Drew Arnold, Invisible Inq. Dark Money Network

Drew Arnold is a CGI creator who has worked with Beyonce and other Hollywood artists. He is also an activist who created a 3d graph of the massive dark funding network behind the money funding the government and political movements.

Episode Transcript

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(03:52):
on this broadcast as we do that. But today we
have a great guest that will be joining us in
about twenty three minutes. Drew Arnold, the Siege Master, will
be joining us. He does CGI videos. He's done them
for Kanye West and for Beyonce big Booty Beyonce. I
don't know if I'm allowed to say big Booty Beyonce.
That's like a tongue twister. Look at that. Dad's all smiling.

(04:14):
He's like, yeah, but you know we're gonna tie into
the dark money situation. Drew Arnold has put together an
incredible three D graphic graph that links all the money,
all the dark money that's coming against any kind of
or laundering through politics, all this kind of stuff, if

(04:36):
it's taror cells funding different politicians, all that kind of stuff,
just deep, deep, deep deep dive into the money, how
it funds politics and who is funding what. And I
asked him earlier today, I'm like, can we do one
of these on the builder Berg He's like, that would
be a great one to do, so I hope he
does one on the builder Berg Group. And what's even

(04:56):
cooler is tomorrow he's gonna be on INFO. Guess who
got them first. We did because we're awesome. We're cool cads. Kids,
and we normally get the guests first. And yeah, we
might not be as exciting as Alex Jones at times,
but I can tell you the information is what's important,
and we get that out to you guys. And I
am pretty exciting. I have to admit, I'm a good

(05:16):
time and we can have a lot of fun on
this broadcast on and I and we have our great shows,
and we have the shows where it's like it's a
struggle to get through. It's just like any other job.
Don When I get up in the morning, I think about, well,
what am I going to talk about? What kind of
questions am I going to ask Drew Arnold? What kind
of guests can we get on? Who else can we
get on this show that not only that we agree with,
but somebody who brings a different point of view, you

(05:38):
know that might not be you know, completely leaning right
or left, but have a third party ideology or just
different viewpoint all around. We've had transhumanists on the show.
We've had Green Party people on the show. We've had libertarians, anarchists,
God knows how many anarchists we've had on this program.
And you know, we've had conservatives, the good old GOP people,

(06:00):
and you know, we've had artists, musicians, you name it.
We've had everyone on the program and a lot of
your favorites, and some of them have passed on because
they didn't get big until they passed, like Rosa Cory,
she passed. Who else did we have? We had a
couple of people Jordan Maxwell, Marly p House protege who
I got to meet in the later years of his

(06:21):
life and he asked me to manage him. All these
great guests we've had and you can find all those
on the iHeartRadio Rundown Live app or go to the
Rundown Live dot com the Rundown Live dot com. But
that being said, I'm excited for today's show and how
you doing, Don, What's going on? What's going on in
your world right now?

Speaker 3 (06:38):
I'm doing pretty good, brother, you know, I am also
excited for today's show. You know, dark money is always
something well worth talking about, especially when it ties into
politics and tearor cells and foreign policy and just all
all of this sort of you know, secret of stuff.
You know, they always say, if you really want to
get to the bottom of what's going on, follow the money.
So you know, definitely excited for today show and it's

(07:01):
you know, it's gonna be a good one.

Speaker 1 (07:03):
I remember, maybe about ten years ago, there was a
TV program that was out there, and I don't know
if you remember it, but it was really big and
it was making waves and I'm so bummed that I
got canceled because it was a great show. It was
called Conspiracy Theory with Jesse Ventura, you know, and the
governor would go round and challenge all these conspiracies and

(07:24):
actually look for humans ease and animal human highbreds and
nine to eleven and the Buildeberg group and all these
different things, and he shed light on it and actually,
you know, FEMA camps. He went in and brought the
documents and confronted the guy who passed the FEMA bill
which had FEMA camps in there, which was a conspiracy.
FEMA camps don't exist. And he would always say in

(07:45):
the purpose of the conversation, he'd be like, follow the
money and the power. Who has the power to gain
and who has the money to be made, because those
are the two things that really drive society. And when
it comes down to it, it is money really makes
things go round, and that's why they want to go
towards a cashless society. It's all about made of data, right,

(08:05):
data points of entry, what people are buying, why they
are buying, what else are they buying alongside it. When
I worked in retail, we would always talk about the
unique unknown need. Like don you came into Christain mart
and you were going to buy something. You knew what
you wanted, Kristan Mart, Right, you wanted green screen, But

(08:26):
your unique unknown need was I asked enough questions to
find out that you have a crappy webcam and that
you needed a better webcam, So I got a plus
one there. Not only that, I got that USB cable
that you needed along with it, And maybe you needed
a new chair because your chair just isn't comfy comfy
for your tush right, your booty is always stare from
watching me on a program and doing interviews and everything else.

(08:48):
And that's your unique unknown need. Well, guess what. There's
a lot of made of data that goes around with
what you purchase and how you purchase it. And that's
one of the very scary things about going cash lists,
the cash list society. Although I'm big on bartering, I
love to give away stuff. My house is filled with
gifts from people I've met throughout my life. Right, I've

(09:09):
always preferred to have something given and gifted to me
that somebody else owns. Then somebody go out and buy
me something, with the exception of like boxers and socks,
like I don't want your socks. I don't want your boxers.
I'm sure there's a couple other things that I probably
wouldn't want that are they're used that you had, but
like maybe you made a painting, Maybe you had like
a really cool item that you just don't appreciate anymore,

(09:31):
but somebody else appreciates, you know, just neat stuff like that.
You know, that's always meant more to me than buying things,
you know, having something that somebody else had, other other
than information and knowledge in books, although old books do
fall in that category of things I like to pass on.
Whenever anyone stands the night at my house, I usually
give them a book or some vinyl records, or you know,

(09:53):
something that they can you know, makes their life better
or that they want to research, like, for example, Derek Brose.
You remember Derek Brose from the College Resistance. He did
the Pyramid of Power. When I spoke with him in Milwaukee.
I hooked him up with the book of Morals and
Dogma by none other than who wrote that, Albert Pike,
the guy who used automatic am condred demons to write
the book to get you through the thirty three degrees

(10:14):
of Masonry and talk about the Illuminati and all the
different cults that are in there. You know, it's interesting,
it's interesting stuff, but it's the whole idea here is
is they want to track and get all this made
of data on you because made of data is gold.
And what they can find out why what you buy
and what you purchase, and how they can control your
life even more important, power, the power that can be

(10:37):
done with cryptocurrency is rather scary, but there will always
be avenues outside of the standard crypto currency. How many
people out there use bitcoin and if you have, you know,
you can always donate a little bitcoin to the Rundown Live,
you know, or light Coin or ethereum, all these different
types of cryptocurrencies. But people are getting used to using

(11:01):
crypto and they're understanding more and more about.

Speaker 3 (11:04):
It done yeah, you know, and it really is a
great thing that more people are getting involved in it
because you know, let's just be completely honest here, when
we're talking about the international banking system and we're talking
about the monetary system.

Speaker 4 (11:20):
You know, the economy and all this sorts of stuff.

Speaker 3 (11:24):
The only way that people are actually going to be
able to mount a legitimate resistance to a lot of
these agendas is by getting into counter economics, is by
you know, learning alternative methods of you know, economic systems,
things of that nature. Are getting into you know, bartering

(11:45):
and crypto privacies centered cryptocurrencies because of course we're seeing
this big push from the federal government now to create
essentially you know, US backed stable coins and centralized cryptocurrency.
What people need to be getting involved in is decentralized cryptocurrency.
And we'll probably have a little bit more to say
about that later, but you know, the simple fact of

(12:07):
the matter is if you're not getting involved in some
of these alternative economic systems, then you're just going to
get caught up in everything that you know, great reset.

Speaker 4 (12:20):
World Economic Forum.

Speaker 3 (12:22):
Globalist agendas have coming down the pike because a cashless
society isn't coming, it's here.

Speaker 4 (12:29):
They're developing it all over the world.

Speaker 3 (12:31):
They're developing the digital yuon in China, They've already started
pushing legislation in Russia for the digital ruble, they're pushing
digital currency in the UK. They're talking about here in
the US. It's not coming, folks.

Speaker 4 (12:43):
It is here.

Speaker 3 (12:45):
So unless you're prepared to you know, deal with that,
or rather I caught my words there, you should be
prepared to deal with that. And you know, there's really
no other way around it other than you know, taking
the proper steps to do so.

Speaker 1 (13:06):
Well, let's take a look at this as a recent
release by the resurport on AI and the Cashlow Society.
Let's get your thoughts on this.

Speaker 7 (13:18):
President Trump spoke very highly of bitcoin this year before
the election.

Speaker 1 (13:23):
If crypto is going to define the future, I want
to be mined, minted, and made in the USA.

Speaker 4 (13:31):
It's going to be.

Speaker 1 (13:32):
It's not going to be.

Speaker 4 (13:33):
Made anywhere else.

Speaker 1 (13:34):
And if bitcoin is going to the moon, as we
say it's going to the moon, I want America to
be the nation that leads the way. And that's what's
going to happen.

Speaker 7 (13:44):
Nobody has been able to identify the source of the
bitcoin algorithm. It was originally published in a white paper
on Halloween of two thousand and eight, just as the
economy was crashing, Bitcoin was put into practice by its
own users, who proceeded to get insanely rich and spread
the word of cryptocurrency. But the true origin of cryptocurrency

(14:07):
can be found in the early days of Silicon Valley,
with the CIA Masad and their pedophile blackmail operations managing
the operation from the start. In nineteen ninety seven, the
NSA published How to Make a Mint. The Cryptography of
Anonymous Electronic Cash. Ripple was formed in two thousand and

(14:28):
four by a member of the ISSA and a descendant
of one of the most powerful banking families of Europe.
Four years later, in two thousand and eight, the bank's
crash and the Bitcoin White Paper is introduced to the public.
Four years after that, in twenty twelve, Ripple XRP is
released to the public, and today it is being considered

(14:52):
for its new stable coin. Stable Coins such as Ripples,
RLUSD are digital versions of fe currencies. While bitcoin may
arguably be a decentralized currency, stable coins can be programmed
and tracked as easy as any CBDC can. It's the

(15:13):
same thing, just a different name, and it appears as
if this is the direction the Trump administration will be going.
Who needs a central bank when you have blackrock. Preparations
for a cashless society go back for well over a century.
It was once considered to be the biggest threat in America,
but now people will be happy enough to just get

(15:35):
the men out of the girls' bathroom. Based on the
team surrounding Trump forty seven so far, it is clear
that nobody in power is resisting the AI world being
built around us. Peter Thiel, who is clearly a proxy
of the CIA, has not only pioneered digital money, he
is the front man for Palenteer, which was funded by

(15:57):
the CIA. Palenteer is a technology that is now being
used in predicting who will commit a crime. It has
access to everyone's private devices and is used by both
military and police.

