to

Ejaaz:
analyze all the frames in that video and then give you a response on that is

Ejaaz:
a massive leap upwards. We just haven't seen that anyway. So yeah, you're right.

Josh:
It's amazing. And every example we go through, it kind of breaks the mold of

Josh:
what I believe should be possible.

Josh:
And I find that it's going to be difficult to use Gemini 3.0 because there are

Josh:
so many possibilities now that have not existed previously. You kind of need

Josh:
to relearn how to engage with AI because it's so capable.

Josh:
And there's a fourth example here that I just want to touch on briefly,

Josh:
which was also cool, is that it works just as well for the other things.

Josh:
The example is a trip planning one where it starts to plan a trip and a vacation.

Josh:
And it shows you a full list that is fully interactive of all the places broken up day by day.

Josh:
And there's an option that you could just choose visual layout.

Josh:
And you see on the screen here, it'll take every single day of your trip,

Josh:
break it into images, section it out into this really nice visual grid.

Josh:
So what I'm seeing the themes here are, okay, real world understanding,

Josh:
video first, and really nice presentation, which I think a lot of models sometimes struggle on.

Josh:
Demo's out of control. I'm excited to use it. Everyone else can use it now.

Josh:
It's live. Now I want to get to benchmarks, EJS, because this is where things

Josh:
get kind of crazy, where we could actually compare one to another and see exactly

Josh:
how impressive this is relative to everybody else. So please, we have the card here.

Josh:
Walk us through what we're seeing in this model card and all the specs that we need to know.

Ejaaz:
As you guys probably know by now, benchmarks is typically how we evaluate any

Ejaaz:
typical AI model against each other.

Ejaaz:
And they're measured against a range of different benchmarks.

Ejaaz:
A benchmark can be considered as sort of like a test.

Ejaaz:
Now, right at the top, you've got humanity's last exam. This is by default,

Ejaaz:
the hardest exam that an AI model is tested against.

Ejaaz:
And it's kind of like an academic reasoning test with no tools accessible to it.

Ejaaz:
It scored a very impressive 37.5%, which is more than I think is about a 15%

Ejaaz:
increase from its previous model.

Ejaaz:
Very, very impressive. But what really blew my mind was the second stat listed

Ejaaz:
here, which is the ARK AGI 2 benchmark.

Ejaaz:
Josh, when I say this 2x'd the previous state-of-the-art model, I absolutely mean it.

Ejaaz:
In fact, let me just show you this chart here.

Ejaaz:
Now, you may notice a couple of bustly specs here.

Ejaaz:
GPT-5 Pro, Grok 4 Thinking. And then can you see that outlier right at the top

Ejaaz:
right. Do you see that, Josh?

Josh:
That's insane. The two outliers.

Ejaaz:
The two outliers. So these are the Gemini 3 Pro and the Gemini 3 deep thinking model.

Ejaaz:
Deep thinking being like, you know, a large number that can like kind of give

Ejaaz:
you a more research response. They are a...

Ejaaz:
Stand out from every single other model. And the reason why this is so crazy,

Ejaaz:
well, there's a few reasons.

Ejaaz:
Number one, all the other model progressions, as you can see over time,

Ejaaz:
has been kind of impressive, but kind of small.

Ejaaz:
Like they've been a good jump. It's been impressive, but it hasn't been as impressive

Ejaaz:
to be like, oh, you know, another model provider couldn't catch up.

Ejaaz:
These results from Google literally put it miles ahead of every other model.

Ejaaz:
So when I sat at this chart, I think, wow, Google probably has the lead for

Ejaaz:
another six months and in six months time, they're going to have a more impressive model by then.

Ejaaz:
So at this point, I'm kind of thinking, can anyone catch up to Google?

Ejaaz:
Josh, do you have any reactions to this benchmark?

Josh:
This is the chart that like the first thing I said to myself when I saw this

Josh:
is like, oh, my God, there is no wall there.

Josh:
We are not going to stop scaling. The scaling will still apply because these

Josh:
two new data points that we have blow everything else out of the water.

Josh:
And this is how exponential growth happens.

Josh:
It seems like a really small cluster down there in the bottom,

Josh:
but the reality is that was the top just a couple hours ago.

Josh:
And Gemini kind of refactored this entire chart to make it seem like it's so

Josh:
small because the progress is so high.

