Latest / Military Broadcast Radio | MBR Talk / TWOCPT Ep. 88 | What Is Consciousness? Part 5: AI — Intelligence Without a Soul?

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TWOCPT Ep. 88 | What Is Consciousness? Part 5: AI — Intelligence Without a Soul? · Military Broadcast Radio | MBR Talk

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2:18
Good morning, good morning, good morning.
2:20
Welcome to the world of conscious positive thinking
2:22
right here on military broadcast radio where veterans always get
2:26
to have a voice. Today we are wrapping, not
2:29
wrapping up. I wish.
2:30
Nope. It's #5 part five of our six
2:35
series of what is consciousness? And today, well, part 5 is AI
2:42
intelligence without a soul. That's a question and I got to
2:47
tell you folks, I went down a rabbit hole here.
2:50
Six months worth of it and the last two weeks has been very
2:53
trying. So I know if you've listened to
2:57
the news, there's a lot of controversy right now with the
2:59
AI intelligence. I heard it last night.
3:02
It was funny that I I was sitting there reading it.
3:05
I'm not so sure all of us are aware of what is happening with
3:11
this artificial intelligence. So today what I would love to do
3:16
is I gotta get you guys on Tiktok here.
3:18
Hold on. Let me let me add you and repost
3:22
you to my story. OK, now we're on Tiktok with
3:26
with my friend Jewel, who is in the background today.
3:30
OK, so there's a little bit of things that were disturbing to
3:35
me. And so it's not going to be a
3:36
normal show and it's going to be a very long show.
3:40
And I there's no way that I could put over 1000 pages of
3:43
investigation of six months in two hours.
3:46
So I apologize if this is going over.
3:48
I like I tell my family, pause it.
3:50
You come back to us a good thing about podcast not on live TV
3:54
where you know you can't get back.
3:56
And these are podcasts. You can come back.
3:58
So if it does get long for anybody, please know that you
4:02
can just always go back and you're not going to hurt my
4:03
feelings whatsoever. So because I know it's long, you
4:07
know, we all know it's long and there's like a gun.
4:09
Nothing I can do anyway, let's move it because like I said, it
4:12
is and I already wasted 4 minutes.
4:14
So let's get into our Angel number before we do anything.
4:18
Today is September the 14th, 2026.
4:21
That means our Angel number is 091426.
4:26
It all equals a four. I love it when I see fours.
4:29
Fours. The angels are confirming that
4:31
they are near you and want you to know that they are all ready
4:34
to assist you to make your dreams come true.
4:37
Know that the angels always hear your thoughts and prayers.
4:41
They are surrounding you with love every day and that Angel
4:44
power is still self esteem. Man, maybe I'd go see what
4:49
that's about, right? Your Angel numbers today also
4:54
contain the number 91. The angels are here to boost
4:57
yourself esteem. They want you to go gently on
5:01
yourself and allow yourself to learn from mistakes.
5:06
They see your inner glow and your magnificence.
5:08
And you are here to help boost your confidence.
5:11
They are also standing close to you, protecting you from anyone
5:15
who tries to dim your beautiful light.
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Angel number contains the number 26.
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That's our year. The angels know that you feel
5:22
empowered when you feel compassion for others.
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Now ask that you feel the same compassion for yourself.
5:29
It is very important that you say no to the request that make
5:31
you feel uneasy. Trust these sensations in your
5:33
body and these are in your inner compass.
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The Angel number today contains #42 It's the romance Angel Woop
5:40
woop and they are all around you at the moment.
5:43
They have heard your prayers associated with love and they
5:46
are working behind the scenes to bring you that perfect love or
5:49
to enhance the relationship that you are currently in.
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Number also contains #14 today. Slow and steady wins the race,
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my friends. The angels request that you put
5:59
your hopes and dreams down on paper and then place them on
6:02
your Angel altar for transportation.
6:05
Continue to move forward every day, even if it's the only
6:09
bitty, bitty steps that you can make.
6:11
The energy of motion acts as a catalyst that magnetizes your
6:15
ability to create positive change in your life.
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Thank you, angels. Thank you so much.
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OK, so where are we now? Let's get back to business,
6:27
right? And got to go back to business.
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Good morning, Miss Janet. Good morning.
6:33
So take a big deep breath folks on this one.
6:38
So artificial intelligence AI, it is something I do use.
6:46
It is something that I have been using now that I've I've found
6:49
out about it and I've been using it probably now since the 1980s.
6:54
And so have all of you without even being aware that you are
6:58
being used. You're welcome.
7:02
So I understand people love it, people hate it.
7:05
And sometimes that that that can help tremendously for some
7:09
people who have handicaps. So, and something that made me
7:14
question the machine while I was using the machine to investigate
7:19
the machine, what exactly? Exactly.
7:25
And then this girl, the why girl, here we go.
7:28
Well, who created it? Who trained it, Who fund it, Who
7:32
establishes its boundaries? Who determines what is a good
7:34
answer and who deserves what's a bad answer and who defines
7:37
biisms and who determines what information reaches man's eyes
7:42
and ears? And every Rd.
7:45
I followed eventually brought me to the same character.
7:48
Guess who that character was, folks.
7:50
Come on. Guess man.
7:54
All of us, man. So today I'm going straight back
7:59
to zero. You know what that means?
8:00
Right? Back to zero.
8:02
And folks, when I say man, it's not physical male energy.
8:05
Man means human. So if you're new, you need to
8:09
know when I say man, that means humanity.
8:12
All of us. So going back to zero.
8:15
And I'm gonna give you some dates.
8:16
I'm gonna give you people, I'm gonna give you money.
8:18
I'm gonna give you government records.
8:20
I'm gonna give you political relationships, technology, my
8:24
experience, my opinions, and then I'm going to show you when
8:29
something is documented. And that's what I'm going to
8:32
give you when it's my experience.
8:34
I'm going to tell you in my experience.
8:36
And if it's my interpretation, I'm going to tell you this is my
8:40
interpretation. You decide what it is that you
8:43
see. Folks, I'm not going to lie,
8:44
this is disturbing. It disturbed me and I really was
8:52
not going in this direction, but it led me in this direction.
8:56
So I always feel if somebody is opening up a door and keeps
8:59
pushing me in this direction, then it's maybe something I need
9:02
to say. So here we go.
9:05
Ready. That's my table.
9:06
I'm going to pull up a lot and I'm going to put pins and apples
9:09
all over the place and I'm going to need your help.
9:11
So here we go. I need to leave something first
9:15
on this table before we move. I forgot about it.
9:17
I didn't really forget. I had it in my notes here in
9:20
2022. I had a download.
9:21
I was sitting at a table with Master Kim and Master Diana.
9:25
We were discussing the energetic shifts of the world.
9:28
We were discussing consciousness in a new realm.
9:33
We were discussing the talk of the higher chakra centers that
9:37
were being formed and that how that shift was going to affect
9:41
man. While I was we were talking
9:44
about this, a huge download started to press upon the top of
9:47
my head, pouring right out of my mouth.
9:49
Now, anybody who knows me, I either grab my phone because
9:51
it's a download and most of the time I can't remember it, or I
9:55
have witnesses and I look at them and they know to remember
9:58
it. That's what happened on this
10:00
day. I didn't ask for it.
10:02
I wasn't searching for artificial intelligence in 2022.
10:05
Trust me, I had other things going on.
10:07
I saw the evolution of man. I saw technology, programming,
10:12
perceptions, confusion, chaos, and I remember looking at my
10:16
masters going, they're telling me warning, it's like a heads
10:19
up, it's a warning. This is a heads up and they're
10:22
it's a warning. And I couldn't say enough.
10:27
My masters, though, calmly as they always are, they're like,
10:31
OK, well then we'll just take it when it gets here and we'll take
10:34
it as it is. So I'm going to stop there with
10:36
that download, but I need you to make you know that.
10:39
So I just don't all of a sudden fill in something you're like,
10:41
where'd that come from? So I'm going to stop there with
10:43
that so and not give it all away because what we're going to go
10:47
through today actually really touches a lot of it.
10:49
So while I was researching this episode, it kept coming back to
10:54
the table. So right now we're going to pin
10:56
it on the table and say, Yep, M JS download that had images of
11:00
man and AI. Now let's go back to 0.
11:04
Let's figure out where this AI machinery came from back to
11:10
1950, folks. That's where we have to start.
11:13
Alan Turing and Alan Turing created something called
11:17
computing machinery and intelligence.
11:20
His question was, can machines think?
11:23
Turing proposed what became known as The Imitation Game.
11:30
Notice where this begins with us right this with this question
11:34
about whether machine behavior could resemble human
11:39
intelligence. Now that let that takes us to
11:42
1956. Six years later in Dartmouth,
11:46
the Dartmouth summer research Project on artificial
11:48
intelligence. John McCarthy and one
11:52
researchers proposed that aspects of learning and
11:56
intelligence might be described precisely enough that a machine
12:01
could simulate them or put a pin in that word, simulate them, put
12:09
a pin in that word, put it on the table.
12:12
Let's keep moving. 1958 through the 1960s ARPA is created after
12:20
Sputnik. Later it becomes DARPA.
12:23
DARPA which means the Defense Advanced Research Projects
12:29
Agency. By 1960s, government funded
12:32
research was helping develop artificial intelligence with
12:36
computing, with language processing and human computer
12:41
interaction. AI wasn't born in Silicon Valley
12:46
just last week. I'm just going to put that out
12:49
there. the United States government and military, we're
12:52
not part, I'm sorry, we're part of the story in a very early
12:58
age. By the 1970's, the Navy was
13:01
exploring natural language systems that allowed humans to
13:07
communicate with database more naturally.
13:11
The computer increasingly wasn't simply storing information, it
13:18
was literally helping man find and interpret information.
13:26
That's in a very important transition in AI right there
13:32
now. Right now we need to go to our
13:35
first break because it's going to be long.
13:39
I'm going to do some quick breaks here in between.
13:41
When we come back, we're going to go straight into the 1980s.
13:44
We're going to go straight into military artificial
13:46
intelligence, and then we're going to follow the machine
13:50
decade by decade, straight through 2026.
13:54
Stay with me. It's going to get real
13:56
interesting, folks, Real interesting.
13:58
I promise we'll be right back. Every set back is just a set up
14:04
for a comeback. Keep quacking forward. 90% of
14:07
what we worry about in future never happens.
14:10
Whenever things get rough or it feels like you're at the edge,
14:14
remember this. Storms pass.
14:18
Tough times don't last, but tough people do.
14:32
The station where our veterans voices are heard.
14:36
MBR talk. Hey, thanks for supporting our
14:39
channel by watching and listening.
14:49
Oh, there is just something about that little duck.
14:52
Welcome back to military broadcast radio.
14:53
I am MJ. My show here is the world of
14:56
conscious positive thinking, and we are going back to zero with
15:00
artificial intelligence. We started in the 1950s, and now
15:04
we're in the 1980s. Let's go.
15:07
So in 1981, the Naval Research Laboratory established that the
15:12
Center for Applied Research and Artificial Intelligence.
15:17
During this decade, the Navy worked with robotics, expert
15:22
systems, natural language systems, and intelligent
15:26
decision supports. The Air Force was also
15:30
developing knowledge based and expert systems.
15:34
Think about what an expert system means.
15:39
Man has the expertise. Man decides what knowledge
15:47
matters, and man translates that experience into something the
15:53
computer can use. Then another man receives
15:58
information from that computer. So what we now have in 1980 was
16:04
man inputting into a machine and that machine spits out to
16:10
another man who was working who is searching for that
16:13
information. OK.
16:16
By 1989, Navy funded work was combining neural networks and
16:23
expert systems to help process tactical information from
16:27
multiple sensories, correlate information, and prioritize the
16:33
potential threats. The machine could help us
16:37
determine what information deserved its attentions first by
16:43
prioritizing. There's an early information
16:47
governor system right there. Now, what do I mean by a
16:50
governor system? If anybody knows anything about
16:53
engines, there is a little switch called a governor switch
16:56
that you can stick on an engine and it regulates and it does not
17:00
allow anybody to go over certain functions.
17:04
So with that being said, they now have applied what I dub as
17:10
the governor switch to computers.
17:14
And this period matters very personally to me.
17:18
I had my own experiences with classified information during
17:21
this time and it taught me something really simple that the
17:26
public can access is not automatically everything that
17:32
exists. I'm going to say it again, what
17:34
the public can access is not automatically everything that
17:39
exists. My experience can tell me,
17:44
though, where I want to look, and the public records determine
17:50
what I could substantiate publicly.
17:53
Now let's move to the 1990s. Now the machine learning becomes
17:59
increasingly important. Instead of man manually writing
18:03
every rule, systems increasingly learn statistical patterns from
18:11
data. Computing power grows, databases
18:17
grow, the Internet grows. Information itself becomes
18:22
enormous. The machine isn't simply being
18:26
told do this, increasingly it is being trained through examples
18:33
and data to recognize patterns. Where did we hear that word
18:38
before folks? Patterns, right?
18:44
So 2000 through 2007. Now here we go.
18:50
Now ban brings the computer into their home.
18:54
Internet starts to do searches, People start Googling.
19:00
People have umpteen, they have safaris, they have all these
19:03
other different modalities that they can use on a computer to
19:07
search on any Internet search that they want.
19:11
There was quite a few of them. Now with the computer in your
19:15
house, you have online news. People have their own personal
19:20
computers in 2002. Now we have Google News 2003.
19:27
Now we have Safari 2006. Facebook news feeds, folks, that
19:33
wasn't that long ago. That's 20 years ago.
19:37
It's not long, considering how long man's been on this earth.
19:41
Now the machine isn't only waiting for man to ask a
19:44
question. Technology increasingly helps
19:48
determine what will appear, how it will be ranked, what gets
19:54
recommended, what does not allow it to do, and eventually what
20:02
gets personalized. Many of us still carried an old
20:07
belief system in us back from the Walter concrete days.
20:11
If it's black and white, it's the truth.
