Welcome to the AI Chat Podcast. I'm your host,
Jaden Schaefer. Every day I cover cutting -edge
AI news and talk with the leaders behind it,
breaking down what it means for your life and
business. Thinking Machines by Miriam Marotti,
who famously left OpenAI after she was the CEO
when Sam Altman got kicked out, have released
their first open -weight AI model called Inkling.
OpenAI has built something called GPT -RED. It's
an LLM super hacker, and they built this to harden
their own models. AI Box has shipped an MPC server
that brings 80 different AI models into Cloud,
ChatGPT, and Gemini. AWS is committing $1 billion
to a forward -deployed engineering organization.
OpenAI and Anthropic are both scaling theirs.
Apple Intelligence has been cleared for a China
launch with Alibaba's Quen and Meta plans to
sell and resell their AI compute following what
SpaceX is doing and kind of copying their playbook.
Let's kick this off with Thinking Machines. This
is a company that I'm really rooting for. They've
raised, you know, over a billion dollars, but
they haven't come out with anything super groundbreaking.
But what I will say when it comes to a lot of
these models, they're so expensive and they take
so much time that when you think of something
like even Anthropic, it felt like OpenAI had
just run away from them and they were never going
to catch up. And little by little, they pick
their lane, they make their product better, and
they're able to get market share until the point
where Anthropic has now exploded and is making
more money than OpenAI. It surpassed them in
revenue. I think we might see a lot of that same
strategy played out by a lot of different AI
companies if they don't kind of shrivel up and
die or get sold off for parts or, you know, an
acqui -hire or something like that. And so Thinking
Machines is one of these companies that I'm really
excited about. I hope that they really go places.
But this is run by Miriam Roddy, who is famously
the CEO of OpenAI when Sam Altman left. And she
has created this thing called Inkling. It's an
open weight AI model. It has 975 billion parameters.
And companies can download this and customize
it themselves. So you don't have to go and pay
for API access to OpenAI or... Anthropic, you
can actually just go and fine tune this all on
your own. You can fine tune it on your own data.
And the bet that they want people to take is
that that is going to be better than a one size
fits all model that OpenAI or Anthropic or Gemini
or any of these other big labs are selling. Inkling
was trained on 45 trillion tokens of text, image,
and audio and video. They did it in about nine
months, which is way faster than OpenAI's five
-year timeline or Anthropic's three years. In
a test with Bridgewater Associates, The financial
model trained on the hedge fund's own expertise
scored 84 .7 % on financial reasoning benchmarks
at roughly 1 14th the cost of the top models
from Anthropic and OpenAI. So we're seeing some
massive improvements when you're taking this
kind of these kind of models and you're fine
tuning it on your own data. The model activates
only 41 billion of its 975 billion parameters
per task, and users can dial up thinking efforts
to trade speed for accuracy. So I'm rooting for
them, but time will tell how well this model
does. We just learned that OpenAI built something
called GPT -RED. This is an AI model trained
to attack their own systems, and they use it
to catch security flaws before release. So the
model cuts successful attacks on GPT -5 .6 from
over 90 % down to 23%, which basically makes
it one of OpenAI's most secure releases yet.
One particularly interesting attack that it was
able to discover is called a novel fake chain
of thought, which basically is tricking a model
into making up fake reasoning steps. So it's
kind of similar to convincing someone that, you
know, one plus one equals three. And then, you
know, saying that I already checked the math,
that's what equals and if it equals that, then
therefore and you, you know, go trick them on
the next thing. So they found that when they
gave the same task as a human red teamer who
tested GPT -5, in 2025, GPT -RED found more effective
attacks than the humans. They also got it to
go and hack like this third party vending machine
agent, which is kind of funny. It does have a
bunch of limitations, so it's not very good at
back and forth conversation attacks, and it's
not very good at exploiting images that are embedded
into malicious text. The idea behind this is
actually functionally working is that GPT -RED
is automating how all of the security holes are
found because it puts an attacker model against
a defender. model, and they put them in these
kind of simulated real world environments, and
they're battling it out. OpenAI is not releasing
this externally. So they're not giving this to
other people to test, which is interesting, right?
Because we had the whole anthropic mythos model,
which was really good at security exploits, and
they gave it out to all the top labs and said,
hey, like, go harden all your security with this.
So OpenAI is not giving this out externally beyond
just using it for themselves. And I mean, it's
got a huge massive drop in the success rate of
a lot of these exploits. I think it shows AI
powered red teaming can be just as effective
or more effective than humans. I mean, you can
just brute force way more tests than humans.
And I mean, it's trained off of what humans are
doing. But at this point, it's doing better than
what a lot of the humans are doing. AI box, which
full disclosure is my own startup has just released
an MCP server and we are allowing people to plug
80 different AI models straight into cloud chat,
GPT, Gemini or cursor. Basically, it lets you
use any model inside of whatever assistant you
already are used to using. Personally, I use
clawed all day long, although I'm kind of switching
over to ChatGPT with their new ChatGPT app. It's
really amazing. But both either way, you get
the AI Box MCP and it allows you to access all
of the images that... OpenAI can generate. It
allows you, if you're on Claude or ChatGPT, to
generate all of the videos that Google V03 can
make. And no matter what platform you're using,
you can access what Eleven Labs can do with audio.
