How GenAI Can Fast-Track Your Career

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Less than a year and a half
later, this dude is the head of

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AI.
He he he will, he will.

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I I I would estimate in the next
three years he will 10X his

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salary.
I got a real life story, Ralph.

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So that was a gentleman.
I'm going to, I'm not going to

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share his name.
There's a gentleman and I saw he

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had something and he was fresh,
fresh out of school and he was

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put in an opportunity and, you
know, kind of a, you know, he

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was a, you know, service desk
help help desk guy and he was

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put in a situation to to work
with the leaders and, and I'm

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like, OK, well, you know, when
leaders, you know, you could

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deal with some of everything,
right?

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Wireless network, blah, blah,
blah.

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So I invested, I'm like, hey
man, I got some learning credits

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with Cisco.
I'm going to send you to get

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this basic networking and, you
know, training.

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He just, he had something,
right.

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Well, the organization start,
you know, a few years later

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start moving into this, you
know, kind of AI space and start

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doing these campaigns to can you
find something to make more

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efficient?
Well, this guy jumped all in.

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Now he's again, in terms of
technical rank, he was

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considered, you know, service
desk, you know, that kind of job

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in terms of the technical stack,
right, hierarchy, you know, you

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know, you're starting that
you're starting, you know, so

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this guy goes all in on that,
right?

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Opportunities.
He's like, I'm gonna try this,

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try that.
And next thing you know, I get

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an e-mail.
Hey, you know, we have this

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internal AI project and he's
kind of the face of he's

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leading.
And I'm like, OK, that's neat,

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you know?
And so he included me because I

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was a early sponsor for him.
So I'm giving him feedback.

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Yeah, I think it's great.
It was a little slow here or I'm

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searching here.
I didn't get this blah blah

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blah.
You know bro, less than a year

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and a half later, this dude is
the head of AII.

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Know who?
I know you know who I'm talking

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about.
And all I could say was, first

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of all, it was his hunger,
right?

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I saw he was hungry from the
beginning and and, and so, you

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know, I saw that and I'm like, I
want to invest in it, but also

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too, there was some benefit to
me because I know he was

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addressing the higher ups.
The more information I can get

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to him, the less that's going to
come to me.

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So it was a it was, it was I
talk about this all the time.

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It's a strange value.
So I'm going to help you, help

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me help you.
That's right.

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So as a result of that, that
kind of start of his journey,

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right?
And again this this.

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Terry, do you realize, do you
realize you changed the

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trajectory of his life?
He is never going to leave AI.

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Now.
I know who you're talking about

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because he's a good friend of
mine too.

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He's never going to leave the AI
industry.

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And he is so far ahead of his
peers like they don't even know

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what's happening right now.
No, they don't.

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Right when you could take on a
title.

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Yes, he got a title.
It's the head.

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That says ahead of AI, I'm
trying to tell you he he, he

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will.
He will, I, I, I would estimate

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in the next three years he will
10X his salary, right?

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Because, because he saw the
opportunity and, and you, you

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like, you push them in that
direction.

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And you know, now he sees like
this is, this is the future.

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Yeah, yeah.
And and this is this is

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available to anybody right now.
Yep, and and he took.

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A risk?
He took a risk, but he was like,

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this is important to me because
here's the I'm going to be

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honest with you.
There are folks were like, I

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don't know why he's doing this.
I don't know why they why, why

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he's getting the opportunity.
Well, he's getting the

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opportunity because he was
hungry.

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Yeah.
But he showed passion.

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That's right.
Let me use a better word.

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Right.
I'm I'm sorry.

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I'm sorry.
I'm you know, we had basketball

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this morning, so I'm using
those.

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I'm using those poster.
How hungry are you?

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Go get it.
All right.

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He had passion.
I'm sorry.

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Yeah, yeah, yeah, yeah, yeah.
No, that's, that's good, man,

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That's good.
Yeah.

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If you, yeah, yeah, No, I, I, I
think I have to sit back and

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smile when I think about,
because you're right.

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He was very passionate and he,
he definitely was never lazy,

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always wanted to go get it.
And now it's paying off for him.

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And yeah, I, I know that he's
going to do well.