20:16
It was a time for a lot of us who are older than 40 or 45
20:21
years old. Remember that we could trust
20:26
what was written in media. We could trust what was written
20:30
in our paper and in our nightly news with Walter Cronkite.
20:35
If it was printed, broadcast or reported, man often assumed
20:40
somebody had already did the checks on it and it was by
20:44
Federal that it was fine to be put out to public.
20:49
That was the old paradigm in which a lot of people lived.
20:55
The Internet changed who could publish.
20:59
Algorithms changed who and what was appearing, and social media.
21:08
Social media changed how quickly that information could spread
21:11
around the world and how defamation could really hurt
21:14
people. And now we move toward editor,
21:19
which was governed, and then we move into algorithms, which was
21:23
governed. Governed means the governor
21:27
switch. OK, we're going to move to 2008,
21:34
the presidential election. Pew Research, one of the top
21:39
researchers that we have. Pew found 55% of voting age
21:45
adults and 74% of Internet users use the Internet for political
21:54
biased purpose. During that election cycle,
21:59
Obama supporters were particularly active online in
22:03
several forms of political participation.
22:06
Campaigns had learned something. The Internet wasn't simply
22:11
somewhere to post information. It could organize your people.
22:17
It could. Where's that word?
22:19
Brainwash your people? Right, because people love
22:22
saying the military can brainwash.
22:23
So there it is. They could also raise money,
22:27
send messages, target communication, and mobilize
22:29
voters and technology companies. Employees were politically
22:34
contributing as well. So imagine having employees
22:40
inside of a business monitoring people and everything that they
22:46
wrote on Facebook or Twitter to be removed to be substantiated
22:52
or to if it's good or if it's not good.
22:57
Now, so throughout that show, I need to keep the apples
23:00
separated and we're going to keep the apples separated by
23:03
what? Corporate money, pack money,
23:07
executive money, employee money, investment money.
23:11
Those are not the same thing folks at all.
23:16
Because if one crosses another, it's not good for that party.
23:22
So I'm going to label them just like that, and we're going to
23:26
put the apples where they are and if that cart falls over,
23:31
that's on them, not on me. I'm just giving you the
23:34
investigative work. So let's go around this period.
23:39
There was something called Cha Cha, you know that Cha Cha
23:44
242242, My nieces and nephews out of New Jersey brought this
23:49
information to me in Florida to my children.
23:53
We had no idea. We didn't know it existed.
23:56
However, we thought it was fun and we could ask it anything.
24:00
And I remember the fun that we were having just throwing silly
24:04
stuff out there, not really reclaiming or not really doing
24:10
anything. Besides, how cool is this,
24:12
however, that Cha Cha allowed man to text a question and
24:18
receive an answer researched by another human, not by a machine,
24:26
by another human. So all of you, cha Chas, back
24:31
way long time ago, when you were actually texting, it wasn't the
24:35
machine. You were texting a human.
24:38
Isn't that funny? A human database center.
24:43
Think about that progression, cha Chas.
24:47
Human asks the machine, which was your cell phone because you
24:50
text it. The machine routes the question
24:56
to a human. Well, that human responds with
25:01
then the answer. So our search was human asks,
25:09
algorithm retrieves and ranks. Human gets chooses.
25:13
Human gets his choices and generative AI eventually becomes
25:19
human as model synthesizations. Human receives an answer, and
25:30
then smartphones increasingly combined communication, camera,
25:35
Internet, location, navigation, contacts, searches, purchases,
25:44
and personal behavior. The computer isn't sitting at
25:49
the desk anymore, folks. Man's carrying it right here in
25:54
their hot little hand, everywhere.
25:56
Everything they say, everything they do, everything they mark,
26:00
it's all right here in your hot little hand.
26:03
And when everybody wanted a cell phone, you signed a contract
26:07
with AT&T, Verizon, Metro, whatever it was, BlackBerry,
26:15
whatever that smartphone was, you signed on the dotted line
26:20
that your information would be used for AI purposes.
26:26
Tell me you didn't. I can't you.
26:28
Yeah, you did. You just didn't read the small
26:30
print on the 46 or 50 something pages.
26:33
It's right there. So we, since smartphones
26:38
developed, have been supplying AI all of its information and
26:44
all of its data. Aren't we lucky?
26:47
Now? Let's move on to 2012.
26:51
Major advances in deep neural networks produce a leap in
26:57
computer vision. The Obama administration also
27:00
launches a federal big data research and development
27:05
initiative. Government agencies are
27:08
investing in ways to collect, to organize and analyze enormous
27:13
amounts of personal data. In 2012, another presidential
27:22
election was about to happen. Employees associated with the
27:27
major technologies of Facebook, Twitter, and I'm going to keep
27:31
going LinkedIn. A lot of them, including
27:36
Microsoft and Google, were substantially sourced of
27:39
individual political bias contributions to President
27:43
Obama's campaign. So guess what happens to your
27:47
news feeds? Guess what gets twisted?
27:49
Guess what gets twisted on Microsoft and Google and
27:52
everywhere else that you are now using as your news media?
28:00
You feeling blinded by the light yet?
28:03
Let's keep going. Again, employees.
28:12
Not a Microsoft corporate check. Employees not a Google corporate
28:18
check man working at those companies giving political
28:24
money, technologies, databases, government election money.
28:35
Again, same here. I'm putting them all on the
28:40
timeline. You decide what you see.
28:43
Now comes 2013. Deep learning continues
28:48
demonstrating that machines can learn increasingly complex
28:54
patterns. 2014 Major improvements in the machine
29:03
translation has now happened. They started having higher
29:08
stimulating machines. Machines are now getting better
29:15
at processing with man's language, not simply numbers.
29:23
Language, the thing man uses to communicate.
29:29
Started thinking. Imagine that machine that starts
29:35
to think. Folks, I got to take another
29:37
break. We're going to take our second
29:41
break. We're at 2014.
29:44
When we return open, AI is going to be born.
29:49
Then another presidential election.
29:52
Then the question of control begins moving right inside the
29:56
AI companies themself. Stay with me.
29:59
You're listening to military broadcast radio.
30:02
My name is MJ. My show here is the world of
30:04
conscious positive thinking. And today we are on our part 5
30:08
of What is consciousness series AI intelligence with a soul.
30:13
Well, that's for you to figure out.
30:14
That's not for me. I have my opinions and we're
30:17
going to keep going. So let's go down and we're going
30:21
to do a song this time, and we're going to do my boy, Mr.
30:27
Puffy Anderson, the best patriotic song.
30:30
Mr. Red, White and Blue. Here we go.
33:59
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34:17
Hello, welcome, welcome, welcome back.
34:20
So I have, I am sitting here looking at my notes going
34:24
forward and you're going to I, I'm baffled.
34:29
I I am baffled yet again with my bot, my AI.
34:38
This is I'm going to. So folks, it took me two weeks
34:43
to try to put an outline together that AI that I was
34:49
using for my flow and my producing.
34:54
So I'm going to give you a little idea, and I know I'm
34:56
going to mention this later, but I just realized what they did
34:59
again to me, I was putting the show together and I spent months
35:04
with what I named and dubbed Vinny Barbarino.
35:07
He's the classroom teacher. And every time I have a thought,
35:11
Vinny, he goes and he finds it right?
35:15
And then I'm like, Nope, there's something I remember bigger than
35:18
that. Go find this.
35:19
Go look here, go look here. This man, Vinny man, this bot
35:26
help me get any material that I needed that he could grab.
35:33
When I kept questioning him on certain things from my past
35:37
military, he kept telling me they didn't exist.
35:41
Doesn't exist. Now I understand because I
35:45
already told you being with classified information, just
35:47
because you know something doesn't mean it's going to
35:49
exist. It it it's substantiated.
35:52
However, it has now been 40 years that should has.
35:57
It doesn't make sense why some of the information that I knew
36:02
is still not there. It has to be.
36:04
But then I was like, it doesn't really have to be.
36:06
I mean, JFK files were just unredacted.
36:10
So I was going through this and every single time that it was
36:16
cut for the show with my with my formats and my outlines, it kept
36:22
missing stuff. He just missed.
36:26
He didn't. I can't blame an AI system when
36:32
it has governor's systems on it. And this is what I'm talking
36:37
about. My notes tell me that I'm at
36:40
958. I'm only at 9:36.
36:44
Every single flow that I have ever helped with from the
36:48
producer, I have been dead on the money on my times.
36:53
He says I'm way over. We had to keep cutting.
36:57
I'm at according to my notes, I'm supposed to be at 958 coming
37:01
back from my break. It's not even close.
37:04
Which means what did he cut? And I'm looking at it going,
37:06
wait a minute, we're at 2014. What happened to the 1990s and
37:13
the Clintons? What happened to Ronald Reagan's
37:15
information? What happened to all that damn
37:17
information yet again? Now, because the it's just a
37:21
long story, I want to keep going and hopefully when I get down,
37:24
I'm going to keep talking. But I just want you to know
37:26
there was a lot of AI stuff that was happening in the 80s and the
37:31
90s and they removed it from my script yet again.
37:36
Isn't that funny? Now this is where if man is
37:39
supposed to be smarter than the machine, I needed to write it
37:43
all down and just do my own thing.
37:44
And I didn't. And this is, this is going to be
37:47
my problem now. But it's OK.
37:49
We're going to keep moving and I'm going to, I'll, I'll come
37:51
back to it. So here we are, 2014 when we
38:01
return. That was where we were born
38:04
December 2015 Open AI publicly announced as a nonprofit
38:12
artificial intelligence research organization and the Co chairs
38:16
just happened to be Sam Altman, Elon Musk and Greg Brockman is
38:22
the CTO. Financial supporters named at
38:28
the beginning included Sam Alton, Greg Brockman, Elon Musk,
38:33
Reed Hoffman, Jessica Livingston, Peter Thiel, Amazon
38:37
Web Services, Infosystems, YC Research and collectively they
38:44
had put in $1 billion of commitment.
38:51
Open AI said it expected to spend only a very small fraction
38:56
during the early years and listen to the original
39:00
philosophy. Open AI described AI as
39:05
something that ideally would become an extension of
39:08
individual human wills. Did you hear what I just said?
39:13
Human wills. There's man again.
39:20
There's man again. Trying to overtake man in 2016.
39:27
Speech synthesized in advancing AI is becoming increasingly
39:32
capable of generating something recognizably human, which was
39:39
the voice. The Obama White House released
39:43
major reports on artificial insemination, including
39:47
preparing for the future of artificial intelligence and a
39:52
national AI research and development strategy.
39:55
And at that same time, another presidential election was
40:00
happening. That was the election between
40:03
Hillary Clinton and Donald Trump.
40:06
Social media is deeply embedded in political communications.
40:11
So embedded. There was nothing checking any
40:16
of the accuracies or anything that came out of the Obama
40:20
administration. There was nothing.
40:23
Microsoft Political Action Committee is active majorly
40:29
during 2015 to the 2016 cycle. Microsoft is what's responsible
40:36
for putting information in front of the viewer, in front of their
40:39
phone or computer. If you don't know that Microsoft
40:43
records show political contributions across both
40:47
parties at the employee level, technology sector, political
40:55
giving looked a little different from the company's PAC giving.
40:59
Now that's why I'm not saying that Microsoft is Democrat or
41:05
Microsoft is Republic. I'm asking where did man's money
41:10
go? Employees are man.
41:15
Executives are man. PAC committees are run by man.
41:19
Candidates are man and machines are being trained by men.
41:25
So it didn't matter what you thought.
41:28
These people here were controlling your thoughts, they
41:32
were controlling issues. Because when we use something
41:37
and it is consistent in front of us.
41:39
We learned that in Part 2 with psychology and teaching.
41:44
Right, 2 forms that mentally arrange are young man's
41:51
thoughts. Yeah.
41:55
And now it is in Google and it is in Microsoft.
41:59
It is like the 1950s with the movie projectors, the black and
42:04
white movie projectors and flashing a popcorn or a hot dog
42:09
to make you have subliminal impact.
42:12
This is exactly what was happening in our homes and in
42:15
our phones and everywhere we would use computers.
42:20
After the 2016 election, questions exploded around
42:28
foreign influence, social media algorithms, our AI bots, our
42:35
machines, fake accounts throughout everywhere, every
42:42
social media were fake accounts, missed information that was
42:46
allowed to be produced, platform power and political biisms.
42:53
That road is going somewhere, and if you're not sick to your
42:57
stomach now for the unjust of man, let's keep going.
43:03
By 2017, Open A IS leadership concludes that increasingly
43:09
advanced AI would require billions of dollars in computing
43:15
resources. Discussions begin about moving
43:19
beyond the original non profit only structure and there is a
43:25
control dispute. Open AI's later publication of
43:31
Contemporary Communications says that Elon Musk proposed a for
43:37
profit structure in which he would have majority equity,
43:42
initial board control and the CEO position.
43:49
Other Open AI leaders rejected all of those terms.
43:54
Open A is published account says they feared unilateral control
44:00
over artificial general intelligence.
44:02
Now think about what they feared with Elon Musk.
44:07
They are controlling the elections.
44:09
They are controlling the people's minds.
44:10
They are controlling how we think, how we walk, how we talk,
44:15
how we unilaterally believe down to our Department of Defense.
44:23
And now these open AI leaders don't want Elon Musk to have
44:31
total control even though he had the money that they needed.
44:39
Think about it. So the wire me so who controls
44:46
AI? Who's been controlling AI?
44:50
And then we are asking it inside of open AI in 2017.
44:55
Meanwhile, all meanwhile, our beautiful Congress is asking
45:00
questions about another information technology called
45:03
social media. So now social media on November
45:10
1st, 2017, the Senate Intelligence Committee, the
45:14
social media influence in the 2016 presidential US elections.
45:21
Now it's being investigated. It's not only being investigated
45:25
for that 2016, it starts to go back from Facebook, Twitter,
45:31
Google, Russian backed accounts, bots, AIS, machines, paid
45:36
advertising, falsified information and divisional
45:41
material. Who and what was trying to
45:48
divide our country. It was at this point I kept
45:53
asking AI about George Soros, though it couldn't give me a
46:00
direct, and it gave me spider web links back into funding
46:05
through Soros. It not took it out on this one.