I spent basically the entire day today getting
ready for a big Facebook campaign that we're
launching here at AI Box. And in the past, doing
Facebook campaigns usually meant hiring a Facebook
ads team. It meant creating tons of creative,
which just takes a lot of time. And it meant,
you know, spending a ton of time on landing pages.
With Claude, and with the AI Box MCP that we
built into it, I actually got almost all of the,
so basically what I did is I went and recorded
a bunch of just selfies of me talking about the
product on my phone. I dropped those into a folder
and I had Claude go and edit all of them. And
then I was able to say, hey, I need to create
a bunch of dynamic, so like image generated ads.
I gave it the style that I wanted. I have these
different ideas. Some of them, it looks like
kind of like breaking news images. Some of them,
they actually look like, it's like me doing a
FaceTime call and there's like a text message
popping up on the screen and it's some sort.
of text message about AI box. So anyways, I had
all these different creative ideas that I went
and got from a bunch of people and to go and,
you know, create a template on Canva and then
switch out tons of different variations of the
title and the backgrounds and stuff like that
takes a lot of time. And before Claude couldn't
do it because it couldn't do any of the image
generation. But now that AI box is embedded inside
of Claude and it can do the image generation.
One in particular that I did is I was showing,
uh, I was showing the ability to generate images
inside of Claude and I needed that generated
as an ad. So you had to have like basically,
uh, the design of a Claude interface. And then
you had to be able to show images generated and,
you know, have like AI box logos and stuff. So
what I did is I was like, hey, go create this
mockup inside of Claude. But for the image part,
just go use AI box to generate the image and
pull that inside of, it's like the image inside
of the image that it's generating. Is able to
do that in a couple seconds. And I said, this
is awesome. Go think of like 10 variations or
like 10 different use cases of my product. And,
you know, and in this case, it's the product
is. showing that you can create images. This
is kind of a meta example, I know. But I was
like, go think of like 10 different variations.
So it's like, okay, well, you could use it for
like UGC content, you could use it for like,
coming up with product images for logos for newsletter
banners, whatever came up with all these ideas.
And inside of the image ad that it's creating,
it would go to AI box anytime it had to generate
one of the actual graphics inside of its image.
So like the you know, the graphic of the logo
or the graphic of the UGC person, whatever the
actual image was, it would hit AI box, it would
generate the image, it would pull inside of its
own thing. So I didn't have to do anything. I
literally just said, go, you know, we have the
concept, we have the template that I like, go
create 20 variations, think of a bunch of good
use cases and use AI box for all the images.
And the cool thing is when when Claude was making
this specific kind of like UI mockup. Um, because
it's UI and it's not just like I went to chat
GBT and got it to generate like one singular
image, which isn't perfect. And the text might
be funky and someone might be a little bit off
or whatever, right? If you're just doing an image
because Claude was kind of, uh, just creating
it with code and then pulling an image into it.
I said, okay, this is awesome. Now go put this
actual graphic onto our website and animate it.
So like where the chat bubble is, I'm like, have
someone typing that out, have the bubble appear,
have a loading screen that makes the image pop
up. So it's so cool because Claude is able. to
build these things. And because we're just pulling
the image in with AI Box, it's not just a picture,
but it's a full element that can be animated
for the landing page. Then it can be turned into
an ad for the Facebook ad and you can actually
have the animated as a video ad. Anyways, so
many possibilities. But if you're doing anything
with Cloud, which doesn't have audio, video or
image capabilities, just go get the AI Box MCP.
It's like $7 .99 a month, I think, or $8 .99
a month. And you get access to over 80 different...
models and anything you need while you're using
Claude, it can go and grab that and pull it in
and save you so much time. No more back and forth.
So go check it out. There's a link in the description
to AI box dot AI slash MCP. If you want to get
started with that. AWS is committing $1 billion
to a new team of engineers who are going to be
embedded inside of customers or in their customers'
companies. And they're going to be building custom
AI agents tailored to each business. And they're
then going to hand off the working system when
the project ends. There's been a ton of these
companies being spun up by Anthropic and OpenAI.
They're basically making these forward -deployed
engineers. So you send the engineer into your
customer's company. They build some sort of automation
workflow. And I think it's kind of like OpenAI.
And Anthropic's way of saying, hey, look, we
know you guys want AI, but you also don't know
how to use it. We are the experts. We'll just
send some people in there to build this thing
for you. They're directly copying the playbook
that OpenAI spent $4 billion on and Anthropic
spent $1 .5 billion on so far. And in those cases,
OpenAI and Anthropic both partnered with some
private equity firms to actually fund the staff
for all of this FDE teams. Anthropic is doing
it entirely with internal Amazon resources. instead.
