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I realize my parents were operators.
They were.

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They were like this,
like most entrepreneurs are right there.

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Like we're focused.

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But if you're not focused on emerging
technology, that's actually hitting

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and you're you're not seeing it,
you're going to be left behind.

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If you believe
we can change the narrative,

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if you believe
we can change our communities,

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if you believe we can change the outcomes
and we can change the world.

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I'm Rob Richardson,
welcome to disruption. Now.

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Welcome to disruption now I'm your host
and moderator Rob Richardson.

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With me is Seema Alexander,
who is a friend of mine, a co builder,

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co-founder of DC startup and Tech Week,
as well

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as co-founder of Virgin
AI and many other things.

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A serial entrepreneur, literally grew up
on entrepreneurship with her family and,

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and just cares
also about community and collaborating.

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So pleasure to have you on CMO.

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How are you doing? Rob?

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I'm so good. I'm excited to be here.

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We've been talking about this
for a long time,

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so looking forward
to chatting it up with you.

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Absolutely. Pleasure to have you on.

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And we're basically called spirits.

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You just did, you're in DC.

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I'm here in the Midwest, but,
you know, we're we're moving and shaking

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and disrupting together.

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So literally, I think you have a company
that says that's a disruption to

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what's there.
What's your original company?

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We're like twin flames

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in a weird way, bro, because my company
is called disruptive CEO advisory.

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So I ran, a repositioning advisory company
for ten years.

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And I was like, when I saw disrupt know
and all the things you're working

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on, I'm like,
we're meant to know each other smoothly.

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Absolutely. It's, oh, I got to get better.

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So yeah.

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Well, I want to talk about your journey
into entrepreneurship

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because it feels like it started

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a long time ago with your parents,
because you bring up the story

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pretty often about your parents business,
their journey in entrepreneurship

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in this country.

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Talk about the story of your parents
and how your parents

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entrepreneurial, journey influenced

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you as a person, as an entrepreneur
and what you're doing now.

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Yeah, I mean, I think it goes to say
with a lot of immigrant families,

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you know, many people come to America to,

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to figure out, like,
the American dream, right?

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For them, you know, they came at a very,

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like, a horror stricken
sort of situation in India.

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And, there were a lot of hard work
and a lot of sweat equity

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where they started the first Indian
vegetarian restaurant in Washington, DC,

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catty corner to the white House.

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And a travel agency.

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And there were a couple other
small businesses along the way.

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And, you know, the brands grew,
the community grew.

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They got to really be pillars in the DC,
Maryland, Virginia area.

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And the story goes that I started working
when I was 12 years old, you know,

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when you're in hospitality at a young age,
you learn a lot of things.

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The really quick I come.

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Coming to
my mom had a restaurant that I worked at.

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Yeah, it's it's interesting, right.

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Because you learn customer service.

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You you just learn people management.

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All these things at a young age, which,

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you know, at that moment in time,
you're like, oh, I gotta go to work.

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And then now you're like, Thank God.

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Like, you know, like because
you learn new lessons at a very young age.

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The story goes,

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it went from doing really well
to close to bankruptcy in the mid 90s.

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And, you know, there were a lot
of personal implications on the family.

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Parents got divorced
a couple of years later.

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My dad tragically passed.

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And it was it was it was sort of when
at that moment in time, at a young age,

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I started to have empathy for founders
because it was like,

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you know, being on the personal
sort of the child side of things, like,

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you see all the ups and downs
when your parents are building something.

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And we were there when things were good

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and we were there when things weren't
good.

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And so,

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I sort of got obsessed
with, like, learning why businesses fail

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and why they succeed.

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And that like, started my curiosity
and entrepreneur worship.

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So I so were

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though after college,
I went to Maryland, studied my,

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my business classes and stuff,
and that's when I started leaning in and

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all the things. But I wanted stability.

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My goal was to be a chief
marketing officer for fortune 500,

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and I wanted to leave the DC area,
and I want to New York.

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So I ended up, moving to outside
of New York City,

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actually spent about 17 years
there, which is kind of crazy,

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but spent 13 years of that time
in corporate America.

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So at Prudential Financial,
sort of an anomaly in my generation.

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State.

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And five of the businesses
there was, under the CMO

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and the retirement business
when things shifted, ten years ago.

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But the two things I will mention here,
which also impacted my entrepreneurial,

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career, if you will,

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I got to spend time
with 2500 financial planners,

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which are like sort of commodities
in the marketplace.

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And my job was,
how do you make them unique and different

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and grow their practices,
in, in a very sort of saturated market.

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And it taught me a lot of lessons about
how do you differentiate yourself

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and brand and all the things.

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And then the second large project,
that I think was a,

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a game changer
for me was working on the repositioning,

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the historical repositioning
of Prudential Financial

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with all the CMO,
the CEO, all the global folks.

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And it was,
how do you take this 136 year old company

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that has seven divisions,
multi, multibillion dollars,

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but it looks like this old stodgy
insurance company to the market.

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And that was the coolest thing
in the world for me because it was like

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I went through a multimillion dollar
process going through all the steps.

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And I had an epiphany moment after.

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Through that process, I was like,
man, like, do entrepreneurs do this?

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Like, do they actually step back?

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Because who you are

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when you first start in a business
is never where you end up, right?

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It was like this moment
in time of inflection

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got me to really think about,
like I, I've always been focused

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on, how do you know how businesses grow
and how they succeed and all the things.

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But I'm like,
this is that mis moment in time

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because people focus on people,
process technology to grow.

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Companies
have evolved and they haven't refined

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their business model or their unique
positioning in the marketplace.

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And so, I mean, I don't know if people
I'm gonna keep going to the story,

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but I want to nail down part of the story
because I've heard you,

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I've heard parts of the story.

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And when I heard you present
a few times. Yeah.

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And you use the example of your parents

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business and not understanding
where the world is going

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as an impetus to where,

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how we need to think about things now.