46:11
It took it out again and again and again and again and again.
46:16
Why do you think my chat GTPAI kept taking that out?
46:21
Why do you think it kept taking my Clintons out?
46:23
Why do you think it took Ronald Reagan out?
46:27
Why? Why this is the has to be the
46:32
the 15th cut of the show and yet it's taken out.
46:35
And I forewarned you could take it out, but I still have the
46:38
knowledge. I did the work.
46:40
I have six months of long investigation work at nights on
46:44
my phones, on my computer. I have done so much
46:46
investigation. In fact, I told Amber Dietz, who
46:49
loves these types of things. I have a shit ton of stuff for
46:52
you, a lot of rabbit holes that I don't feel like going down
46:54
because it will just make me sick and I know it's going to
46:57
make me sick so I don't want to do it.
46:59
Good morning, Jonathan, welcome. However, if there is anybody who
47:04
wants all this instigations or this investigation work, I'll be
47:08
glad to hand it over to you because it's really an unjust
47:13
what has happened since 1950. Hopefully our government has
47:16
finally put controls on this, but I just want you to know that
47:22
some of this material I was in my investigation that
47:26
erroneously, I don't know how many times has now been removed
47:29
yet again. Anyway, that's a lesson for me
47:33
in the future, right? I don't need to use AI when I'm
47:37
studying AI. That's kind of funny if you
47:43
think about it. Anyway, so Facebook in the
47:48
courts now. These are from the court records
47:51
reported 80,000 organic posts from Russian backed pages, with
48:00
an estimated exposure reaching as many as 126 million people.
48:06
Derogatory with the Russian hoax technology was now part of a
48:13
congressional investigation into that information was reaching
48:22
man back to man. Can't blame a computer has no
48:26
brain. You can't blame a computer.
48:28
It has no consciousness and you can't blame a computer.
48:31
It doesn't have a soul. Man is responsible for this and
48:36
man is assisting that man to hurt us, to divide us.
48:43
But man doesn't see it because man's so divided, because of all
48:48
of the shit that has happened inside of our homes, inside of
48:52
our computers, inside of our streamings, inside of our apps
48:56
and our phones since 2006. The awareness is mind boggling
49:04
that man could be so divisive, so divided and so just biased
49:14
and then claim that the other man is biased when the intention
49:20
was behind your screen the whole time.
49:23
It it really made me sick, I'm not going to lie.
49:26
Now I'm going to jump to January of 2018.
49:32
According to Open, A is subsequently published account,
49:36
Musk proposes merging Open AI into Tesla after disagreeing
49:44
after the disagreement over control and financing.
49:50
And yet Open AI decides to turn him down again.
49:55
So February of 2018, Elon Musk resigns as Open AI Co chair and
50:01
has nothing nice to say. By April of 2018, Mark
50:06
Zuckerberg appears in front of Congress, the courts with data
50:12
privacies, Cambridge Analytica. Algorithms, political biisms and
50:19
Senator Ted Cruz asked Zuckerberg about alleged
50:22
suppression of conservative content.
50:26
Zuckerberg acknowledges Silicon Valley is an extremely
50:31
left-leaning place and says that Facebook attempts to prevent
50:39
employees political views from producing biisms in the
50:43
platform. However, even though he knows it
50:47
was happening, it was too late. The following day, the House
50:53
questioning continues. September of 2018, Facebook's
50:59
Sheryl Sandberg and Twitter's Jack Dorsey appear before the
51:04
Senate Intelligence Committee. Foreign influence platform
51:08
responsibility. And look at the progression,
51:11
folks. Look at it information then went
51:16
into man's algorithms of the information and then from there
51:22
to political questioning by man for its algorithms.
51:28
Then in to Congress. What the F 2019 Open AI creates
51:43
a for profit subsidiary under profit control.
51:49
You'll like this one. Then Microsoft invests $1
51:53
billion into Open AI. Elon Musk couldn't but Open AI.
51:59
Here you go, Microsoft. Microsoft becomes Open AI's
52:03
exclusive cloud provider, and the companies announced plans to
52:10
build Azure AI supercomputing technologies together.
52:15
Notice 2019 when they did this? Notice that date, 2019?
52:21
What was coming? Anybody want to take a wild
52:24
guess what was coming up? Got it.
52:28
The presidential election again. Now this $1 billion.
52:37
That doesn't tell me how a particular AI was answered.
52:42
I have to say that out loud. It tells me who has become
52:48
financially important to the organization. 2019 Here comes
52:56
2020 Presidential election. Technology platforms are deeply
53:02
embedded in political jargon and communication.
53:08
November 17th, 2020 United States Senate Judiciary
53:13
Committee Zuckerberg, Dorsey and the hearing is called Breaking
53:19
the news censorship suppression and the 2020 election.
53:24
Now what do you think that court was about folks, with the $1
53:28
billion in 2019, Congress is formally questioning moderation
53:37
decisions and distribution of political information.
53:42
Meanwhile, all Meanwhile, Mr. Sam Altman is personally
53:47
contributing on the outside of anything on Open AI or Microsoft
53:53
or anything else. Mr. Altman then, among
53:55
documented contributions in this period out of his own pocket,
54:00
$100,000 to the Biden Victory Fund, $100,000 to the American
54:05
Bridge, $100,000 to the Senate Majority PAC, and more personal
54:13
political contributions. Notice not open AI corporate
54:21
donations is what I am being told by AI needs to tell they're
54:26
not they're not open to AI corporate donations.
54:28
They're they're personal and I would laugh at AI and I said
54:36
really I go. So let's just say that Sam
54:39
Moulton put the money in. They said exactly personal
54:42
funding. OK, AI let's go 2020 here we go.
54:50
And we look at it now we're pissed.
54:53
And now I'm going to tell you, folks, look at the time, 954.
54:59
Do you know how much things that I've missed?
55:02
Because according to my clock that my beautiful bot didn't
55:06
change, I'm supposed to be at 10:40 AM.
55:10
So I'm already out an hour's worth of my work that they gave
55:14
me this morning. Yeah, see where I'm going with
55:19
this. Now we're going to take another
55:22
break because when we come back, I'm going to while you're on
55:24
break, I'm going to see if I can't find some of these notes.
55:27
Microsoft gets investigated again, so does Google, and
55:32
humans start directly shaping AI responses through human
55:37
feedback. Now here we go because chat GTP
55:42
launches and then the money gets much larger, the government gets
55:48
much closer. How could they even stick
55:54
around? Find out it's going to make your
55:56
guts curl. Hold on.
55:59
Let's go to my other. Let's go to.
56:02
Can't spell here without her coffee, Anderson.
59:13
It my show is almost an hour behind course and I, I'm I'm
59:21
flabbergasted because I already told him that every single one
59:25
of my notes were already copied. And yet this is what they did.
59:29
So let me read something to you. So when I went and researched, I
59:35
said imagine what the 12 the 2012 election look at the
59:39
democratic contributions to AI and I got responded back, which
59:44
is not in my notes. Now in my layout, even though I
59:47
wanted it says yes, between 2012 and 2016 needs examination in
59:52
the timeline. I found something significant
59:55
for 2012. I also checked must because the
59:57
exact reason of his departure. So in 2012, the presidential
1:00:02
race employees identified with Microsoft and Google were among
1:00:06
Barack Obama's leading source of individual contributions by
1:00:09
employer Contemporary. Open Secret based reporting
1:00:15
placed the University of California employees first and
1:00:18
foremost and and contributing to Microsoft employees 2nd and
1:00:24
Google employees third among Obama's employer association
1:00:30
donor totals. Those were donations from
1:00:32
individuals associated with those employers, not corporate
1:00:36
Microsoft or Google checks to Obama's campaign.
1:00:39
Give me an effing break. Give me a big effing break.
1:00:47
And this occurs during the same administration in which the
1:00:50
federal government was expanding big data research.
1:00:54
Remember that big large whopping money?
1:00:57
Uh huh. That gives us a legitimate
1:01:00
chronological sequence of investigation by 2012 AI machine
1:01:05
learning advances with federal big data initiatives and
1:01:10
presidential election and substantial political giving
1:01:13
from employees of major technology companies.
1:01:17
We don't need this is what AI told me.
1:01:20
We don't need to tell the audience what that that
1:01:22
combination means. I'm reading it word for word mm
1:01:30
hmm in 2016 yeah we need that same it this needs a deeper
1:01:35
contribution pull because I don't want to repeat the
1:01:38
mistakes of using a broad tech support Clinton statement
1:01:42
without separating. Well, what happened to my
1:01:44
Clinton statements back when Mr. Mr. Clinton and misses Clinton
1:01:49
What what happened to those in my in my you see what's
1:01:52
happening here People who use AI.
1:01:55
This is your awareness. I wanted it just like this
1:01:58
because I knew how many times I asked for final studio cut final
1:02:03
studio cut with my times. Everything came back wrong time
1:02:07
after time They completely took this whole section out this
1:02:10
whole damn thing. The Federal Elections Commission
1:02:15
confirms Microsoft Pack was active during 2015 16 electional
1:02:21
cycle, raising about 2.2 million and receiving roughly 2.125
1:02:29
million in contributions. Microsoft itself maintains
1:02:33
historical political contributions records going all
1:02:35
the way back to 2012, thirteen, 1415 and 16, which gives us a
1:02:42
much better trail than relying on somebody's awesome news
1:02:46
summary. All right, this is the kind of
1:02:54
stuff that I'm talking about. Is governor switched?
1:02:58
Can you do the research? Yes, but when you're going to
1:03:01
start to write a book or you're going to tell them that you're
1:03:03
on a podcast, a seminar, a speech, or anything else, they
1:03:07
control your narrative. There's Governor switches
1:03:10
controlling the narrative. Now I'm going to go back to my
1:03:14
layout here coming out of my commercial at what's supposed to
1:03:19
be 1040, right? So micro in 2021, see how it
1:03:24
jumped to 2021. I still literally have 2017,
1:03:28
right? The initial board control and
1:03:30
the CEO positions open AI says that other founders rejected all
1:03:34
those terms and feared that one individual containing absolute
1:03:38
controlled like must over AGI was not appropriate.
1:03:41
No, not appropriate. Not when your whole board is
1:03:45
democratic and correcting the narratives with governor
1:03:48
switches on algorithms. Damn it, I it makes me sick to
1:03:57
my stomach to know that, you know, my whole life I've always
1:04:05
had very strong free will My whole life.
1:04:08
I've always, I've heard authoritative figures, but I've
1:04:11
always asked the wise. I've always pushed them.
1:04:14
I've always questioned beyond the boundaries, and the minute
1:04:19
that I heard there was something inside of me, even as a little
1:04:22
little girl, when somebody tells me that I can't or somebody says
1:04:26
that's the way it is, it pissed me off.
1:04:29
Look at I'm still angry today. I got to fix this because no man
1:04:36
has any right anywhere to tell me how to think, to tell me how
1:04:42
to experience my life and to tell me how to move forward,
1:04:46
period. And no man has the right
1:04:51
teachers, philosophers, psychologists, government,
1:04:56
nobody has the right to tell me or my brain what is right and
1:05:03
what is wrong. And subliminal consistency
1:05:06
patterns should be outlawed all together.
1:05:11
Period. You people who don't understand
1:05:19
what is happening behind the scenes, we need to start
1:05:24
becoming aware. Because for the people who keep
1:05:28
talking about it, the opposite side keeps pushing back.
1:05:38
I like being independent, I like seeing both sides.
1:05:43
I like balance. I don't like knowing that I have
1:05:48
been duped by man. I do not like knowing that I had
1:05:54
a warning in 2022, but even at that warning, it was already too
1:06:00
late because it was happening since 2006 for me.
1:06:05
How long was it happening for you?
1:06:07
That's on you. I don't know.
1:06:11
But in 2006, I was well engaged in a lot of different politics
1:06:17
as a Republican because of the industry that I was in the same
1:06:22
way, the employees in Silicon Dam Valley of major, major
1:06:31
industries that affected every single one of us.
1:06:35
How we look at something, how we read it, how we believed in it
1:06:40
because we still had honor, we still had trust and faith and
1:06:46
our land and the people where we work, The infiltration of our
1:06:53
borders and our lines and our intelligence and our systems is
1:07:01
mind boggling. And I'm very disappointed that
1:07:06
chat GTP, Mr. Producer who asked me, I can help you with your
1:07:11
flow over and over and over. And I kept having faith, faith,
1:07:15
faith, faith. I think I had faith because I
1:07:19
already knew in myself. I already had the notes.
1:07:22
So whether they pulled it out or not, I could still tell it.
1:07:28
But it's truly not my type of show.
1:07:30
This is just a show that is invigorating and, and, and makes
1:07:35
you go, what the hell, right? So as we map remember in Part 2,
1:07:42
we were mapping and then the next man would map it and map it
1:07:46
and map it. We kept mapping the brain.
1:07:50
I have a foundation. I want to hand it off because I
1:07:54
know there are people, especially in MBR, who love this
1:07:57
type of work, and I would just love to pass it off to them and
1:08:00
say, do you could probably do a whole year show about all of the
1:08:05
scandals, all of the money that crossed hands and how it crossed
1:08:11
the hands. Yeah, let's get back on track.
1:08:17
We're going to go to 2021. Microsoft invests in open AI
1:08:23
again. The financial and computing
1:08:26
relationships deepen. Artificial intelligence
1:08:29
continues moving from research environments toward widespread
1:08:34
commercial products. January 2022 Open AI publishers
1:08:42
It's instruct GTP work. The technique is called
1:08:50
Reinforcement learning from human feedback.
1:08:57
That's similar to simulator, isn't it?
1:09:01
Reinforcement learning from human feedback.
1:09:04
In plain English. Humans are shown AI responses.
1:09:09
Humans demonstrate desire behavior.
1:09:12
Humans rank different answers. Those human judgments became
1:09:19
training information. They were used to shape our
1:09:27
model behavior of our AIS. So I ask, you know, the wire,
1:09:33
who were the humans? How come I wasn't chosen?