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So that's.
And it's just a story, right,

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that shows that if you embrace
it, it can change your

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trajectory, right?
Everyone's going to be a little

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different, right?
But again, if you embrace it

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early, right?
He was an early embracer of it.

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Yes, yeah.
So yeah, that's also the story.

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Just get, you know, just get it
early.

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I'm sorry.
Go ahead bro.

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No, no.
But to your point, right, we are

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in this moment in history right
now where it's still optional,

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yes, right.
But if you go get it, you're

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going to stand out.
Yes, it's.

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Going to be VM Ware.
It's going to be VM Ware.

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Yeah, all over again, right.
And it's going to be a part of

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everybody's job.
And if you want to have your

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job, you're going to have to
know how to do this.

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Well, The opportunities to take
those advancements, those leaps

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forward really quickly, those
are going to be gone.

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Right now is the time to to, to
leverage that, you know, that

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technology to make those big
changes in your career, right?

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For sure.
So yeah, yeah.

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And another pro tip shout out to
Gary because we were talking

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this week and he he said, hey,
you know that pro tip you gave

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me about using a feedback loop
in, in, in AI that really helped

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me out.
I just want to reiterate again,

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right?
So a is first answer is probably

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not going to be the 100% correct
output that you want.

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You have to learn how to make it
give you feedback on what you

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told it to produce, right?
You know, so if you said, hey, I

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want you to do this and I want
it to look like that and it

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gives you an output, you don't
just take that as face value.

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You know, a pro tip is the next
thing you ask, it is OK, I want

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you to give yourself feedback
based on what I asked you to do.

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9 times out of 10, it'll say,
oh, you know what?

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I forgot that.
I forgot that because AI is not

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perfect, right?
But by incorporating those

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feedback loops into your
prompts, into your questions,

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into your, into your
interactions with AI, you will

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drive to a solution that is.
Yeah, so, so, so yeah, I got I

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got a real life example, right.
So I'm watching the football

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game last week.
I think it was what was the big

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game last week?
It was last.

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Was it Georgia and somebody?
What was the big game last night

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last week?
Saturday night game.

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Yeah, Saturday night game.
I think it was yeah, I think it

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was gosh, I forget who it was,
but anyway, so I'm watching it

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right?
And so this commercial comes up

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about the N out and about some
bill or at that.

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They want us to sign right?
It's about let's make it fair.

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And I'm like, I think I know
what that's about.

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So of course I go to the
assistant.

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Hey, can you give me a breakdown
of what the blah blah blah bill

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is that they're talking about
that's in the Senate or they

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want us to vote for Yeah, so I
get all this feedback, right?

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And they're giving me the way
they're giving me the

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information is in a manner that
that's a it's not giving me it

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in a non biased fashion.
So I I, but I, you know, I keep

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talking to it and I'm like, hey,
why are you giving me the

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information with this tone?
Oh, I'm sorry, you're right.

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I need to give this in a non,
you know, pro or against manner.

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I'm, you know what I told him.
I said it's too late.

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You've done it already.
Because I'm look, look, I may

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lose some friends on this.
I'm pro athlete when it comes to

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NIL, right, Because, you know, I
know the first hand, you know,

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you may say they getting I don't
want to.

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I don't know if anyway, let me
just get off myself.

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Anyway, I'm like, Hey, can I
just get the information?

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It was like, I'm sorry, let me
give it to you in a in a more

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neutral position.
I'm like, thank you.

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I just want the information.
That's a fantastic example,

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especially now with, you know,
our country being so polarized,

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you know, the left or the right,
you know, for this and against

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that and you don't know exactly
what to believe and what not to

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believe.
You can utilize this tool to get

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yourself some facts right.
To Terry's point, you got to

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tell it.
Hey, I don't want your, your

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response to be for or against.
I just want it to be purely the

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facts and help me understand
this so you can get some clarity

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amongst all the noise that's
actually.

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And and it's his right, because
the one thing we want to have is

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get the data because you, you
also too, you got to understand

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this right?
It's going out and pulling data

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from sources that may have an
opinion.

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Either way, you don't want the
opinions.

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You just give me the give me the
facts as as they've been stated.

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And then what I will do is draw
a conclusion from what I'm

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receiving.
Well, in the same way, hey, give

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me information about what Cisco
is doing in terms of these data

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centers.
Now what I do know in terms of

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that.
And so Ralph, to your point on

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that is I, I had the pleasure
and thanks to Cisco and some of

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our other partners to attend
Cisco Live this past year.