Josh:
And although Gemini 3.0 thinking is seemingly the most impressive,

Josh:
the really anomaly chart is the Gemini 3.0 Pro, which is basically a vertical

Josh:
line up from these other models, where the score is higher, but the cost is

Josh:
actually slightly lower.

Josh:
And if you connect a dot between these averages, you start to see literal vertical

Josh:
line in terms of improvement and acceleration in these models.

Josh:
And that to me shows that there is no scaling wall that we're hitting.

Josh:
Like we can continue to scale resources, energy, compute, and we could continue

Josh:
along this path towards AGI in a world where some people were saying,

Josh:
we don't know if it continues. The answer to me is very clearly, it continues.

Josh:
This is a step much closer to AGI.

Josh:
And again, that real world understanding makes it feel much closer to AGI than it ever has before.

Josh:
Because now it really like intuitively understands the world through video,

Josh:
through photo, through audio, through basically every sensory input we have

Josh:
outside of what taste and feel.

Josh:
So this to me, I saw this chart. I was like, oh, my God, Gemini,

Josh:
you really outdid yourselves.

Ejaaz:
I'm just going to be honest. I think over the last couple of months,

Ejaaz:
I've been getting a little bored with the models that have been released by other model providers.

Ejaaz:
And it led me to think that we're not going to make many breakthroughs until

Ejaaz:
some model provider figures out a new, unique way to train their model.

Ejaaz:
Gemini or Google has convinced me otherwise with this release.

Ejaaz:
But I know you guys are probably like fed up with listening to us hop on about benchmarks.

Ejaaz:
So how about I materialize that for you in a much more easy to understand way, right?

Ejaaz:
So here are the four big takeaways that you need to learn about Gemini 3.

Ejaaz:
Number one, for its intelligence, for the intelligence that you're getting,

Ejaaz:
it is not that super expensive.

Ejaaz:
Google trained this from scratch, as this tweet says, using their own GPU infrastructure.

Ejaaz:
And it used this kind of like layout called a mixture of experts,

Ejaaz:
which basically means that whenever you prompt the model, it's not going to use the entire model.

Ejaaz:
So it actually ends up being cheaper than what it could eventually become.

Ejaaz:
One million token context input, 64K token output. We'll get to the costs in

Ejaaz:
a bit of a second, But the point that I'm making here is that it's not as expensive

Ejaaz:
as you would expect for the intelligence that you're getting.

Ejaaz:
Now, if you compared Gemini 3 to GPT 5.1 from OpenAI, on a relative basis,

Ejaaz:
it is more expensive. But for the jump in intelligence that you're getting,

Ejaaz:
it's way better. So it's, in my opinion, worth it.

Ejaaz:
Number two, when it comes to computer use, so that means letting the AI model

Ejaaz:
control your computer and do tasks for you whilst you go do something else.

Ejaaz:
It is state of the art. It is the best here. They measured it against a benchmark

Ejaaz:
called ScreenSpot Pro, which is a benchmark which kind of like analyzes its

Ejaaz:
ability to understand images and visuals on a desktop. It just absolutely crushes it.

Ejaaz:
Number three, it is the best AI for math by far.

Ejaaz:
So again, the point I'm making here or the theme that we're seeing here is it's

Ejaaz:
not just good at one thing, it's good at many things, which makes it the best

Ejaaz:
generalist AI model in the world right now, by far.

Ejaaz:
And the final thing, Josh, and this is where it might slip up.

Ejaaz:
I'm curious to get your take on this.

Ejaaz:
It is insanely good at coding, but we don't quite know if it is the best at coding yet.

Ejaaz:
What I mean by that is it completely crushed everyone else on one coding benchmark,

Ejaaz:
but the coding benchmark that matters, which is the software engineering,

Ejaaz:
SWE, it didn't do as well as its competitor, Claude 4.5 from Anthropic.

Ejaaz:
So those are the four main takeaways.

Josh:
I would much prefer a model that understands the world than understands how to code.

Josh:
And I think we're starting to see these subset niches where if Anthropic has

Josh:
the best coding model, that's great.

Josh:
Let them focus on code. Let them narrowly make that the best model.

Josh:
Let Google handle everything else. And I think that's what Gemini is focusing

Josh:
on. So the code thing doesn't really bother me because I don't care to use Gemini for code.

Josh:
I'm happy to be in Claude Camp for code and then use Gemini for everything else.

Josh:
And then one of the points earlier that you mentioned on the pricing is.

Josh:
I find it a little interesting because it's a little bit more than just a little bit more expensive.