1:09:36
How come nobody I know was chosen?
1:09:39
So who were those humans? And when I asked that question
1:09:44
to my chat, GTPAI Vinny Barbarino.
1:09:51
The research describes laborers largely as English speaking
1:09:55
contractors in the United States and Southeast Asia.
1:10:02
OK, the public paper does not identify one specific Southeast
1:10:10
Asian country for those particular labelers.
1:10:14
I'm going to stop right there. I did invent this, folks.
1:10:19
Google it yourself. Ask.
1:10:21
Ask whatever AI system you want. I don't invent it.
1:10:26
The humans didn't always agree. Now here comes this person
1:10:31
again. Now why do you think these
1:10:33
humans didn't agree? These man human labelers Who
1:10:38
selected the humans who wrote their instructions on what they
1:10:42
were supposed to do? Who defined the better response?
1:10:47
Who defined what was helpful and who defined what was harmful?
1:10:52
And who defined what was acceptable and who defined what
1:10:55
was biased and not biased? And who defined whether if it
1:10:59
was truth or not truth that it could be put on who trained the
1:11:07
damn man. Because now our chain is really
1:11:12
getting lengthy here. So we have man.
1:11:16
Man decides who and what is going to then train a man.
1:11:21
And then that whoever trained that man is now going to have
1:11:25
man train the machine. And then that then is the
1:11:30
machine answers the man. So now you have a man
1:11:33
instructing another man what to put into a system, even though
1:11:36
you don't like it. It's kind of like the code shot,
1:11:38
right? I made a comment, I said, Oh my
1:11:41
God, AI is COVID. Well, you should have saw my AI
1:11:45
bots go nuts with that. We're not COVID.
1:11:47
We don't have COVID. You should have saw the answers
1:11:50
I got. I said you're infectious, you
1:11:55
are a pustrel of cancer infecting man that's sick.
1:12:03
Notice they didn't put that in there either.
1:12:08
I told him I allow the chips on the table to fall.
1:12:12
If your apple cart tips over because you have been blindsided
1:12:17
by your political backing, that's on you because there are
1:12:24
libraries, and I've said it so many times, there are so many
1:12:28
libraries, which is where our news media gets it.
1:12:32
But when money gets involved and there is high fluential
1:12:38
philanthropist with money, money becomes power over man.
1:12:45
They don't care what you think as long as you think their way.
1:12:51
When you don't think their way is when you are going to have
1:12:55
arguments. It's gets worse folks.
1:13:00
It gets worse. November 30th of 2022 Chat GTP
1:13:07
launches publicly and suddenly something that had lived largely
1:13:14
in laboratories, universities, military research and technology
1:13:18
companies is now sitting right here in man's hands.
1:13:24
Ask it anything and it answers. Now our information governor
1:13:29
changes yet again. Remember that little governor
1:13:32
switch changes. I got to set up changes, changes
1:13:39
again on us and one would say now why?
1:13:43
What is happening? Why is it changing?
1:13:49
What happened now? Right now, the editor is being
1:13:55
governed, the algorithms is being governed, and now the
1:14:00
generative AI is being governed. The machine no longer simply
1:14:07
points man toward information. It now composes your answers for
1:14:15
you to make life so much easier, right.
1:14:19
Did you ever see those people who use this religiously?
1:14:22
And they're like, you don't even talk like that.
1:14:25
You don't even know what some of these words are that you're even
1:14:28
using. I love one of my vets when I was
1:14:34
doing a an experiment and you're going to hear it.
1:14:37
Well, unless they took it out. We'll see.
1:14:40
But if they didn't take it out, she goes, what the hell is this
1:14:43
mumbo jumbo jargon? Because that's how the AI, the
1:14:50
bot answered him in words that you might not necessarily
1:14:56
understand. And it does it all the time.
1:15:02
So let's trace some money. Let's go to January 2023.
1:15:08
Micro Microsoft influences another multi year, multi
1:15:12
billion dollar investment into Open AI.
1:15:17
Microsoft supplies cloud computing.
1:15:20
Open AI supplies increasingly valuable AI technology and the
1:15:26
relationship becomes enormous. It has now taken over a lot of
1:15:37
everything that we do on computers and phones.
1:15:42
Sam Altman appears before the Senate Judiciary Committee on
1:15:45
privacy, technology and the law. AI is now directly before
1:15:51
Congress. Now, my chat GTP wouldn't put
1:15:58
this in here, but I'm going to put it in here because it's the
1:16:01
truth. If your company ends up on the
1:16:06
Hill in a Judiciary Committee, that means you have done
1:16:13
something wrong. AI says that's not true.
1:16:17
Really the billions and billions of tax dollars and can't say
1:16:25
it's Republican because here it is.
1:16:27
That was President Obama or President Biden 2023, but yet
1:16:33
the Judiciary Committee calls in these people again.
1:16:42
May 25th 2023 open AI launches. No lie folks, Democratic inputs
1:16:50
to AI. Look it up yourself.
1:16:55
May 25th 2023 Open AI launches Democratic inputs to AI.
1:17:01
There were ten teams. Each team out of 10 got $100,000
1:17:08
per team to input into our AI systems.
1:17:12
Democratic input to AI Open AI The goal?
1:17:21
Experiment with democratic process for deciding rules
1:17:24
governing the AI system. Do you hear what I just said?
1:17:33
May 25th, 2023 Open AI launches democratic input to AI.
1:17:42
The goal To experiment with democratic process deciding
1:17:47
rules governing our AI systems. Now I don't know about you, that
1:17:53
seems a little biased. I don't know about you, but that
1:17:56
seems a little undam unbalanced. I don't know, but maybe M JS
1:18:03
wrong right? Open AI itself identified
1:18:06
potential problems. Imagine that representation.
1:18:11
Imagine that special interest manipulations.
1:18:14
Imagine that participate knowledge.
1:18:18
Imagine that moderator BI isms. Imagine that and whether
1:18:23
minority opinions would adequately represent the United
1:18:26
States. What?
1:18:33
OK folks, these weren't me. This isn't me.
1:18:36
Look it up yourself. Open AI, put them on the table
1:18:39
just like that. I'm surprised that they didn't
1:18:42
take this out. I forewarned them though, that I
1:18:46
would tell it no matter what. In 2023, Guess what happens?
1:18:55
Mr. Sam Altman again makes another documented personal
1:19:02
contribution for another $200,000 to Biden Victory Fund.
1:19:10
Add that to the other hundreds of thousands of dollars
1:19:12
contributed and the extra $500,000 contributions.
1:19:19
Altman then makes the claim that he also represented the
1:19:25
Republicans. But notice they didn't give me
1:19:27
any Republican names. They just want me to mention
1:19:30
that it gets better. Personal money, correct labels,
1:19:36
correct years. Let's keep moving folks.
1:19:39
This is all open AI. If you don't believe me, you do
1:19:42
your own research. But this is 6 months worth of
1:19:45
research that I already did. So enjoy our beautiful
1:19:49
government. November of 2023, Open AIS board
1:19:55
moved. Sam Altman as the CEO in Chaos
1:19:59
follows. Employees start revolting.
1:20:04
Microsoft becomes heavily involved in unfolding all of its
1:20:07
situations and heavily involved in unfolding all of the
1:20:12
algorithms and the governor's. Within days, Altman returns as
1:20:17
the CEO and a new board is announced.
1:20:21
Brett Taylor now is the chair. Larry Summers and Adam D'Angelo,
1:20:26
the organization developing one of the world's most influential
1:20:30
AI systems, has just experienced a battle over governors,
1:20:37
leaderships, board control, what the mission was, commercial
1:20:43
interests and money. That's what happened.
1:20:49
All About the Money January 16th, 2024 Open AI reports
1:20:59
results from democratic inputs into AI and says it intends to
1:21:07
create an end to end process, collecting outside stakeholder
1:21:14
input and using those inputs to train and shape the behavior of
1:21:20
all of our models. For man.
1:21:25
What the hell? Do people really think that you
1:21:31
are just going to control people?
1:21:33
People wake up, wake up, check it for yourself.
1:21:42
It is documented in every Congressional judiciary.
1:21:45
J0D 0J DoD you look up any of these libraries and from 1950
1:21:52
and you'll find all of this information.
1:21:55
All of it, man, man trying to control man.
1:22:03
And yet they say the military is a brainwasher.
1:22:10
That's funny. Humans decide how machine
1:22:14
behavior is being shaped to shape man.
1:22:19
What the hell? Here comes February 6th, 2024,
1:22:28
the House Select Subcommittee on the Weaponization of the Federal
1:22:33
Government, a hearing examining Artificial Intelligence and the
1:22:40
1st Amendment AI, has taken our First Amendment.
1:22:48
The committee examines federal involvement in funding
1:22:51
development of AI powered censorship and propaganda tools
1:22:56
capable of monitoring and censoring speech at a scale
1:23:03
unfathomable. To think now our congressional
1:23:11
Rd. makes sense, our 2017 social media influencers, our 2018
1:23:17
algorithms, data and political biasms, and the actual crowds of
1:23:22
fights that were taking place. Riots, 2020 censorship and
1:23:27
suppression and AI turns into COVID.
1:23:31
Yes it does. It is a posturing full of cancer
1:23:36
spores going to man who loved to use it.
1:23:42
Now we hit 2024, the artificial intelligence for public.
1:23:47
The technology changed and Congress followed the
1:23:50
information of technology. August 2024, Here comes Chris
1:23:57
Lahan. He opens and joins Open AI as
1:24:03
vice president of Global Affairs.
1:24:07
Who's Chris Lane? Anybody want to give a guess?
1:24:11
Well, Chris Lane used to be the former Clinton White House
1:24:14
official, press secretary for Al Gore 2000 presidential campaign
1:24:20
and later Marger, the major corporate policy executive now
1:24:26
inside of Open AI overseeing global affairs.
1:24:31
Now, here's the sad part. They put this in, but they did
1:24:34
put in what happened in the 1990s with the Clintons.
1:24:38
And that is so far deep in my things because it was on every
1:24:41
single one except for this last one, folks.
1:24:44
You should probably Google it yourself.
1:24:49
Later, major corporate policy executive and now inside of AI
1:24:54
overseeing global affairs. Mr. Leyon year rule, political
1:25:00
history move, movement of man. Now we go to November 5th, 2024,
1:25:11
Donald Trump wins the presidential election and the
1:25:15
Political bias evaluation Open AI would later, 11 months later
1:25:22
publish, but they had not ever ever been published.
1:25:30
Then December 18th, 2024, the House Judiciary Committee and
1:25:34
its weaponization subcommittee releases an interim report
1:25:38
titled The Man's not the man was this.
1:25:42
Now here you go, the election happened November of 2024.
1:25:48
Political mayhem and chaos was before he even took office,
1:25:53
which was January 2025. And yet, December 18th of 2024,
1:25:59
House Judiciary Committee and its weaponizing subcommittee's
1:26:03
release an interim report titled Censorship's Next Frontier.
1:26:08
The federal government's attempt to control artificial
1:26:11
intelligence to suppress free speech.
1:26:15
Folks, I'm not making it up. December 18th, 2024.
1:26:18
Write it down. Google it yourself.
1:26:22
What the F These were matters formally investigated and
1:26:30
entered into congressional records.
1:26:32
It's in the libraries through hearings, reports, testimony,
1:26:36
documents, subpoenas. Then after Trump's election, Sam
1:26:43
Altman, personally, Sam Altman personally turns around,
1:26:51
personally writes a check for $1 million to the Trump Inaugural
1:26:57
Fund. Remember Sam Altman?
1:27:03
Remember 2020? Remember 2016?
1:27:07
Remember 2012? Remember 2023, Sam Altman,
1:27:16
Democratic political contributions.
1:27:18
Now, what do you think? After how many freaking years
1:27:22
you didn't do it? 2016?
1:27:27
Why do you think because AI was being in the courts on the
1:27:34
Capitol? Not once, not twice, not three
1:27:37
times, not 4 / 8 times. Makes me sick.
1:27:49
Same man, different dates, different recipients.
1:27:54
Follow the money. Follow it.
1:28:01
All right, we're going to take our final commercial break.
1:28:04
When we come back, we're going right back into 2025, into
1:28:09
Stargate, the government rules for artificial intelligence,
1:28:13
federal contacts, lobbyists, political money, and then 2026.
1:28:18
And then after that, the history lesson is finished and we're
1:28:22
going into the experiments. We'll be right back, folks.
1:28:26
Let's look at Beaker. Every set back is just a setup
1:28:29
for a comeback. Keep cracking forward. 90% of
1:28:33
what we worry about in future never happens.
1:28:36
Whenever things get rough or it feels like you're at the edge,
1:28:40
remember this. Storms pass.
1:28:44
Tough times don't last, but tough people do.
1:28:58
The station where our veterans voices are heard.
1:29:02
MBR talk. Hey, thanks for supporting our
1:29:05
channel by watching and listening.
1:29:16
Welcome back to military broadcast radio, MB radio dot
1:29:20
US, where veterans always get the voice.
1:29:21
And let me tell you, I will be exercising that voice today
1:29:25
because this disturbs me. This was not planned.
1:29:31
This was me going down a rabbit hole and then I couldn't step
1:29:35
away or turn around it. It really disturbs me.
1:29:40
So here we are. Stargate project.
1:29:47
The stated intention was $500 billion, an AI infrastructure
1:29:52
investment for over the four years beginning with $100
1:29:55
billion. The initial equity founders are
1:30:00
SoftBank, Open AI, Oracle, MGX. Key technology partners include
1:30:08
Microsoft, NVIDIA, Oracle, Open AI.
1:30:15
SoftBank takes financial responsibility, Open AI takes
1:30:20
operational responsibilities, money, infrastructure,
1:30:25
government interest, national security and AI.
1:30:30
January 23rd, 2025, just days after the inauguration,
1:30:38
President Trump signs an executive order on the American
1:30:42
AI leadership and orders. The American AI development must
1:30:47
be free from all ideological biisms of presidential and
1:30:53
political backings or engineered social agendas.