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Right?

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In terms of like, your,
your parents going from brick and mortar

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to, to thinking about things online
and for now, how we think about where

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we are in this moment, which I don't know
if you call it where we are at web 2.0.

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I have no idea what
we're calling this moment.

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And, I don't know what the hell
we call this moment, but.

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Pre generative AI and

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I like how did you draw upon the lessons
of what

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you went through with your parents,
and how do you relate that to

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when you talk about businesses now
and their need to embrace AI

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in terms of how they actually implement it
into their business?

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So fast forward advisory company

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ten years work with over a thousand
founders, different industries

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the last several years
to keep things happen.

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One was, I realized that I was working
with a lot of emerging tech companies.

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So Web3, smart cities,
and then I was asked to advise

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in artificial intelligence
development environment

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that specialized in AI agents
a couple of years ago.

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Okay. And a moment in time.

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It was very interesting for me
because I got deep

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with some of the visionaries in the space
on both sides, like extreme sides of AI,

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but it was like when I started
to understand the genetic workflows,

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when I started to understand
like what was actually happening.

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This was pre LMS and generative AI,
and then it got really ahead of it.

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It was I don't care,
but it was like it would Twitter.

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But what was happening
was while this like that

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moment in time I was like this is bigger
than the advent of the internet

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because the power in what is actually
is possible

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with the current infrastructure,
where it's being built for accessibility.

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And that's when I actually went back
and I was like, shit, man, like, excuse

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my language, but I was like, my,
you can trust on this is cool.

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Okay, cool.

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But I was like,
I started to think about like, you know,

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I used to say, whose strategy
was this for my parent's business?

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But what was happening in
the 90s were up like,

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that was like the rise of the internet.
Absolutely.

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And to your point, right.

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I always preach about like before
the internet, businesses

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were brick and mortar
for the most part, right?

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Post internet.

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All of a sudden you have digital,
you know,

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you have internet, obviously,
and you have digital.

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Then you have Google SEO, AdWords,
all the things.

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So market your business
in a whole different way.

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Different segments were actually,
growing and new segments are growing.

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And then all old, some old segments
were failing in the market because of

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they weren't paying attention to
what was happening in emerging technology.

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And I realized my parents were operators.

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They were they were like this,
like most entrepreneurs are right.

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They're like, we're focused.

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But if you're not focused on emerging
technology, that's actually hitting

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and you're you're not seeing it,
you're going to be left behind.

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And so I do a lot of talks now on this,
like comparison of the rise

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of the internet and where we are,
what I, what I consider

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is the biggest technological revolution
of our lifetimes with this

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AI transformation, you know,
all the things that come along with it.

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I agree. Yeah.

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And they're going to be businesses
that come out of the woodwork

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that we've never, ever seen possible
before.

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They're going to be businesses
that were major players that fail.

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They're gonna be a lot of small businesses

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that get really affected
because they're not paying attention.

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No, I completely agree.

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So when it comes to AI,

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what are

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we underestimating when it comes to AI

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and what are we overestimating
when it comes to AI?

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I would say underestimating
is the power of the technology.

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I think people okay,
when the world of Web3 was happening

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and you and I,
so you and I have been in that way.

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All right.

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And for the folks like who are listening,
like Web3 is a big word, right?

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It means a lot of things.

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Blockchain ledger, NFTs, like,
protocols, layers.

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Like there's so many crypto,
obviously things that go within Web3.

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When you think about AI, it's
the same thing.

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People have this one general idea,
and for most it's like Terminator

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type stuff, right?
It's the right kind of things.

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They don't have real understanding
of what the skills of the art of

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AI and machine learning, what is possible,
what is accessible.

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So not only create,

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you know, these unique automations
that no one's ever seen before.

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And it's possible today, right.

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But for innovation.

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And I think that to me, you know,
I'm trying to remember your question,

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but that to me is the missed part.

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And I totally underestimated what you

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were underestimating,
which I completely agree.

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Yeah.

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And actual power and the transformation

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that is happening
and what is going to happen.

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Yeah.

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Certainly being as much as people
are talking about AI,

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it is still underestimated
in terms of the impact

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it's having
and it will have on our complete society.

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And Web3 is your example, right?

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Web3 is, simplified as like Google Docs.

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Without Google. It's about ownership.

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Yes. And understanding and being able to
understand and own and all sense of data.

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That's what it is.

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AI is, is the amplification

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and the manipulation of data at scales
that you can't even understand.

233
00:11:15,699 --> 00:11:15,932
Right?

234
00:11:15,932 --> 00:11:18,965
So it's it's, it's going to be the fuel

235
00:11:19,465 --> 00:11:21,999
that, that
that makes everything possible in a way.

236
00:11:21,999 --> 00:11:22,232
Right.

237
00:11:22,232 --> 00:11:25,365
Because data has been that
it is now going to take data

238
00:11:25,832 --> 00:11:28,865
and put, put like fuel in it
to make it go to the moon.

239
00:11:29,665 --> 00:11:32,265
I can't wait to talk a little bit
more about that, because I think data is

240
00:11:32,265 --> 00:11:36,265
what's going to make businesses
stand out in the future, and how they use

241
00:11:36,265 --> 00:11:40,432
their unique proprietary data to create
unique experience is that I want to answer

242
00:11:40,432 --> 00:11:42,532
that second part of your question. Sure.

243
00:11:42,532 --> 00:11:45,032
You question that.
That's a good way to go.

244
00:11:45,032 --> 00:11:45,599
Yeah.

245
00:11:45,599 --> 00:11:50,099
The overestimates, estimation, to me
comes in.

246
00:11:50,165 --> 00:11:54,765
I think there's a lot of pressure
for CEOs from board members.

