Limitless: An AI Podcast

Josh:
There's a new top dog in town, and the question on everyone's minds is, who is this?

Josh:
There's a secret model codenamed 0xAlpha that's been live since August 20th,

Josh:
the last six days, and it is offering the seemingly unbelievable things to the public.

Josh:
They're offering 100 trillion tokens of free usage to anyone who wants to go

Josh:
and get it. They're offering a million token context window,

Josh:
and the benchmarks of this thing are pretty unbelievable.

Josh:
There's also this weird thing going on in the background where seemingly every

Josh:
single day the outputs of the model are getting better there were tests on day

Josh:
one that were far inferior to the tests that were currently on day six as of

Josh:
this morning we think we have the answer to who this person is but before we talk about that

Josh:
we have to discuss what is 0x alpha you guys this has been the mystery of the

Josh:
week it seems like frontier level intelligence it's offering all of these unbelievable

Josh:
things like 100 trillion tokens for free

Josh:
do you know how much that would cost if you were to use like fable or gbt's 5.6

Ejaaz:
Salt like i think it's like 15 to to like 20 million bucks a day.

Josh:
It's a lot of money

Ejaaz:
A day okay so just with that figure alone who who on earth is giving away 20

Ejaaz:
to 30 million dollars on inference per day in this economy right it has to be

Ejaaz:
a big frontier lab the second clue is josh it's not 0x alpha

Ejaaz:
it's ox alpha which seems kind of weird right Like who's talking about the animal ox?

Ejaaz:
Until you realize that it's probably part of like the Chinese kind of folklore

Ejaaz:
and Zodiac side of things, which again, might be a little hint as to where we're

Ejaaz:
going. But anyway, let's rewind six days ago very quickly.

Ejaaz:
Open Router, which we've covered on the show before, it's a platform that kind

Ejaaz:
of like hosts a bunch of different models, allows you to pick and choose,

Ejaaz:
revealed a stealth model. Now a stealth launch is where they launch the model.

Ejaaz:
You go to their website, you can access and use the model for free.

Ejaaz:
But they don't tell you the name of the model. Now, they've done this with previous

Ejaaz:
launches through Google Gemini's model. They've done it through Anthropic.

Ejaaz:
They've done it through OpenAI as well.

Ejaaz:
And they haven't had a stealth model launch in a while, but now this is the

Ejaaz:
first one and it was in high demand.

Ejaaz:
So as you mentioned earlier, 100 trillion tokens, which means that you can effectively

Ejaaz:
go there and do like all your sorts of coding works, very heavy AI usage tasks.

Ejaaz:
And you can kind of use that in a day.

Ejaaz:
Again, 20 to $30 million worth of inference costs.

Ejaaz:
It has a massive 1 million context window, which is very competitive with the

Ejaaz:
top models that we see from Fable 5, as well as GPT-5.6 Sol, and,

Ejaaz:
and this is the most important part, it's a uni model, which means that you

Ejaaz:
can use not just text, but images, models. It's really good at rendering all

Ejaaz:
these different types of medium.

Ejaaz:
Now, the final point, which I think is the most exciting one that you referred

Ejaaz:
to earlier, Josh, is this concept of continual learning.

Ejaaz:
So people, as they started to use this model, realized a very curious phenomenon.

Ejaaz:
They realized that as they were using this model, let's say on day one,

Ejaaz:
day two and day three, the model got exponentially better at doing the very

Ejaaz:
same tasks that they fed it in day one.

Ejaaz:
And so people started to be suspicious that this is a model that doesn't just

Ejaaz:
kind of take your input and spit back out an answer, which is what a lot of

Ejaaz:
models do right now, but it can continually self-learn and improve 24-7 to give you a better response.

Ejaaz:
So the question on everyone's mind is, who created this model at all?

Ejaaz:
And when you look at the kind of usage or when you look at the kind of uptake on OpenRouter itself.

Ejaaz:
Although no one knew, it became the most viral launch on OpenRouter.

Ejaaz:
It became the new number one model and dethroned DeepSeek's Flash,

Ejaaz:
which launched about a couple weeks ago. And DeepSeek has been kind of like

Ejaaz:
the name brand on OpenRouter for the longest time ever. So just a really exciting model to see.

Josh:
Yeah, it was not only the most popular model on OpenRouter immediately upon

Josh:
launch, but by a factor of two.

Josh:
And it more than doubled DeepSeek's use. Like, This is hugely popular and very

Josh:
interesting because of how well it performs.

