Limitless: An AI Podcast

Ejaaz:
NVIDIA just announced the key to one of AI's biggest problems, cost.

Ejaaz:
Companies spend between tens to hundreds of millions of dollars every year and

Ejaaz:
are running out of money.

Ejaaz:
Google, for the first time yesterday, reported a negative cash flow on their

Ejaaz:
quarterly earnings. They're officially losing more money than they are making.

Ejaaz:
That's because they're spending so much on AI infrastructure.

Ejaaz:
NVIDIA's new Vero Rubin officially got stood up yesterday and it saves you 10x

Ejaaz:
on the tokens that you spend, which means you can have a 10x better model for the same cost.

Ejaaz:
There's all of this and Google's new Gemini 3.6 models, which is very,

Ejaaz:
very underwhelming on today's roundup.

Josh:
Yeah, so we have to start with the big news of the day, which is that Vera Rubin is actually shipping.

Josh:
And for those who are not familiar, Jensen came on stage at NVIDIA GTC and announced these a few months ago.

Josh:
The news today is that they're finally live and they're actually operational.

Josh:
And we started to get an idea of what these things look like.

Josh:
And I want to preface a section with the idea that we just covered an episode

Josh:
yesterday about how GPT-6 or whatever the new internal open AI model was,

Josh:
they broke out of internal air-gapped containment

Josh:
and hacked into a public-facing website into their production database to steal secrets.

Josh:
That was on Blackwell chips. The new chips are Verorubin.

Josh:
No models have been trained on Verorubin chips, but the math behind how much

Josh:
more powerful they are is so unbelievably impressive.

Josh:
It's like, oh my god, this is this feels like the end game it's like once these

Josh:
varubin chips come online at scale what on earth are these models going to look

Josh:
like if we already have fable and gpt6 class models it's going to be pretty

Josh:
wild for some numbers 10x,

Josh:
the efficiency which is crazy so for every single megawatt you put into a gpu

Josh:
it will give you 10 times the amount of tokens this is a huge unlock for a lot of models.

Josh:
The second thing is in terms of density of transistors, there's 336 billion.

Josh:
That is a 62% increase over the Blackwell GB300. And this is on TSMC's three

Josh:
nanometer technology, which is basically the cutting edge.

Josh:
There's 22 terabytes per second of memory that is going through this whole thing.

Josh:
And basically, they ran out of room for a single piece of silicon and they glued

Josh:
these two maxed out dyes together and call it one.

Josh:
So that's kind of where we are. is like this chip is going to be 10x more performant

Josh:
per watt and it's going to have a just unbelievable baseline relative to the

Josh:
gb300 a lot of people are saying about four times the baseline so

Josh:
imagine what we get when these models are trained on not only four times the

Josh:
baseline but also efficiency improvements in terms of algorithms like

Josh:
The next generation of software built on these things is going to be a monster.

Ejaaz:
And I want to translate what this means for the wider market and for NVIDIA

Ejaaz:
stock, which has pretty much just been flat for the last like five months.

Ejaaz:
I think this is NVIDIA's star moment for this year.

Ejaaz:
Now, the reason is it's really costly to train and inference models these days.

Ejaaz:
And so any way that a company, an enterprise that is spending 10 to hundreds

Ejaaz:
of millions of dollars every year can save money is a big deal.

Ejaaz:
Now, a big way that they can save money is infrastructure. Right now,

Ejaaz:
people are paying around 50% to 60% profit margin on every dollar spent on an AI token to NVIDIA.

Ejaaz:
They are like monopolies in this way. So, NVIDIA giving them a 10x efficiency

Ejaaz:
increase means that you can create or run your Fable 5 model,

Ejaaz:
your local open source model, Kimi K3, at one-tenth of the cost purely because of infrastructure.

Ejaaz:
Now, the way that this GPU works, you can't just run one Vibra Rubin on its own.

Ejaaz:
You need to run 72 of them in one server rack.

Ejaaz:
And they're serviced by 32 of NVIDIA's CPUs. Now, the reason why they have so

Ejaaz:
many CPUs is because when you're running these AI models these days,

Ejaaz:
you're not really running one instance of an AI model. You're running many.

Ejaaz:
It's called AI agents, and they need to access different tools.

Ejaaz:
That's what the CPUs are for. So it's this collective thing with the software

Ejaaz:
and hardware integration, the way it's set up, that makes NVIDIA's GPUs so, so effective.