247
00:11:54,765 --> 00:11:57,332
There's a lot of pressure for founders
to really think about how to use this

248
00:11:57,332 --> 00:12:00,899
technology without the actual education,
and people are making decisions

249
00:12:01,099 --> 00:12:04,599
based on limited information,
and they're not going to the experts or

250
00:12:04,799 --> 00:12:08,165
people, you know, experts is a big word
right now in this space with the next

251
00:12:08,465 --> 00:12:13,832
wave of AI and ML,
but they need to really invest

252
00:12:14,099 --> 00:12:19,665
in education, understanding
what is happening, and what is possible.

253
00:12:19,665 --> 00:12:22,565
Because if they do it right,
and they're much more because

254
00:12:22,565 --> 00:12:25,665
AI's infrastructure technology,
at the end of the day, you have to focus

255
00:12:25,665 --> 00:12:29,132
on solving the bigger business problem,
the bigger pain points, you know, and

256
00:12:29,399 --> 00:12:32,432
and there is so much opportunity
right now.

257
00:12:32,432 --> 00:12:33,999
It's like almost crazy.

258
00:12:33,999 --> 00:12:37,499
Like it makes me excited,
because I see it on both sides where I've.

259
00:12:37,599 --> 00:12:39,665
The one thing I forgot to mention,
and you mentioned

260
00:12:39,665 --> 00:12:42,432
earlier, is I'm one of the co-chairs
here of DC Startup and Tech League.

261
00:12:42,432 --> 00:12:45,132
So I see the innovation
coming on that side.

262
00:12:45,132 --> 00:12:46,265
It's very high.

263
00:12:46,265 --> 00:12:48,632
We're
focused on sort of this midsize enterprise

264
00:12:48,632 --> 00:12:50,599
and you know
they're established companies.

265
00:12:50,599 --> 00:12:53,765
But it's like when you start
to bring both of them together of like,

266
00:12:53,999 --> 00:12:55,432
wow, if you use this innovation

267
00:12:55,432 --> 00:12:59,365
and put it into this automated flow,
what is possible for your company now?

268
00:12:59,365 --> 00:13:04,999
And I think there is a lot of like people
just don't realize that until they,

269
00:13:05,132 --> 00:13:08,865
even with education, also understand
like what is the right education

270
00:13:08,865 --> 00:13:10,732
because there's like fundamental stuff.

271
00:13:10,732 --> 00:13:13,399
Here's what AI is. Here's
what natural language processing. Yeah.

272
00:13:13,399 --> 00:13:14,865
But it's like,

273
00:13:14,865 --> 00:13:17,999
how do you bring this
these pieces, these Lego pieces together

274
00:13:17,999 --> 00:13:19,232
to create real innovation?

275
00:13:19,232 --> 00:13:21,332
I think it's very overestimated.

276
00:13:22,399 --> 00:13:22,665
Yeah.

277
00:13:22,665 --> 00:13:23,532
No, I completely agree.

278
00:13:23,532 --> 00:13:26,132
So getting back to the other point
about data

279
00:13:26,132 --> 00:13:27,899
and the importance of data
with businesses.

280
00:13:27,899 --> 00:13:32,032
So like what is your perspective there
in terms of how businesses

281
00:13:32,032 --> 00:13:35,065
can differentiate themselves in terms

282
00:13:35,065 --> 00:13:38,232
of how their data is leveraged?

283
00:13:39,265 --> 00:13:41,232
I'm going to give you an example.

284
00:13:41,232 --> 00:13:41,965
You better I love it.

285
00:13:41,965 --> 00:13:44,965
Yeah. Yeah. Because it's very

286
00:13:45,232 --> 00:13:46,965
there was somebody
who just actually shared this with me

287
00:13:46,965 --> 00:13:49,499
and I loved it for this data
specific example.

288
00:13:49,499 --> 00:13:53,532
So I think it's got City Sports Group
and I do please forgive me

289
00:13:53,532 --> 00:13:56,699
if I'm saying it wrong,
but they're a company

290
00:13:56,699 --> 00:14:00,065
that has collected data over the years
on performance.

291
00:14:00,065 --> 00:14:06,032
Athletes pre like being designated
at a sports sports team.

292
00:14:06,132 --> 00:14:06,865
Right.

293
00:14:06,865 --> 00:14:08,799
And they just said
they've had this information

294
00:14:08,799 --> 00:14:10,799
and they've used it for multiple reasons.

295
00:14:10,799 --> 00:14:14,599
But when you think about the sports world,
right, when people are like looking at,

296
00:14:14,899 --> 00:14:17,899
you know, finding the next,
the next LeBron, the next,

297
00:14:18,265 --> 00:14:21,065
the next big, you know, the next Kobe
whatever.

298
00:14:21,065 --> 00:14:21,332
Right.

299
00:14:21,332 --> 00:14:24,765
Like it's they're looking they're you
know, they're scouts they're agents.

300
00:14:24,765 --> 00:14:26,932
They go out
they look it's subjective right.

301
00:14:26,932 --> 00:14:29,499
And they're you know
and there's some stats obviously.

302
00:14:29,499 --> 00:14:33,365
But this company now
has curated all this data over the years.

303
00:14:33,365 --> 00:14:36,432
And now what they're doing
is they're saying, hey, create

304
00:14:36,665 --> 00:14:39,999
your decisions based on informed data.

305
00:14:39,999 --> 00:14:42,032
We have the data of these individuals.

306
00:14:42,032 --> 00:14:45,332
We know the well
the missing things within your team.

307
00:14:45,699 --> 00:14:49,699
Let us help you identify
the right types of players.

308
00:14:49,699 --> 00:14:51,032
A right precision right.

309
00:14:51,032 --> 00:14:54,032
That precision player of the team.

310
00:14:54,065 --> 00:14:56,965
And there was this, there was a use case.

311
00:14:56,965 --> 00:14:59,965
And again, forgive me
because this is a Spanish team, but

312
00:14:59,965 --> 00:15:02,965
it was like an, a small, a smaller city.