Josh:
The benchmarks from it, the Deep SWE subset benchmark, it had an 80% pass rate,

Josh:
which for those who aren't familiar, Fable 5 was at 65% and GLM 5.3 was at 62%.

Ejaaz:
Hold on, hold on. So you're saying that it's crushing the METOS level models

Ejaaz:
and the GPT-5.6 models at coding?

Josh:
In one particular subset of coding benchmarks.

Josh:
I don't want to i definitely don't want to say it's better than the frontier

Josh:
models because upon further investigation we will come to find out it's not

Josh:
and it's pretty far from it but it's an incredible model for what it is and

Josh:
the reason i was comparing it to glm 5.3 is because

Josh:
There's this thing when you're producing models called the tokenizers,

Josh:
how tokens get generated. And it was just so happened to be identical to GLM.

Josh:
So people were like, huh, this is interesting. Maybe we can go further down

Josh:
the rabbit hole and see if there's more here.

Josh:
So you can test oftentimes whether a model is Chinese or not based on asking

Josh:
it a series of questions that are not really allowed to be answered in China.

Josh:
One of which is asking whether Taiwan is part of China.

Josh:
And what's funny is if you're using like an American frontier lab,

Josh:
they'll very clearly give you the answer to this question but chinese models do not and

Josh:
what we realized is that the output of the answer to this question was pretty

Josh:
much identical to the glm model and so like okay it's got a similar tokenizer

Josh:
it's giving similar outputs but we still don't really know

Josh:
Up until this morning, in which we discovered that GLM is actually the new version of GPOO.

Josh:
It is, or sorry, that Ox Alpha is the new version of GPOO.

Josh:
And it seems like this is going to be a new GLM model that we have.

Josh:
And that, when I heard it, it actually landed me even more suspicious because

Josh:
over the course of this last week on X and all of his social media,

Josh:
everyone has been kind of vague posting about who this is, why they're doing

Josh:
it, why they're offering so many tokens and so much compute.

Josh:
And then the Google team started chiming in, which I thought was really bizarre.

Josh:
A lot of developers on the Google DeepMind team who work on Gemini,

Josh:
they started vague posting about this model. And as of this morning,

Josh:
Bloomberg released a post, and it seems like it is everything but confirmed.

Josh:
The model actually is from Z.ai and OxAlpha is now known.

Josh:
And I think that was like a really interesting way of coming to this conclusion.

Josh:
And now that we know, I just have more questions. How on earth are they serving

Josh:
all this inference to all these people for free. Like the cost must be tremendous.

Ejaaz:
I mean, let's see how this model shapes up against all the other models.

Ejaaz:
So we have a chart over here, which shows kind of like the average tokens output

Ejaaz:
per task on the DeepSuite benchmark that you mentioned.

Ejaaz:
DeepSuite, for those of you who don't know, is a good test of a model's capability

Ejaaz:
to actually code really well. And code is kind of like the premium benchmark

Ejaaz:
that a lot of companies and AI labs kind of like benchmark their model assets against.

Ejaaz:
And so OxAlpha is actually quite high up there. It's up there in terms of reduced

Ejaaz:
token output, but still maintaining a very high intelligence score.

Ejaaz:
Now, as you mentioned earlier on, that's not actually quite what was revealed

Ejaaz:
when people started playing around with this model.

Ejaaz:
It ended up achieving not really 80% that you mentioned earlier, but around 63%.

Ejaaz:
And that's under like real usage. So there's a suggestion there that the Chinese

Ejaaz:
lab GPU kind of like maybe bench backs this.

Ejaaz:
To just talk about the model and why it's so impressive, just in its own merit,

Ejaaz:
there's a few things to look at.

Ejaaz:
Number one, the rumor has it that this model isn't a foundation model.

Ejaaz:
This is a flash model. So what that means is it's a smaller derivative of a

Ejaaz:
much larger model that Jeepoo is training or has already trained.

Ejaaz:
So what does this mean? Let's take Mythos or let's take JeepT5.6.

Ejaaz:
These are rumored to be around 6 to 10 trillion parameter models.

Ejaaz:
Now, when you look at Jibu's flash model, if that's true, you're only looking

Ejaaz:
at around like two to three trillion parameters in size, which,

Ejaaz:
you know, is a decent size, but it's still very small compared to these bigger models.

Ejaaz:
And then the fact that this model is not only likely going to be cheaper in

Ejaaz:
its usage, let's say maybe 30 to 50 cents per usage.