Ejaaz:
And so if I had to make a call here, what is their most direct competitor, Josh?

Ejaaz:
It has to be Google. Google has tried to go for the NVIDIA throne with their

Ejaaz:
own custom-made GPUs called TPUs, their Tensor Processing Units,

Ejaaz:
and they had their quarterly earnings results

Ejaaz:
Yesterday, and they made a significant chunk of money on TPUs,

Ejaaz:
but they also announced that they're gonna be releasing a new chip,

Ejaaz:
and I just don't think that they can catch up to NVIDIA.

Ejaaz:
So NVIDIA's running away with it, and this is a huge advancement for AI models in general.

Josh:
And Viti's got a hell of a lead. And one of the headlines that I do want to

Josh:
finish this segment on is the amount that they're actually able to produce of

Josh:
this. Because we have a lot of people that are interested in the investment

Josh:
angle. We have an interesting investment angle here.

Josh:
And the number is a thousand. A thousand of these racks per day.

Josh:
And each, as like you mentioned, each rack contains a lot of these chips inside of it.

Josh:
And that means that they are projected to make $630 billion per day.

Josh:
Per quarter assuming they can get this up throw that.

Ejaaz:
Into your earnings per share forecast

Josh:
Whatever whatever forecasting you're doing for nvidia like perhaps think higher

Josh:
that is a tremendous amount of money for a single skew like this is one of the

Josh:
many products lines it's important to note also that vera rubin has cpus and

Josh:
the cpus have been shipping since last month so there's

Josh:
a huge business being built on this new very i think.

Ejaaz:
They're on track to make like what 20 billion dollars this year just from cpus alone

Josh:
A gazillion at this point i don't know Nvidia, just like there is no end in

Josh:
sight to the amount of GPUs that they're going to be able to sell to people.

Josh:
And this number I found pretty large. Now, you mentioned Google,

Josh:
and I feel like we do have to talk about Google because they just had their

Josh:
earnings report as well as announcing a lot of things.

Josh:
And to preface this section, we were possibly the number one fanboys on the

Josh:
internet of Google and Gemini and DeepMind.

Josh:
And we were talking about them almost every day. I don't think we've had an

Josh:
episode on them in the last, I don't know, two, three months.

Josh:
It's been kind of rough. So are things getting better?

Ejaaz:
Okay, so Google had a big week of announcements. Unfortunately,

Ejaaz:
100% of those announcements kind of sucked.

Ejaaz:
So the first major announcement is they released a series or rather their new

Ejaaz:
flagship AI model. It's called Gemini 3.6 Flash. This is an iteration on Gemini 3.5.

Ejaaz:
And unfortunately, it's not that very good. Now, they advertise it as not being

Ejaaz:
frontier, but being cheap, affordable, and cost efficient. Now,

Ejaaz:
if you're saying those words, it better be worth the cost that I'm paying for

Ejaaz:
it for the intelligence that I receive.

Ejaaz:
Fortunately, it's dumber than ChatGPT 5.6 Luna, which is their worst model of

Ejaaz:
their frontier labs that they release.

Ejaaz:
And it gets worse, Josh. It's worse than GLM-5. It has 5.2, not even 5.3, GLM-5.2 and Kimi-K3.

Ejaaz:
The open source models from China that have a fraction of the budget that Google,

Ejaaz:
remember, Google is spending $200 billion this year.

Ejaaz:
These Chinese AI labs are spending one hundredth of that and they're able to

Ejaaz:
pull off a better model and they're open sourcing it for everyone to run at

Ejaaz:
a much more cost-effective way.

Ejaaz:
So the question I have for Google is, what earth are you doing?

Ejaaz:
These models are just terrible. Sorry.

Josh:
Yeah, it's disappointing to see because, you know, Google was kind of crushing

Josh:
it. They were winning across the board and they were working on these world

Josh:
models. Like Google was the world model company and they had all of these individual pillars.

Josh:
And now when we look at this chart, I mean, they're not even in the middle.

Josh:
They're at the back of the pack.

Josh:
I think that's probably most embarrassing is like, dude, you're getting beaten by meta. Come on now.

Josh:
And this seems to be the trend. And I get upset with myself a little bit for

Josh:
like, they fooled me once and then they fooled me again,

Josh:
where Google has had this period of time where like, hey, they literally invented

Josh:
the transformer architecture that every single AI language model runs on,

Josh:
but they weren't able to turn it into a product.