313
00:15:02,999 --> 00:15:06,265
And there like, they were comparing
like they actually use this service

314
00:15:06,265 --> 00:15:08,699
and they were saying that
the big Spanish teams, like,

315
00:15:08,699 --> 00:15:12,499
they get like $50 million
of marketing budgets to use for spend.

316
00:15:12,499 --> 00:15:15,499
And for them, it was like a lot smaller
8 million or something like that.

317
00:15:15,699 --> 00:15:18,399
And they said, you know,
to be able to compete because you can't

318
00:15:18,399 --> 00:15:21,399
even get into the same arena
with some of these bigger teams

319
00:15:21,432 --> 00:15:25,499
unless you have created
a return on investment in some capacity.

320
00:15:25,799 --> 00:15:28,799
And so they ended up saying, like,
you know, we're going to use this,

321
00:15:29,232 --> 00:15:33,265
this generation using data created a team
and their team has been doing

322
00:15:33,265 --> 00:15:34,032
like fantastic.

323
00:15:34,032 --> 00:15:36,532
Just doing fantastic
like it's not heard of.

324
00:15:36,532 --> 00:15:36,999
But now

325
00:15:36,999 --> 00:15:40,799
they're up against these bigger teams
because they can be with performances.

326
00:15:40,799 --> 00:15:42,632
They're they created the ROI

327
00:15:42,632 --> 00:15:45,599
both from a revenue perspective
and a performance perspective.

328
00:15:45,599 --> 00:15:48,399
And what I'm saying is data can change.

329
00:15:48,399 --> 00:15:54,332
Experiences like it will change like
your own proprietary data will and will.

330
00:15:54,565 --> 00:15:55,532
So that's this one, right?

331
00:15:55,532 --> 00:15:57,499
That's like a whole new segment
of the market.

332
00:15:57,499 --> 00:16:00,932
Think about like precision medicine
or anything that you're like, oh,

333
00:16:00,932 --> 00:16:05,065
I was actually speaking to an insurance
company the other day and they're like,

334
00:16:05,065 --> 00:16:08,432
you know, we have all these Laughlin runs,
we have all this information

335
00:16:08,432 --> 00:16:09,565
about our customers.

336
00:16:09,565 --> 00:16:12,965
How do we use that data to create
better programmatic,

337
00:16:13,065 --> 00:16:16,099
better experiences
for for our folks going forward?

338
00:16:16,099 --> 00:16:19,165
Because now it's like we can use that
for predictive analytics.

339
00:16:19,165 --> 00:16:23,932
We can say, hey, these folks, you know,
in the past, because of these losses,

340
00:16:24,065 --> 00:16:26,065
these are things that you need
to start to mitigate,

341
00:16:26,065 --> 00:16:29,499
or you need these additional insurance
clauses to help support you because

342
00:16:30,032 --> 00:16:31,832
you know,
you don't want to be in this situation.

343
00:16:31,832 --> 00:16:35,599
It's that level of personalization
precision

344
00:16:35,832 --> 00:16:37,565
that I think that can really shift.

345
00:16:37,565 --> 00:16:39,999
And and just the last thing
I'd say is like,

346
00:16:39,999 --> 00:16:43,165
you know, a lot of people are like, well,
we don't have a lot of data like,

347
00:16:43,165 --> 00:16:46,165
you know,
and so it becomes like and in general,

348
00:16:46,232 --> 00:16:49,165
you know, there's this data lake houses,
there's different structures.

349
00:16:49,165 --> 00:16:54,132
And to be able to start to curate what,
where, where you are in your data cycle.

350
00:16:54,132 --> 00:16:55,332
But you need to start now.

351
00:16:55,332 --> 00:16:58,332
You need to start to really think
about it's a foundational it's currency.

352
00:16:58,432 --> 00:16:59,698
Absolutely, absolutely.

353
00:16:59,698 --> 00:17:01,665
And something where we're working with

354
00:17:02,832 --> 00:17:04,865
is, advising governments on this.

355
00:17:04,865 --> 00:17:06,965
Right. Because you talk about
who's got the most data.

356
00:17:06,965 --> 00:17:11,065
Yes, governments and the most inefficient
use of data is also governments.

357
00:17:11,065 --> 00:17:11,265
Right.

358
00:17:11,265 --> 00:17:12,565
So from my perspective, right.

359
00:17:12,565 --> 00:17:16,998
It's, and there's just
so many opportunities to serve citizens

360
00:17:16,998 --> 00:17:20,965
better, to be more efficient, to even
just organize their information better.

361
00:17:20,965 --> 00:17:23,365
Like, I just like it's
just that there's just the start of that.

362
00:17:23,365 --> 00:17:26,232
Like, there's a lot of,
you know, know where the good is.

363
00:17:26,232 --> 00:17:27,098
Yeah.

364
00:17:27,098 --> 00:17:30,998
In the government sector,
how are you finding the current adoption

365
00:17:30,998 --> 00:17:32,998
cycle compared to other emerging

366
00:17:32,998 --> 00:17:35,198
technologies in the past,
or are they open to it

367
00:17:35,198 --> 00:17:38,298
or is it segment segments like what
are you seeing right now.

368
00:17:38,332 --> 00:17:40,432
Yeah it's a good question.
So they're they're open.

369
00:17:40,432 --> 00:17:41,532
They're open to it.

370
00:17:41,532 --> 00:17:44,532
Once we explain the opportunities and I

371
00:17:45,065 --> 00:17:46,832
and I think, you know,
I've ran for office.

372
00:17:46,832 --> 00:17:51,998
So I have like kind of unique opportunity
and relationships in those space. So

373
00:17:53,298 --> 00:17:54,565
I talk to them in a

374
00:17:54,565 --> 00:17:57,565
way that makes them understand
how this could

375
00:17:58,532 --> 00:18:02,232
help them right now, and how it's how
we make their life easier.

376
00:18:02,232 --> 00:18:03,232
Right.