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The data centers that you're
talking about these are highways

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specifically for nothing else
but AII mean rolls and rolls and

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rolls of GPU's right to process
super highway.

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They're talking about I'm
telling let me remember I have

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to remember my number my my date
on this.

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But you're talking about these
are not like I remember 100 gig.

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These chassis are 100 gig ports
yeah, throughput.

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Yeah, this is not a gig.
You know, we made we were

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excited about 25 gig 10 gig.
No, this is 100 gig, right, Not

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single, but they're do bind it
together.

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Yeah, you know, and so the
amount of traffic, the amount of

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data that this that's going to
be piped through these data

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centers, man, it's it's it's
going to pull it's going to pull

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as much power as a city.
Yes, yeah.

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And and just just a quick,
quick, quick shout out selfless

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plug.
Terry, you remember back in man,

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I don't know, this had to be
like 2006.

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I was like TI got this idea.
I remember that, I think about

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it all the time.
You were on it, bro.

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Yes, I.
Had this idea of distributing

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computing back in 2005, 2006.
I just didn't know what to do

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with it and here we are today.
Yes, and that's exactly what

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they did.
When you said you said TI,

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remember, I remember, like you
said, T we got to build

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something.
We're compute, storage,

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networking.
It's all in 111 chassis.

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Of course, there's been
iterations of it, right.

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I think the best at the consumer
or the OR the enterprise level

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at this point, I think is new
Nutanix.

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I think they were doing it the
best, I think here recently.

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But yes, but you had that into
because remember, you took it to

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what was the guy at?
Oh, gosh.

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Who we had gotten our one of our
chassis from who Chris used to

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work for.
What was the name of that

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company?
And you, you took it to the CTO,

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remember, because he was a
musician, too.

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You took that idea to him.
Yeah.

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Yeah.
You were there, bro.

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You were there years.
Yeah, I was you.

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You were 20 years ahead.
I I distinctly remember saying,

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you know, what if we just had a
whole rack of nothing but CPU I.

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Remember that.
Right.

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00:12:55,480 --> 00:12:58,080
You know, and a whole rack of
nothing but memory by itself was

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distributed and then something
controlling it all.

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00:13:00,880 --> 00:13:03,200
So just want to make, you know,
I didn't invent the Internet,

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00:13:03,600 --> 00:13:06,560
but I didn't have that idea.
Ralph, Hey.

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00:13:06,720 --> 00:13:08,200
Hey again.
I hey.

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I'm a witness.
I remember.

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00:13:10,480 --> 00:13:12,440
You don't only witness yet
because you know the person I

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00:13:12,440 --> 00:13:14,280
told.
We were I, I see it.

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00:13:14,360 --> 00:13:17,040
I see that, man.
That conversation comes to me a

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00:13:17,040 --> 00:13:20,640
lot like Ralph was.
It's crazy awesome.

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00:13:20,640 --> 00:13:24,400
It's crazy.
Guys, again, right, this is all

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00:13:24,400 --> 00:13:29,120
about jumping in when it's in
it's we are in the infancy right

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00:13:29,120 --> 00:13:32,400
now of Gen.
AI and moving on to a gentic.

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We'll get to that because I got
a guy I want to bring on here

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00:13:35,680 --> 00:13:38,360
when we start talking about a
gentic and he's doing some

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00:13:38,360 --> 00:13:42,040
things with a platform out
there, man, that is, I mean,

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just revolutionary.
And when, when they talk about

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00:13:44,360 --> 00:13:49,960
people are building apps with
AI, they are and they're not.

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00:13:50,360 --> 00:13:53,960
These are not technical people.
They just have an idea.

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So here's here's the beauty of
what, and I think we use this on

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the first episode, we said AI
can supercharge your idea.

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00:14:04,760 --> 00:14:07,040
Yes, that's it will supercharge
it.

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And if you can think of it,
yeah, there is a platform out

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00:14:12,080 --> 00:14:15,120
there that will help you realize
it sooner.

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00:14:16,920 --> 00:14:20,320
Hey, hey, if we had AI back when
I had that idea, you and I'd be

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00:14:20,320 --> 00:14:22,680
millionaires right now.
Yes.