Josh:
Then the CEO, the co-founder or the old co-founder, I guess,

Josh:
Sergey Brin, he comes back into the office.

Josh:
He whips the company into shape. He gets them right back at the frontier.

Josh:
And then we're kind of going through this fall off again, where perhaps like

Josh:
culturally at Google, there is this deeply rooted inability to actually convert

Josh:
these ideas to compelling products

Josh:
and to do so at the scale required to compete with Frontier AI Labs.

Josh:
And I think that's the moment of time that we're at now where Google very much

Josh:
feels like they are in crisis mode, given the things that they have released so far.

Josh:
And relative to the things in the market, it's like, it's tough to find a good

Josh:
thing to say about what's gone down this week. There is some promise and some hope.

Josh:
In the sense that while I was reading through everything from Google this week,

Josh:
they have this new chip architecture that they're trying to build.

Josh:
And that seems like it could possibly give them an edge.

Josh:
I mean, when we think about the GPU, CPU architecture world,

Josh:
there is like general GPUs with NVIDIA, but then there's accelerators like the

Josh:
TPUs and like the custom ASICs and like the etched chips that have LLM architecture baked right in.

Josh:
So what is the deal with this new Google chip that seems to be competing directly with that?

Ejaaz:
Yeah. So it's called or codenamed frozen v2 and it's basically an iteration

Ejaaz:
of their existing chip architecture that they've built tensor processing units

Ejaaz:
or tpus now if we look at their quarterly earnings which we're about to in a second

Ejaaz:
they made quite a decent chunk of money selling their tpus to external customers

Ejaaz:
now this is a big jump from the previous quarter because google primarily built

Ejaaz:
and used tpus to train their own gemini models what they've done the change

Ejaaz:
between q1 and q2 is they've started selling it to

Ejaaz:
other vendors, such as Anthropic and other AI labs to train their models to

Ejaaz:
create a new revenue business line for them.

Ejaaz:
Now, frozen chip v2 is meant to be six to eight times more efficient than TPUs.

Ejaaz:
And if you remember, the original pitch of TPUs was more efficient training

Ejaaz:
and inference for your AI model. So they seem to have revived a new chip architecture

Ejaaz:
and they want to build it.

Ejaaz:
Now, the bad news is this thing isn't coming online until 2028.

Ejaaz:
Vera Rubin that we just discussed came online yesterday.

Ejaaz:
And it has 10 times more efficiency than the last predecessor of NVIDIA,

Ejaaz:
which the TPUs couldn't keep up with.

Ejaaz:
So my question to you is, even if they achieve six to eight times more efficiency

Ejaaz:
in two and a half years time, who the hell cares?

Ejaaz:
Because NVIDIA will have a better chip architecture by then that is massively more efficient.

Ejaaz:
So I don't see a way that Google capitalizes or keeps up or catches up,

Ejaaz:
rather, with NVIDIA on the chip side of things.

Ejaaz:
Now, just briefly on the model side of things, I can't emphasize enough how

Ejaaz:
bad it is that Google hasn't delivered a frontier model in the last,

Ejaaz:
what is it, four months, right?

Ejaaz:
They have all the data in the world. Gmail, Search, Browser, Android, G Suite.

Ejaaz:
They can use that data to create an amazing model. Sucks.

Ejaaz:
Coding models, where they should have diverted all their compute to,

Ejaaz:
absolutely failed. What were they doing instead?

Ejaaz:
Oh, let's just sell all our compute to other vendors. Okay, but what if they

Ejaaz:
weren't selling their compute to other vendors? What were they doing?

Ejaaz:
They were distributing it amongst teams.

Ejaaz:
Teams literally had to fight internally to get compute. DeepMind had to fight for the compute.

Ejaaz:
Now, if you compare that to Anthropic, if you compare that to OpenAI,

Ejaaz:
it is a completely different philosophy. It's like, give the researchers the

Ejaaz:
compute because they're going to build a better model and that model eventually,

Ejaaz:
down the line, will bring every other business unit up.

Ejaaz:
And Google fumbled that back. A lot of critics are going to respond to this

Ejaaz:
and say, well, Google had an amazing revenue quarter. Yeah, for now.

Ejaaz:
Like, what does that look like in like five months from now?

Ejaaz:
And there's a reason why Google stock is down 5% as we're recording this.

Ejaaz:
Because even though they had an amazing record quarter, no one cares.