377
00:18:03,232 --> 00:18:06,632
And so, like, I will give you, you know,
an example of not the actual person,

378
00:18:06,632 --> 00:18:10,432
but the type of what the type of the type
of, client that we're looking at,

379
00:18:10,798 --> 00:18:13,498
like, it's a, it's an office
that deals with criminal justice.

380
00:18:13,498 --> 00:18:15,365
We'll just say. Right.

381
00:18:15,365 --> 00:18:18,365
And, you know, we had a conversation and,

382
00:18:18,698 --> 00:18:22,398
one of the conversations that we had
was like, oh, well, part of what they do

383
00:18:23,198 --> 00:18:25,932
is they listen manually, listen

384
00:18:25,932 --> 00:18:30,932
into conversations, between like,
you know, people that are in jail

385
00:18:31,332 --> 00:18:35,198
and, and, and people from the outside
because often these folks will confess

386
00:18:35,198 --> 00:18:38,232
the crimes that they did,
and they were able to prosecute

387
00:18:38,232 --> 00:18:41,232
the right people and get the right people
out of prison and things like that.

388
00:18:41,232 --> 00:18:42,998
They manually listen to these things.

389
00:18:42,998 --> 00:18:43,365
Right?

390
00:18:43,365 --> 00:18:46,332
So, like,
you can just see, like we can save

391
00:18:46,332 --> 00:18:49,932
all types of time probably,
make sure we're freeing people up.

392
00:18:49,932 --> 00:18:52,232
Yeah. You still have to set up
the right processes.

393
00:18:52,232 --> 00:18:53,798
You still need to have a subject
matter experts there.

394
00:18:53,798 --> 00:18:54,832
You need to be very intentional

395
00:18:54,832 --> 00:18:57,998
about how you are fine
tuning and training this algorithm.

396
00:18:58,265 --> 00:19:00,698
Yeah,
but you can just see that's one area.

397
00:19:00,698 --> 00:19:02,798
And this person came up with it.

398
00:19:02,798 --> 00:19:03,432
We like.

399
00:19:03,432 --> 00:19:06,265
And she's not a tactical person,
but she just brought that up.

400
00:19:06,265 --> 00:19:06,832
So like

401
00:19:06,832 --> 00:19:10,965
once we kind of kind of inquire about,
well, what are some of the pain points

402
00:19:10,965 --> 00:19:14,732
that you have in terms
of dealing with your job day to day?

403
00:19:14,732 --> 00:19:15,765
What takes the most time?

404
00:19:17,332 --> 00:19:19,532
What I found that's the most useful
and then it's, open

405
00:19:19,532 --> 00:19:23,165
is a much of the conversation moves faster
if you try to start with.

406
00:19:23,165 --> 00:19:25,365
Because I made this mistake
to all the things they can do,

407
00:19:25,365 --> 00:19:26,532
it just loses them.

408
00:19:26,532 --> 00:19:28,898
So I usually try to say, yes.

409
00:19:28,898 --> 00:19:31,498
What are some pain points
you're having? And it's much easier.

410
00:19:31,498 --> 00:19:33,165
I tell you,
this conversation is much easier

411
00:19:33,165 --> 00:19:35,532
than, you know, anything
I've had in the past, like in terms

412
00:19:35,532 --> 00:19:38,532
of the internet and other things,
because it's so much easier to see,

413
00:19:39,498 --> 00:19:44,065
and they see you that they see the
opportunity, to save them time and effort.

414
00:19:44,065 --> 00:19:48,732
The challenge this is that they are like
they have systems that are 30 years old.

415
00:19:49,865 --> 00:19:50,932
That's the challenge.

416
00:19:50,932 --> 00:19:52,832
Not that it can't have them,
but that there's

417
00:19:52,832 --> 00:19:55,298
they're not even that like automation
let alone.

418
00:19:55,298 --> 00:20:00,032
Yeah, I yeah, I say there's two things
that you said, one of the thing is

419
00:20:00,465 --> 00:20:04,665
when it comes to, the government,
are you seeing because what we've also

420
00:20:04,665 --> 00:20:09,932
seen is like those internal processes
to start sort of these beta pilots

421
00:20:10,298 --> 00:20:13,765
versus like those external like,
well, let me actually step back.

422
00:20:13,765 --> 00:20:15,265
What I loved about what you said

423
00:20:15,265 --> 00:20:17,598
is very similar to
our process is figure out

424
00:20:17,598 --> 00:20:20,165
what the pain point is
and obviously what problem it solving,

425
00:20:20,165 --> 00:20:22,565
because then
it just becomes much more real.

426
00:20:22,565 --> 00:20:24,332
And it's not like, oh God, this big.

427
00:20:24,332 --> 00:20:26,532
I think we have to figure out
how to use it.

428
00:20:26,532 --> 00:20:27,898
And it's scary. Right.

429
00:20:27,898 --> 00:20:32,098
And and I think that's the again,
going back to your earlier question,

430
00:20:32,098 --> 00:20:35,765
it was like, again, people don't know
what they don't know until someone like

431
00:20:35,765 --> 00:20:38,765
yourself comes in and explains it to them
for the opportunity.

432
00:20:39,265 --> 00:20:42,365
But I always I feel like
and in most cases, not just government.

433
00:20:42,365 --> 00:20:45,265
And most companies
these days are looking at

434
00:20:45,265 --> 00:20:48,532
how do we build something internally
to prove the model.

435
00:20:48,798 --> 00:20:50,298
Correct? Correct.

436
00:20:50,298 --> 00:20:54,298
Like prototype, approve it
so that we can feel comfortable ourselves

437
00:20:54,298 --> 00:20:56,265
before we go to any external sources.

438
00:20:56,265 --> 00:20:58,332
Just curious
if you're seeing that's definitely

439
00:20:58,332 --> 00:20:59,732
that's definitely across the board.

440
00:20:59,732 --> 00:21:03,098
What I've seen with governments,
with unions for example.