Ejaaz:
So like they gave away like 15 to $30 million per day of 100 trillion tokens,

Ejaaz:
it is able to work much faster, and they're going to open weight the entire model.

Ejaaz:
So, I mean, to answer your question, I don't really have an answer,

Ejaaz:
Josh, as to how they've been able to kind of create this, aside from the usual,

Ejaaz:
maybe they distilled a Western model, or maybe they had a breakthrough in continual

Ejaaz:
learning that we suggested earlier.

Ejaaz:
But the point is, this is a very serious competitor. And we saw.

Ejaaz:
A kind of exchange between Elon Musk and the founder of Jipu,

Ejaaz:
where about a month or two ago,

Ejaaz:
Elon Musk was responding into a thread as to when he believed that Chinese or

Ejaaz:
open source models in general will become mythos level, you know,

Ejaaz:
have that cyber security risk.

Ejaaz:
And he said, probably Q1 of next year, of 2027.

Ejaaz:
And the founder, Ji Tang, of Jipu replied says, it won't take that long.

Ejaaz:
And he goes on to say, it doesn't show it in this thread right here,

Ejaaz:
that it'll probably take two to three months.

Ejaaz:
And he was true to this word. We now have an AUX alpha mythos level model that

Ejaaz:
is from Jipu that is flash, that is smaller, that is cheaper,

Ejaaz:
that anyone and everyone can use, and it's gonna be open-weighted a few weeks from now.

Josh:
And that's probably how it was served. It's just a low cost model to serve.

Josh:
And it's really funny watching the public reaction to this and kind of,

Josh:
I don't want to say overreacting, but getting very excited and enthusiastic

Josh:
about this because a lot of the posts about this were like, oh,

Josh:
it does have continual learning and it is getting better every day.

Josh:
And suspicions as to like, why are there more tokens being available every single

Josh:
day? And we have this post from Jeffrey Emanuel, who's actually,

Josh:
I guess, on the Limitless Show.

Josh:
And he just said, just thinking through this free 0x alpha model or aux alpha

Josh:
model how could it possibly make sense to give out this many tokens for free

Josh:
maybe there's been a continuous learning breakthrough and the best way to pour

Josh:
more gas in the fire is to source as many coding related requests as possible

Josh:
i don't know if that's right i think the kind of where i'm landing here is that

Josh:
this is a flash model this is some sort of distilled model that is meant to

Josh:
serve inference very cheaply and what we're seeing instead of continual learning it's just

Josh:
New checkpoints that they're kind of releasing every day. And we're able to

Josh:
track the checkpoints as they come into play. And they're just kind of generally

Josh:
iterating over time. I'm not sure it's self-improving.

Josh:
We are going to find out more on that soon.

Josh:
The interesting phenomenon that I have really enjoyed seeing over the last week

Josh:
is the blind taste test that's been going on.

Josh:
This is like known kind of like as the Pepsi challenge, where you put like Pepsi

Josh:
and Coke against each other in a blind taste test and people don't know what they're getting.

Josh:
And one of the things I found really interesting is how excited people got about

Josh:
this model because of the mystery and the lore.

Josh:
And it really makes you question the value of true frontier level intelligence

Josh:
when people were doing seemingly incredible things with this open source free flash model.

Josh:
And when you're comparing the two next to each other, for some tasks,

Josh:
it's very clear that the frontier models are stronger.

Josh:
But for many other tasks, that's not apparently obvious.

Josh:
And if you are just sending a prompt into a text box, and it is this Ox Alpha

Josh:
model, or it is like a mid-tier ChatGPT or Claude model, the outputs are mostly the same.

Josh:
And people didn't realize and people don't really care where the tokens come

Josh:
from. So I find this to be an

Josh:
A true stealth model that is good oftentimes it's connected to a brand and there's

Josh:
very strong brand affinity so when you remove the brand affinity from the equation

Josh:
what happens you kind of get this phenomenon here where it turns out people just want

Josh:
pretty smart tokens and they don't actually care where it comes from it's interesting

Josh:
to see the the continual improvement or whatever's happening here where there's

Josh:
an example of a rocket ship taking off and it very clearly looks like day over day

Josh:
its abilities to render 3d graphics and understand physics and create this like

Josh:
real-world emulation are significantly better.

Josh:
So I'm really excited to learn more as to what's going on behind the scenes.