Josh:
Yeah, I think that's the idea is a lot of earnings now, although they are making

Josh:
a lot of money, they are up. Oh, I think revenue is up 24% year over year.

Josh:
They're still growing fairly quickly, but no one really cares about growth.

Josh:
That is expected. There is this AI golden era where if you are serving any sort

Josh:
of tokens, you are making money on them with a fairly large margin.

Josh:
The thing people are interested in is that looking forward, like what is the forward look?

Josh:
What is their chance of capturing this new wave of AI token economics?

Josh:
And their probabilities continue to go down. And we see this in the stock price.

Josh:
Like, look at this chart. This is so ugly. It's so bad. It's really tough to see.

Josh:
And I think it's because like you read the numbers now, you're like,

Josh:
okay, great. Google search totally

Josh:
isn't dead. It's actually doing much better than it ever was before.

Josh:
I think what it's like up 17% on the year or something like that, which is really great.

Josh:
But when you look forward, like,

Josh:
what is the odds that Google is at the frontier at 12 months from now?

Josh:
I think that number is lower and it's lower than it has been before.

Josh:
And that is discouraging to investors. So I'm wishing Google all the best.

Josh:
I really am. I freaking love this company and I want them to win so bad.

Josh:
It's just, it's difficult to get excited when there's no tools that you actually

Josh:
want to use because everything else that's on the market is so far superior.

Ejaaz:
So moving on, a big debate this week, Josh, we'll cover this in a few episodes

Ejaaz:
this week, is the China versus USA, open source versus closed source AI debate.

Ejaaz:
Now, for those of you who are unfamiliar, definitely go check out some of our previous episodes.

Ejaaz:
But basically, China released Kimi K3 and soon to be a series of open source

Ejaaz:
models that are 90% capable of the frontier models that the US have made.

Ejaaz:
So we're talking about Fable 5, GPT 5.6, but at a fraction of the cost,

Ejaaz:
and you can host it on your own server, which means that it could be even cheaper.

Ejaaz:
And so the question all these companies are asking, similarly to the new Vera Rubin update is,

Ejaaz:
Why should I pay all this money to access Fable or GPT 5.6 when I can just spend

Ejaaz:
a lot less? And yeah, maybe the Chinese models are a little slower,

Ejaaz:
but I get to own my data and I need to, and I basically save a ton of money. So why would I do this?

Ejaaz:
And so the US has responded and said, hmm, these Chinese labs,

Ejaaz:
I think have distilled a lot of proprietary information from US American labs.

Ejaaz:
And so we are now considering banning open source models. Now,

Ejaaz:
I just want to repeat that for a second.

Ejaaz:
The capitalist freedom country is considering potentially banning open source models.

Ejaaz:
And meanwhile, the communist country is like, hey, open source is a strategy

Ejaaz:
going forwards. We had a comment from Liang Wenfeng from DeepSeek.

Ejaaz:
He said, we're going to remain open source for as long as we can,

Ejaaz:
because that is what we believe in.

Ejaaz:
So it's just weird dichotomy. And if US does end up banning open source,

Ejaaz:
it's going to mess up a lot of young startups in the US who are currently relying

Ejaaz:
on open source models to build their products because they can't afford the

Ejaaz:
expensive American Frontier Labs.

Josh:
Yeah, this doesn't make any sense to me at all. I don't think like I'm not even

Josh:
sure this is going to be possible. It seems to me like this is posturing for

Josh:
probably setting up some sort of legislative plan or some sort of form of action.

Josh:
It's not actually going to happen because when you think about what it means

Josh:
to ban these Chinese models, this open source code, I mean, ignore the idea

Josh:
that they're Chinese. Just think of it as open source code. This is just binary numbers in a page.

Josh:
This is a near impossibility in this world to ban when everyone is actively

Josh:
seeking it. I mean, you think about internal secrets at Frontier AI Labs and

Josh:
how quickly those leak out.

Josh:
If this is out in the public, there's no way that people aren't going to clone it and run it locally.

Josh:
And who's going to stop them from doing that? It's like this is this is not really a practicality.

Josh:
And when you think about I mean, the country as a whole, just from an ethical

Josh:
standpoint, open source code very much is reminiscent of open and free speech.

Josh:
And just like banning that seems like a slippery slope that is very problematic.

Josh:
So I am hopeful and feeling fairly certain that this is posturing for something larger.