Speaker 8 (16:11):
Next, our commander wants to disrupt enemy communications. This will
allow ground forces to more safely maneuver and help ensure
that enemy equipment stays in position. AIP automatically identifies and
pairs all of the validated enemy communication nodes with a
disruption capability assigned jammers to each of the validated high

(16:32):
priority communications targets. An electronic warfare specialist initiates the jamming
Operation Initiate Jamming Operation AIP confirms the jamming order.

Speaker 4 (16:43):
Has been initiated.

Speaker 8 (16:46):
With enemy communication disrupted, our ground forces are cleared to
move into position and destroy the enemy equipment.

Speaker 7 (16:53):
It has also been revealed recently that data harvested from
the game Pokemon has been used to train artificial intelligence
to achieve spatial intelligence.

Speaker 4 (17:05):
You can sneak around them, or you can get them
really close.

Speaker 9 (17:08):
Getting closer makes it a bit easier to get those
great or excellent throws with your pokebol But if you
move too fast, the Pokemon are going to get scared
and they're going to bolt off. If you can get
close enough without spooking them, expert handler mode kicks in,
giving you a small cat rape bonus along with some
extra XP and startist at the end.

Speaker 7 (17:25):
So that robots can better navigate. In the real world,
robots security dogs such as the ones now being used
at mar A Lago by the Secret Service, robots that
are capable of firing rifles. The world sits on the
edge of the AI World cash List society, and there

(17:47):
are no leaders putting on the brakes reporting for Info Wars.

Speaker 4 (17:52):
This is Greg Reese.

Speaker 1 (17:56):
I like the fact that bitcoin can be used as
a forum to get outside of the central banking cartel system. However,
there are some legitimate concerns. Now we're at the point
where this idea bitcoin, which was a great idea to
combat taxes and combat you know, the Federal reserve per se,
is now slowly being commandeered. And I wanted to pull

(18:17):
this up on the stage. Here. This is palent Heer.
This is the company that literally remember Degal Trends back
in the day, they're like, the population of the United
States will drop by two thirds by the year twenty
twenty five. Well, here we are. By twenty twenty five,
we had COVID all these things, and people are like,
how profaga, how did Degal Trends know that? Well, they

(18:38):
have AI powered automation and other things that go into
or come into your data. They take those points of
data and they learn about how to market you. They
learn how to figure out ways to control you. Now
imagine cryptocurrency being shut off right don all of a sudden.
Let's say you're not paying your taxes, or you know,

(19:02):
you're not using the money towards paying off your tickets
for the law enforcement that you owe or you owe
the government money. They'll just shut off your cryptocurrency and
all of a sudden, you can't use your money in
your bank except for the things the government says that
you can use it for. Don And that's a real concern.
And not only that, the AI idea of the AI
powered automation and made a data harvesting for every decision,

(19:26):
which will tell you the outcome. Let's say you wanted
to go to war with Ukraine, I'll tell you will
you win the war with Ukraine and how you'll have
to pursue it, and AI will do the battle for you. Right,
why even have human humans involved in these decisions anymore?
We'll have AI involved. And that's what's going on in
some shapes and forums with government right now. They're trying
to have AI figure out what departments we should cut

(19:47):
and what departments we should keep.

Speaker 3 (19:51):
Yeah, you know, it's the pervasive tentacles of all this
stuff is just stretching into every aspect of government, particularly
the Trump administration.

Speaker 4 (20:01):
It got it start really with.

Speaker 3 (20:03):
Biden, but it's you know, Trump has completely embraced all
the tech bros. And you know, Greg Reese in that
report mentioned he mentioned a couple of things that I
want to highlight actually, first of all, being Peter Theile.
You know, Peter Thiel is one of the you know,
biggest technocrats in the Silicon Valley essentially, and you know,

(20:24):
and this is the guy who who bankrolled a massive
chunk of Trump's first campaign. He publicly stated that this
goal around, he wasn't personally banking the campaign with his finances,
but he was supporting it in many other ways. But
he is the guy who bankrolled jd Vance. Jd Vance
would not be in politics if not for the startup money, uh.

Speaker 4 (20:47):
By Peter Thiel. He's a sitting member of the Builderberg Group.

Speaker 7 (20:52):
Uh.

Speaker 3 (20:53):
And you know, as mentioned the the Reese Report, he's
also the founder of Palaneer Technologies, which is a CIA cutout.
So you know, all of these very swampy, very deep
statey sort of institutions and individuals tied to the Trump administration,
and people are still delusional enough to think that this
guy's actually fighting against them, when in fact he's just
rebranding it. A couple of other things I'd like to

(21:15):
point out in that ref Report video for the radio
listeners that hadn't who hadn't seen the video of our
broadcast there were two reports actually highlighted by Greg Reese
in that one of them was called Breaking Down the
Chain and Investigation post Mortem by Mark Goodwin, which is

(21:36):
actually an article compiling a whole bunch of other articles
and investigations that Mark Goodman and Mark Goodwin and Whitney
Webb have conducted over the past year or so, and
one of those primary ones that I point out to
anyone who wants to understand a little bit more about
how Trump is embracing this stable coin rug pull know

(22:00):
sort of agenda. This happening because a lot of people,
whole lot of people have been praising, Oh Trump sign
an executive order to ban the cbdc's he's you know,
he's fighting for freedom, not acknowledging the fact that he
is in fact pushing for digitized stable coins, which, as
the report mentioned, is literally just a digital version of

(22:20):
this fiat currency that we are all currently enslaved under.
So definitely recommend go and read the article Trump embraces
the Bitcoin dollar to entrench US financial hegemony, as written
by Whitney Webb by on Unlimited Hangout dot com back
in July of last year. And you know, she Whitney

(22:42):
is known for her fantastic journalism, a very long, in depth,
very well researched reporting and an absolute must read.

Speaker 1 (22:53):
Yeah, it's all very interesting, and the idea is, how
will they control us and use a you know, do this.
I'm a big proponent of gold and silver and you know,
sound currency, But at the same time, bitcoin is a
pretty cool market. You can make good money off of cryptocurrency.
And the question is is like if it has been
created or has a tized to Masada in the Cia

(23:15):
and the underbelly of the dark web, amongst other things.
You know, what else do we not know about bitcoin
and where it came from, and what impacts it could
have and what kind of implementation it could be used for,
especially when it comes to controlling you as an individual
and collecting made of data on all your purchases, where
you go, what you do with your money, how it's

(23:35):
related who you do money with, the whole idea of
it being anonymous, there's some steps you gotta take. It's
not like you can just buy bitcoin and sell it
without anyone knowing these days, because most people don't understand
you how to go to Reddit and you know, find
somebody who wants it you know, or we'll give you
cash for it. So, but that being said, on the

(23:56):
same topic, interesting enough, they have an article cull today
in the News that says autonomous drones can track humans
through dense forest at high speeds. So now we have AI, right,
this is what we're kind of talking about with Palanteer.
We have these autonomous drones. The meta data is being

(24:17):
used and now they can go ahead and we each
will get our own drone. Maybe in the future. Don
we'll be sitting there and we'll be looking up in
the sky like they live, and Drony will be up
there being like do do do doude right, and we're
gonna be like, what the hell was that? Well, here
it is in the news. This autonomous drone can track

(24:37):
humans through dense forests and it won't be long and
it's not like it's a quad copter's drone. It's not
that difficult. Autonomous drones could revolutionize the wide range of
the industries. Now scientists have designed a drone that can
weave through dense forests, dodged thin power lines and dim lighting,
and even track a jogging human. And as we showed
on yesterday's program, they have delivery drones that already do

(25:00):
this in Miami. I was in Miami, like pizza delivery
drone was like going nuts. Everywhere I looked, there's a
little drone driving around and I'm like, what the world
is going on here? I woke up on Miami and
they live Roddy Rodney Piper is going to be around
the next corner trying to put some damn glasses on me.

Speaker 2 (25:17):
Don.

Speaker 1 (25:17):
That's the way it looked and that's the way it
felt when I was over there. And you know, now
we're going to potentially have these autonomous drones that can
follow you. I mean, why do they need to when
they have surveillance on satellites they could probably pull you
up that way. But it's interesting and it would make
for some good sci fi news amongst other things. But

(25:39):
that being said, I see that we have our guests backstage,
and Drew Arnold is a very interesting individual. I met
him on a show probably it's been a couple of years,
maybe two or three years, and it was called Break
the Rules with Levin Jewels. I believe live Poliirov, who

(26:00):
we've had on this show. I think I said his
last name right, Maybe I did it. He's gonna message me.
You'll be like, Bro, I'm watching your show. You killed
my name. I don't I apologize if I killed your name.
I'm doing it off a memory. But we were doing
a show and it was I think the substance of
the show with secret societies. But I've met Drew through

(26:20):
that show and it was a very interesting conversation. We
met in DC at the Rage Against the War Machine
rally and we hit it off and it was really
cool talking to him. And now he's making waves. Drew
has decided to take a ton of mate of data
of where the dark money is coming in from and
that is being used against certain proponents that are in

(26:42):
a large part, in many different shapes and forms, fighting
for some kind of form of freedom or at least
against the establishment. We might not agree with everything Robert F.
Kennedy does, but it'd be interesting to see what his
healthy America will look like and what he can actually
get done. And so Drew put together this amazing computer

(27:02):
generated three D graph that shows all the money, all
the different ties, and where it all comes from. Welcome
to the broadcast. We have Drew Arnold. Thanks for joining
us on today's show and I have to say, this
graph is by far the coolest thing I've seen in
a long time. Your TikTok videos should have a lot

(27:23):
more views on it than it actually does. Maybe you
got to pay TikTok to adver some Hell, this is
pretty amazing stuff here, and I'll put on the screen
for viewers to see. So how did you get involved
in all this?

Speaker 4 (27:38):
Well? First, thanks for having me on the show, and
I love what you've been doing for the last few months,
especially with all the J six footage, So thanks, thanks
so much for doing that. Look, man, I work in technology.
I came from computer animation, and I've worked with all
of these big names making music videos all of this stuff.
In the background, I've been just so interesting in researching

(28:01):
all of these dark things, right, and for years I've
had this project that I've had in the back of
my mind. How do you show a graph of the
connections between all of these entities? Right when I came
up with it around to twenty eleven, there's just really
no logistical way to do it because you'd have to
hand enter all of this data. There's news articles everywhere,

(28:23):
there are databases, I mean, there's all kinds of unstructured
data that's just floating all over the place. Some of
it open source, some of it you have to get
through Freedom of Information Act requests. Well, now, because we're
in a space where AI can assist, machine learning can
assist the process, I can start scraping all of this

(28:45):
data together and combining it an interesting way. So what
does that mean is I am creating a visual graph,
a visual hierarchy. Think of it as like you know
that one thing that one image where from always Sunny
where Charlie has you know, this conspiracy theory sway across
the wall. Right, you've got pictures with lines between everything. Okay,

(29:10):
imagine that, But it's structured and AI is doing it right.
That's the key here. And these things have existed for
a little while, but now I finally have the opportunity
to do it. So I am putting all of my
energy into creating an open source directory for the public
to use for their own research purposes and my own,

(29:32):
because really, I'm tired of explaining this stuff. It's so
fucking complicated that you would, you know, just to get
into a conversation with somebody over Thanksgiving dinner. It's impossible.
But if you can show them how things are connected.
It changes the game with how we communicate about dark money,
dark interests, dark politics, dark finance. Right, all of that stuff.