Josh:
The pricing, I was looking through it and it's for over 200,000 tokens.

Josh:
They're charging $4 for inputs and $18 for outputs.

Josh:
Now, relative to GPT 5.1, which just got released, they're charging for a million

Josh:
tokens, $1.25 in, $10 out.

Josh:
So you're talking about, what is that? that's about $20 versus $1.25 on inputs.

Josh:
And that is a fairly significant margin that you're paying for this quality.

Josh:
So we're starting to see the trade-offs happening on that Pareto curve that

Josh:
we talked about in a few episodes earlier, where there are trade-offs coming

Josh:
in terms of cost and quality.

Josh:
And it's clear that while OpenAI may have optimized for cost,

Josh:
Google is kind of optimizing for a little further up the cost curve in exchange for super high quality.

Josh:
And it seems like this is kind of a balanced data point for now because unless

Josh:
you are using this via API and you're requiring a ton of tokens,

Josh:
a $20 a month Google membership will get you all of the use that you need. And that is just fine.

Josh:
So in terms of a usability perspective, I think that's okay.

Josh:
But it's just an interesting thing to know is that this is a better model.

Josh:
It is also more expensive.

Josh:
And that is a trade-off that was made. And in the case that OpenAI decides to

Josh:
make this trade-off with GPT-6 or Grok decides to make this with Grok-5,

Josh:
or Grok 6. I'm losing track of all these models now. I think we're going to

Josh:
start to see the dynamic shift in terms of that Pareto curve and what model

Josh:
architects decide to remove and add.

Josh:
And in this case, it looks like Google added quality, but they also did add

Josh:
quite a significant cost increase.

Ejaaz:
I personally don't think it matters. I think it's a nothing burger.

Ejaaz:
I think that if Google wanted to make it affordable for everyone,

Ejaaz:
including the developers that want to get API access, that think it might be

Ejaaz:
too expensive, they could subsidize it.

Ejaaz:
They are a cash flow giant. They have enough money to do that.

Ejaaz:
OpenAI has been doing that for so long now that it doesn't even matter.

Ejaaz:
I don't see any reason why Google couldn't do that.

Ejaaz:
The other reason is Google just released their latest TPU, which is their GPU

Ejaaz:
that they use to train their models and inference their models.

Ejaaz:
And typically with every generation, we get a much cheaper cost of inference.

Ejaaz:
I think by the time that they release their next generation model,

Ejaaz:
which might be, you know, Gemini 3.1, we're going to see a considerable reduction

Ejaaz:
in the cost for using Gemini 3 Pro and Gemini Pro deep research.

Ejaaz:
So I'm not too worried about that. I think it's kind of like a short-term problem

Ejaaz:
and not a long-term problem.

Ejaaz:
But kind of speaking of TPUs, I just want to take a moment to really kind of

Ejaaz:
belay the point that using their own TPUs to train a state-of-the-art model

Ejaaz:
that is 2x better than the previous state-of-the-art model and probably puts

Ejaaz:
them in a six-month lead after Google started off on the back foot,

Ejaaz:
creating probably the worst model I've ever seen and

Ejaaz:
changing that all around in what's it under two years is

Ejaaz:
nothing short of insanity tpus is

Ejaaz:
uh google's kind of version of the gpu gpu is

Ejaaz:
kind of like what nvidia controls the monopoly over this is the hardware that

Ejaaz:
you use to train your ai and inference your ai the uh unique part here is that

Ejaaz:
google's never used an nvidia gpu uh or in any considerable way to train their

Ejaaz:
models they've always trained it in-house and that's such a difficult and tricky

Ejaaz:
thing to do because designing and building these

Ejaaz:
TPUs at scale, these GPUs at scale is a super hard and complex thing.

Ejaaz:
You need so much talent, you need so much expertise and insight to be able to do that.

Ejaaz:
The unique thing about Google's TPUs, well, there's two main takeaways.

Ejaaz:
Number one, it's cheaper to train the same amount of intelligence that an NVIDIA

Ejaaz:
GPU is. So it's more cost efficient.

Ejaaz:
And the second way is, and this is their secret sauce, you can stack those TPUs

Ejaaz:
on top of each other in a really scalable way that you can start training really, really large models.