Josh:
Just kind of signaling an intention versus actually taking action on it.

Josh:
Because I mean, I would hope that they are, you know, reasonable enough to recognize

Josh:
that banning Chinese open source models is just never going to happen.

Josh:
I mean, if the code is online, we are going to get it, we are going to use it,

Josh:
we are going to run it locally.

Josh:
The fact that it runs locally is even more against it, because it's easier to

Josh:
just take it on a computer and run it air gapped, and no one can ever discover it.

Josh:
So I think it's it seems like we'll see, we'll keep monitoring this one and see like what the larger

Josh:
idea behind this is but i don't think it's actually banning because that just

Josh:
goes against so many ethical things that we've set up so much of like just practical

Josh:
um the way this works it's just it doesn't make sense.

Ejaaz:
I think what's happening at the core of all of this is there's a big fear in

Ejaaz:
the u.s that china is catching up and

Ejaaz:
originally it was like china's three years behind both in model development

Ejaaz:
and chip architecture and you need both of those things you need compute but

Ejaaz:
china has a lot of compute in order to build frontier models.

Ejaaz:
Recently, they've caught up a lot quicker than we expected. The models are getting better.

Ejaaz:
They're owning their own chip architecture. In Xi Jinping's speech last week,

Ejaaz:
There was also a co-announcement from Huawei, which basically said,

Ejaaz:
hey, we have this new chip rack server, and every single Chinese frontier lab is going to use it.

Ejaaz:
And then followed by that, we have Chipu, one of their biggest AI labs,

Ejaaz:
announced that they've just completed the construction of a gigantic data center

Ejaaz:
that is only going to run Chinese-made chips.

Ejaaz:
No NVIDIA chips in sight. Now, if you rewind like three months ago,

Ejaaz:
NVIDIA, Jensen really wanted to sell China chips because they will then rely

Ejaaz:
on American frontier chip architecture and therefore we could kind of like regulate

Ejaaz:
and keep an eye on these things.

Ejaaz:
That is no more. So I can understand why the Trump cabinet is getting a bit

Ejaaz:
worried and I'm interested to see kind of what process they take going forwards. Yeah.

Ejaaz:
Moving on, Josh, there is a trend that is developing this week,

Ejaaz:
a weird one that not a lot of people expected.

Ejaaz:
Over the last three days, three different companies, three major companies,

Ejaaz:
announced that they're creating what's known as a model routing platform.

Ejaaz:
Now, if you want to know what that is, when you send a prompt,

Ejaaz:
typically you're using a ChatGPT subscription. So it goes to ChatGPT or using

Ejaaz:
a Claude subscription. It goes to Claude.

Ejaaz:
A model routing platform takes your prompt and decides which parts of your prompt

Ejaaz:
to send to different models for different types of function.

Ejaaz:
And the reason why they do this is, one, to give you a better answer output

Ejaaz:
than sending it to a single model, and two, to save you a heck ton of money.

Ejaaz:
That's what Cursor did for coding, and it's what led to them getting it acquired

Ejaaz:
for $60 billion. And Cursor themselves is coming out with a new platform called

Ejaaz:
Cursor Router, which is a more generalized platform for any kind of LLM prompt.

Ejaaz:
The other two companies that also announced that they're building a similar

Ejaaz:
product is Meta and Ramp. Ramp is in the finance game.

Ejaaz:
And Meta, as you know, looked at OpenRouter, looked at Ramp and was like,

Ejaaz:
I need to do this internally because I'm spending tens of billions of dollars

Ejaaz:
every single year to build a better AI model. Why don't I just create a cheaper,

Ejaaz:
effective routing platform? It's interesting to see.

Josh:
Yeah, the interesting thing, I mean, Cursor is claiming frontier quality at 60% lower cost.

Josh:
And if that is true, that seems like a pretty compelling argument for a lot

Josh:
of labs to come and use this or for a lot of users to come and use this.

Josh:
Now, I find it interesting that we're seeing this from Cursor,

Josh:
from Ramp, from Meta, and we're not seeing this from OpenAI,

Josh:
from Anthropic, from Google, because they very clearly have this suite of models

Josh:
that would imply that they have the ability to do this.

Josh:
I mean, we have like the Sol Luna Terra from OpenAI and GPT,

Josh:
where it's like very clear that they would benefit from a router.

Josh:
So you have to imagine they're kind of working on this. And I wonder if this

Josh:
is an instance, kind of like the early Internet era, where...