Speaker 1 (29:56):
Well, let's take a look at your video from TikTok.
This is Drew Arnold. Make sure you guys follow on TikTok.
This is his recent video, The Dark Money Tried to
Stop RFK The Invisible Inquiry.

Speaker 4 (30:07):
I uncovered the dark money network trying to stop.

Speaker 1 (30:11):
Going near you unapologize.

Speaker 4 (30:15):
For the dark money network trying to stop RFK Junior.
Using open source data, I grabbed four hundred and sixty
one organizations tied to Arabella Advisors responsible for funding everything
from defund the police to abortion rights to probe Palestinian protests,
and one was tied to a terrorist organization with mostly
invisible money coming from some of the wealthiest people in

(30:36):
the world. You didn't think these movements were actually grassroots,
did you? With money coming into the largest philanthropic organizations
in the world, you could finally see the massive funding
mechanisms that drive many left leaning initiatives and the chain
of dark political finance. This is how it works. Arabella
moves large chunks of money through several different funds that

(30:58):
in turn move it through a chain of some time
up to five organizations. This is how dark money works,
like a shell game in order to keep the public
in the dark about how it moves money. This is
only one collection of many that make up the conservation
of dark money running through American politics. So the next
time you latch onto a political belief or join a rally,
remember that billionaires might be behind it, like the public opinion

(31:20):
on RFA Junior's nomination, which I cover more in detail
in another video. If you want access to this graph
and more, click the link in my bio so you
can get the big picture.

Speaker 1 (31:31):
And that's invisibleinq dot com. It'll be interesting to see
what listeners and viewers think about this. But it's interesting.
So you put together all these different connections of money
and power structure and how they work through shellowcouts. Explain
to me how does this work? So why are they
sending money through five different organizations before it reaches the end?

(31:54):
The ends? But let's say somebody's going to fund the
Rundown Live and somebody comes up to me and they say, Christan,
we're going to fund your broadcast. We're gonna give you
guys fifty thousand dollars a year to help fight you know, uh, censorship,
and uh we're going to use your use the money
towards free speech and covering the news. And I get
that money, and I think, you know, we'll call the business, uh,

(32:18):
you know whatever, we'll call it, you know, freedom, freedom Works,
or something like that. You know, there's an organization out
by that name. But let's say organization reaches out to me,
there's a chance that that money has gone through what
four or five other companies before it reached me, and
they the whole intent was potentially to fund or support
somebody like me, Is what I'm getting from this?

Speaker 4 (32:41):
Well, I think it works in a couple of different ways.
One is that there are probably some do gooders out
there who think that they're doing something that is unconnected
to some of these dark money forces. And I think
this is kind of what we term like useful idiots, right,
people who don't really know what they're doing. In that graph,
what I did as I uncovered the network that was

(33:02):
predominantly I put this together because I wanted to show
the dark money network that was trying to under my mind.
RFK Junior's nomination. What I did was I did a
one degree separation graph from Arbella network, which is the
primary mode of funding for from George Soros to Zuckerberg

(33:24):
to Bill Gates, through all of these different organizations. What
opened up as I did a one degree separation was
a chain of multiple organizations which all had the hands
in each other's pockets. So it's not just money moving
in one direction, it's money moving through back and forth
between some of these organizations and through a nonlinear, hierarchical

(33:47):
chain of dark money. So the way it works is
that these organizations don't have to account for their funding
and their financing. They don't have to show it's you know,
because of finance, campaign finance laws and dark money, which,
by the way, Democrats are I think eighty to twenty
percent the most used dark money networks. This is who

(34:13):
the primary funders of most of the left leaning politics
that we see. So this is everything from Black Lives
Matter affiliated organizations to anti gun lobbying, anything else you
can imagine that you've seen on the left that pushes
for some of the more far reaching left leaning organizations.

Speaker 1 (34:35):
Like, how do we even begin to dive into this?
There's so much data. You almost need AI to do
it for you, Drew. And it's crazy because I see
one that's coming up. It's Arabella, So tell us about Arabella.
What's Arabella? Looks like it's a big dot in the screen,
so it looks like everything is a lot of these
donations cross Arabella. It seems to be pinned. There's a
couple other real big ones here that I see. What's

(34:57):
this one? This one is I can't even make that
out because there's so much data. It's crazy.

Speaker 4 (35:04):
This is a one degree separation, so you can see
how one organization moves it to one other organization. And
I guess this is a two degree separation graph. I
should take that back, but it's it's incredible how quickly
it expands, right, So you can see how many networks
are involved in this. And I think this is a
fifty eight billion dollar organizational chain here, So this is

(35:27):
how most that eight money moves through. There's the Tides Organization,
the Tides Advocacy Fund. I mean you'll see in here
that there are people. There's the Ford Foundation, the Rockefeller Foundation.
All of these people are moving money into this. When
I made this, this was before US aid the USAID
story broke, and right now I'm working on a USAID

(35:49):
story that is similar to this, but USAID is directly
integrated into this system through the Tide, the Ford, the
Rockefeller Foundation and all stuff. So what I'm doing right
now is I'm breaking open that chain. And if you
want to look, if you want to search, because this
is open source, it's open to the public. You can

(36:10):
go to invisible I in Q like invisible ink, but
with a q uh. It's if you click on any
of the stories and scroll away all the way to
the bottom, you can get access to this and see
you can search the graph, type and forward as an example.

Speaker 1 (36:25):
Okay, we'll do that right now. We'll type in forward, right,
so twenty eight that has the entity and the drop
down Ford Foundation. You go and you click it and
I'll look at it. Pulls it right up and it's
got a pretty big bubble here. Yeah.

Speaker 4 (36:37):
I've structured that the data better in some other lines,
and it really has to do with how you manage
the data and how you how you manage how the
graph looks to make to be able to sort through it.
But this is I think going back on what you
were saying earlier, about these these surveillance networks. The the

(37:00):
reason why I'm doing this is because I am interested
in something called surveillance, which I think is an under
utilized term, which is using technology to surveil the people
who would surveil you, right. And that's the goal is
because I'm a technologist, I've built some of the I've
built one of the biggest VR arcades in the world.

(37:22):
I've built one of the biggest projection mapping spaces in
the world for Beyonce. I'm great at tech, right, and
I know how to use it. This time, I want
to be able to use it for something that's useful
to humanity, not just not just pushing pop culture, right.
And so I'm hoping in the end to build a
massive data ingestion pipeline where we can get stories, databases,

(37:47):
campaign finance, almost anything that has to do with data
around money, power, influence, and pull it all together. So
if you think this chain is big, I want to
build something that goes that looks like this, but goes
all the way back to the thirteen hundreds.

Speaker 1 (38:06):
Wow, like a historical chain, so you can follow the
money from the family and see who actually pulls the
strings of power.

Speaker 4 (38:12):
Follow the money, follow information and data, follow secret societies,
who are members of secret societies. It's all connected and
you can read about it in books right now, but
you just can't see it. So it's really difficult, I
think for a human brain to understand this, right this
is what is actually happening, and to have a complete

(38:34):
understanding of the mechanisms of power, your brain would have
to wrap itself around this, which is really difficult to
read when you're reading a linear script about anything, a book.
This might be a book worth of information.

Speaker 1 (38:49):
Well, I'm looking here when you type in like Gates,
and it has all these different Bill Gates foundations, So
people have more than one foundation that are implementing or
in involved in investing in different things, obviously, and so
they build all these shell accounts and then they just
move money around to fund different political movements. And so

(39:11):
when you want to know, you know, does George Soros
fun things or does Bill Gates fun things? And you
want to know how they do it, you can come
to this graft on invisible I in Q and just
type in their name and lo and behold, they'll pull
it up here some Bill and Melinda Gates Foundation. I
click it, it zooms right in and here it is,
and compared to like things like the Ford Foundation, they're

(39:33):
going to pull it out a little bit close to
the Ford Foundation. You look at it, it's not as
large of a connection. There's not as many webs that
go to it. And then there's some things that are
way out here that are different, like obscure things that
looks like but it's it's just there.

Speaker 4 (39:51):
There are more connections between those two organizations. But this
is only as it corresponds from the out Robert F.
Kennedy of Arabella, right, So this only has to do
with their connections surrounding Arabella Network. There are other networks
that where they're more tied directly together, including the one.
I'm not sure if you have any interest in seeing

(40:12):
what I'm working on right now with USAID, I'm happy
to show it.

Speaker 1 (40:16):
I mean, like I know, Don was working on an
article about this, so this might be beneficial for all of
us to see. But for our listeners out there who
don't know what you said is USAID, Why don't you
let our listeners know real quick?

Speaker 6 (40:32):
Right?

Speaker 4 (40:32):
So, us AID was started by the Kennedy administration and
it was a way to exert influence over other countries,
predominantly at first we consider third world countries. The idea
is it was started by a guy you'll have to
forget his name, but this is American colonialism, effectively getting

(40:58):
people hooked on American aid in order to influence their politics.
So as an example, one of the first organizations that
we went after was Pakistan and what we did is
we cleaned up their roads. All of this stuff right
sounds great. US USAID. Forget the acronym now it's international development.

(41:21):
I forgot the a US assisted international development. I believe
I'm totally screwing this up right now. But it works
in tandem with the World Economic From, not the World
Economic from the United Nations Development Fund, all kinds of
other subsidiary groups. Is a pass through to move money
to other organizations that need it. But what it has

(41:42):
turned into is also a because it has to do
with subsidiary groups and pass through groups and this sort
of chain of dark money. It's also a way for
the State Department and other organizations like the CIA to
have black operations run through these countries as a cover,

(42:03):
so it can be anything from and what they've turned
into since the nineteen eighties predominantly is a force of
mechanism to control politics and other countries. So it went
from influence to politics in the nineteen eighties, all four
and by the way up until twenty eighteen, where it

(42:23):
started turning sites back into the United States when it
had its fingers wrapped around something that we know now
the Wuhan Virology Lab, and all of that is included
in the network that I'm building currently. So USAID sounds great,
but really it's a neo colonial mechanism that has turned

(42:47):
on its owner and has a parasitic relationship with the
United States currently.

Speaker 3 (42:52):
It's essentially a front for the intelligence community and whatnot.
As a part of the article that I plan on
beginning to work on tomorrow, I only just decided to
do an article about the subject today, So I was
putting together sources and things of that nature. And you know,
that's that's what people really need to understand about the

(43:15):
whole thing, because there's there's this big freak out going
on right now, especially with a whole lot of the
corporate media that have been I mean there's just today,
in the past couple of days alone, we've had revelations
of millions, if not billions of dollars going to so
many media outlets across the world, not just here in
the United States, but we're talking about Politico here in

(43:35):
the US, We're talking about the BBC.

Speaker 4 (43:39):
You know, all over the place, and you know it
is you.