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00:14:23,440 --> 00:14:26,120
Yeah, Yeah, yeah, yeah.
Because I mean, it was, there

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00:14:26,120 --> 00:14:30,720
was just no way to, to, to, to
get that to, you know, fruition,

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00:14:30,720 --> 00:14:32,400
right?
It was hard to conceptualize.

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00:14:32,400 --> 00:14:36,200
Yeah, it was conceptual, but to
move it from a conceptual to a A

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00:14:36,440 --> 00:14:40,840
and, and be connected into
those, into those, because

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00:14:40,840 --> 00:14:43,040
here's the deal, right?
And here the Ralph, I think this

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00:14:43,040 --> 00:14:46,480
really kind of brings us to why
we're doing what we're doing is

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it's about access.
But access starts first with

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00:14:53,840 --> 00:14:57,360
information and understanding
where to go, right?

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00:14:57,520 --> 00:15:03,080
And so this platform that we've
created is about creating a

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00:15:03,320 --> 00:15:10,800
access to these platforms and
areas that we traditionally

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00:15:10,800 --> 00:15:14,200
didn't have understanding or
knowledge of, right?

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00:15:14,200 --> 00:15:16,600
Just because we weren't in those
circles.

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00:15:16,600 --> 00:15:20,440
Well, God has blessed us to be
at the table.

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00:15:20,440 --> 00:15:25,240
God has blessed us to get favor
with different persons, right?

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00:15:25,240 --> 00:15:27,240
I'm able to do what I'm doing
today with lift.

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00:15:27,480 --> 00:15:30,440
Like man, I remember when I
launched Lift Life Technology

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00:15:30,720 --> 00:15:34,200
and all I could think is how am
I going to get, I know the

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00:15:34,200 --> 00:15:37,160
technology, but how do I get in
front of people?

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00:15:38,840 --> 00:15:41,680
God allowed me to connect with
the right people.

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00:15:42,000 --> 00:15:45,720
So now that I'm connected with
those people, I can connect you

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00:15:45,720 --> 00:15:48,080
with those people through
through the information.

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00:15:49,320 --> 00:15:52,120
Yes, yes.
Right, Ralph?

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00:15:52,120 --> 00:15:56,000
Has connected with people so now
we're connecting you to those

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00:15:56,000 --> 00:15:58,760
people through the information
we're not giving.

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00:15:58,760 --> 00:16:01,840
Hey, hey, hey, John, this is
this is Mark.

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00:16:02,120 --> 00:16:04,920
We're not necessarily giving you
that face not say that we can't.

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00:16:04,920 --> 00:16:07,960
But what I'm saying is what
we're doing is giving you

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00:16:07,960 --> 00:16:10,600
information to get to the
places, right?

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00:16:10,600 --> 00:16:14,440
Whether it's a methodology,
whether it's a way of thinking,

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00:16:14,600 --> 00:16:20,040
whether it's a, a concept on
networking, right?

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00:16:20,040 --> 00:16:24,720
And we point you in those again,
you know, we were trying to use

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00:16:24,720 --> 00:16:27,640
the little resources we had, the
little the people we knew.

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00:16:27,920 --> 00:16:30,920
And it was just, it was hard to
get it off the off the mat, so

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00:16:30,920 --> 00:16:34,240
to speak, so.
No, that's good, that's good,

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00:16:34,240 --> 00:16:35,200
that's good, that's good, that's
good.

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00:16:35,640 --> 00:16:39,360
So you know, just, you know, in
closing, you know, we just, we

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00:16:39,360 --> 00:16:44,000
do want to encourage our mindset
of experimentation and iteration

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00:16:44,000 --> 00:16:47,640
when working with AI, right?
Hit it with any, any, any

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00:16:47,640 --> 00:16:50,280
question you have, nothing is
off the table, right?

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00:16:50,280 --> 00:16:52,760
You know, put it out there, see
what it comes back with.

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00:16:53,160 --> 00:16:57,600
Remember that your interaction
with AI is a continuous

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00:16:57,680 --> 00:16:59,640
iteration, right?
You throw.