441
00:21:03,198 --> 00:21:04,232
Like that's what we've seen.

442
00:21:04,232 --> 00:21:07,398
Like that's start
start something with a small specific.

443
00:21:07,598 --> 00:21:09,698
And then show some success.

444
00:21:09,698 --> 00:21:12,698
Like instead of try to do something major,

445
00:21:12,732 --> 00:21:16,965
try to do something where you can show
how much you can, you know, change them.

446
00:21:16,965 --> 00:21:18,965
And even then even
you start in a small area and, and grow.

447
00:21:18,965 --> 00:21:19,998
That's exactly what we're seeing.

448
00:21:19,998 --> 00:21:23,732
I mean, so it sounds like it's
very similar to even mid-sized companies.

449
00:21:24,398 --> 00:21:27,698
But but the conversation has been easier
because people at least have a

450
00:21:28,998 --> 00:21:31,098
they have some idea,
like when the internet first started,

451
00:21:31,098 --> 00:21:35,232
it felt like it can be completely foreign,
where AI is not as foreign

452
00:21:35,232 --> 00:21:39,332
as the internet was to
when things were totally brick and mortar.

453
00:21:39,332 --> 00:21:42,032
Right? Because it's like people
had no concept, like, what do you mean?

454
00:21:42,032 --> 00:21:44,798
We're going to go on like it? Really,
if you think about it. And we were right.

455
00:21:44,798 --> 00:21:48,832
We we rewind 30 years
that it was that long ago.

456
00:21:50,032 --> 00:21:50,932
Yeah. Yeah.

457
00:21:50,932 --> 00:21:53,832
We still look young,
but it was that long ago.

458
00:21:53,832 --> 00:21:57,998
But, it
it seems like a weird foreign concept

459
00:21:58,465 --> 00:22:00,665
where now people understand
because we've been through.

460
00:22:00,665 --> 00:22:01,298
Or at least they should.

461
00:22:01,298 --> 00:22:02,632
We've been through so many iterations

462
00:22:02,632 --> 00:22:05,098
of what happens online
that people, I think, are

463
00:22:05,098 --> 00:22:07,032
more open to it than they used to be.

464
00:22:07,032 --> 00:22:10,498
I agree, I totally agree,
and I think there was this big like

465
00:22:10,765 --> 00:22:13,798
and I think it happened
after the LMS and generative AI, that's

466
00:22:14,765 --> 00:22:15,631
that's when everything

467
00:22:15,631 --> 00:22:18,931
sort of shifted and people ChatGPT
give them credit.

468
00:22:19,498 --> 00:22:23,598
Oh, I actually created the UI, UX
because that's what it comes down to.

469
00:22:23,598 --> 00:22:25,098
It's like, how do you make this?

470
00:22:25,098 --> 00:22:28,265
That's, you know, Web3 is still problem

471
00:22:28,265 --> 00:22:31,598
is that the UI, UX, the
the user experience is not easy.

472
00:22:31,598 --> 00:22:34,698
It's still like it's good
for like developers and tech nerds,

473
00:22:34,698 --> 00:22:37,698
but it's not enough. Like, you know,

474
00:22:38,031 --> 00:22:39,131
what's had GPT?

475
00:22:39,131 --> 00:22:42,098
They made it accessible
to anyone, technical or non-technical.

476
00:22:42,098 --> 00:22:43,531
And that really opened up the world.

477
00:22:43,531 --> 00:22:47,631
Speaking of that,
how how do you see this when it comes

478
00:22:47,631 --> 00:22:51,531
to AI in terms of accessibility
and where we're going?

479
00:22:51,531 --> 00:22:53,631
So I'd like to I'd like to hear from you.

480
00:22:53,631 --> 00:22:56,631
What is the best case scenario?

481
00:22:57,031 --> 00:22:59,198
For AI and how do we make that happen?

482
00:22:59,198 --> 00:23:03,231
And in terms of how you define
accessibility, building inclusivity.

483
00:23:03,631 --> 00:23:05,398
And then what is the worst case scenario?

484
00:23:06,365 --> 00:23:06,798
You know,

485
00:23:06,798 --> 00:23:09,698
I think we're in an era because of

486
00:23:09,698 --> 00:23:14,698
AI and the tools
that are truly out already for almost free

487
00:23:14,698 --> 00:23:17,631
on the marketplace.

488
00:23:17,631 --> 00:23:21,631
It's not like, anybody can start today.

489
00:23:21,665 --> 00:23:25,765
Like that's like one of those things
in a sense of like, if you are curious,

490
00:23:25,865 --> 00:23:29,598
if you're trying to get ahead,
if you understand

491
00:23:29,598 --> 00:23:32,598
even an inkling of like where AI is going,

492
00:23:32,731 --> 00:23:35,965
and obviously if you have the internet
and you have accessibility, there,

493
00:23:36,565 --> 00:23:39,131
you can truly learn
a lot of these things on your own.

494
00:23:39,131 --> 00:23:42,998
I mean, we're in the fastest time
frame of being able to prototype things.

495
00:23:42,998 --> 00:23:44,298
You don't need to code.

496
00:23:44,298 --> 00:23:46,165
I mean, people are using cursor.

497
00:23:46,165 --> 00:23:47,298
I don't like it.

498
00:23:47,298 --> 00:23:49,165
Prompt things that took forever.

499
00:23:49,165 --> 00:23:52,231
I just found out about a, a a new

500
00:23:52,231 --> 00:23:55,331
bolt that new to help prompt

501
00:23:56,531 --> 00:23:58,665
all that new old skin.

502
00:23:58,665 --> 00:24:00,998
You, you know, every day
there's a new tool.

503
00:24:00,998 --> 00:24:04,465
But I think from an inclusivity
perspective, way before you get

504
00:24:04,465 --> 00:24:08,198
what is built in, what does that
you know, I'm going to play with it.