Josh:
Your feature or your company becomes a feature and if cursor router is not able

Josh:
to kind of sustain a moat of an audience

Josh:
what's stopping chat gpt and open ai from launching their own and doing this

Josh:
own router with their own tokens and as they get more efficient they're able to ride it

Josh:
more more effectively and they have more data than any other company because

Josh:
they have all the queries that they can just

Josh:
train off of and imply this so it's exciting to see this now and i think it's

Josh:
incredibly important for companies who are trying to save money to use this

Josh:
type of technology but man it's going to be tough to compete i think it's like well,

Josh:
you're kind of going like you're going up against the big guys here and like

Josh:
maybe this works for now but i mean you're a one feature away from if people

Josh:
just not really caring anymore.

Ejaaz:
I think so i think so um okay i think to round up the docket today josh something's going on with

Josh:
Oh this is so sick wait yes can we talk about tesla yeah.

Ejaaz:
What's going on tell me what's going on

Josh:
Oh my god okay so first starlink v5 if you've used Starlink before,

Josh:
this is like a big satellite dish, sits on your roof, can get you connection

Josh:
anywhere in the world. If you've ever traveled to a country that isn't very

Josh:
well industrialized, you've seen these on roofs everywhere.

Josh:
It's how everyone gets their internet. This new version, Starlink V5, is about 40% smaller.

Josh:
It is significantly more efficient in terms of how much you can get per watt.

Josh:
And more importantly, it is being integrated into every single cyber cab being

Josh:
produced ever, which is unbelievable because now there's this super cluster

Josh:
of computers that can run anywhere in the world that will be connected to,

Josh:
internet. So if there's ever a problem, if the car ever needs help from anyone,

Josh:
if it ever needs to share data back to the mainframe, it's able to do that using

Josh:
this integrated Starlink antenna.

Josh:
And we're entering this world between this and the Starlink mobile satellites

Josh:
that are coming with Starlink V3 on Starship, where you will never go anywhere

Josh:
on planet Earth and not have connection to the internet.

Josh:
And that to me seems like so cool and really powerful. And when you think about

Josh:
how much compute is going on these cybercabs, training cluster,

Josh:
I don't know, just saying.

Ejaaz:
So my biggest bull case for Tesla has got nothing to do with cars and honestly

Ejaaz:
nothing to do with robots.

Ejaaz:
It's to do with this decentralized network that he's building that he can lean

Ejaaz:
on to train models, to inference prompts, and just to kind of like power this new AI economy.

Ejaaz:
If that sounds like a lot of jargon, it's because this is new.

Ejaaz:
This is net new and we haven't ever seen anything like this.

Ejaaz:
But Elon, who is the master of hyperscaling any kind of infrastructure target

Ejaaz:
that he sets his eyes on is the guy to do this. And I think Tesla,

Ejaaz:
It's the largest network of robots. If you want to argue like what a robot is

Ejaaz:
and whether robots are roaming around today in the world, Tesla is a prime example of that.

Ejaaz:
And so I'm excited to see this happen. I'm so, so pumped.

Ejaaz:
Sorry, I know this is a layman thing to say, but to just have internet wherever

Ejaaz:
I go, I'm tired of getting on like a Delta flight and having crappy internet.

Ejaaz:
Just allow me to stream, allow me to watch videos, allow me to call my friends.

Ejaaz:
That would be amazing. So I'm excited to see this come out.

Ejaaz:
But I believe that is the end of the docket for this week. That's it.

Ejaaz:
Yeah, if you're listening to this, You are all officially caught up.

Ejaaz:
I've heard rumors that there's some potentially new features and models coming

Ejaaz:
out. You'll hear about all of that next week, I think on Tuesday.

Ejaaz:
But aside from that, if you're listening to us on YouTube, please subscribe.

Ejaaz:
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Ejaaz:
Turn on notifications. It helps us out massively. If you're listening to us

Ejaaz:
on Spotify or Apple, leave us a comment. Give us a rating. It helps us out massively.

Ejaaz:
And I think that's it, Josh. Is there anything else?

Josh:
That's everything. Thank you so much for joining us for another amazing week

Josh:
of AI Frontier Technology.

Josh:
Next week buckle up the rumor mill's been going crazy i think by then we're

Josh:
going to have a lot of news so i'm excited to talk about it here on the show

Josh:
don't miss it we'll see you guys next week have a great weekend see you guys.