Ejaaz:
If you wanted to train the same size model with nvidia

Ejaaz:
gpus it would cost way more and it would take way

Ejaaz:
longer so google made a really risky and big bet about a decade ago saying we're

Ejaaz:
going to build our infrastructure in-house and we're not going to rely on nvidia

Ejaaz:
and we're going to benefit from the full stack experience and this model is

Ejaaz:
a prime example of that bet paying off so i just want to call them out like

Ejaaz:
it's not like google has gotten lucky here they've been planning it for a while now The

Josh:
Interesting thing to me is that this is the first number one model in the world

Josh:
built on something other than an NVIDIA GPU.

Josh:
And that's fairly significant because every company in the world is trying,

Josh:
but this is proof that it's actually possible.

Josh:
And I think when we talk about Tesla and AI5 and the XAI team,

Josh:
when we talk about OpenAI working with whoever they're working with to build

Josh:
their own in-house GPUs, I think this sets a precedent that it is possible.

Josh:
And I suspect that will result in more companies putting their foot on the gas.

Josh:
When it comes to kind of destructing part of NVIDIA's monopoly that it holds

Josh:
over GPUs. So that to me is the interesting takeaway of this.

Josh:
And hearing that it was fully done, trained on these TPUs, that's very high

Josh:
signal to me saying, okay, there is an architecture chips happening.

Josh:
There is a real benefit to vertical integration if you could figure out manufacturing

Josh:
these compute units at scale.

Josh:
And now the race is on for everyone to do this.

Josh:
Because again, using the Apple example, the M series chips, unbelievable,

Josh:
and they unlocked the best computers in the world.

Josh:
And if companies can really start to refine this vertical integration of their

Josh:
own chips, you're going to see that exponential curve go vertical times 10.

Josh:
Like it is going to, I suspect that is very...

Josh:
Obviously now how we reach AGI faster than people previously thought,

Josh:
because the efficiency improvements from those vertical integrations,

Josh:
once they're able to manufacture these at scale, are going to be unbelievable.

Josh:
And I'm so excited for that to happen in the near future. Google has a big head

Josh:
start, but let me tell you, the other companies are not far behind.

Ejaaz:
Well, let me introduce you to another big advantage of being the big dog, Google.

Ejaaz:
You thought you were going to come on to this episode and listen to us hopping

Ejaaz:
on about a generalized model? No.

Ejaaz:
You're forgetting Google has many other products in their arsenal,

Ejaaz:
and you're forgetting that they can plug in their new state-of-the-art model into all of them.

Ejaaz:
So Google not only today announced Gemini 3, but they also announced a different product.

Ejaaz:
It's called Google Anti-Gravity, which is basically a new software environment

Ejaaz:
for you to code up AI agents, except this time these AI agents are going to

Ejaaz:
be super, super smart because they get plugged in with Gemini 3.

Ejaaz:
Now, if you remember earlier, I mentioned that one of the cool benchmarks that

Ejaaz:
this new model sets is in computer use, which means that it can control your

Ejaaz:
computer, it can do things autonomously for you.

Ejaaz:
Now, typically, the reason why we haven't really spoken about that on the show

Ejaaz:
is that they've been kind of lame.

Ejaaz:
Like they can book you a dinner reservation and do different kinds of stuff.

Ejaaz:
With this model, it's way more intuitive. It can do way more intelligent tasks

Ejaaz:
and it can take a lot more complex work off of your hands such that the value

Ejaaz:
that it produces to you over like the eight hours that you take to sleep overnight

Ejaaz:
would be considerable for you to actually be serious to use in your enterprise,

Ejaaz:
in your business, or just at your at-home lifestyle, right?

Ejaaz:
So the point I want to make around here is Google's moat is not just its intelligence

Ejaaz:
or ability to create new models. It's not its TPUs.

Ejaaz:
It's its distribution. It's the entire product suite that it has that regular

Ejaaz:
users like you and I that use Gmail, that use Google Suite can now kind of benefit

Ejaaz:
from simply by plugging in that model.

Ejaaz:
And I think like products like this, anti-gravity, I bet you,

Ejaaz:
Josh, we're going to see a slew of new Google product releases over the next

Ejaaz:
couple of weeks simply because they created this model.

Josh:
I hope so. I guess the contrarian take is like, okay, how many people are actually

Josh:
going to want to use them?

Josh:
We just spoke about how Claude is the superior code model. Everyone loves Cursor.

Josh:
No one really uses the mobile applications of these. A lot of people are engaging

Josh:
with AI on their phone. So maybe it works for the right type of person.

Josh:
But Google still does have that product problem where they kind of have a tough time.