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00:16:59,640 --> 00:17:03,160
So I, I've always said that, you
know, the, the, the speed in

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00:17:03,160 --> 00:17:06,520
which the, the, the society
evolves has been based on how

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00:17:06,520 --> 00:17:09,800
fast information has been able
to spread across the world,

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00:17:09,800 --> 00:17:12,160
right?
Let's just go back to, you know,

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00:17:12,560 --> 00:17:14,960
biblical days.
People had the right stuff on

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00:17:14,960 --> 00:17:18,000
scrolls, but how did other
people, you know, on the other

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00:17:18,000 --> 00:17:19,760
side of the country get that
information?

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00:17:20,079 --> 00:17:22,000
Those scrolls had to be carried,
right?

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00:17:22,040 --> 00:17:26,200
Copied, hand copied, right?
You know, so society evolved as

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00:17:26,200 --> 00:17:29,520
fast as the information couldn't
move when the Internet came.

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00:17:29,960 --> 00:17:33,240
Now you had information moving
from one side of the world to

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00:17:33,240 --> 00:17:36,240
the other in seconds.
Whereas it may have taken months

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00:17:36,240 --> 00:17:39,360
or maybe even years for books
and stuff like that to cross the

305
00:17:39,440 --> 00:17:42,800
ocean, right now information is
moving at the speed of light.

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00:17:43,160 --> 00:17:46,400
Well, now it's moving even
faster with AI because you're

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00:17:46,400 --> 00:17:48,320
asking questions and you're
getting exactly what you want in

308
00:17:48,320 --> 00:17:51,280
seconds, right?
You know, so our ability to

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00:17:51,280 --> 00:17:55,520
evolve is, is, is, is speeding
up and you want to be able to

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00:17:55,520 --> 00:17:57,960
stay on the, on the leading
curve of that, right?

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00:17:58,280 --> 00:18:00,960
So, you know, again, just call
to action, go to

312
00:18:00,960 --> 00:18:06,080
leadershipsovereignty.com/AI to
get your free AI tool kit so

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00:18:06,080 --> 00:18:09,000
that you can start using this
tool, you know, in your

314
00:18:09,000 --> 00:18:12,000
day-to-day personal and
professional life, you know, to

315
00:18:12,000 --> 00:18:14,640
take advantage of the
opportunity that it brings for

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00:18:14,640 --> 00:18:16,640
you.
Any any any final thoughts too?

317
00:18:16,680 --> 00:18:20,600
Look man, you got the assistant
in your pocket.

318
00:18:21,840 --> 00:18:24,600
In your pocket.
It's in your pocket, right?

319
00:18:24,600 --> 00:18:25,800
Ralph was talking about the
Internet.

320
00:18:25,800 --> 00:18:28,200
We had to wait.
We had to wait to get down at

321
00:18:28,200 --> 00:18:32,000
the computer, Bailey.
With the dial.

322
00:18:32,000 --> 00:18:36,680
Dial up, right, Right.
I mean, just think about our

323
00:18:36,680 --> 00:18:38,680
parents.
They had to wait for the

324
00:18:38,680 --> 00:18:43,400
newspaper, Yes.
They had to wait like 24 hours

325
00:18:43,400 --> 00:18:46,520
for the next print.
That's right, right.

326
00:18:46,520 --> 00:18:49,360
I mean, right.
I think what you shared that

327
00:18:49,360 --> 00:18:53,200
information aspect is, is
critical, right?

328
00:18:53,200 --> 00:18:55,320
Because think about it, right?
I mean, let's, let's take a

329
00:18:55,360 --> 00:18:56,440
step.
Let me walk through just a

330
00:18:56,440 --> 00:18:58,040
little slower.
Sure.

331
00:18:58,160 --> 00:19:02,440
It was on rocks first.
No, it was word of mouth first.

332
00:19:03,640 --> 00:19:04,960
Word of mouth.
Right, you have you know the

333
00:19:05,280 --> 00:19:09,080
story changed the story, right
Then they started.

334
00:19:09,080 --> 00:19:10,840
Man, this dude didn't messed up
my story.

335
00:19:10,840 --> 00:19:16,160
Let me put this on this rock.
But the problem, the problem is

336
00:19:16,160 --> 00:19:17,880
the person has to come.
Hey man, you got to come over

337
00:19:17,880 --> 00:19:19,200
here to The Cave.
You got to read that's.