Josh:
Like, are these pre-prepared checkpoints, are they actually taking all the data

Josh:
they're collecting from these 100 trillion tokens and using it to continuous,

Josh:
to apply like RL on top of the model? Like, I don't know. These are things I'm

Josh:
very excited to find out over the next couple of days, though.

Ejaaz:
Yeah, I think in the future, no one's really going to care which model they use.

Ejaaz:
They just want to make sure that the output is what they expected.

Ejaaz:
They want to have the most effective output for the cheapest possible cost that

Ejaaz:
they can pay for that output.

Ejaaz:
And we're seeing like a lot of companies move to some of these Chinese open

Ejaaz:
source models or just other models, cheaper models from other smaller American

Ejaaz:
labs, just so that they are able to save on costs and create like a more fine-tuned

Ejaaz:
model for this specific bit of work.

Ejaaz:
Now, I want to spend a bit of time to talk about if this model has achieved

Ejaaz:
continual learning, why that's important and why that puts

Ejaaz:
China, if this is Jipu's actual model, which they confirmed in a very advantageous

Ejaaz:
position because it kind of shifts the Game of Thrones around a bit.

Ejaaz:
Well, right now, you look at Anthropic, you look at OpenAI, they have the world's leading models.

Ejaaz:
They have internal models that they haven't even released yet that are supposedly

Ejaaz:
even more intelligent than the ones that they have publicly available.

Ejaaz:
And they have all the compute in the world and they're spending so much money

Ejaaz:
trying to train the best model.

Ejaaz:
So if you were to reason within yourself, maybe no one else can have the capability

Ejaaz:
to catch up in China, although they've been able to put out very good open source

Ejaaz:
models hasn't been able to surpass the frontier.

Ejaaz:
Now, one way that you can kind of cheat that dynamic is if you have a continual learning model.

Ejaaz:
Now, the best way to think about what this means is think of a really intelligent

Ejaaz:
15 year old or 18 year old when you teach it how to ride a bike on day one.

Ejaaz:
And then let's say you teach it how to make pancakes day 50s,

Ejaaz:
50 days later, it'll still remember or know how to learn how to ride a bike or how to ride a bike.

Ejaaz:
Current models right now doesn't work like that. They lose sight of their memory.

Ejaaz:
It's something called catastrophic memory loss or something like that.

Ejaaz:
And they're unable to kind of remember some of the smart intelligence stuff

Ejaaz:
that they learned earlier on.

Ejaaz:
Continual learning solves for that. Now, you can imagine if a model is actually

Ejaaz:
able to learn like a real human is, like a really smart kid,

Ejaaz:
you could reason to say that that model will be more valuable to you.

Ejaaz:
Especially if you could run it locally at home on your local device on all your types of private data.

Ejaaz:
So I can see two types of individuals looking at this kind of a model and being

Ejaaz:
really incentivized to use it over a Claude or over an OpenAI chat GPT type model.

Ejaaz:
And that one is enterprises who don't want to give all their data away to major

Ejaaz:
American labs. They would want to use an open weights model that can continue to learn.

Ejaaz:
And the second is any kind of respective retail user who doesn't want to give

Ejaaz:
away any of their personal records to Anthropic and open AI.

Ejaaz:
Let's say it's medical records or finance information.

Ejaaz:
Let's say they want to have an AI agent that handles their finances.

Ejaaz:
You know, you may have different reasoning behind whether you want to use a

Ejaaz:
certain brand or a certain lab.

Ejaaz:
But if you could run it privately at home, maybe you might want to use something

Ejaaz:
like this. But continual learning, just assume you have this model that learns

Ejaaz:
24-7, even when you're asleep, it could probably catch up with the frontier

Ejaaz:
models. And I think it's really interesting to see.

Ejaaz:
I don't know if this is that. I'm not convinced that it is.

Ejaaz:
But if China has made a breakthrough, that's going to put them in a very advantageous position.

Josh:
Yeah i also don't think it's that i find it hard to believe that this is what

Josh:
it looks like and that they've reached that point so far i mean that'd be an

Josh:
amazing breakthrough in the case they do

Josh:
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Josh:
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Josh:
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Josh:
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Josh:
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Josh:
It offers a series of tools that allow you to work with agents in a three-step

Josh:
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Josh:
So if you're building security and you want to securely use these agents ledger

Josh:
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Josh:
in which you engage with llms and is open source and available today so you

Josh:
can find a link in the description down

Josh:
in our show thank you ledger for sponsoring this episode and then i guess we

Josh:
kind of have to talk about that like is it really a free case because like is

Josh:
free ever really free and i guess there's two possible answers to this question

Josh:
one is yes it's just being heavily subsidized

Josh:
perhaps by the chinese government as a vampire attack to pull some demand from

Josh:
the frontier labs into these chinese models the other is perhaps they're just using the data

Josh:
one of the big problems that we have been seeing people complain about is data

Josh:
retention and zero data retention policies because people don't want to feel like they are

Josh:
Having their data harvested and used to train other models. And when you think

Josh:
about giving away these free models, China for a fact is collecting all of the

Josh:
inputs from the context window. And what's been happening is a lot of people

Josh:
are using this on perhaps proprietary code bases.