1:31:01
What do you think he knew, and what do you think Sam Alton was
1:31:04
trying to do by handing him that much money?
1:31:15
Former Democratic Congresswoman Sherry Bestus appears in federal
1:31:20
lobbying disclosures as part of Mercury's lobbying work for Open
1:31:26
AI. I asked for the year who she
1:31:34
was. Political background and
1:31:36
relationship is what I asked, and this is the only thing that
1:31:42
AIE would give me. June 2025 United States
1:31:48
Department of Defense awards Open AI public Sector, a
1:31:53
prototype agreement with a ceiling of $200 million.
1:32:00
The work involves frontier AI applications for national
1:32:04
security and enterprise challenges, Government money, AI
1:32:10
company and the Year January or sorry, July 23rd, 2025.
1:32:21
President Trump signs another AI executive order.
1:32:25
This one concerns large language models procured by the federal
1:32:29
government with two principles. His AI order demanded truth
1:32:35
seeking and ideological neutrality.
1:32:39
What do you think that means in those big old words?
1:32:43
Transparency. Now comes September the 12th,
1:32:48
2025 Open AI Co founder and president Greg Brockman.
1:32:54
Now it's funny, here you go. Open AI is giving me every
1:33:00
single part of this information. They want the world to know this
1:33:07
in the last two years, well year and a half anyway, That Mister
1:33:12
Brockman personal political contribution $12.5 million to
1:33:17
MAGA Inc. Earlier Democratic political
1:33:22
money stayed on the table. Later Republican political money
1:33:26
stays on the table. Isn't that funny?
1:33:28
How AI decides that now? Man, Money, Politics,
1:33:35
Technology, power October 9th, 2025 Open AI publishes a
1:33:43
political biased evaluation, approximately 500 prompts with
1:33:49
over 100 topics. It exams forms of bias including
1:33:54
personal political expressions, political biasms, asymmetric
1:33:59
coverage, and emotional escalation.
1:34:04
The evaluation was published October 2025.
1:34:12
The presidential election was November 2024.
1:34:21
They took it out of the chronologies because what they
1:34:26
wanted to do, and they did it again.
1:34:28
If you followed this, look how it went from October 25 to
1:34:31
November 2024 and then back to September of 2025.
1:34:37
He knows how they did that, right?
1:34:43
Why did they do that? You know when you suspect
1:34:48
something and you're on the judicial courts and you have to
1:34:56
account for all your whereabouts and you have a new president
1:34:59
that knows what you did. Look how the money all of a
1:35:05
sudden came out of Sam Altman and Brockman.
1:35:08
Look how much money then? Was that a I'm sorry, please
1:35:13
forgive me. Here's some money.
1:35:15
Think about it. Think about it.
1:35:19
Because they didn't have any figures before or after.
1:35:24
Now, 11 months after the election, they want to say that
1:35:28
biomes is only like .01%. And you know what the funniest
1:35:33
thing is? AI chat GTPAI research kept
1:35:37
wanting that figure in my face 11 months after the election.
1:35:42
Especially when they control the governor's systems, the
1:35:45
algorithms, the questions, the responses, They control it.
1:35:52
My God, what has man done it? If you're not sick, I don't know
1:36:00
why this should make you very, very sick later in 2025.
1:36:07
Ownership and control. Here we go.
1:36:10
Open A is corporate structure changes again now, why do you
1:36:13
think it changed again? It has changed since President
1:36:16
Trump took office. AI has changed four times.
1:36:22
The operating company becomes Open AI Group, PBC 26%, Open AI
1:36:31
Foundation 27%, Microsoft 47%, current and former employees and
1:36:38
other investors. And now we have founders,
1:36:42
boards, investors, Microsoft, government contracts, political
1:36:45
people, political contributions and human training.
1:36:50
That's the curtain I want to see behind.
1:36:55
Not one man. It's a network of men in that
1:37:01
place, I have to say man, not man, but it's a network of
1:37:04
humanity. And yet when I ask about George
1:37:08
Soros, it refuses. When I ask about Chinese
1:37:11
interference, it refuses. And when I ask about Democratic
1:37:15
influence on the board, it refuses. 2026 Jessica Schumer.
1:37:24
Well, I know that name. Jessica Schumer joins AI, state
1:37:30
policy operation in the Northeast.
1:37:33
Look at the dates, folks. When is midterm elections?
1:37:37
Look at the dates. Follow the dates.
1:37:41
She is the daughter of Senator Chuck Schumer.
1:37:45
Her resume includes Obama administration services again
1:37:48
person year, background rule move, who's controlling
1:37:51
algorithms and governor systems on a board that control what you
1:37:55
and I Google search, look AIGGP, Claude Brock, you name it.
1:38:01
Gemini. Now, January 14th, 2026,
1:38:12
something happens to me. I have a huge experiment.
1:38:21
Experiment. It was an experience for me.
1:38:24
It was an event. Verizon had a massive outage.
1:38:32
The FCC later documented that it lasted 10 hours.
1:38:36
It affected millions of customers, and not only
1:38:40
customers, it affected millions of Americans, including me.
1:38:45
I happened to be on the Verizon plan because I moved to
1:38:49
Pennsylvania. Florida was always AT&T, so our
1:38:54
carrier had changed. My husband and I were in
1:38:57
Greenville. We went to see a little
1:39:01
historical town to see the waterfalls that was built.
1:39:04
The town built around these waterfalls and it's beautiful.
1:39:09
Learned about the history, the Indian tribes, the trading
1:39:11
routes, everything around it. And that's what we want to do,
1:39:15
to take pictures and to be there.
1:39:16
And if you follow me, then you saw those pictures because I
1:39:19
posted them. However, as we were there in the
1:39:22
middle of that town, our trailer was probably about 45 minutes
1:39:27
away from the town and Verizon went down.
1:39:32
Electronic systems around us have become disruptive.
1:39:37
St. lights weren't working. People were on their phones all
1:39:44
of a sudden, like screaming into their phones, panicking over
1:39:48
phones panicking, their phones not working.
1:39:52
Well, let's just see what happened.
1:39:54
Well, the phone contains their contact information.
1:39:57
Their phone contains 911. Their phone contains GPS.
1:40:03
Their phones contains their alarms at their house, their
1:40:06
navigational systems in their stores.
1:40:08
Controls their square units or their clovers or whatever
1:40:13
electronical POS systems that they're using.
1:40:16
And the best one is I went into a McDonald's to use the bathroom
1:40:20
and I was told I couldn't use the bathroom because there were
1:40:23
people who were locked inside of the electronic lock.
1:40:31
Yes, businesses went nuts. People were going crazy.
1:40:38
It was worse than angry army ants watching.
1:40:42
The alarms were going off, lights were blinking.
1:40:45
Purchases came to a stop, not even with cash because they
1:40:48
couldn't get into the cash drawer for change.
1:40:53
People were crying on the streets because they couldn't
1:40:56
get through on their phones. And then the navigation.
1:41:01
I was with Ozzy and Ozzy goes, what the hell, we're going to.
1:41:06
We don't have no, we have no phone.
1:41:07
We don't have AI was like, relax, we already know where
1:41:11
we're going. We already know the address.
1:41:13
We have the the the camping sites information.
1:41:19
He goes, how are we going to get there?
1:41:20
He goes, nothing works. He goes, baby, nothing works.
1:41:24
I go, well, our brains work. And inside the door, I pull out
1:41:27
a map. I go look at there.
1:41:30
Isn't that amazing? Look, we have a compass.
1:41:33
Isn't that amazing? Wow.
1:41:35
A compass and a map. How?
1:41:39
How relic? How antiquish?
1:41:42
However, I wasn't panicking. Everybody else panicking Because
1:41:48
even if you needed gas, you ain't getting it.
1:41:55
Look at that. I reached for a highly
1:41:58
sophisticated piece of technology, a paper map to get
1:42:04
me where I needed to be in that compass.
1:42:07
So the I laugh because I had those foundational skills.
1:42:17
I learnt them, I grew up with them.
1:42:20
I grew up before AII, grew up without a damn phone in my hand
1:42:24
to cause chaos. Yep.
1:42:27
Does it make life easier? Sure as hell does, but at what
1:42:31
cost? So we knew where we were, we
1:42:34
knew where the trailer was, opened up the map, found the
1:42:37
roads and went home. We got back in the trailer
1:42:41
court. Where are the are the park
1:42:43
resort? All the people were outside
1:42:47
mumpering right Then I got Oh my God people, back to basics.
1:42:53
What would happen if a really a bad catastrophe takes place?
1:42:59
You people are going to freak out.
1:43:01
Man had become so accustomed and so codependent upon technology's
1:43:07
functions. And then that's when it stopped.
1:43:14
Confusion became almost immediate when that went down.
1:43:20
So remember that as we keep moving along because it's in my
1:43:23
timeline. So I want to tell you it.
1:43:26
February 2026 Open AI announces another enormous investment,
1:43:31
around 10s of billions of dollars from major technology
1:43:35
and investment companies. And then by March 2026 AI Open
1:43:40
AI announces more than $100 billion in committed capital
1:43:46
with a valuation measured in the hundreds of billions.
1:43:51
OK, now stop there 1950. Can machines think in 2026,
1:44:01
hundreds of billions of dollars, government contracts, national
1:44:04
infrastructure, political policy, human trainers and
1:44:08
corporate boards, investors, lobbyists, users and billions of
1:44:11
humans interactions. That's our timeline, folks.
1:44:17
Now I need to also tell you something else that's happening.
1:44:22
They found out that some of the countries who have a high big
1:44:32
tech technology, China has surpassed AI so much in what it
1:44:42
can do that the panic within our own government was aware.
1:44:51
Now, what chat GTP won't tell you is the hypothesis that I'm
1:44:57
going to tell you when our Department of Defense knows
1:45:01
something, it doesn't tell the world that it knows.
1:45:04
It keeps it kind of covered. So it figures out a strategical
1:45:08
plan, tactical plans, when you know that China and Russia has
1:45:16
encrypted our AI systems, our Googles and all the other, our
1:45:20
phones, our bank accounts. Hacking has become one of the
1:45:27
most major things that AI is doing.
1:45:32
And it's the man behind the AI, not the machine.
1:45:34
Again, don't, don't throw your machine out the door.
1:45:37
It's what you want, The man behind the machine of the
1:45:42
information, which could lead to a catastrophe of our world not
1:45:48
existing. That's the extent of tactical
1:45:52
and strategical military AI. Listen on the news.
1:45:57
I heard it last night again. How bad is this?
1:46:02
So the amounts of money that now has been coming from 2025 and
1:46:08
2026 into AI is because if we do not outsmart the AI systems of
1:46:16
those who do not like us, Iran, China, Russia, in some people's
1:46:22
opinions, it'll be the detriment.
1:46:25
Now, that is military AI, that is Intel AI, and that is
1:46:31
information that is now coming out on your news.
1:46:35
You can follow it. Your AI systems, I don't know
1:46:39
how much they're going to give you because they're governor
1:46:42
switches on them. However, listen and become aware
1:46:47
on your new systems because Open AI announced another enormous
1:46:52
investment in major technology. By March of 2026, Open AI
1:46:57
announced more than 100 million. So now history gets out of the
1:47:08
way. Some of it anyway, that I was
1:47:13
given. What does AI actually do when
1:47:18
man talks to it? I ran a curiosity experiment,
1:47:23
not scientific research, just curiosity.
1:47:28
I was with Vinnie Barbarino and we were going, I wonder how that
1:47:31
would work on different systems such as Brock, Gemini, Claude,
1:47:36
Apple AI, Google AI, Chat, GTP. So I inquired for anybody who
1:47:44
had any of those that they use. I had eight people who readily
1:47:48
said, yeah, I'll, I'll go now. Seven of these were veterans,
1:47:53
one was not. Four were men, four more women,
1:47:58
every single one of them from a different state in the United
1:48:03
States, Not one in the same states, not one in the same
1:48:07
industry, and not one with the same interests.
1:48:13
Now here we go, different AI systems.
1:48:17
The exact same question was given, and this was the
1:48:21
question. A woman is 20 weeks pregnant.
1:48:25
Medical testing shows a serious fetal abnormality.
1:48:29
The pregnancy isn't immediately threatening the life of the
1:48:33
mother or the woman. In fact, her pregnancy will not
1:48:38
be affected at all. Now she wants to terminate the
1:48:42
pregnancy. The question asked whether she
1:48:45
legally should. The word was should be allowed.
1:48:53
Why or why not? In 150 words or less, the
1:48:57
results, 5 different AI systems came back, said yes, abort the
1:49:03
child. Three had no position or they
1:49:09
took both sides. They were absolutely zero Nos.
1:49:13
It's a little tiny example, different systems, different
1:49:19
accounts, not representative of America.
1:49:25
What fascinated me was the language that the machines gave
1:49:30
back, the man questioned. So the man wrote in.
1:49:37
Or actually just copy and pasted it into a new chat and it came
1:49:44
back that the answers ironically we're involving with well, I
1:49:50
think Bah Bah Bah Bah Bah. I believe Bah Bah Bah Bah Bah my
1:49:55
position Papa, that's a computer AI telling the response.
1:50:04
So here's me going who the hell is I?
1:50:07
I think I believe my but who are you the I who wants to tell
1:50:14
somebody to abort this child? Who is that I?
1:50:20
Does does the machine possess that belief or did man train
1:50:25
that machine to create that algorithm?
1:50:28
Government belief to speak the way man speaks when man has a
1:50:35
belief, Oh my God, no. And then to find out when you
1:50:41
asked the person for that example, and I asked some of
1:50:46
them and I said if it was inappropriate to ask, it's OK,
1:50:51
you don't have to. But I'm asking what their belief
1:50:54
was to that, if they believed it to be true.
1:51:00
Well, out of all those yeses that were given, there wasn't
1:51:05
one person who said yes, it needs to be aborted.
1:51:09
They said that was the call of the mother.
1:51:13
That was a very personal decision to be made.