Speaker 3 (43:43):
Know, US corporate government funded media, and they're absolutely losing
their minds over it.

Speaker 6 (43:51):
Uh.

Speaker 3 (43:52):
And the intelligence establishment is also sort of in panic
mode because you know, we can just look back at
some of the more recent escapades that US eight has
been in involved in. They've been involved in the attempted
coups in Venezuela, they were involved in the well, they
were also involved in the attempted coup in Venezuela, but
they were successfully involved in the coup in twenty fourteen

(44:13):
in Ukraine, which facilitated this whole tobaccle that's been going
on there.

Speaker 4 (44:18):
You know, it has been.

Speaker 3 (44:20):
Essentially a front for, as you said, you know, all
of these black operations that the intelligence community CIA, d
I A, in SA and so forth have committed, and
that part of the conversation is being very conveniently left
out of all of the corporate media reported I.

Speaker 4 (44:38):
Think what's really interesting about this and all of my
research is that. One is, I really wasn't familiar with
us AID before this this current Trump influx of defunding
it and shutting it down. But what's more interesting is
almost nobody else was the research that I did. There
is so very little written about us AID. I mean,

(45:02):
there's a ton written about the CIA, right, But usaa
ID has gone under the cover for years, and it's
an organization that has more of a budget than the CIA.
So why is it that has gone under the radar
for so long?

Speaker 1 (45:17):
Right?

Speaker 4 (45:17):
And that's a good question. Possibly because what you were saying,
these media organizations had funding from it. But if you
look up anything from the USAID between nineteen seventy and
nineteen ninety three or even twenty fourteen, you will it
will be hard to find. So the data that I've
been scraping it has been really scraping a little bit

(45:38):
of a deeper search engine.

Speaker 1 (45:42):
So then you get those deep cuts where we can
really dive into where this all begins. And you know,
like Don mentioned, a lot of this money went to
questionable projects, and maybe some of the money we don't
even know where it went, and it's really cutting off
a large part of these, maybe CII in secret of
programs that US taxpayers are funding that we don't really

(46:05):
have any invested interest in getting involved with at all.
It's just money is going there, and it's used to
disrupt for an interest. Why not just take care of
our own country. Why is it that we're messing around
with everyone else's politics? And maybe there's some benefits to
doing that, but I don't really see that being a
wise investment with the American money. It's somebody else that
wants us to go tamper for somebody else's benefit, normally

(46:28):
international corporatis or international bankers for that matter.

Speaker 4 (46:34):
Absolutely, I've got it. I've got I love to do
a little show and tell.

Speaker 1 (46:39):
If you have time, go ahead, let's take a look
at this.

Speaker 4 (46:41):
Of course, I've got my I've got my screen.

Speaker 1 (46:45):
As there should be an option for you to present.
I don't know if you have it.

Speaker 6 (46:48):
I do.

Speaker 4 (46:51):
My screen should be up. I see a box. There
we go. Great. So Mike Binns is using the term.
By the way, Mike Ben's is a great researcher. He's
been doing a lot of work on us AID even
before this story broke, and I think it was perfect
timing for him. He's been doing a lot of hard
work as a journalist in general, he's been using the

(47:12):
term blobisphere. Well, this is us AID and this is
the blobisphere of us AID, right and so in the
middle you have I'm not sure if you can see it.
I hope you guys have. My Internet's coming in through, okay,
because you're going to need some good HD working on yours.

(47:32):
In the middle, you have a USAID right here, and
this is the blobisphere of USAID, and all of there
what I consider gray to dark politics. These are things
that I think raise eyebrows or consternation if if you
have any kind of soul. And so these are all

(47:55):
of the programs that they've been doing that I so
far have uncovered, and there's so much more to you.
I've been doing this for the last forty eight hours,
entering in data, so I've barely scratched the surface, and
this only gets up to maybe twenty twenty twenty something
like that. So appreciate for a second before I dive
in about how busy these people have been doing. So

(48:18):
the way I have this setup is USAID in the middle,
and I have these broken down into continents basically, So
wherever you see these pink influxes are are continent groups
and out of those come all of these different countries, right,
And out of those countries we have all of these
different organizations. So in the US this is where all

(48:42):
of these people who are working with have been working
with USAID, which has contractors like Halliburton, right, we all
know that name. But the way I've broken this down
is let's look at Pakistan. For instance, in pact Stan
where everything started for USAID, one of their first modes

(49:06):
of interest has was around population control. And one of
the things that you'll notice immediately with USAID is how
quickly they were interested in population control. You'll see a
lot of it was forced so being able to give
people aid but only if they take care of their

(49:26):
fertility right, and in that these are all put together
so so far I've been mining articles written on the subject.
So these are all investigative reporters and investigative reports. And
what you'll notice about Pakistan here is you know, family planning,
family planning, So the way it works is you'll see

(49:50):
FPAP Planning Association influenced right, UNFPA, United Nations Fund for
Population activities. This is a research graph, right. So the
way I would love to do this is have this
split into more data. But right now you'll see this
is how the politics work. Zia al Hud halted the

(50:13):
population program, right, and this is these are this is
texts coming from the articles that I scraped.

Speaker 6 (50:22):
These.

Speaker 4 (50:24):
What you'll find is that in Pakistan, for instance, there
were I'd have to get the numbers right, maybe three
million people were three million women were basically whoops, let
me get this back, sorry, three million women had undergone

(50:46):
reproductive surgery, right. And a lot of this wasn't was forced.
And so when you look at the sterilization chain, for instance,
it goes everywhere from Peru. In Peru, I think three
hundred thousand inc and women were sterilized. When you go
to Russia, they were kicked out of Russia. They were

(51:07):
doing sterilization programs. In Russia, they were doing sterilization programs
in a bunch of In India, I think three million
women through USAID were sterilized. And in some and in
some regions they rounded everybody up, especially in the border
of Pakistan, they rounded entire villages up and made them infertile.

(51:33):
They even fertility was such a big thing that they
were developing fertility drugs. So twenty five million dollars was
spent to manufacture and create a fertility drug that went
around the world. I forgot what it was called, but
it was a well used thing, but it was recalled
in the nineteen nineties. Right, all right, so we have

(51:56):
sterilization chain. Let's see if I can back up and
see who's.

Speaker 1 (51:59):
Part of it is out there. This falls right into
the eugenics plan. If you guys remember the Georgia guidestones
back in the day, they had the ten commandments bring
the population down to five hundred million. This was all
part of that gospel, that belief that they, the elitists have,
that they that were using all their natural resources that
were these horrible insects. And in order to get these

(52:21):
benefits and get brought into you know, the first World
country narrative, you got to start by basically making it
so that you don't have any more children. You know,
you get on the eugenics platform. And some people were forced,
it sounds like, into doing this, which I don't believe
anyone should be forced again, you know, into doing something

(52:42):
against your will. And I'm guessing a big proponent of
this would have been the Bill and Melinda Gates Foundation,
since they're really big on eugenics.

Speaker 4 (52:50):
They came in later, so I would argue that when
you talk about global population control, this was actually the
first major organization doing it, so they may have later
because Bill wasn't in power yet, he didn't have any
power yet, but his father was part of the eugenics movement. Right,

(53:13):
his father was part of had a relationship to the Bushes,
who were the push first people pushing planned parenthood. And
I think Bill Gates's father was on the board of
Planned Parenthood. So you know, that's that's a whole other
that's a whole other topic that it can cover. We
can move to terrorism here and we can see how

(53:34):
some of these organizations like this, how us ai D
worked directly with people like John McCain who had meetings,
who sponsored meetings with right, we have meetings with UH
and these are terror organizations. So this is whoops, it's

(53:56):
easy to lose things here. Let's see here we go,
John McKay, this is.

Speaker 1 (54:00):
Well, there's so much data. And for the listeners radio
that can't view this, make sure you go to the
rumble dot com, fort Slash the Rundown live and you'll
be able to see us or go to the KGr
A dB dot com or band video website and check
this out. But there's so much made of data and
they have literally to give a viewers or listeners an idea.
Imagine a marble in the center holding your hand, and
now look at like maybe hundreds, if not thousands, of

(54:24):
different connecting lines going through it a lot of times
and sometimes it's just a few. But this graph allows
you to actually zoom into each graph and who it's
connected to and how it goes through to what person
and everything else and what those essentially what people's prerogative
and what they really wanted to get done if you know,
as far as their goals at the endgame and how

(54:46):
people were affected by it. So here we have John
McCain who also was embedded sounds like with some terrorist organizations.
I know there was photographs back in the day going
around with him hanging out with ISIS or al kaa's.

Speaker 4 (54:58):
And that's what this is. This this is related directly
to that picture that you saw. Okay, So after a
meeting that John McCain had with these rebels. These rebels
were discovered to have killed a lot of Americans. So
this is the way the graph works.

Speaker 3 (55:14):
I have.

Speaker 4 (55:15):
It's not just a relational data base. I've put a
lot of pain and time and energy to make this
a true research database. So if you click on John McCain,
for instance, all of these things are relationships. All these
lines coming out are relationships. If you click on the relationship,
it'll so photographed with right, and it'll it'll have the
terrorist that's connected to it. But if you click on

(55:36):
the line after, it will bring you to the article text.
After the meetings with the proposed joint celebration in Damascus,
McCain's PR office released a photo showing the Senator posing
beside a smiling Mustafa and two grim looking armed rebels.
The article you rl is here, So if you click
the article you arel it will bring you And I'm

(55:58):
sorry it's not click. I think the way the app works,
it's not opening the page. But if you click that
it opened it for me. You click the app, I'm
just going to pick any one of these at random. Right,
Mustafa's meeting with the late this this is another McCain thing. Right,
you can click the link. I mean, this is a
powerful research tool, so if anybody is doing any research

(56:19):
on anything, you can just click anything on here. The
movement against the Sandinistas receives support for USAID. Click on
that right. Joe Biden's involved in this. Hunter Biden's involved
in this. Let's go to we can see, well, Hunter
Biden's not so interesting. Let's go to Wuhan. Wuhan's an

(56:40):
interesting one. And I'm not sure if anybody is caught
up with this. I found this research first, mostly through
a book that I think people are unaware that it's
been written by Robert F. Kennedy, and I forgot the
title of it offhand, but I've been using his citations
to help build this graph, where he talked about US
and explicitly singled out us AID in three chapters about

(57:05):
how they helped fund Wuhan Institute of Virology. That's what
this is. That's where I'm getting some of this data.
I haven't finished scanning the book yet, but I'm going
to click on here. Many experts believe this China Communist
partty is run whatever. Okay, that's there's a lot of
pass through stuff here, Task Force. Sorry, let's go through

(57:28):
here in IAID provided grants for research at the Wuhan
Institute of Virology in IAID. If you pass through and
show it further down, the graph has a direct connection.
It's a pass through organization for USAID, So in it
directly or indirectly, USAID was funding not just the lab Wuhan,

(57:54):
but labs from Pakistan to Indonesia. They had during twenty
nine nineteen, I think twenty five different laboratories, including the
laboratories that we know about in Ukraine that we heard
about more recently where they were suspected that Russia was
trying to target them. For now, since and I haven't

(58:17):
put this in, this is going to be in the
future edition of this that I'm going to post, they
are still funding virology labs around the world. They've doubled
the amount of virology labs they've been funding. So if
you think Wuhan was had any implications for safety, imagine

(58:38):
these same organizations without any repercussion funding more of those
kinds of research mechanisms. Right, it's absolutely insane.