505
00:24:08,198 --> 00:24:11,165
But, one of our clients
was playing with it basically,

506
00:24:11,165 --> 00:24:14,665
and you could create it's prompting,
but you can create like landing pages.

507
00:24:14,665 --> 00:24:16,131
You can create anything with it.

508
00:24:16,131 --> 00:24:18,431
It's it's pretty, it's pretty.

509
00:24:18,431 --> 00:24:19,431
It's pretty cool.

510
00:24:19,431 --> 00:24:20,365
Okay. Good.

511
00:24:20,365 --> 00:24:23,131
Good stuff. It's not like,

512
00:24:23,131 --> 00:24:26,765
it's not like some of the tools out there
that like the, the early stage

513
00:24:26,765 --> 00:24:30,665
user experience or user generated
in terms of visuals are bad.

514
00:24:30,931 --> 00:24:32,531
And again, I need to play with it more.

515
00:24:32,531 --> 00:24:33,831
So I'll tell you more about it.

516
00:24:33,831 --> 00:24:36,265
But my whole point is like it.

517
00:24:36,265 --> 00:24:40,398
There's free courses from Google
from Nvidia I mean so many YouTube.

518
00:24:40,398 --> 00:24:42,631
You know, it's like inclusivity.

519
00:24:42,631 --> 00:24:45,065
And in terms of like
this is an opportunity where we're all

520
00:24:45,065 --> 00:24:46,365
learning together.

521
00:24:46,365 --> 00:24:47,665
You know I feel and and

522
00:24:47,665 --> 00:24:50,565
and it can make sense.
And it's not totally over your head.

523
00:24:50,565 --> 00:24:52,931
I think there is a moment
in time for that.

524
00:24:52,931 --> 00:24:55,931
I think that whole responsible framework,

525
00:24:56,231 --> 00:25:00,298
you know, ethics board
about not having biased models.

526
00:25:00,298 --> 00:25:02,998
I think there's a lot to be done there.

527
00:25:02,998 --> 00:25:04,731
I think we I agree with that.

528
00:25:04,731 --> 00:25:07,498
We've learned a lot from previous cycles,

529
00:25:07,498 --> 00:25:10,498
but that doesn't mean it's
everyone's top priority.

530
00:25:10,898 --> 00:25:12,565
And I don't think it's any priority.

531
00:25:12,565 --> 00:25:14,365
I think their priority is to build,
make money

532
00:25:14,365 --> 00:25:18,431
and then worry about that consequence
later, which is been the model.

533
00:25:18,431 --> 00:25:18,698
Right.

534
00:25:18,698 --> 00:25:22,965
And we have to I think that's
what makes me the most nervous.

535
00:25:22,965 --> 00:25:24,865
But the other thing we could do
is build right.

536
00:25:24,865 --> 00:25:27,131
And and until there's policy.

537
00:25:27,131 --> 00:25:27,565
Yeah.

538
00:25:27,565 --> 00:25:31,398
And I think I mean so again
you are a DC startup in tech week.

539
00:25:31,398 --> 00:25:32,765
And you were on a panel

540
00:25:32,765 --> 00:25:36,665
that I wanted to curate very intentionally
around this conversation on AI

541
00:25:36,831 --> 00:25:37,698
and responsibility.

542
00:25:37,698 --> 00:25:40,531
But really that innovation
has implication.

543
00:25:40,531 --> 00:25:41,265
Right?

544
00:25:41,265 --> 00:25:44,898
And I say that a lot is one of my pillars,
because it's easy

545
00:25:44,898 --> 00:25:47,831
to get really excited for a technology.
And there are a lot of entrepreneurs.

546
00:25:47,831 --> 00:25:51,231
This is one of the most
biggest entrepreneurial moments.

547
00:25:51,231 --> 00:25:53,831
It is it goes right
and a lot of opportunity.

548
00:25:53,831 --> 00:25:58,298
But again, looking at the internet,
looking at social, looking at digital like

549
00:25:58,331 --> 00:25:59,965
there are a lot of things that you can do.

550
00:25:59,965 --> 00:26:04,065
I had a time and get over your riches
and actually it's not a very feasible,

551
00:26:04,065 --> 00:26:06,331
viable,
you know, business or whatever it is,

552
00:26:06,331 --> 00:26:08,931
and either going to hurt a lot of people
or you're gonna hurt yourself.

553
00:26:08,931 --> 00:26:11,598
Right. And I think, this concept of,

554
00:26:12,565 --> 00:26:15,298
making sure you're in
a, when you're thinking about innovation,

555
00:26:15,298 --> 00:26:20,565
I think about impatience came from that
example I had shared, not too long ago.

556
00:26:20,565 --> 00:26:24,365
But it was kind of like when you're on
when you're on your cell phone and you're

557
00:26:24,465 --> 00:26:27,698
going through your social media,
you don't know if you see a cell phone.

558
00:26:27,698 --> 00:26:28,531
Okay.

559
00:26:28,531 --> 00:26:30,798
But it's it's called doom
scrolling, right?

560
00:26:30,798 --> 00:26:34,531
Like it's a list in C of like,
you know, like looking down

561
00:26:34,531 --> 00:26:39,798
and just constantly being by yourself
and the the individual who created

562
00:26:39,798 --> 00:26:43,265
that feature was on the Oprah special,
and he's been talking about it.

563
00:26:43,931 --> 00:26:44,531
All over.

564
00:26:44,531 --> 00:26:48,298
And he was like, if I had known
15 years ago that this feature would have

565
00:26:48,631 --> 00:26:51,865
how much loneliness it's
cause depression is cause anxiety.

566
00:26:51,865 --> 00:26:54,698
It's caused, people,
I would have never created it.

567
00:26:54,698 --> 00:26:58,131
And it's an extreme example
because you don't know always what goes in

568
00:26:58,131 --> 00:27:01,598
like what is actually going to happen
from an intentionality perspective.