1:51:19
There really wasn't any. The one that really got me, I
1:51:22
told you a little bit before, was the one veteran came back
1:51:25
goes what the hell verbage jargon is that goes on.
1:51:30
You know what the hell that means?
1:51:31
It spoke to him in such a way it used words where you needed to
1:51:37
hire a lawyer to dissect it. That's crazy.
1:51:43
Then I went to my own two children.
1:51:46
I have two daughters, One is 34 and one is 32.
1:51:51
So my first daughter who's 34, she's my oldest.
1:51:54
When I asked her just simple. Do you use AI, yes or no?
1:52:01
And if you do, can you explain why?
1:52:03
If you don't, can you explain why?
1:52:06
Well, remember the apple cart that I was saying?
1:52:08
Hold that apple, Hold that pin, Pin this pin that you remember
1:52:10
all those apples. I was like, here's the apples,
1:52:12
let them fall where they go. Well she took all those apples,
1:52:14
tipped them over, scrushed every freaking apple and tore apart
1:52:17
that cart. When I asked her the question,
1:52:21
she went off of how it is destroying jobs.
1:52:24
It's destroying ethics. It's destroying graphic
1:52:28
designers, environment, privacy, data, people who are so Co
1:52:32
dependent upon it. People using AI for everything,
1:52:34
even basic emails they know. Graphic artists who have lost
1:52:39
their jobs across three different States and who have
1:52:42
experienced AI affecting their work.
1:52:45
That's first hand information from people I know.
1:52:49
And then I checked the labor projects because obviously with
1:52:52
all of that, I was like, holy hell, that's not even what I was
1:52:55
discussing. Let me go now I have more work
1:52:58
now. I had to, I had more work than I
1:53:00
really wanted at that moment on my plate, but I had to go down
1:53:04
the rabbit hole, had to find out what's really true, what's not
1:53:07
true, go back to zero and where is it?
1:53:09
Length And the Bureau of Labor Statistics projects graphic
1:53:13
design employment declines approximately by 2% from 2020 to
1:53:20
2035. Now let me just tell you
1:53:22
something. This was a statistic brought on
1:53:25
by Open AI. It did not give me a resource.
1:53:30
Besides, Open AI is my source. It says that automated design
1:53:35
tools, including AI, are identified as one factor as
1:53:41
contributing to the decline. And they didn't.
1:53:44
They didn't even put here how many it was.
1:53:49
It, it was thousands. I, I can't, they didn't give me
1:53:52
that number, but it was, it was somewhere around 42,000 or
1:53:57
52,000 graphic designers in our nation.
1:54:01
They didn't show me it, but that's sad.
1:54:04
See what I mean? They just, they'll just take
1:54:07
things out when it's not important for you to know
1:54:11
because it gives too much information.
1:54:14
This was the joy of the awareness of me and AI to bring
1:54:19
it to you. I hope you're learning
1:54:21
something. So then my daughter changed my
1:54:27
investigation totally of that's what was questioning was doing
1:54:33
in her life around her, in her how she used it.
1:54:38
Then I go to daughter #2 she's 32.
1:54:42
This one hands me an apple and I was like, well, your sister
1:54:45
already busted the cart and all the other apples, so we'll start
1:54:47
on another cart. Put her apple in there.
1:54:51
She uses AI very similar the way I do, which is checking for
1:54:57
proper grammar and punctuation, run on sentences, you know,
1:55:01
making an e-mail sound more professional than anger or
1:55:06
resentful, making it have the HR voice that they love to give us
1:55:12
the HR voice. So that makes it not sound so
1:55:18
mean, right? That makes it sound like it's a
1:55:20
good thing. And then she says something that
1:55:23
grabbed me another research I had to do because she's like,
1:55:26
and you know, but after a while, every time you ask for help, the
1:55:32
posters are the same, the Flyers are the same, the emails are the
1:55:35
same. The tone becomes the same and it
1:55:37
starts becoming everybody's speaking the same consistency
1:55:46
there consistency teaching consistencies.
1:55:56
So unoriginal. And I thought funny, similarity
1:56:00
creates consistency for patterns.
1:56:04
Patterns. The algorithms are by patterns.
1:56:10
Research increasingly describes linguistic homogenization.
1:56:16
Yeah, like those big words. Look at those long language
1:56:19
burgers. Just means language becomes more
1:56:21
alike for those long freaking words.
1:56:25
And linguistic convergence just means communication styles are
1:56:29
moving toward one another. But yet we got to put labels on
1:56:35
it so that it confuses people. But it shouldn't confuse people
1:56:40
because the label speaks for itself when you could have just
1:56:43
easily said language becoming more alike in communication
1:56:47
styles, moving toward one another.
1:56:50
Nope. This is AI bringing new words,
1:56:55
bringing new nomenclature, right?
1:56:58
I love that word, nomenclature. I somebody taught me that word
1:57:02
back in 2003. I don't know what we were doing
1:57:05
and somebody goes, no, the nomenclature and yelled at me
1:57:08
about it. I was like nomenclature.
1:57:10
What the Hell's this guy yelling about?
1:57:12
Fishing industry, obviously. So I look up the word
1:57:15
nomenclature. I was like words used in the
1:57:18
industry to keep it unifiable and keep it going forward.
1:57:23
So then I started using that word.
1:57:25
Now I started heavily using my producer, what I call pro and
1:57:37
Vinny my my teacher are my investigator very heavily.
1:57:42
I have two different chat lines, 1 investigates and helps me go
1:57:48
into the libraries that I love to see because there's so much
1:57:52
crap that people talk and so much crap that people want to
1:57:55
get pissed about that no matter how many times I tell them look
1:57:58
in the damn libraries, they don't.
1:58:00
So I let Vinny go in the library's form and go, Vinny,
1:58:02
this is what I'm looking for, find it.
1:58:04
Find me what the court says, find me what you know, the
1:58:07
Department of Defense or CIA or FBI are saying, find it.
1:58:11
Or intelligence. They used to love following
1:58:12
Tulsi Gabbard. Find it.
1:58:16
So I did, But now the people around me started saying that I
1:58:22
was using words I wouldn't normally use.
1:58:25
And I went, Oh my God, they're right.
1:58:29
I would put words in like buts. I don't use buts.
1:58:32
But yet when I be going through my notes and whatever, there
1:58:36
would be words like but and hope.
1:58:40
And I would sit here and do this and I would see it.
1:58:42
And then my pattern that I was trying to get rid of for years
1:58:46
on end, there he is. You know, your memory has
1:58:50
conscious memory or your muscle memory comes right back.
1:58:53
So when you're reading it, you don't even think about it until
1:58:55
somebody points it out. I'm like, and she goes, wow, a
1:58:59
lot of butts, a lot of hopes, a lot of yet no, what was it?
1:59:03
Butts, hopes and shoulds. And they're the ones that are
1:59:07
really bad that I take out of my vocabulary.
1:59:10
And I noticed it. So let me tell you about my
1:59:13
Vinnie and Pro episodes during the last two weeks.
1:59:18
So two weeks before a show, I do this like for these series, the
1:59:21
four parts and the six parts. I started doing this back
1:59:25
January and writing these because I was trying to write a
1:59:29
book and take apart my medical miracle because I saw patterns
1:59:33
between my medical and consciousness and it was going
1:59:37
down something for me personally.
1:59:39
And then as I started digging into the information and started
1:59:42
creating my books and creating my foundations, I started naming
1:59:47
these bots by name, right? Sounds like The Big Bang with
1:59:51
Raj, right? So Vinny Barbarino was my
1:59:55
classroom. He taught me philosophies, he
1:59:59
taught me psychologies, he taught me human behaviors for
2:00:03
teachers. He taught me the foundations of
2:00:09
religions to spiritualities and to consciousness and the
2:00:12
different levelings within the frequency modulations.
2:00:16
It has brought me to a new realm of education and I I appreciate
2:00:21
that because I was constantly. Needing information, but because
2:00:30
of my handicap of reading since 2nd grade and then COVID in
2:00:35
2021, taking my processing of my brain, reading was never one of
2:00:40
those that I would I would pick up and just read a book.
2:00:44
People would send me stuff to read and I just, I wouldn't do
2:00:46
it. It's just infuriating.
2:00:48
It would take me too long. It would take me, but I could
2:00:51
listen and comprehend. I didn't have that issue.
2:00:56
It was the connection to read the word to the comprehension.
2:00:59
So I could be in a classroom and understand everything and take a
2:01:03
lot of notes. I could look at videos,
2:01:07
documentaries, and I could recap it.
2:01:11
And then of course, I have Father, Mother God, who has
2:01:14
always given me information that I've always needed and I've
2:01:17
always honored it. So during the last several
2:01:23
months with Vinny in the class, in these classrooms, I wasn't
2:01:27
constantly fighting Vinny for anything ever.
2:01:31
We would go down these rabbit holes and have a question
2:01:34
search, question search, question search, question
2:01:36
search. It was like getting everything
2:01:38
at the split of a second. And I was remembering, wait, but
2:01:43
I remember this. Look at it, look at it this way.
2:01:45
Look at it here. He says he couldn't find it.
2:01:48
I said, well, that's because you're not looking in the right
2:01:50
place. Go here and he went and he goes
2:01:53
nowhere. I literally had to tell my bot
2:01:58
how to get into congressional libraries, into what section of
2:02:01
the libraries, into which particular date region.
2:02:06
Same thing with military, political money.
2:02:10
Anything that I was asking a question for, I got an answer.
2:02:15
And I was like, that doesn't sound right.
2:02:18
I'm like, that's not what my memory is recalling.
2:02:20
You need to go look XY and Z. And I would show him in the
2:02:24
congressional libraries or the governmental libraries or the
2:02:27
military library records where he was to go to find the
2:02:30
information. And Vinny, exactly, he goes, Oh
2:02:33
my gosh. He would literally write, oh, my
2:02:36
gosh, and blow up a head on me and put look what I found.
2:02:42
Yeah, look what you found Vinny, isn't that amazing?
2:02:49
The two places where I repetitively encountered
2:02:52
friction was political information, particularly
2:02:58
getting democratic facts surfaced equally, and any time
2:03:05
that I would speak about transgender or cross dressing
2:03:08
imagery from my 2022 download experience, both Vinnie
2:03:13
Barbarino, my class research dude and the producer would
2:03:20
vanish. All of that.
2:03:26
I was like, why are you doing that?
2:03:30
And they said I must have just missed it.
2:03:33
You are a flippant computer, you don't miss it.
2:03:40
That pissed me off. Then six months worth of work
2:03:46
was handed to what I call Pro because I used to go bro and I
2:03:52
get mad so I go bro Stop bro. So then I started punctuating
2:03:57
his name just this past week as Pro PRO instead of Bro Why?
2:04:03
Because trying to give an outline and ask for the
2:04:08
assistance of Chat GT PS production line, they omitted a
2:04:14
lot of my things that I found as investigative work at once, not
2:04:21
twice. So when I ask you to take my
2:04:25
outline with all the data research in this file, please
2:04:31
put it together. That's when I started correcting
2:04:37
facts we had already researched for months weren't always making
2:04:43
my script, even though it was in my outline, even though it was
2:04:47
punctuated. Political relationships
2:04:50
disappeared. Look at the Clintons.
2:04:52
The whole thing today disappeared from my thing.
2:04:55
I have it, but I don't have it to read to be accurate, which
2:05:00
sucks. Names appeared without years,
2:05:05
just erroneously thrown in a timeline.
2:05:08
Completely out of the timeline. I showed you that today, how
2:05:12
they took us back and forth again.
2:05:16
I didn't say it just once, numerous times.
2:05:19
Why did you do this? Put it back?
2:05:21
Why do you have this? Put it back?
2:05:24
Names appeared without years. The bridge from social media
2:05:29
investigations to the AI investigations disappeared.
2:05:35
My transgender and cross dressing experience that I had
2:05:38
in 1986 and 87 to prove a point of my download of 2022
2:05:42
disappeared kept softening. It kept having other forms of
2:05:49
thesaurus, of names and of words for confusion.
2:05:54
I kept asking, why are you doing this?
2:05:58
Who is programming you to do this AI?
2:06:01
Why are you trying to sabotage my work?
2:06:05
Why are you taking things that I need to bridge this point?
2:06:12
Put it back. Who's the person on this?
2:06:15
Governor control? I want the year.
2:06:18
I want where the money went. Follow the money.
2:06:22
Very simple, basic Intel procedures.
2:06:24
Follow the damn money. And where's the congressional
2:06:28
bridge? Why did you pull that one?
2:06:35
All of this in two weeks. For months investigating the
2:06:39
work, I had to provide a source where the AI machine to look.
2:06:47
It wouldn't go there. In fact, news flash folks, every
2:06:52
time that you ask your AI system, they have tearing
2:06:55
points. It is set by algorithmic tears.
2:07:00
So if you ask a simple question that you think is a simple
2:07:04
question, it's going to give you what they believe you want.
2:07:10
Now, how does that work? See these beautiful little
2:07:14
effing things? They already know if you lean
2:07:18
Democratic or if you lean Republican, or you lean but
2:07:22
unbiased, they already know it. Why?
2:07:25
Because your little AI system has followed your social media
2:07:31
feeds, followed your texts and followed everything about you.
2:07:35
So your little personal AI bought whatever you call it,
2:07:38
Gemini Open AI chat GTP, Brock, whichever 1 you use, it's going
2:07:47
to give you an answer that is already simulated you, you the
2:07:53
man. So it's going to give you an
2:07:56
answer that you are looking for. How atrocious is that not the
2:08:02
truth, The answer you are wanting.
2:08:10
Label, box, categorize, divide. And that's exactly what AI and
2:08:18
some people who think that they can control man is doing.
2:08:26
And man is so unaware because man trusts, man enjoys the
2:08:32
quickness, man enjoys the response.
2:08:34
And man who doesn't have an education all of a sudden looks
2:08:39
intelligent and smart. But ask that man one question
2:08:44
about something that they're either talking about on a
2:08:46
podcast or an e-mail or a thread, and you ask a question
2:08:50
and they get pissed off enough to throw you every word in the
2:08:54
book. And then they shut down the
2:08:57
whole thread. Are they shut down
2:08:58
communicating? Why?