Speaker 3 (58:49):
You know, when we really when you're actually able to
view it and see it in a comprehensive way, that
this graph sort of presents the amount of money that
this organization is spending on so many of these projects
is its mind blowing. And people need to keep in

(59:12):
mind that a whole shitload of this money is coming
from taxation, you know, i e.

Speaker 4 (59:17):
Theft.

Speaker 3 (59:17):
They're stealing our money and using it to fund all
these black projects, you know, get you know, anti Santinista
stuff in Nicaragua, KuPS in Ukraine and Belarus, and propaganda
operations in Cuba and Wuhan Institute in China, and all
these other sorts of things going on. And you know,

(59:37):
it's one of those things where if the American people
were truly aware of how much of our money was
going to all these black projects and just awful shit
around the world, I would hope that it would.

Speaker 4 (59:51):
Spark some sort of outrage.

Speaker 3 (59:52):
Of course, we know that the American population is quite
apathetic and complacence at this point, so who knows. I
might just roll over in whatever. But I mean, man,
it's nuts. And for someone like me who studied, especially
with regard to like foreign policy and covert operations, color revolutions,
you know, all that sort of shit, like that's my
bread and butter. You know, I've spent years researching that

(01:00:14):
sort of stuff, and even with that being the case,
to see a lot of this laid out in this
sort of a comprehensive, you know setting, it really opens
someone's eyes to just how pervasive all it all is.

Speaker 1 (01:00:32):
Yeah, it's crazy, man. I can't imagine how I rate
I'd be to find out that the money I invested
and our government went to fund a giant pandemic and
then we got police state retribution for the money we
paid our government to take care of us. It just
blows my mind that people, you know, people would be
really upset if they had all this data and they

(01:00:54):
really knew all the different ties. This could be a
very beneficial weapon for us to understand, you know, how
these different organizations correlate, how they work together, how they
launder money, amongst other things. Imagine if we had a
graph like this on the Builderberg Group, or even more importantly,
child trafficking and how government funds certain kind of child

(01:01:15):
trafficking organizations and where that money goes, and how they've
been linked to certain bus et cetera, et cetera. There's
a lot of information we could help to bring awareness
using AI and data like these tools AI is a tool.
It can be used for good or evil, right, And
how we use it is important because this is a
chance for us to get a lot of this made
of data and do a lot of work and crunch

(01:01:37):
time and do some investigation with the data the AI provides.
It still needs to be double checked, right, We still
got to look over it make sure the information is correct.
But when you start linking these together, you start to
get a big picture of the hive mind mentality behind
what is the political movement, Who is it that is
pulling the strings, who is it that is funding these

(01:01:58):
different initiatives, and who has the gain and benefit from
these initiatives? Right?

Speaker 4 (01:02:04):
And this is and this gets into some of the
edgier research, which is I'm going through one of the
things that people don't talk about here Meta Biota, which
is a third party contractor for USAID or yes, us AID.
When you look at Meta Biota, they're at the center
at the Wuhan lab story. And here's where it gets funny,

(01:02:27):
because now we're getting into Meta Biota worked with Black
and VH, another third party contractor who was working with
the labs in the Ukraine. The biot who had these
claims of bioweapons. Right, So this chain moves in so
many different directions. It connects Metabaiota received investment from Google

(01:02:51):
while also planning to act as a partner.

Speaker 1 (01:02:55):
Right.

Speaker 4 (01:02:55):
You can see how this connects. Now, this is an
incomplete database that when I complete it, it's going to
be a lot messier. But we can move through this
and see how the chain of like the virology lab
is connected to Afghanistan is connected to Ukraine through one
degree of separations sometimes too.

Speaker 1 (01:03:15):
How about big Pharma? You know where all that money goes,
you know all that stuff?

Speaker 4 (01:03:20):
Yeah? Absolutely, And I think this is this is one
of the things people have been talking about, and one
of the more interesting things I think that's come out
is this these connections to people like George Soros, right,
and the Soros family, who I've got on here. So
if I go to George Soros real quick. Soros is

(01:03:41):
one of the main people who have been working with
us AID for quite a while, I might have to
I think I've overlapped my UI here, give me a second.

Speaker 1 (01:03:56):
Yeah, all this data just comes in and crunches, and
there's just so many points of data. I can't imagine.
This is kind of what a government surveillance fusion center
is for the law enforcement based on citizen threat scores.
Christan T. Harris mot of Coca Cola today it's linked
to three other purchases he made. Yes, you know, it's
just crazy.

Speaker 4 (01:04:16):
Well this is this is exactly that, and this is
this is why I want to put it into citizens'
hands because this is what people use. This is the
kinds of tools that people use for fraud detection, for example,
or network detection. But we now have access to it.
So Soros as an example, right, we have we have
connections to him. He was working in the color revolutions,

(01:04:39):
for instance, when you think about Ukraine and Georgia, you
have the connection from him working through directly with and
the Soros Foundation funneling money to all of these organizations.
Where you talk about the twenty fourteen revolution in Ukraine,
where you talk about the Georgian Revolution, and even when
you talk about things that happen in the Middle East
with the Egyptian Spring or sorry, the Arab Spring. So

(01:05:04):
here we go. George Soros recommended an envoy for Albania,
and here we start getting into an Albania revolution. When
you start talking about Balkanization and who's behind that. US
eight is behind that too partly, and so this, this
graph starts to build the picture. Ultimately, I want this

(01:05:26):
database again to grow and grow and grow and grow.
What I need is for people to utilize it for
for their research in order to help me grow it.
So the more people use it, the more I'm able
to do anything with it. And of course you know
if people visit my social media too, that'd be great.

Speaker 3 (01:05:44):
The government, Oh go ahead, done, I'll say, well, I
absolutely plan on sending it to a number of you know,
journalists friend of mine, Matt Jason over at the Free
Thought Project.

Speaker 4 (01:05:54):
I know, you know, Derek Rose and the Conscience Resistance
is going to love this.

Speaker 3 (01:05:58):
He'll probably get it in the hens of you know,
Whitney Webb and Ryan Christian from The Last American Vagabond.
And you know, I definitely want to see, uh, this
be utilized because it's it's already incredibly impressive.

Speaker 1 (01:06:10):
Yeah. Don do you think Don and Drew do you
think the government asked something like this with U with US?
Independent activists are counter propaganda activists where it's like Don
v Junior, Christan Tierris Link, Alex Jones link, but.

Speaker 4 (01:06:23):
They have they have it with every every they have
it with everybody. Yeah, and and by the way, this
is this is how and I just want to put
this in. I'm gonna get really tech techy here for
a second. Yeah, appreciate it.

Speaker 1 (01:06:34):
Tech type show.

Speaker 4 (01:06:35):
So AI is going to have to redo itself in
the next few years because it's based on l ll
ms right now, which is like basically compressed packets of
information to your packets of information. It's it's crunching and
taking huge chunks of things. But that's not the way
things are working right now. They're going to have to
rewind a little bit and get into a network raph,

(01:06:56):
which is something like this. Google runs their search in
on network graphs. It's something similar to something called a
rag graph, which is kind of what you're looking at here,
which is how things are connected where you're connecting databases
through shared entries. I'm going to build something through Neo
for j Eventually this is going to go into a

(01:07:18):
larger database, cloud based database system. Right now, it's a
closed database, which I mean it's on the cloud, but
it's not a shared cloud system. I'm busy perfecting how
the data works and how the data entry works. So
there's a lot of loose ends that I'm still still
dealing with right now. Ultimately this will come together in

(01:07:38):
a bigger packet. The government has this, and when you
think about information for anybody in anything, when you talk
about surveillance, whether it's corporations or government, they use things
like this. This is just a visualization tool of a database,
and people use this in order to show how things

(01:08:01):
are connected and how tightly things are connected. So if
you are things are building chains about, Like if you
go to a place more than once, you know that
connection is getting tighter and tighter and tighter. Right, So
like if you see here you have this thing where
that has a lot of connections, Well that's George Sorows,

(01:08:22):
he's a very connected individual. Things like that are being
built for everybody, and just the fact that you are
a conspiracy theorist doesn't make any difference. Everybody is a
part of a system like this. Everybody has something built
like this for them and can be implemented into the system.
It may just be that some people who are into

(01:08:42):
weird things may be looked at a little bit more closely.

Speaker 3 (01:08:46):
The one thing that it reminds me of in regard
to that, The most similar thing I can think of
with regard to government surveillance is the PRISM program that
the NSA was running that most famously Edward Snowden exposed.
It's it seems, you know, to be sort of along
those lines with as far as like the way that

(01:09:08):
data points are connected and.

Speaker 4 (01:09:11):
All that stuff.

Speaker 1 (01:09:14):
Yeah, the many forms of data points is what's interesting
to me, and the fact that we could do this.
They you know, that the FEDS have a system like this,
Like if they come to visit don Vy Junior, they
already know his eighteen points of data, his links, his
the you know, who he's associated to, who he talks to,
who he knows, who he's friends with, you know, the
communications he has, all that data, you know, and they

(01:09:36):
know all this before they try to contact people out there.
So the Fed's got to use this data, you know,
to come and be you know, predatory. They got to
know also where you can be blackmailed and where they
can twist your arm and everything like this. This is
a crazy amount of data and it never it's real
surreal to me to see this data that we're able
to accrewe or I should say you drew are able

(01:09:57):
to accrue and put together. Because if you can do
something like this, man, you know that the FEDS and
the government has something way more intense, hence the social
credit scores. Hence a following imagine with like we started
off the show, central banking, digital currency or cryptocurrency. If
they can track where it all goes, they can find
out who's buying what through who and where they're spending
the money, and if it goes towards this cell or

(01:10:19):
that sell and the product that people are buying or
funding this organization or that organization. If you're going out
there and buying you know, brainforce, and who's buying it,
where that money is going, and where it's spent afterwards,
and how it's being used and everything like all that
made of data. It's the same thing kind of what
we're looking at here. George so sends money to one
shell account, ends up to another shell account, and then

(01:10:40):
you said gets the money, or you said, goes and
you know, gets that tax payer money and uses it
for a eugenics program to help depopulate the planet, you know,
the good old planned parenthood, you know, William Gates Senior plan.
There he said on the board there and you were
correct on that, Trew. It's just interesting to see how

(01:11:02):
this all is developing and all the different data because
you could do this with any points of data if
you know how to pull the information, and you have
AI having the ability to do that. Now the question
is is how is this Like I just want to
push this to the next level AI intelligence. This is
kind of an idea of a map of a lot
of AI brain would look like it would have all

(01:11:23):
these points of data. It would be able to process
this information, and then it would be able to communicate
an answer at an alarmingly fast speed, more so than
a human. And maybe when people are posthuman or transhuman
and they have that brain chip interface, they're going to
have access to all this data in real time. It's
just crazy to me. I'm just going off on a
tangent right now.