Josh:
They have the amazing intelligence. They just have a tough time using it.

Josh:
I mean, I don't have the Gemini app on my phone. I mostly use Grok and ChatGPT.

Josh:
And there is this bar that they

Josh:
still need to cross that I think they're trying with Google AI Studio.

Josh:
And we had Logan Kilpatrick on, who was the head of that, to talk about it when Nano Banana came out.

Josh:
But there is still a bit of a long shot for them to get good at products to actually develop this.

Josh:
But what we saw this week is that there was a resounding, overwhelming amount

Josh:
of support, to your point, you guys, where the market just believes in Google.

Josh:
And in a week where all of the stocks, all of the Mag7 was down,

Josh:
Google was the one anomaly. Google was up this week.

Josh:
And I think it's because the market is starting to realize, one,

Josh:
vertical integration through these TPUs is a huge deal.

Josh:
Two, Google has an existing business that is not reliant on AI.

Josh:
And sure, AI places a huge hand on that scale, but it is not everything.

Josh:
And they are cashflow positive in the absence of AI. So all of this innovation

Josh:
that they're doing is really just applying later fluid on top of an already

Josh:
great business. And the market's starting to evaluate that properly.

Josh:
So Google is positioned very strongly.

Josh:
They have very high intelligence. Gemini 3 rocks.

Josh:
And I mean, again, we continue on the bull train for Google.

Josh:
I am a believer. I am a supporter.

Josh:
I am stoked that they have the crown. I assumed it was only a matter of time.

Josh:
And now the question is, who's next?

Josh:
Who is the next competitor? Who's going to set the next plot on that chart and

Josh:
set the vertical trajectory on the exponential curve we're on?

Josh:
Do you have any guesses who you think it's going to be?

Ejaaz:
Yeah, well, I don't because I don't think it's going to be anyone for a while.

Ejaaz:
I said this earlier in the show and I'm going to say it again. I think there's going

Ejaaz:
to be a six month period now where either the other model providers don't release

Ejaaz:
the model because it's not as good as Google's or they just kind of release

Ejaaz:
these kind of mediocre kind of like consumer products that kind of maybe benefit

Ejaaz:
certain consumers in one way or another,

Ejaaz:
but doesn't really kind of break the generalized model

Ejaaz:
standard that Google has just set.

Ejaaz:
Just a last point on the kind of Google bull case thesis, they may not just

Ejaaz:
play in the same ring as cursor does.

Ejaaz:
Like I was critiquing Microsoft on another episode, Josh, do you remember?

Ejaaz:
And then I got off that episode and I was just like, Microsoft like dominates

Ejaaz:
the enterprise environment.

Ejaaz:
All the boomer companies and institutions love Microsoft and they have all their data and memory.

Ejaaz:
And just because you and I don't use it or just I'll speak for myself,

Ejaaz:
just because I don't use it and I think it's doesn't mean that they're not absolutely crushing.

Ejaaz:
Google just came off a hundred billion dollar quarter of revenue.

Ejaaz:
That's like the highest they've ever had. So I don't want to be too hasty to

Ejaaz:
say that like Google's not going to make it because they can't make a sick consumer

Ejaaz:
product like OpenAI can maybe.

Ejaaz:
I just think they're maybe playing in different fields.

Ejaaz:
But to the point around like I don't think anyone else is going to catch up.

Ejaaz:
Look at these comments. I want to show you two comments all right one is from sam altman

Ejaaz:
He goes, congrats to Google and Gemini 3. This looks like a great model.

Ejaaz:
The other is from the almighty being, Elon Musk, saying, I can't wait to try this out.

Ejaaz:
And this is just one of a series of tweets that he's been putting out this week

Ejaaz:
saying, can you guys just drop Gemini 3? Because I need to see how good this thing is.

Ejaaz:
And the reason why I bring up these two people is both Sam Altman and Elon Musk

Ejaaz:
have released new versions of their models, GPT and Grok respectively,

Ejaaz:
but it's been the 0.1 upgrade.

Ejaaz:
It's GPT 5.1. It is Grok 4.1. and they are almost identical updates.

Ejaaz:
You want to know what the biggest and coolest thing about their model updates were?

Ejaaz:
Personality traits, which don't get me wrong, is cool. Like I would like my

Ejaaz:
model to kind of respond in a very intuitive manner and get me,

Ejaaz:
but it's nowhere near the state of the art standard that we've just seen broken by Gemini.