And I'm going to be honest, this might be an
interesting strategy. If I was any of these big
AI companies, and you know, like, let's say meta,
for example, and you're thinking about doing
layoffs, well, maybe instead of meta doing layoffs,
they should build one of these forward deployed
engineer teams, get a bunch of money and go and
get, you know, meta embedded into their customers
businesses and just deploy the engineers over
there. Anyways, I'm not sure if this is Amazon
getting around layoffs, but it is an interesting
strategy, you can imagine. because OpenAI and
Anthropic definitely didn't have any extra engineers
they had to partner with people for this. AWS
has a really big advantage, I would say structurally,
because when the project ends, the customer runs
AI agents on AWS's cloud, and that's basically
just creating long -term revenue. OpenAI and
Anthropic make money per token used. That's a
lot smaller of a payoff per engagement, but the
cloud is a really big win for AWS. Also, I say
all of this like AWS is copying OpenAI and Anthropic
like they pioneered. this. But this is actually
something that Palantir has spent the last 20
years doing. And so I don't think this is, you
know, something that's just brand new in the
situation. It's something that's been done in
the past. And it's it's kind of something that's
been successful. We'll see how big Amazon is
able to scale this. Apple has just won regulatory
approval to launch Apple Intelligence in China.
They're partnering with Alibaba to power all
of the AI features there. It's interesting, right?
Because Apple said, hey, look, like they were
going to have their own AI in Syria. And yeah,
that probably would have been a big pain for
them with China. But then they said, look, we're
just going to say anyone with an iPhone can go
and use whatever AI model they choose. So in
China, that's going to be something from Alibaba.
And in America, that's probably going to be Anthropic
or OpenAI or whatever the model that you probably
pay for that you have. premium of you could probably
plug that straight into siri i think this matters
a lot because china is apple's second largest
market 20 .5 billion dollars in sales last quarter
and i think being able to close that gap helps
keep apple their number two smartphone position
there's rivals like huawei alibaba's quen model
is going to handle text and image understanding
and generation across all of the different you
know ipad and mac and vision os and apple's exploring
a deal with baidu deep seek and ByteDance. I
think they finally have settled on Alibaba after
kind of talking to all of the other options.
Alibaba's US listed shares went up 6 % when that
was announced. This deal is basically going to
give Quen some built -in distribution to the
very new iPhone that will be sold in China. I'm
going to be honest, I've tried some Quen models
and been really impressed. Their text -to -speech
model in particular is really good. But kind
of the bigger story for me on all of this is
that for not just Apple, but for any of the Western
companies, China is not going to approve any
sort of Western AI service if there isn't a local
model partner that's locked in and that is powering
everything. Meta is launching a cloud business
called Meta Compute. They're going to be selling
AI compute powered AI models to other companies,
and they're doing this directly to compete with
Amazon, Google, and Microsoft. And all this is
right after Meta committed a whopping $182 .9
billion to AI infrastructure, which is basically
the SpaceX strategy. They're turning all of their
excess data center capacity into revenue. It's
interesting, right? Because Meta, I think, hopes
that or would have hoped that their AI model
was way more used and way more popular. But having
all All of the extra AI infrastructure is, I
mean, basically a goldmine. It's money that they're
not spending and now money that they're actually
making, similar to Grok, I think. Meta is going
to sell both raw computing capacity, basically
just like CoreWeave does, and they're also going
to have access to their own AI models that they'll
sell, including the recently launched Muse Spark
model, which has gotten a lot of attention because
it kind of finally pushes Meta to the forefront.
The Ohio data center that is described by Mark
as a Manhattan -sized project. is expected to
open this year, and it's going to provide all
of the excess capacity that Meta needs to resell.
And SpaceX basically showed this model works.
XAI signed deals in May with Anthropic, Google,
and Reflection AI to buy Compute Time, and they
basically turned all of their idle capacity into
immediate revenue, and people paid a lot of money.
I think Anthropic is paying over a billion dollars
a month for access to that. For companies with
deep pockets, this seems to be a good strategy.
If at any point Meta's AI models get super, super
popular, right, they can go and use their own.
capacity. But if not, they're just going to make
all of the money from all of the other AI companies.
And I think at the end of the day, the demand
for AI is not going to decrease. So it's a pretty
smart bet. Guys, that was everything for the
podcast today. Thank you so much for tuning in.
If you enjoyed today's episode, make sure to
go check out AI box .ai. Like I mentioned, where
you can get our MCP that gives you 80 different
AI models. And more importantly, if you're using
Claude, you get images, audio, and video generated
right inside of Claude. It's like actually magical
to use. I've been using it all day. It takes
two seconds to connect and it's only $8. Please,
I beg you, if you have Claude, you have to try
this out. It will just make your life so much
easier. Also, if you want to get all of these
different stories that I talk about on the podcast
here straight into your inbox, go check out AIChatDaily
.com. That's my website, my news site that is
tied to this. I have deep dive articles on every
story that I covered here. And I also have links
over there where you can go and read more about
it. There's a subscribe tab at the top of that
website where you can get this all as an email
or you can go get the deep dives on the site.
Guys, thank you so much for tuning in and I will
catch you in the next episode.