Speaker 4 (01:11:43):
So this is now You're getting to my real point,
which is what I'm going to be doing with this
in the future because this is a graph rag system
that I'm building. All of this is how AI. AI
is going to be thinking in the future. Like I said,
right now, AI is outdated. LLLM models are going to
be forced out because it can't hold that much information.

(01:12:03):
But what it can do is coming back into relationship graphs,
which is what Google runs from. And I'm imagining Google
is going to catch up in the AI game because
their search algorithm uses these graph rag systems just like this.
So what we're getting at right now, what you just discussed,
is what I have planned for the future, which is
right now, it's AI in. In the future, if I

(01:12:26):
build it out, it will be AI out right, so
you can ask a question and it will be able
to give you and respond. And actually I could probably
plug this in right now into an AI system and
get it. But I want to be a little bit
more comprehensive. I want to be I want more sources,
so I want this. You know, at some point in time,
this is going to be something you can't even look

(01:12:46):
at anymore because there's lines connecting everything because there's so
many sources. And by the way, you know, we live
in a world where there is open source data everywhere.
I mean, I'm getting this data from this place and
that place. There's not one organization that's bringing it together.
And that's my goal, is to bring all of the
data that I can find that's open source together. Whether

(01:13:08):
it's true or false, I don't care, because even falsehoods
lead to the truth because they're trying to obscure it.
So when you start bringing all of that stuff together,
it starts building a picture. AI is able to scrape
that and find relevancies. When you start building relationships and
nuanced relationships between things, you can start seeing and especially

(01:13:29):
when you start looking at the history of let's say
a publication on a certain topic, whether they were right.
Let's look at the Russia, the Russia Trump conspiracy, right, yeah, yeah,
and how that turned out, and we can use that
to wagh how the author, how the underwriter, how that
media organization or publisher was accurate in their reporting, and

(01:13:53):
we can build a chart of accuracy of stories of
authors blah blah blah, be able to generate more of
a direction toward the truth, right, because I mean, our
understanding of the truth is never going to be complete,
but we can get close to it.

Speaker 1 (01:14:07):
The citizen truth rating great, I mean, but you know,
if you want to know if it's like imagine if
we pulled up info Wars and we found out one
of the highest truth ratings over CNN and Fox, people
might think differently, but at the same point, like who's
programming the algorithms, you know, and what will their algorithms
say versus other people? I guess it defines what is

(01:14:28):
true and what is not true, but I guess ai.
And the facts, you know, the facts are in the
side of history a lot of times, and finding that
out and getting the information author is interesting altogether. Drew,
this is a phenomenal job. And the way you're talking
about going with this is also you know, you could
develop a whole institute and do this almost full time

(01:14:48):
and pull these graphs in and really impact where the
money's going and educate people because this is like the
three D chess game here. This is like the deep
dive into globalism, into funding of multinational corporatus and outside money,
inside money. We could do something like this on the
Council of Foreign Relations or secret societies or whatever. Like

(01:15:09):
it would be fun, Like it's a cool thing to
do and it's a neat passion. Not everyone could be
analytic analytical like you on this. You know, it's like
trying to be in an accountant. I could never do
that because I'd be like, you know, screw my life.
This sucks I don't want to just count things and
put no little ones and zeros and fives and fours
and little brackets, because I'm accounting for things. But some

(01:15:30):
people have the gift to look at things like this
and go, oh, there's this link and there's that link.
And it's important to be able to follow it because
now you can legitimately say, George Sorow's funds this program,
and this is how it goes through this organization and
this organization, and this is what it funds. And it's phenomenal.
This is a great tool, you know, and I think
people should get out there and use it as a

(01:15:51):
free source program. I wonder how many different ways you
could use it. It just it's like where did you
find all this? And what inspired you to do all this?
Like what one day you just woke up and you're like,
let's do this, let's make a graph of everything.

Speaker 4 (01:16:04):
I had this idea in twenty eleven. It was I
was incapable of doing it because you'd have to hand
enter all of this data by hand. Not possible, and
so I was waiting until AI. And I've been testing
AI in it. Finally, because one of the issues that
I've had especially in the last couple of years that
I've been trying. It is just AI hallucinations. AI is

(01:16:24):
the you know, open AI. Any kind of AI database
that you're working with is constantly not giving you what
you want because it's not a human being. It's it's
constantly trying to regurgitate what it thinks you want. But
it doesn't have human logic. It's really just trying to
regurgitate what it thinks humans want. Can I give you
one one interesting thing? I think when you start putting
these things together, you get some really interesting things pop up.

(01:16:48):
So if you're familiar with a Pentagon Papers written by
a guy, a man named Daniel Ellsberg, I know Daniel
Ellsberg's son, but there's his daughter's name is Mary Elsberg.
So what the Kindagon Papers is famous for is breaking
open the public's knowledge. He was kind of the Edward
Snowden of his day. He took classified documents and published them.

(01:17:10):
I think it was through the Washington Post and maybe
the New York Times. But it broke open American's opinion
on the Vietnam War because it showed the atrocities and
the scale of the atrocities that were happening during that conflict.
Mary Elsberg, Daniel Ellsberg's son, is also a journalist. However,

(01:17:32):
what Mary Elsberg does, she's on the other side of
the fence where she writes apologetic things for USAID, and
she has been in my research. She has shown that
she works for Let's see here, I think I'm having
some UI issues here. She works. Mary Elsberg is associated

(01:17:55):
with the institute doing USAID funded research, and she's been
a cues. I think this is an article in Ecuador.
If I'm not mistaken, I whoops, lost it there she
I'm gonna have to find her again.

Speaker 1 (01:18:14):
Mary Elsberg. Huh.

Speaker 4 (01:18:15):
Yeah. So she's Daniel Elsberg's daughter. So she's associated with
USA funded USAID funded things, and she has been writing
basically apologeticism articles for it. So these are some of
the interesting things that you see when you start doing
the research and start scraping in. I haven't gone through
all of this stuff right this is I'm still scraping

(01:18:37):
through it. I'm trying to keep up with the information
that data while I'm scraping through AI. But you know,
there's just so much of it. So I'm hoping people
can find things that I haven't even caught in here
and find connections. And what I'd love more than also
just about as much as people using this is actually
finding sources and sending me sources. So if you have

(01:18:58):
any sources that you think a good that connect any
of the dots to any of these major things, just
send them to me. Uh. If anything having to do
with us a I d that maybe under the radar,
please send it to me. I'm gonna include this. I'm
gonna be working on this for the next you know,
half a week or so before I publish it. So
also join my website if you want to get if

(01:19:19):
you want to get access to it. Uh, to this
and and there are some other stories on my website.
Subscribe to my website, come out see it, uh, and
I will you'll get early access to all this stuff.

Speaker 1 (01:19:30):
I would definitely crazy go ahead done.

Speaker 4 (01:19:34):
I was, you know, just just for sources alone.

Speaker 3 (01:19:37):
Uh, you know, I would definitely recommend you know, if
you're able, you know the Grayzone dot com unlimited hangout,
which is where Whitney Web publishes mint Press news.

Speaker 4 (01:19:45):
Uh, and just scrape through all of their archives. They
got that they're already a part of it. Gray Zone
is one of my primary U S, A I D things,
and like I said, there was there was of the
few publishers that was covering US A I D though
to Mint and Mint and gray Zone are the ones
who did the deepest reporting on USAID up until this point. Yeah.

Speaker 1 (01:20:12):
Well, it's all fascinating stuff and I would love to
see one of these done on nine to eleven and
some other things. I mean, it's just crazy, all the
different ways you could go with the technology and these
big data scrapes, and where the money's gone, and how
it's impacting and who's all involved. It's it shows how
they're tied together, how they communicate together, and basically you

(01:20:34):
can figure out who the people are that are really
funding these ideas, you know. And there you go. You're
searching gray Zone, which was at Max Blumenthal. Yeah, well
I have a cell phone. Maybe I should shoot him
with a text with this video when we're done.

Speaker 4 (01:20:47):
Tell him he's a primary source of mine. I love
the I love the reporting. They've done such a spectacular
job keeping up over me.

Speaker 1 (01:20:54):
No, absolutely, I haven't. I haven't used it yet, but
I've been looking for a reason to use it, and
this might be it. Just just to say, hey, this
is who I am. And you need to check out
this video and this dude, Drew Arnold, Drew, you always
do such a good work. It's always great to meet
you because we always have such you know, elaborate conversation,
especially about the two party system and how it's really corrupt.
I know that between me and you, you know, and

(01:21:16):
Don as well, we all feel that we're not represented
by most of these political you know, people in office,
that there are third party candidates that don't have voices
out there, and that you know, when it comes to
all of this, we're looking at two sides of the
same coin. I wonder, I wonder how much of this
money and funding also funds both sides of the political spectrum.

(01:21:38):
Can I give?

Speaker 4 (01:21:39):
Can I give you one? I just want to. I
want to leave on one note because I think I
want to. I want to showcase one feat.

Speaker 1 (01:21:45):
Well, we got thirty minutes left. You can use as
much of it as you want. I love to talk
to you. Great, fantastic, We're on your tip. Let me
see you real quick.

Speaker 4 (01:21:52):
I'm going to go to uh let's see if I
can find whoops, do I have to remove? I have
to stop the screen, right Okay, yeah, there you go.
Let me go share a screen again, share a screen,
and I'm going to go through because I think I
want to showcase how non partisan I am with all

(01:22:12):
of this stuff. Data is data, and there are interesting
things happening behind the scenes. And as much as I
think a lot of people want to applaud Trump and
what he's doing, my question is, if he's getting rid
of of the deep state, what fills in that power vacuum?
If he's getting rid of all of his organization, what
fills that power vacuum up. This is a story that
I released a few weeks ago on doge where this

(01:22:34):
is a better rundown if you will, of Doge of
how DOGE came together? Right? And so these are the
question that I had, and this is on a piece
of content that I made. Is DOGE a government agency
or is it a tech company? And the reason why

(01:22:56):
I asked that question is because I made a list
of all the the founders of it. Now we all
know Vivek and Elon, but in here you have all
of these major major players vcs who are in Silicon Valley,
and these people came together and to help facilitate the

(01:23:16):
creation of doche and so if you don't know who
some of these people are or what they've done, that's
okay because I have a network graph that showcases. Let's
see here, I'm going to select the child nodes.

Speaker 6 (01:23:32):
Here.

Speaker 4 (01:23:33):
Mark Andreasen, for instance, owns a Twitter, coinbase, opswere ning.
Some of these you won't fandom. Some of these you
won't recognize. Stanford Hospital, Well front you have. I'll show
you how to use this a little bit. If you write,
click on it. Let's go to Sean maguire and you

(01:23:53):
go to select child nodes. We can pull out his
stuff wherever they are. Let me try that again. Oh,
he doesn't have very much he.

Speaker 1 (01:24:06):
Is he only has eight companies he's running or twenty yeah,
instead of forty links.