338
00:19:19,760 --> 00:19:21,800
That's right.
That's how you think about it.

339
00:19:21,800 --> 00:19:24,040
The Egyptians, they used to put
this stuff all on the walls,

340
00:19:24,040 --> 00:19:26,280
right?
But the evolution part came

341
00:19:26,480 --> 00:19:31,120
when, if Terry introduces a
piece of information to me, I

342
00:19:31,120 --> 00:19:34,880
now absorb that information.
I now take my own personal

343
00:19:34,880 --> 00:19:37,600
experiences and I build a block
on top of that.

344
00:19:37,640 --> 00:19:40,480
That block didn't come until I
was able to absorb the

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00:19:40,480 --> 00:19:44,360
information that Terry gave me.
So evolution of society when as

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00:19:44,360 --> 00:19:45,800
fast as information could
travel.

347
00:19:47,280 --> 00:19:50,200
Now I have the information in my
glasses.

348
00:19:51,600 --> 00:19:54,840
I'm talking to my glasses.
And it's telling me, yeah, you

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00:19:54,840 --> 00:19:56,160
can do this, you can do that,
you can do that.

350
00:19:56,240 --> 00:19:58,960
So every time he gives me a new
piece of information, I build on

351
00:19:58,960 --> 00:20:00,840
top of that and I create
something new and I ask it

352
00:20:00,840 --> 00:20:03,760
another question he gives me.
So that reiteration process is

353
00:20:03,760 --> 00:20:07,680
happening constantly, right?
And things are evolving fast.

354
00:20:08,920 --> 00:20:12,120
Yeah, guys.
So look, get in getting rough.

355
00:20:12,120 --> 00:20:16,880
I think that is a brilliant,
brilliant, brilliant story about

356
00:20:17,400 --> 00:20:21,080
we develop as fast as the
information is able to be

357
00:20:21,080 --> 00:20:26,720
disseminated, received,
represented, and that that's

358
00:20:26,720 --> 00:20:29,880
that iterative process over and
over because and that's

359
00:20:29,880 --> 00:20:32,840
essentially what learning is,
right?

360
00:20:33,000 --> 00:20:38,440
It's the exchange of ideas.
Yes, yeah.

361
00:20:38,440 --> 00:20:41,280
Think of the medical community,
right?

362
00:20:41,320 --> 00:20:45,160
They have only been able to
evolve medicine as fast as

363
00:20:45,160 --> 00:20:47,520
information has been able to
travel because when one

364
00:20:47,520 --> 00:20:50,240
scientist figures something else
out, they have to spread it out

365
00:20:50,240 --> 00:20:52,560
to the rest of the world.
When somebody else figures out

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00:20:52,560 --> 00:20:53,960
what that is, they build on top
of it.

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00:20:53,960 --> 00:20:55,360
Correct.
But yeah.

368
00:20:55,800 --> 00:21:00,880
Great show, man, today I am I'm
glad that we, you know, added

369
00:21:00,880 --> 00:21:04,520
this bonus and and and this is
not the end right for for AI.

370
00:21:04,560 --> 00:21:06,040
This is really just the
beginning.

371
00:21:06,400 --> 00:21:10,480
Again, as I alluded to, there's
a, a friend that I've met over

372
00:21:10,480 --> 00:21:15,960
the last month who's in into he,
he's got AAI company and they're

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00:21:15,960 --> 00:21:18,800
doing some fabulous things.
And, and we'll start, you know,

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00:21:18,840 --> 00:21:22,960
in future shows, we'll talk
about agentic AI and what that

375
00:21:22,960 --> 00:21:26,160
means.
And again, that's another

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00:21:26,160 --> 00:21:30,360
evolution of what this
technology is bringing to

377
00:21:30,400 --> 00:21:34,480
enhance, you know, our
experiences and enhance our

378
00:21:34,480 --> 00:21:36,640
exchange.
So thank you, Ralph, great show

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00:21:36,640 --> 00:21:37,600
today.
Thank you, Sir.

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00:21:38,280 --> 00:21:40,240
Awesome, thank you too.
All right, take care of y'all.

381
00:21:40,880 --> 00:21:43,680
Thank you for listening to the
Leadership Sovereignty Podcast.

382
00:21:44,000 --> 00:21:47,040
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383
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384
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386
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