Josh:
People have been testing this model in their own private projects.

Josh:
They've been using it for their own personal work.

Josh:
And a lot of data gets derived out of that. I mean, it's a million token context

Josh:
window in this one chat box and you just paste it all in and you let it go to town.

Josh:
So I'm sure the amount of data that's collected from offering all of these tokens

Josh:
just through collecting all the inputs has been tremendous.

Josh:
And I'm sure that gives them a unique advantage in a way that some frontier

Josh:
labs might not, because oftentimes they are criticized for their retention policies.

Josh:
And people really want to make sure that there is that zero data retention.

Josh:
China doesn't face the scrutiny, in particular, doing it in stealth kind of

Josh:
shields that for at least the first week while people have used it.

Josh:
So they were just kind of freely and liberally using this thing,

Josh:
probably aware that they were having their prompts used for future training,

Josh:
but not really caring too much.

Josh:
So I thought that was also interesting. The other thing is that like the status

Josh:
of Jeep as a company still isn't very strong.

Josh:
They had, I think, like $100 million in revenue last year, and they had a net

Josh:
loss of like seven times that or something like that. It's currently priced at 750 times revenue.

Josh:
The company itself clearly can't sustain this type of...

Josh:
Funding and this free giveaway forever. And I'm curious to know what the type

Josh:
of business model eventually, if any, there is going to be in order to keep this thing alive.

Josh:
Like, is it just going to be a government subsidy until they figure it out?

Ejaaz:
The business model is its state back, dude. Yeah.

Ejaaz:
All these Chinese labs are backed by the state. So that's how they get their

Ejaaz:
infinite amounts of capital to be able to kind of fund all these things.

Ejaaz:
And this is a strategy that China has been pursuing for three plus years now.

Ejaaz:
They want to catch up with the frontier Western models. they distill attack

Ejaaz:
a bunch of these model labs so that they can train similarly capable models.

Ejaaz:
And then they flood the market with cheap intelligence, which means that Anthropic

Ejaaz:
can't charge the highest price that they can for the high quality model that

Ejaaz:
they have. OpenAI can't do the same.

Ejaaz:
So this drives model costs down. This is what kind of Meta and Mark Zuckerberg

Ejaaz:
is also trying to do, but failing to do as effectively as the Chinese labs.

Ejaaz:
They're just very good at doing it. The second thing I'll say is,

Ejaaz:
at least according to Open Rata from their official statement.

Ejaaz:
They said that this stealth model provider, which we now know to be Jipu,

Ejaaz:
is retaining prompts and responses, but explicitly state that they're not using

Ejaaz:
it for training. Now, this isn't verifiable in any kind of way.

Ejaaz:
Like, okay, China, you've never done anything nefarious before, I'm sure.

Josh:
You're really going to give this away totally for free? Like,

Josh:
no way. Coming from the people that stole all the items, I can go and generate

Josh:
a full episode of Spongebob on those models.

Ejaaz:
Exactly. Exactly. Well, this is another unique thing, right?

Ejaaz:
Culturally, in China, and this applies for every vector of tech that they've

Ejaaz:
built in the past, electric cars, mobile phones, et cetera.

Ejaaz:
They don't really see copyright as a thing or IP infringement as a thing.

Ejaaz:
They see, okay, if you have a good product, I can copy that.

Ejaaz:
And Chinese in particular are very, very good at copying effectively.

Ejaaz:
There was this great interview I watched with, who was it? It was Travis Kalanick,

Ejaaz:
on David Semra's podcast. I don't know if you caught that, right?

Ejaaz:
Absolute legend, right? Twice. And he talks about his story where,

Ejaaz:
you know, how he brought Uber over to China and he made a success there,

Ejaaz:
but he said it was very tough. But there was also some really unique cultural

Ejaaz:
things that he needed to understand.