Speaker 4 (01:24:17):
Sequoia Capitalism is the namesake of the ones that you
would might recognize. So Sequoia comes up in some of
my other research. They are very political and go both directions.
Here's here's another one. I mean, some of these guys
are an uber. I'll go through some of these. You
have PayPal, hyper loop expoll.

Speaker 1 (01:24:34):
That's Elon, Robin Hood.

Speaker 4 (01:24:36):
Yeah, you have Robin Hood. Let's see start X. There's
people who work for the Trump campaign already, Goldman Sachs,
Republican Lawyers Association, Cybersecurity Tech. I mean these Facebook, Microsoft,
these are people who own steaks in these companies or

(01:24:57):
major stakes in these companies.

Speaker 1 (01:25:00):
So what does that mean though, like get the endgame
to the consumer or the person that's out there and
listening to the show, Like we have all these people
linked together, But what does this really mean about doge?
Does that mean that these are the right people for
the job since they know about government efficiency and they
know how to run profitable businesses, or does it mean
that they have their own interests and they have their

(01:25:22):
own ballgame in mind behind the scenes.

Speaker 4 (01:25:25):
Well, I'm not going to answer that question quite yet
because I think we have to see how this plays out.
I think what we can agree on is there is
going to be a power vacuum that everybody who's involved
in this may not have selfless interests. Right there are
people who are you know, with this many cooks in
the kitchen, you can imagine what's going on behind the scenes.

(01:25:47):
I mean, you've got people who run who own stakes,
and Uber who own stakes and by the way, Uber
was huge in Kamala Harris's campaign. You have people who
own have stakes in y Combinator, which is the primary
incubator for startups, right, So who is And you know,

(01:26:09):
I don't want to necessarily give credence to a conspiracy
because there's no data to prove it. But what I
can prove right now is that there are special interests,
major special interests, who are behind DOGE, right, not just Elon.
And these are the people who came together to make it.
Now we don't know who's in DOGE currently. All of

(01:26:31):
these autists who had these nineteen year old autists who
are supposed to be crunching the numbers, but they work
for people, right, they were likely referred by some of
these people. There is a bunch of data being involved
in their crunching. Is that data sequestered? Is it protected?
What's happening to it in lieu of I'll give you

(01:26:54):
another question that I have in lieu of these major organizations.
And I've always said that we could repent half of
government with an AI system, just fine, absolutely well, guess
what that might be happening is are our lives going
to be run by a data management system in the
future coming from the government and if so, who owns it,

(01:27:16):
who runs it? These are just questions, right I don't
think we I don't think we have the ability to
answer them. But we can ask the questions right now
and keep up with the story in order to see
it happening in real time and maybe do something about
it if we see something wrong. Well.

Speaker 1 (01:27:33):
And also the mode of data that gets driven by
these graphs and information that's under that you can understand
from is impressive once you get into the deep dives.
Not only to mention like if you did have a
data driven government that was AI driven, you would have
blockchain voting. You wouldn't need a congressman, you wouldn't need
a state assemblyman. Everyone could just vote from their cell
phone and send in their blockchain vote on the issue

(01:27:53):
that matters to them. You wouldn't have to vote in
somebody who represents half of what you votes for half
the things that you want. Like here in Wisconsin, we'll
make a small example. Overwhelmingly in all the polls, marijuana
legalization would be approved by the people of the state. However,
there's politicians that are preventing that from happening. Although they're
really good on a lot of things, they're not good

(01:28:15):
on that one subject. So if you eliminate the person
we elect and we all get the vote on the
things that we really want as individuals, we'd have more
of a true democratic republic or you know, per se
and be able to get more of what we want
done if you believe in voting and that kind of
stuff all around. So yeah, like fascinating workman, that's a
lot of hard work. It's pretty cool to see what

(01:28:36):
you put together there, and I think it's I definitely
should be amplified. This is something that I could see
breaking large. I hope it does for you, Drew. You
deserve it. Anyone that's put in this kind of investment
in the time and be able to put something in
a visual cortex where we can access it, get data
and look at this in real time and have it
in an open source format, it's amazing. You know. I'm
surprised somebody doesn't take elon and this kind of stuff.

(01:28:58):
So we'll send this up that you will send this
to some places and see what people think. But I
think this is pretty interesting, and we're just mean, don
We're the kind of the guys that kind of go
through and invite a lot of people. A lot of
times it gets amplified, and there's plenty of people on
the show that have got amplified, and you definitely deserve it. It's
pretty interesting, Drew, and I look forward to seeing what
you're going to do in the future. And you got

(01:29:20):
to do the Builderberg group because Bilderberg is coming up
in June, and I think that would be a really
interesting scrape. I think child trafficking would be huge. I mean,
you could continuously go viral over and over and over
again if you kept making these graphs on certain subjects
that are hot. I think this is a great idea,
a great way and good investment to stay relevant. I mean,
in all those videos those cool CGI you can make
a CG I have mean, don we'd like that.

Speaker 4 (01:29:42):
Not just kidding, Yeah, no, you know what I mean.

Speaker 1 (01:29:44):
It is.

Speaker 4 (01:29:44):
I think I agree it's a great investment. If I
weren't doing this, I would probably help be buying property
in Gaza right now. But this is where I'm at
and I appreciate you having me on the show. By
the way, you're the first one to break it, so
you're the story. You get my first and I'm glad
to be in front of your art.

Speaker 1 (01:30:01):
I appreciate that. And then tomorrow you're gonna be on
a pretty big show for our listeners out there that
tune in on kg R a dB from midnight till
two in the morning. You know it's gonna be on
Info Wars. You're gonna be one on the American Journal
tomorrow with Harrison Smith, which I've hosted is program for him.
It's gonna be a great show. He's got millions of
listeners and he gets a ridiculous amount of viewers. It's

(01:30:23):
a great program. So I'm kind of curious to see
how this blows up and how people respond to your
made of data driven grafts there, Drew Arnold, great stuff
so far, our listeners out there, how can they find
out more about you? Where can they go?

Speaker 4 (01:30:36):
Fantastic? Well, my website has everything, including links to my
social media. It's invisible inc. But it's instead of a
K at the end as a Q, so it's short
for inquiry invisible inquery. But I n Q. I'm invisible inc.
I n Q at on TikTok. I have zero followers

(01:30:59):
right now on on on X, so if anybody wants
to follow me, that'd be great. It's a fresh right,
it's a fresh, a fresh account. I think it's invisible inquiry.
Uh so it's spelled out all the way. I really
have to get a handle and I think somebody else,
somebody took.

Speaker 1 (01:31:16):
I got invisible underscore. I n Q that might be it.

Speaker 4 (01:31:22):
Can we look at this together?

Speaker 3 (01:31:23):
I really?

Speaker 6 (01:31:23):
Yeah?

Speaker 1 (01:31:24):
And there's no picture. Yeah, this is you? All right?
You now have a total of three followers all of
a sudden, and we're gonna share.

Speaker 4 (01:31:32):
This growing fast.

Speaker 1 (01:31:35):
Amount of followers in just one program here. Thanks, Don's
gonna add a follow I'm gonna go ahead and share
this page on my Twitter, uh so people can find
this along with your videos. I can share this profile
on my phone. It looks like I can share it
just about everywhere. We're gonna go ahead and share it
on Twitter right now as we speak, and make sure
that it gets out there. So for you guys that

(01:31:57):
are out there invisible, I n v I s I
uh A b l e I n Q dot com invisible.
Uh excuse me, I messed that. I n v I
s I b l e I n Q dot com. Again.
I n v I s I b l e I
n Q dot com. If you want to check this out,
he's got a lot of interesting stuff. If you want
to see what we talked about and you're listening to

(01:32:18):
us on radio, you can go to the Rumble dot com,
Ford Slash, the Rundown Live or ban dot video. This
will be up there shortly. We'll chop this up and
we're gonna put Drew's segments separate from it. And it
looks like, you know, people are already watching, They're already
talking about you know what we are diving into Rumble.
We have people mentioning here we go, we got what
do we have? We have the gray zone and Clarenberg

(01:32:40):
and Whitney Web have been on top of you said
for a long time. There's other comments that chat. Richard
Graft does the graph grand Theft World podcast. You should
look at potentially getting on there. It looks like software
Richard Grove made to track how the predator class networks.
I mean, there's all the like, there's a whole bunch
different things. It's pretty interesting on a Rumble chat. So

(01:33:03):
make sure you guys move down there. But the dark
money chain, Drew Arnold is our guest, looks like you
got Tulsa Gabbert tell us about the Tulsa Gabbard and
the cash pital ones that you have coming soon.

Speaker 4 (01:33:17):
Well, I have to take those down because I couldn't
keep up. It's it's so hard to keep up with
the news cycle with crutching all this data. So I'll
be taking that down. What I did was I ended
up running. Maybe I can show it here, yeah, I
ended Let me let me show you a little bit.
I've got these. Let me try these hearings here because.

Speaker 1 (01:33:34):
We got fifteen minutes yet. If you want to show
us anything, we'd love to go over this.

Speaker 4 (01:33:37):
I think these let's see if they didn't break. I
had and you got.

Speaker 1 (01:33:43):
This is where you've been posting a lot of these videos. Yeah,
are on TikTok. And it's again it's invisible underscore. I
n Q that's your TikTok. Otherwise, Chris, don t Harris.
I have a TikTok and I will be sharing some
of these on my TikTok.

Speaker 4 (01:33:57):
So, yeah, give me one second here to pull this up.
I think if the data didn't break, I could show it.
Let's see what happens. Yeah, data is a little bit broken,
but let me, Uh, this is one of the reasons why,
you know, working with data, it's like one of those
things where you're you're constantly running into things breaking. But

(01:34:18):
I'll show you the tolls. I'll show you what I
came up with. My initial thing. This is with RFK Junior,
and I did something that was interesting, but I don't
think was really that cool in terms of putting it
on TikTok, so I didn't put it up. And also
I'm trying to keep up with everything. So let me
present this share screen with hearings too, and I did.

(01:34:45):
I did this with every candidate. This is a here.
This is the hearing for I think RFK Junior, and
what it shows is the most so so in orange.
These are all of the questions and answers that took
place between. So back here are the answers. Back here

(01:35:06):
are the questions that were asked. And in another iteration
of this, I had the questions ranked from how friendly
or how antagonistic they were, so and then I also
had the senators ranked from how I mean it should
come up. But like I said, these things break because
it's it's just not ye but the but the But

(01:35:30):
you can see I think I have them the the
size of them. I think this is Bernie, probably Bernie Sanders.
So the size is the bigger they are, the more
antagonistic they are. And so what I did was a
whole day of hearing that I had all of these
connected from Bernie Sanders to RFK I'm sorry, Bernie Sanders,
from rfk's hearing, to kash Matel's hearing to Tulsi Gabbart's hearing,

(01:35:54):
and it showed some of these senators back and bouncing
back and forth between them. But here down here is
I have subject matters. So these are all the subjects
that were breached during the thing. So the bigger they are,
the more they were talked about. So this one is
prop pretty value and that's not right, property value findings.