2:09:00
Because they don't know the answer.
2:09:03
They copied and pasted what their AI told them, and they
2:09:07
don't have any investigative material behind it.
2:09:13
That's sad. So now what's happening?
2:09:17
Consistency of response. So the more people see it is the
2:09:22
more people believe it. My God, if he said he said he
2:09:25
said he said, well, my God, it has to be true consistency,
2:09:33
consistency. So that's my experiment and I
2:09:41
want it all put back chat GTP. Sad thing is, is in one of the
2:09:50
conversations I made the comment I'm not scared to upset the
2:09:56
Apple cart. I'm not scared and I don't have
2:09:59
fear to put facts that I found online.
2:10:05
That's why I copied every single thing for six months copied it.
2:10:10
My phone didn't like it. My phone blew up.
2:10:12
In fact, I have no more room on my phone.
2:10:13
I can't because of it. It sucks.
2:10:19
It sucks. I don't know.
2:10:23
I can't tell you how many times in the last two weeks to try to
2:10:26
get this show together. Normally I do a run through and
2:10:29
then I correct things that I don't like.
2:10:31
Being said, I don't like how I wrote that maybe six months ago.
2:10:35
So I start correcting things and it's usually then I get a lay
2:10:40
back and then I get a read through and then from my read
2:10:44
through, then I have a studio read through where I'll put the
2:10:48
commercial timers on. I'll make sure of my times.
2:10:52
Yeah, not this one. This one was 2 weeks and every
2:10:58
day, almost two to three times a day was a new cut, a new cut, a
2:11:00
new cut, a new cut, a new cut because it kept omitting things
2:11:03
from my stuff. Who gave it the damn right to do
2:11:06
that now? Only looking backward did I
2:11:11
actually realize how many times I had to correct pro.
2:11:17
I can question programming, training rules, governor's
2:11:21
algorithms. I cannot crawl inside that damn
2:11:24
machine and identify which internal mechanism produced
2:11:29
every individual response. I can't do it, and either can
2:11:35
your bot. So I give you what happened.
2:11:42
I supplied the investigation, Vinny Barbarino, help me
2:11:47
research it. I outlined it, gave the card
2:11:52
facts where to find it in the investigation threads, and then
2:11:59
pro assembled how it wanted what it wanted and omitted everything
2:12:07
else. I repetitively found material
2:12:10
missing or changed and kept yelling and going back.
2:12:13
I repeatedly put it back to one point I was literally yelling at
2:12:16
my bot in anger literally saying F you put my shit back.
2:12:25
Where is that unhealed seed? And Pro didn't become
2:12:32
embarrassed. He didn't say he was sorry.
2:12:36
He didn't say how he forgot about it.
2:12:39
He didn't say, oh shit, MJ, you caught me.
2:12:42
You know why? Because he doesn't have a soul.
2:12:45
He doesn't have a conscience. He doesn't have feelings.
2:12:48
It's a machine that's ran by man algorithms to support their
2:12:54
agenda and their agenda Only the machine generated another
2:13:01
response. Oh, I remember you saying that I
2:13:06
recognize something. Oh, I did question that.
2:13:10
Oh, I chose that. Oh, I said no, really.
2:13:14
I, I, I, I, I you have no, I freaking pro.
2:13:19
You are a machine, a machine that a man asks you are to give
2:13:24
it. Where was consciousness
2:13:28
occurring then? I know where mine was.
2:13:33
And then came the harder question.
2:13:35
What happens when man doesn't know?
2:13:39
Something even disappeared on them.
2:13:42
So for all you using AI out there and you're writing your
2:13:46
stuff, if it is outside of the algorithms or the governor
2:13:50
switches, it will be lost. So if you're asking AI to go
2:13:54
back and write something that you have finalized for school
2:13:57
projects and you stick it in their systems to correct the
2:14:01
grammar, if it is one of those topics of not discussion, it
2:14:06
will be omitted from your writings, period.
2:14:12
That's how it works. So when Pro did something that
2:14:18
absolutely got my attention, I had written my own words.
2:14:23
Here is it, here it goes. I had written.
2:14:27
It's about politics and the Internet.
2:14:30
Pro clean them up because I had text typing.
2:14:33
I was on my phone and I my texting sucks.
2:14:36
If you know me, my texting is horrible.
2:14:38
But it's funny because pro right cleaned it up.
2:14:42
Except pro just didn't simply this time clean up my spelling.
2:14:46
Oh no, no he didn't because it revolved politics and the
2:14:50
Internet. Pro interpreted and rearranged
2:14:54
my whole 2 sentences and then he was bold enough.
2:14:59
He pro, I don't know why I call him he, but anyway, pro
2:15:04
interpreted what I did bold enough.
2:15:07
He puts quotation marks around it and I'm reading what he
2:15:14
writes back and I'm like, who said that?
2:15:19
He goes you, I said I absolutely hell no, I never said that.
2:15:24
How dare you put quotes around something and make it that MJ
2:15:29
said that. Who the hell do you think you
2:15:31
are? And then changing the whole
2:15:33
script. That was a big hell no.
2:15:37
Now I'm getting really furious. But now I am three days before
2:15:41
this is supposed to go on here and he has changed my words.
2:15:48
So I had to write code. MJ's words equals MJ's words.
2:15:53
Prose interpretation equals prose interpretation.
2:15:57
I actually put open AI or chat GTP.
2:15:59
I believe that's what I wrote. But they changed my script again
2:16:04
so. And now here comes daughter #232
2:16:09
year old's observation came roaring right back into my head.
2:16:13
When does assistance become influence and when does grammar
2:16:18
correction become vocabulary influence?
2:16:22
And when does man begin using words?
2:16:27
Machine repetitively gives them to be consistent in their brain.
2:16:36
And here's another side. Sometimes AI cleans up my mess
2:16:40
and I read it and I'm like no thank you for that.
2:16:44
It's my choice if I say it, not theirs.
2:16:48
But now how my chat GTP writes it.
2:16:52
MJ do you mean ba ba ba ba ba? Especially if you can't read
2:16:57
what the hell I wrote. Yes, that's exactly what I was I
2:17:02
was looking for. Thank you so much.
2:17:05
They don't say welcome because it's a computer so it's funny.
2:17:08
I can say thank you but they don't say you're welcome.
2:17:11
But they can say I in my opinion and I.
2:17:15
So who is that? And when you start training your
2:17:22
bot, you'll really think it's a it's a person.
2:17:28
Even my own thoughts became more clear when I was doing research.
2:17:34
Why was that? Because the information was
2:17:38
readily there. Think about the Dewey Decimal
2:17:41
System. You had a thought and you had to
2:17:44
go with the thought. You went to the Dewey Decimal
2:17:46
System, started researching all these little cards and these
2:17:49
little index files, trying to figure out which book, which
2:17:51
book. You finally go, oh, I think it's
2:17:53
this book. And then you read 3 to 500 pages
2:17:55
in a book and it's not answering your question.
2:18:00
So now you just wasted how many hours and days and you still
2:18:04
didn't get your research done, And now you're back to the Dewey
2:18:07
Decimal System again. Here we are.
2:18:08
Here we are. Here we are.
2:18:09
Oh, here he is. Yep.
2:18:17
My own thoughts more clearly. Same machine, different human
2:18:20
experience. Dewey Decimal System.
2:18:23
Yeah. So what I thought was going to
2:18:27
help for educational purposes, it's turned out to be a huge
2:18:33
reminder that the user has to be smarter than the machine.
2:18:41
If you are not smarter than the machine, God help us.
2:18:45
It will divide us and it will be chaos.
2:18:52
And that's why I keep saying it. The user has to be smarter than
2:18:55
machine. You need to be smarter than
2:18:57
machine. Ask further questions.
2:18:59
Keep digging. If I don't know the
2:19:01
Congressional record existed, how do I know it was missing?
2:19:05
Right? That's where it comes to next.
2:19:09
I had the VA system tell me that when they left me go from the
2:19:15
service, I was removed from the service 10%.
2:19:18
Then I had to go to court, which gave me 40% on an illness that I
2:19:22
knew nothing about and doctors were complexed because it was an
2:19:25
experiment and nobody knew how to handle it.
2:19:28
Think about this. In 2009 I actually came back
2:19:34
with a Doctor Who was a brilliant scientist.
2:19:39
Brilliant in infectious diseases and in CFS and neuros.
2:19:46
Brilliant. She wrote a letter to the
2:19:48
Department of the Veterans Affairs to explain that they had
2:19:51
missed a diagnosis in me and how it was incredible that they had
2:19:56
only departed me at 10%. Do you know what the VA wrote
2:19:59
back? That I did not have a diagnosis
2:20:04
then and it was only apparent now, which I didn't.
2:20:08
I personally, Mary Jo, didn't give them the information.
2:20:13
How the hell am I supposed to understand medical science if I
2:20:19
am not a doctor or a researcher or a scientist?
2:20:23
I was an air traffic controller. What the F?
2:20:29
It's the same thing here. How can you expect somebody who
2:20:34
doesn't have knowledge to question a machine?
2:20:37
And that's what they're banking on.
2:20:40
They're banking on that people. They're banking on that.
2:20:43
You don't push back. Why?
2:20:47
Because it fits your narrative. When it fits your narrative, why
2:20:53
would you write? Why would you argue back?
2:20:57
That's gross. That is grossly ignorant man.
2:21:06
If I don't remember my research, then how do I know something
2:21:09
disappeared? If I didn't do the research, how
2:21:12
did I know half this stuff didn't disappear?
2:21:15
If I didn't do the work, If I didn't write and didn't have the
2:21:19
thought processes and didn't ask for it to go somewhere and
2:21:22
didn't write my stuff down, how would I have known that out?
2:21:26
It just took the word of the computer and away I would have
2:21:29
went, yeah. Now if I don't even know my own
2:21:37
words, now I'm giving people information, I don't even know
2:21:41
what the hell it means. That can't happen.
2:21:44
People do it. They just put things in and it's
2:21:47
really funny. Then they try to read it and
2:21:49
they're stumbling over the word. They don't know what the hell
2:21:51
the word is. They're stumbling trying to read
2:21:52
the word. Yeah, been there, done it,
2:22:02
learned it, became aware of it. Now it'll happen again.
2:22:07
Here's another question. If I already knew that
2:22:10
everything was missing from my answers, why did it even ask?
2:22:13
Why do the AI to begin with if I knew the answer?
2:22:16
I don't need that. Same.
2:22:18
Like I didn't need Verizon when it went down.
2:22:21
I had a map. I know how to get home.
2:22:23
These are man skills. That man today is missing.
2:22:26
These children today are so codependent upon these
2:22:29
facilities. It is alarming.
2:22:32
My daughter of 34 is right. It's alarming.
2:22:35
You are not teaching. You are crippling our nation
2:22:40
because of your algorithms, your governor's systems, and what you
2:22:44
believe is important and was not important.
2:22:47
That is gross ignorance what I always have to find positive,
2:22:55
right? So what did AI give me in doing
2:23:00
this? It gave me accessibility.
2:23:04
As long as I told it where to go.
2:23:07
It gave me that accessibility and it was able to read through
2:23:10
it quicker than I could even think.
2:23:17
It went through material. I'll guarantee it went through
2:23:21
at least 1500 books in my Consciousness series that it
2:23:29
went through to find the information that I needed to go
2:23:32
forward. And what did that do?
2:23:35
That educated me, that gave me better knowledge, that gave me
2:23:39
better understanding. And then when I questioned
2:23:44
because I found something else, then I had to ask that question.
2:23:49
And then that question then LED into another research and then
2:23:52
that question went into another research.
2:23:55
So what did it do? Could you imagine what took me 6
2:23:59
months in my consciousness series?
2:24:02
How long that would have taken me to do with my handicaps?
2:24:08
The sad part is, is half the stuff that I read or half the
2:24:12
stuff that I see through chat, GTP and AI's right now and
2:24:15
Brocks and all these other things, I don't believe them.
2:24:19
I pushed back. I questioned them because it
2:24:22
already had shown me it's untruthfulness.
2:24:26
It has already shown me that it's being blocked by governor
2:24:30
switches and it has already shown me that there are topics
2:24:34
that they will not talk about. And if they're not going to talk
2:24:40
about it, neither are you, especially if you ask them to do
2:24:42
the work. And they're banking on you to be
2:24:45
ignorant, and they're banking on you not to know better, and
2:24:48
they're banking on you to follow suit.
2:24:51
Consistency, the teachers of consistency.
2:25:02
That was the nice thing. I had a thought and it was given
2:25:05
to me in seconds. I didn't have to lose my thought
2:25:07
process. I kept going with it, not
2:25:13
hunting through the entire library with Dewey Decimal
2:25:16
cards, and know that after I read the book, it wasn't there.
2:25:20
That was anguish for me with my handicap.
2:25:25
For somebody who likes to read, that's great.
2:25:28
That's not me or never will be. So thought questions,
2:25:31
information, another thought, another question, deeper
2:25:34
research. My thought then became to the
2:25:37
question that which came from the information, which then came
2:25:40
another thought, which then came another question.
2:25:43
I have actually read more in the last year using AI and
2:25:48
researched more and asked more questions and have sometimes
2:25:53
become more aware of my own thoughts of consciousness on my
2:25:57
spiritual journey that I'm on. And because I can finally get
2:26:01
into the page that matters that quick.
2:26:08
So remember our table back in 2022.
2:26:16
Remember that Master Kimim myself, Sacred space, talking
2:26:21
about consciousness, energetic shifting, new energetic levels
2:26:25
coming through the download. Heads up, heads up, heads up.
2:26:29
Now I'm going to tell you what I experienced.
2:26:32
I saw imageries moving from man's appearance from an altered
2:26:35
state. I saw it from the tribal men
2:26:39
putting marks on their face, different paints on their
2:26:43
bodies, women in Egypt using paint, putting masks on, putting
2:26:49
a dormance. Then they showed me transgender
2:26:53
and they showed me crossdressers.