Ejaaz:
So the point I'm making is, I think these two companies might have run out of fuel for the near term.

Josh:
Grok is going to be next. You think? They're the next one. By the end of Q1,

Josh:
Grok will have the crown.

Josh:
Why? And I assume by a fairly large margin. But I assume it will be a different type of crown.

Josh:
And this is where I'm really excited to see how these models progress.

Josh:
We spoke a little bit earlier about how Cursor is kind of the coding model.

Josh:
Google has a very deep understanding of the real world and physics and video

Josh:
and understanding how that works.

Josh:
Grok and the XAI team are very focused on the pursuit of truth and information.

Josh:
And I think that's kind of the alley that we'll see them going down.

Josh:
So they have the real-time data with X. They have the pursuit of truth.

Josh:
And where Google and OpenAI and all these other companies are trained on an

Josh:
existing data set, the XAI team and the Grok team are developing an entirely

Josh:
new synthetic data set that is maximally truth-seeking.

Josh:
And we saw that early version with Grokopedia that should provide the most accurate

Josh:
and I guess thoughtful information. It should be the best of thinking because

Josh:
it's the closest to source truth. So while I think,

Josh:
Gemini will probably be better at physics and video and understanding the real

Josh:
world for quite some time.

Josh:
I suspect Grok will be really good at just communicating via text.

Josh:
If text is a modality in which we interface from, Grok should be really good.

Josh:
And again, the rate of acceleration, Grok has been around for the least amount

Josh:
of time. They're accelerating the fastest.

Josh:
And I'm very, very, very excited for a Grok 6, Grok 5, whatever we're at announcement,

Josh:
hopefully early next year. So that's the predictions.

Josh:
That's the episode. That's Gemini 3.1. It is an unbelievable new model.

Josh:
Everyone could try it out. So here's how you try it out.

Josh:
I believe you need to be a Google premium plus subscriber, whatever it's called. It's $20 a month.

Josh:
You can go on the Gemini website and it's just a text box and you can play around

Josh:
with it. They also have a mobile application.

Josh:
It's very easy to download on your phone, play around with it.

Josh:
I'd love to see examples of cool things because I think one of the problems

Josh:
for me and one of the things I'd love help with from anyone who's listening

Josh:
is how do you use this thing to test it?

Josh:
What do I ask it? And how are you interfacing with it to get the maximum amount of results from it?

Josh:
Because intuitively, I would never think to record myself and ask for feedback,

Josh:
but that's a new possibility.

Josh:
So I guess the challenge to anyone who's listening is figuring out how to get

Josh:
the most out of these new models as these new features get released.

Josh:
And Gemini 3 has just opened up the gates to a gazillion new use cases.

Ejaaz:
Yeah, I mean, this is a super cool release for Google.

Ejaaz:
And weirdly enough, it's not the only release over the last week.

Ejaaz:
I mean, I've got a list pulled up here. They've released new Android iOS updates.

Ejaaz:
They've got a new search AI mode. They've released anti-gravity that we mentioned earlier.

Ejaaz:
We've got CIMA2 research, which we demoed on a previous episode.

Ejaaz:
You should definitely go check that out.

Ejaaz:
I mean, they are just not stopping and they're a force to reckon with.

Ejaaz:
And kind of similar to them, Josh, just to kind of round this episode out and

Ejaaz:
thank you guys for listening.

Ejaaz:
We are here in Argentina, in

Ejaaz:
Buenos Aires. We are kind of meeting some of the fans that are out here.

Ejaaz:
And we spoke to one just this afternoon, Josh. And you know what he said to me? Have a guess.

Josh:
What's that?

Ejaaz:
He said, your podcast Limitless is like the state-of-the-art AI podcast.

Ejaaz:
In fact, it is 2X better than any other AI podcast that I've ever heard. And you know what?

Ejaaz:
That sounds very similar to

Ejaaz:
the Gemini 3. So you could potentially call us the Gemini 3 of AI podcast.

Ejaaz:
And so if you're a listener to this, if you are a non-subscriber on our YouTube,

Ejaaz:
you should probably click that subscriber button.

Ejaaz:
You should probably click that notification button because guess what?

Ejaaz:
We've got more episodes coming this week. And guess what? the five star ratings help us out massively.

Ejaaz:
So if you enjoyed this episode and if you want to hear more episodes of this

Ejaaz:
nature and of cutting edge news in AI, you should give us a follow and we will see