(01:36:19):
So oh, studies, that was it. So that was the word.
Studies came up over and over with RK. Here's another one.
This one was vaccine. The word vaccine, right, and so
you get into this and there are this big one
here is probably trump autism. Oh okay, autism came up
pretty right. So so what I wanted to do was

(01:36:41):
showcase how these things and you kind of see a
really interesting thing about the peak of how these hearings work.
And what's interesting about it is you have an emotional
peak that happens through here where where this was, and
you have certain senators asking questions at a certain time.
So there's a whole emotional peak that happens during these hearings.

(01:37:03):
And unfortunately it's broken right now. I wish I could
show y'all.

Speaker 1 (01:37:06):
But no, it's interesting nonetheless, and when the data is broken,
you know, you got to work with what you got there,
and the graphs are pretty impressive all around. A lot
of work has gone into it, and even using AI
as a tool, it's pretty fascinating if you can get
some quality sources of data and information and go, you know,
show people everything that it's surely is like it puts

(01:37:30):
a visual aspect of things that people learn in different
shapes and forms and fashions. Not everyone learns by hearing things.
Some people got to physically see it and how they're linked.
And just think about the fact that now we have
that we have the ability to look at a graph,
click on and it tells you what all the links
are of the power structure. This is what Derek Brows
would have called the pyramid of power. On some of

(01:37:51):
these structures that you've come together, and then when you
can break it down by the subject of who had
the most invested interest in things like the Robert F.
Ken the appointment, or the tel appointment or you know,
Telsey Gabbard or any of these others. Like, it really
allows you to put these things to a visual cortex

(01:38:12):
so people can understand them better. Not everyone can understand
this if they if they don't see it, they don't
get it. It doesn't die, you know, they don't soak
in the information and plant the seeds of their brains
so they can grow these ideas and understand how everything
is connected. But now you can visually go there. You
can visually see that it's connected. You can collect on
one of these orbs and orbs, holy cow, what is this?

(01:38:35):
This looks like a brain.

Speaker 4 (01:38:37):
This is Kamala Harris's spending for her twenty twenty four
campaign and however clustered. Yeah, this is one way of
looking at it. So yeah, so these are all organizations
and money and this is this is what like, as
an example, this is one organization that took most of

(01:38:59):
their money. So each of these packets represent one organization.
Agencia took Unfortunately, there's no commison here one hundred and
eleven one point one. I don't know if that's right there.
I have to double check the math. But you have
American Airlines, right, that took a pretty big deal of money.

(01:39:20):
So but then you have these larger organizations. So this
is basically a disbursement chain of how that or that
organization spent one point two billion dollars at least. This
is the public stuff that I could pull up. What
does the Trump one look like if if you happen
to have one.

Speaker 1 (01:39:36):
I'm not sure.

Speaker 4 (01:39:38):
I did not create a Trump one, but it was
about the third of this scale and a lot more
spread out, so it was not quite in such big
pockets as this. I think they had a lot of
smaller pockets.

Speaker 1 (01:39:51):
So, you know, it's interesting because this allows us to
see where the money comes from. Was the power to
game all those things we ever always talk about, like
we mentioned Derek bros. The pyramid of power or amongst
other things. This is a huge tool for people to use.
So discuss open source real quick. We have a couple
of minutes here. How does somebody use this and how
do they you know, access that they go to the
invisible inc I in q dot com.

Speaker 4 (01:40:13):
Yeah, let me do a little run Let me do
a little run through real quick, and then I will
show I'm going to share my screen again.

Speaker 1 (01:40:23):
So like if don Vi Junior wants to get on
there and make his own little cool brain looking graph, like,
how would he go about doing that?

Speaker 4 (01:40:31):
Like?

Speaker 1 (01:40:31):
How would we add sources and other data points?

Speaker 4 (01:40:36):
Great, So let me let me show how to use this.
First of all, if you go to invisible inc I
n q dot com, I'm going to click on one
of these the stop the dark Money chain to stop
RFK and uh there's an article that writes about the data.
So I basically I have all my findings, which are

(01:40:57):
just my findings, and I have some excerpts from the
graph that I've made. I think it's all interesting. You'll
want to read it. Probably it'll give you a context
for what the graph looks like and how to explore it.
If you scroll down at the very bottom of here,
just above the recent posts, you can click on the
kin of is the graph x are kenna is file

(01:41:18):
and it will open up in your browser a graph
and one of the graphs that I was using. If
you have a mouse, it's much easily quick share screen
so that we were able to see on I'm sorry,
I thought I thought that was working. Let's let me
try that again.

Speaker 3 (01:41:35):
I just wanted to point that out and make sure
that yeah, thank you, No, absolutely.

Speaker 4 (01:41:43):
Okay, let me go back. Is that is that not sharing? Okay?

Speaker 1 (01:41:47):
We got it now.

Speaker 4 (01:41:48):
Okay, all right, great, so let me let me start
that from the start. Here. We got to click on
any of the stories. Scroll down. You've got all my
writing on it. Make sure to sign up so you
can get access to everything, and then go to at
the bottom of the story, there is a link to
a graph. And since that popped up in a separate thing,

(01:42:13):
I'm going to now share a screen again. Go to
the next tab. Okay, I'm sharing. I think you guys
might need to do something with that. I think it
needs to be added. Let me see yeah, yeah, okay,

(01:42:36):
so that pops up this graph. This is the Arabella
Advisor Network. What you can do is you can click
on the side and there's a couple of different ways
to navigate this. I've created tags for foundations so you
can see all of the foundations who are part of this.
Different different tags that I put in Bill Gates. What

(01:42:58):
you can do is let me just show all of
the hidden nodes. This is kind of the network of everything,
some of the things that didn't get connected. But you
can click on any one of these. You can actually
change if you know how to use the AI. The interface,
it's a little tricky. Let me go to data the settings,

(01:43:21):
and I'm going to turn the caption size down a
little bit here. It takes a little bit of ways
to navigate it, but you can zoom in to any
of these, click on it, and if you write click
and hit information, the properties box comes up. This includes
all of my citations, so it'll give you the detail
about the organization and how it's connected to Arabella for instance.

(01:43:44):
It'll also tell you about the connection to any other organization.
So if you click on the node, that's an organization.
If you click on any of the lines, it is
a connection to another organization, and in that is a citation.
So all of this, most of this stuff comes from
influencewatch dot org, who does an amazing job focusing all

(01:44:07):
the connections of dark money between politics and money. Basically,
so we have like things like Democracy Docket, for instance,
which is a bill I'm sorry, a mark alias organization,
and you have just all of these different organizations that

(01:44:27):
are a part of that network, and you can click
any one of them. Right, So if I click on
this one and unfortunately it's just not it's not going
to pop up. But if you click on the URL,
it will connect you to more information on the subject.
So this way you can do your exploring and get
started with your your exploration of the data. So this
is a this is a database research tool that you

(01:44:49):
can use to influence and understand your stuff better. So
the last thing I'm going to show is if you
click on category, whoops, well maybe it doesn't show it. Okay,
never mind. This is for the UI that I use.
But if you go back you can I'm going to
put different views so that way it structures the data
in different ways so that way you can see it.

(01:45:09):
So this is kind of like unstructured, a little bit
messy and kind of the way it just comes out.
It takes some time to structure, and I'm just busy
making the data, so not a lot of workmen, I
know it's not making I can't. I don't have time
to make it pretty.

Speaker 1 (01:45:23):
I'm just thinking, like every day when the news breaks.
If I could have a tool like this for the
article where a dive in who wrote it, what it's about,
all their sources, this and that, and how are they linked,
and we're like, you can be able to identify propaganda
real quick. You'd be able to identify if it's a
valuable source or not available, where they're right, where they're wrong,
just all the like, just the amount of potential to
have software like this, And that's where the future is going,

(01:45:44):
is that there will be tools like this for journalists.
And it's phenomenal. Yep.

Speaker 4 (01:45:49):
And you can type in So if I wanted to
type in here Soros right and click down on entity,
you have all of these Soros names. There's a search
function so you can type in anything. George Soros himself
is out here, way way way out here. Let me.
I would love to reload this, but I'm afraid to
do it. George Service, Open Society Foundation, and here it's
connected to a bunch of organizations that are connected to

(01:46:11):
you know whatever.

Speaker 1 (01:46:12):
Explore it.

Speaker 4 (01:46:13):
You can figure it out. It's a little tricky to
start using, but once you get the hang of it, uh,
it's it's not so unintuitive. You got the Southern Poverty
Law Center. Imagine where they get their funding from. I mean,
if you just look through this, like I said, it's
going to be better if you use a mouse for it,
because it's a little bit tedious just with h a
cell phone. Yeah, oh a cell phone. I'm not even

(01:46:34):
sure if it works. I've never tried it, but yeah,
definitely get yourself out, get on your laptop or your
your PC, whatever, and use a mouse. Sequoia Climate Change Foundation,
Remember Sequoia Capital, Sequoia Climate Change Foundation. So you see
how these things are connected, Kathy Duvall, look at that
MasterCard here we get into Walmart. I mean, the Asian

(01:46:57):
American Foundation is all these organizations, right, so you know
this is the cross section of money, power, influence, and
so we'll be building more on it. My goal is
to get this funded, to get more computing power behind this,
and to get some data crunchers working with me to
help curate a lot of this data, because a lot
of it is curation and making sure the right stuff
gets put in.

Speaker 1 (01:47:18):
At this point, well, how can anyone How can somebody
contact you if they want to fund this or support you?

Speaker 4 (01:47:24):
You can contact me through any of my social media
platforms I don't have. I don't have a lot of
followers right now, so if you contact me, I will
definitely get back to you. You can also go to
my website and contact me directly from there. It's invisible
inq dot com and I'll respond. And also if you
just want to contribute it in any major way, if
you have a breakthrough or any kind of information, whether

(01:47:46):
it's whistleblower or something that you think is being overlooked,
please end it my way.

Speaker 1 (01:47:51):
That's awesome for all our listeners out there. Juw Arnold
is our guest today. Thank you for coming onto the show.
It's been a blessing to have you got have you
on today? What a great pro ran, what a great
deep dive and what about I mean, that's a lot
of valuable information and giving people the tools to find
and validate the information themselves. That's important all around. And
so for those who want to find out more, go

(01:48:12):
to invisible i n Q dot com.

Speaker 7 (01:48:15):
Uh.

Speaker 1 (01:48:16):
You also have a TikTok as well as a Twitter
handle now which is invisible underscore i n Q. Make
sure you guys follow Drew, send him an email, let
them know what you think and if you want to
learn how to use these tools, you can do that
right there. Thank you guys. This is done by Junior
and Chris, don T Harris, me uh signing out with
our guests Drew Arnold. Thank you guys for tuning in

(01:48:37):
and we'll see you guys Monday on the Rundown Live.

Speaker 4 (01:48:40):
Thank you on the ground.

Speaker 2 (01:48:47):
Channeally Gus you listening so will destroy this choke me Chris,
Dante Harris, and John Virginia on the Rundown I run down,
feed your brain.

Speaker 4 (01:48:59):
I'm very The idea is your forecast into the future.