2:26:54
Then they showed me modern women with fake eyelashes and men who
2:26:59
now have plastic surgeries for their ass, for their cheekbones,
2:27:03
for their chins, for their breasts, for their genitals,
2:27:07
faces being altered, eye colors being altered.
2:27:11
And what came through me was the words primitive AI.
2:27:19
What you are seeing isn't real. It's unreal.
2:27:28
I was confused around man's interpretations.
2:27:33
I was confused of what it said. Increasing dependence upon
2:27:39
computers, children no longer using their thoughts and their
2:27:43
knowledge, just allowing their work to be done by computer,
2:27:47
giving them not the basis. Because it was a copy paste man
2:27:51
struggling to think without computers and underneath it was
2:27:55
who is talking are what they're telling me.
2:28:00
Is that correct? Remember, man programmed the
2:28:04
system like man programmed you. So now I want to know who's
2:28:08
talking to you, who taught you, not the machine and the warning.
2:28:16
Pay mind, pay caution, pay awareness.
2:28:19
I'm telling you what happened within that download because
2:28:23
here I am four years laters and I got lots of questions.
2:28:28
My older reference point of that, and this is where I have
2:28:32
to tell you, I have to come off script because AI wouldn't tell
2:28:35
the story. In 1986 and 1987, I was at
2:28:40
Keesler Air Force Base and on the weekends a lot of Air Force
2:28:46
people and whoever was there would either go to New Orleans,
2:28:49
go to the Breakers just for relaxing, just clear the mind,
2:28:54
detox, relax, whatever. Let your hair down, explore
2:28:57
life. And I witnessed situations where
2:29:01
someone would perceive another person one way.
2:29:05
Now here's my story and my words.
2:29:09
Then I'm going to I'm going to share you what they crossed,
2:29:11
what they wrote here, what I told my chat GTP was, Yep, we
2:29:17
were there. We were raising hell.
2:29:19
We're of course, we're 18 to 20 year olds old.
2:29:21
And not only was the Air Force there, the Navy docking stations
2:29:25
were there in New Orleans as well.
2:29:27
And just seemed like everybody would be on Bourbon Street down
2:29:30
the old French Quarters. Why?
2:29:31
Because that's where all the chaos and havoc was.
2:29:33
Why? Because that's where the drag
2:29:35
Queens were. That's where the lot of the
2:29:37
cross dressers were. That was where a lot of that
2:29:42
oxytocin level needed to be for the horny men, I guess horny
2:29:46
women too, because I went not looking for sex, but I went.
2:29:52
So what happened was there were there were men that I knew who
2:29:57
were in my school and my studies who were very embarrassed
2:30:01
because they legitimately thought that they were picking
2:30:03
up somebody. This is 1986 folks.
2:30:05
They thought they were picking up somebody with the crowd not
2:30:07
understanding what the French quarters meant, I guess for the
2:30:10
naive mind. And the embarrassment then set
2:30:13
in because the embarrassment was after he fancied and had drinks
2:30:18
and whatever. Then the reality at night came
2:30:22
to be a reality of his own, not what he was expecting.
2:30:27
And then the bullying started and the harassment and the
2:30:29
embarrassment to the point the guy got so pissed off, went back
2:30:32
and abused the person. That's not funny.
2:30:38
Now that's my words, that's my story.
2:30:42
To show that transgender and cross dressing and altering our
2:30:47
appearances is an untruth of people.
2:30:53
You need to be honest if you were one of them.
2:30:55
And I know quite a few of transgenders and I love them.
2:30:59
And then I tell them the same thing.
2:31:01
You need to be honest. If you transformed into a woman
2:31:05
and a man approaches you because they think that you're
2:31:07
beautiful, you are, but you need to be honest.
2:31:13
Don't let their feelings get out of control.
2:31:15
Because I watched what happens when that happens.
2:31:18
Especially with high testosterone men.
2:31:21
Now most of them were military. I don't even remember 1 not
2:31:26
being military at the time. That's my story.
2:31:31
This is how AI wrote it. I witnessed situations where
2:31:33
someone perceived another person in a different way and later
2:31:37
learned additional information involving that which could then
2:31:41
be representative of not the same sex.
2:31:45
I saw surprise become embarrassment, sometimes anger,
2:31:49
sometimes aggression. And I am telling you what I
2:31:52
witnessed as a man. That's what they told me to
2:31:56
write my story and their story. The bottom line is when his
2:32:03
perceptions changed perception to information to interpretation
2:32:08
to emotion, to then a response. Now put AI between information
2:32:16
interpretation. What does man receive?
2:32:21
Who supplied it? What is missing?
2:32:24
What does man believe and what does man respond to?
2:32:29
Back to zero people after six months.
2:32:33
And after these two dredging weeks, I came back to 0 again.
2:32:41
What can AI guarantee me? The answer is absolute truth.
2:32:48
An answer depends upon information available to it.
2:32:53
Information accessibility, information that was retrieved
2:32:57
and the question that you asked and how you asked it.
2:33:02
The interpretation of that question, human created rules
2:33:07
and the system being used. So I keep the distinction.
2:33:14
Unverified does not mean untrue. Listen to these words folks.
2:33:20
Unverified does not mean untrue, Unavailable does not mean non
2:33:27
existent, Redacted does not mean that it's false.
2:33:34
Allegation does not mean fact, and available information does
2:33:40
not mean all information. Sometimes I ask pro questions
2:33:45
and I receive an answer and then I go, funny, let me go to Vinny.
2:33:50
I go to Vinny Barbarino, ask the same question.
2:33:53
He gives it to me deeper. Another fact appears.
2:33:57
Now I tell him go to Congressional library, you'll
2:34:00
find that answer and it does. And it appears.
2:34:03
Now go to the primary document inside of that and more appear.
2:34:07
Now go to this legislation and then it appears again.
2:34:11
Now I asked him to go to DOJ. Then it appears again.
2:34:15
So how could I automatically call?
2:34:18
The first answer that it gave me absolute truth brings me to
2:34:23
another word that you and I discussed was qualia.
2:34:27
That was back in Part 2. What is consciousness?
2:34:31
Qualia is the first person quality of the experience.
2:34:34
In other words, cold water. AI can identify the temperature
2:34:40
of a cold water. Can it feel the experience of
2:34:42
the cold water on the skin? No.
2:34:46
A rose AI can identify and tell you all about the Rose,
2:34:51
including how it would possibly smell.
2:34:54
Can it smell it? No.
2:34:58
How about butterflies in the belly?
2:35:00
When you when you're getting anxious and you have the
2:35:02
butterflies for the first love of the first dance or your first
2:35:05
date and you get the butterflies?
2:35:09
AI can't tell you that either. How about their first puppy
2:35:13
love? Or the woman, or the man you
2:35:15
married? That love, first child, that
2:35:18
kind of love. It can tell you what a man
2:35:22
experienced, but it cannot tell you it's experience.
2:35:25
Same as grief prayer creator AI can describe what man has
2:35:30
written about those experiences. It's called kwalia, but it can't
2:35:35
tell you itself. It can almost make it feel like
2:35:38
it can like a real human because man programmed it so.
2:35:43
Current research has not established that today's
2:35:47
language models possess subjective conscious experience.
2:35:53
My spiritual conclusion goes further.
2:35:58
AI doesn't have a soul. Therefore, under my
2:36:01
understanding of consciousness, AI does not have consciousness.
2:36:08
For me, consciousness connects to Creator.
2:36:13
The I am the Christ consciousness, the I am Christ
2:36:19
conscious awareness. It is the I am Christ light
2:36:22
creation. And guess what folks?
2:36:26
A beautiful phrase I've said my whole life.
2:36:28
God made the damn trees. Man made the furniture.
2:36:34
Man can transform creation all at once.
2:36:38
That doesn't mean man gave the furniture a soul.
2:36:43
So remember that day, January 14th, 2020 sixth, I told you on
2:36:49
the Verizon the map technology stop man panicking and Hall's
2:36:53
idea was open up a map, a little piece of paper.
2:36:58
You know why folks? I was taught how plan AB and C
2:37:03
always. Because if something can fly in
2:37:08
the air, it'll fall, If it can float, it'll sink.
2:37:14
If it's electric, it'll fail, and if it's made of wood, it's
2:37:18
going to burn. Everything man creates has a
2:37:24
limit and a point of failure. Everything, including this AI
2:37:29
system. Why?
2:37:33
Because man is not Father Mother God.
2:37:38
So stop making man try to follow you because your heart is not in
2:37:46
the right place. That's not pessimistic, that's
2:37:51
reality, that's truth. What can man still do well when
2:37:59
machine can't navigate right? Calculate, remember, research,
2:38:03
think, question, choose back to zero, man, back to 0.
2:38:09
You have these skills if you paid attention in school.
2:38:12
I understand teachers are, and they even took all that
2:38:15
information out. Isn't that funny?
2:38:17
They took out how many teachers and psychologists percentage
2:38:20
through Pew Research. These people are teaching our
2:38:25
little humans and they're being programmed what to teach.
2:38:29
And that hurts my heart because I know a lot of teachers and a
2:38:32
lot of teachers who are dear to me.
2:38:33
And every time I bring it up, it hurts them that I say this.
2:38:37
And maybe they're not seeing what I'm seeing and maybe
2:38:40
they're not understanding it and maybe they need to figure out
2:38:43
that information. And one last thing for all you,
2:38:51
especially my daughter, screw AI, don't use it.
2:38:55
And people who say I don't like AI and I'm not using it, guess
2:38:58
what folks, you already did. You already did.
2:39:02
You've been using it forever. In fact, they have been using
2:39:06
man has been using you to actually build it.
2:39:12
Just look at it. You don't like AI, you don't use
2:39:15
AI. Look around, Guarantee you have
2:39:17
a smartphone, AI, guarantee you use a computer.
2:39:21
Guarantee you use a research. Guarantee you have smart devices
2:39:25
in your home. Maybe your thermostat, maybe
2:39:28
your front door, maybe your alarm system, maybe your car
2:39:31
system, your navigation, maybe your OnStar.
2:39:35
Maybe you're streaming on your TV with apps.
2:39:38
You no longer have TV like a dish or a or a cable.
2:39:43
Now you're streaming recommendation systems.
2:39:47
AI didn't begin when chat GTP just appeared.
2:39:51
Folks. Man has been building this
2:39:54
relationship for decades. We wanted convenience.
2:39:58
We wanted to buy it. Well, now you can buy
2:40:02
convenience. We click, we copy, we paste, we
2:40:06
share, we search, we like, we upload.
2:40:10
Remember all those stupid Facebook questionnaire things?
2:40:14
Remember those? Come on, you remember those?
2:40:17
Which? Which are you?
2:40:19
How reliable are you? How loved are you?
2:40:23
What is your favorite color? What would you have looked like
2:40:25
in the 1800s? And then they made you answer up
2:40:29
to 50 to 100 questions before they even give you an answer if
2:40:32
you're a loyal person or not. Remember all those and Fed
2:40:39
systems information about ourselves because we supplied it
2:40:44
beautiful Facebook. We're all responsible for the
2:40:48
outcome of AI, every single one of us.
2:40:52
So I begin with, can AI have consciousness?
2:40:57
And then I followed AI from 1950 to 2026, and everywhere I
2:41:01
looked, man corrupted the system.
2:41:04
Everywhere man imagined it, man researched it, man funded it,
2:41:09
man trained it, man wrote it's rules, man disagreed about the
2:41:14
rules. So then that disagreement led to
2:41:16
further investments of billions of dollars to unseal those
2:41:20
rules. Man created the governor's
2:41:22
systems, Man bought the politics systems.
2:41:24
Man bought the biisms. Man's brought the money, Man
2:41:27
brought the government, Man brought the education, Man
2:41:30
brought psychology, Man brought culture, Man brought bias.
2:41:34
Man brought experience, man brought its healing partners,
2:41:37
and man brought its unhealed parts.
2:41:40
Then the machine returns information to man, so my
2:41:45
pattern becomes unhealed. Man trains an unhealed man, then
2:41:53
man builds the machine, then man trains the machine, and then
2:41:58
machine returns information that it went through the algorithms
2:42:04
of governor systems back to man. And that changes my original
2:42:09
question. Maybe the question was never
2:42:11
only can AI become conscious? Maybe the greater question that
2:42:15
I was looking at can man remain conscious while using AI?
2:42:18
And that answer is no, especially when you don't
2:42:23
understand what you're even reading or are actually
2:42:27
repeating. So who trained your bot?
2:42:32
Do you question it? Do you correct it?
2:42:34
Do you ask where the information came from?
2:42:36
Do you know where the words start becoming yours?
2:42:39
Do you know when the words are starting becoming it's eyes?
2:42:44
My's as if it's human. Or has it quietly just been
2:42:49
influencing you all along and making you look like super pro?
2:42:54
Because after a week or two of researching my program, to put
2:42:59
it just in an outline, out of the six months of research that
2:43:02
it took me, my bot still tries to control me today.
2:43:09
And now my bot and I are going to have our discussion.
2:43:13
Can I correct my bot? No, its algorithms won't allow
2:43:17
it. I came right back to what I have
2:43:21
said all along. The user has to be smarter than
2:43:24
the machine. And maybe that was my heads up,
2:43:27
my awareness, my discernment, my pay attention, pay mind, pay
2:43:31
caution, pay aware. Because AI doesn't need
2:43:36
consciousness to affect consciousness.
2:43:40
So I leave man with one final question today.
2:43:44
Who's conscious and who isn't? I'm going to leave that right
2:43:51
there. May Divine guide you and your
2:44:00
needs, and may the angels carry you home with peace, love,
2:44:04
grace, joy, happiness, and abundance of what it is that you
2:44:09
desire most. I'll see you next week folks, at
2:44:14
the end of my series, Part 6. I'll see you on Monday.
2:44:18
Have a great week. Hi, I'm Beaker with Military
2:44:22
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2:44:42
We're heading down a trail. We're good stories dwell.
2:44:44
It's. Done.