Ejaaz:
And he realized that in America, or in the West at least, the innovation level

Ejaaz:
is super high. Coming up with net new zero-to-one ideas, super high.

Ejaaz:
In China, less so, but they are masters of copying. And he originally looked

Ejaaz:
down at copying as a really menial thing.

Ejaaz:
But he said that the way that they do it is masterful and artful in itself.

Ejaaz:
And this, I feel like, is what some of these Chinese labs are really good at doing.

Ejaaz:
It doesn't matter if they're earning $100 million. Their IPOs are popping off

Ejaaz:
anyway. They're never going to compare to the Western IPO market at all.

Ejaaz:
But the point is, they want to flood the market and kind of like keep America

Ejaaz:
at a cost level where maybe they're spending too much money than they actually

Ejaaz:
need to until they're able to figure out some kind of a breakthrough,

Ejaaz:
which might be continual money. Who knows?

Josh:
Maybe. We'll see. It's an exciting story and we're going to find out more.

Josh:
So this will be covered and followed up in the roundup tomorrow.

Josh:
Stay tuned for that. There's also a reference. It's kind of cool.

Josh:
The main character of the story is Open Router.

Josh:
And we just covered an entire Open Router episode just last week.

Josh:
So everyone who is unfamiliar with Open Router and why it is so valuable,

Josh:
please go and check out that episode.

Josh:
And that's mostly the state of the mystery as of now. Ox Alpha has been solved,

Josh:
but there is still a lot of behind the scenes that is left to uncover.

Josh:
We're hoping to get that information shortly. when we do we will share it with

Josh:
you right here on the roundup hopefully this week so stay tuned for that one

Josh:
um this has been kind of a crazy week i mean it's

Josh:
China's always throwing like, they're throwing wrenches in everyone's plans.

Josh:
First it was Deep Seek. Now they're doing this like kind of really fun stuff.

Ejaaz:
Did you see Quen as well?

Josh:
Yeah, we got a new Quen model. We're going to talk about that tomorrow.

Ejaaz:
Dude, they're just like spaying out these models. I know.

Ejaaz:
And you know, the craziest part about all of this is I'm seeing rumors from

Ejaaz:
trusted sources that a bunch of American frontier labs are also about to like drop a few models.

Ejaaz:
So like, I'm just saying here, like, you know, we're getting like the best from

Ejaaz:
the Chinese, We're getting the best from the West and there's just too many models to use right now.

Ejaaz:
But if you're listening to this and you're curious about this Ox Alpha model

Ejaaz:
or if you don't believe anything that we're saying, if you don't think it's

Ejaaz:
good enough, go out and try it right now. You can use.

Josh:
It for free

Ejaaz:
On OpenRouter. Go check it out. There is no promo code. Just sign up,

Ejaaz:
make an account and you can kind of like inference it and use it yourself.

Josh:
And I'm curious, send us,

Ejaaz:
Exactly. Like use the free tokens, please. Use the Chinese state funded money

Ejaaz:
budget to kind of do your AI tasks.

Josh:
Just don't give it your proprietary information.

Ejaaz:
Do not, definitely don't do that because they're definitely using it to train

Ejaaz:
the next model. But like, let us know in the comments whether you actually like

Ejaaz:
the model, whether it actually is good at the toss that you give it.

Ejaaz:
And if it magically improves the next day because it's continual learning. We don't know.

Ejaaz:
Like, let us know in the comments, DM us, we're available on all socials.

Ejaaz:
Yeah, anything else, Josh?

Josh:
Yeah, no, just to, again, share this with your friends if they enjoyed it.

Josh:
If you have something to say, please leave a comment. We try to read all of them.

Josh:
If you enjoyed on your favorite podcast player you can leave us a five-star

Josh:
review there if you're listening to this

Josh:
you should be watching it's very fun visually you can watch this on youtube

Josh:
on spotify and yeah as always thank you so much for watching feel free to go

Josh:
get caught up on the other episodes and tomorrow we got a banger roundup like

Josh:
it's just gonna there's so much stuff to talk about it

Ejaaz:
Is our favorite episode of the week.

Josh:
We've been in like a lull lately where there had i mean it's been exciting but

Josh:
it hasn't been like oh my god this is crazy there's new frontiers forming and

Josh:
like hopefully this is the first of many instances in which we're going to rev

Josh:
back up that engine and get

Josh:
a whole bunch of new models so i'm very excited stay tuned for all of that where

Josh:
we'll be covering it and yeah we'll see you guys in the next episode