569
00:27:02,131 --> 00:27:05,798
But it is just it's more of
being like open to understanding.

570
00:27:05,798 --> 00:27:08,365
Like not every innovation
is a good innovation, right?

571
00:27:08,365 --> 00:27:11,965
Like, yeah,
let's put it in that risk factor.

572
00:27:12,165 --> 00:27:14,798
I mean, Elon says it's really interesting
because he's like,

573
00:27:14,798 --> 00:27:17,865
you know, there's a 20% chance
that things could go really wrong.

574
00:27:18,231 --> 00:27:22,265
Like, you know,
and I think it's just keeping that in mind

575
00:27:22,265 --> 00:27:27,031
because this technology is I think it's
not like a to Sam Altman talks about like

576
00:27:27,031 --> 00:27:31,131
there's like a I don't know if it's 1 to 5
from an AGI perspective.

577
00:27:31,131 --> 00:27:31,398
Right.

578
00:27:31,398 --> 00:27:35,065
An artificial general intelligence
besides the level of intelligence

579
00:27:35,265 --> 00:27:37,531
these AIS can actually have.

580
00:27:37,531 --> 00:27:40,531
And we're between a 1.5 and two right now.

581
00:27:40,631 --> 00:27:42,831
So the stronger, the more powerful
the stuff gets.

582
00:27:42,831 --> 00:27:44,598
It's going to get more autonomous.

583
00:27:44,598 --> 00:27:46,265
It's going to start thinking for itself.

584
00:27:46,265 --> 00:27:47,898
And if we're not, again,

585
00:27:47,898 --> 00:27:51,564
going back to your original question
of what people are underestimating,

586
00:27:52,298 --> 00:27:56,631
they have no idea what the power of this
is actually going to look like.

587
00:27:56,664 --> 00:27:57,631
I agree with that.

588
00:27:57,631 --> 00:28:00,464
Yeah,
I think I'll take it even a step further.

589
00:28:00,464 --> 00:28:05,031
Yeah, I would say even the people
that are building the AI models

590
00:28:05,198 --> 00:28:06,664
don't fully appreciate

591
00:28:06,664 --> 00:28:09,631
the power of what's going to happen,
let alone the general public.

592
00:28:09,631 --> 00:28:10,898
Right? Because like when,

593
00:28:11,864 --> 00:28:14,364
algorithms were
being built even on social media, like.

594
00:28:14,364 --> 00:28:16,798
And I mean, you
I'm sure you know this, but,

595
00:28:16,798 --> 00:28:19,664
no one knows how the any of those
algorithms work

596
00:28:19,664 --> 00:28:21,431
within one person
because they're so complicated.

597
00:28:21,431 --> 00:28:25,364
It's like one person takes a part
in, like, Cincinnati

598
00:28:25,364 --> 00:28:26,898
versus another person in California.

599
00:28:26,898 --> 00:28:29,898
And the algorithm is a nation
journey of AI.

600
00:28:30,464 --> 00:28:32,964
Builds on that because
then it just builds on its own on that.

601
00:28:32,964 --> 00:28:34,531
So there's great opportunities.

602
00:28:34,531 --> 00:28:37,664
But if we're not intentional
about how this is guided

603
00:28:37,664 --> 00:28:41,164
by ethics and principles,
there could be problems.

604
00:28:41,164 --> 00:28:45,031
And, you know, I'm a I'm
a pragmatic optimist.

605
00:28:45,131 --> 00:28:49,464
So what I mean by that is I think history
doesn't repeat itself, but it rhymes.

606
00:28:49,464 --> 00:28:53,698
So I believe we're going to probably go
through some bit of pain

607
00:28:54,298 --> 00:28:55,364
to recognize this,

608
00:28:55,364 --> 00:28:59,164
because we're going to keep moving
until we are forced to be intentional.

609
00:28:59,164 --> 00:29:01,331
I hope I'm wrong on that, by the way.

610
00:29:01,331 --> 00:29:03,998
But let me ask you what what do you think?

611
00:29:03,998 --> 00:29:06,464
Like what do you think
is going to solve for this round?

612
00:29:06,464 --> 00:29:06,764
Right.

613
00:29:06,764 --> 00:29:09,931
Because government
like what we're seeing with Virgin.

614
00:29:09,931 --> 00:29:10,231
Right.

615
00:29:10,231 --> 00:29:14,564
It's like people don't have governance
policies and that's should be part of it.

616
00:29:14,564 --> 00:29:16,298
And you know,
when they're thinking about building,

617
00:29:16,298 --> 00:29:18,064
they're not thinking about there's
a level of education, right.

618
00:29:18,064 --> 00:29:23,964
But from a higher level
government perspective, is it a priority?

619
00:29:23,964 --> 00:29:27,164
Like like the answer is it's not exactly.

620
00:29:27,331 --> 00:29:30,331
So like it's
so what's going to solve for that is

621
00:29:30,498 --> 00:29:33,964
I think in terms of how we're and I hope
I'm wrong, by the way, I hope that

622
00:29:35,298 --> 00:29:36,698
that, you know, private sector

623
00:29:36,698 --> 00:29:40,831
intentionally builds
and is very thoughtful about this.

624
00:29:41,331 --> 00:29:44,331
But I believe
even if they want to be individually,

625
00:29:44,664 --> 00:29:47,664
the market will not allow
that behavior to happen.

626
00:29:47,864 --> 00:29:48,131
Right.

627
00:29:48,131 --> 00:29:49,931
So how I think we how I think

628
00:29:49,931 --> 00:29:52,531
unfortunately the correction will be
is something

629
00:29:52,531 --> 00:29:55,198
the same way we have to have correction
with the housing market.

630
00:29:55,198 --> 00:29:59,031
Like there will be some boom,
some pain that will happen,

631
00:30:00,231 --> 00:30:02,131
to society.

632
00:30:02,131 --> 00:30:04,831
And we will have to come up
with that moment to adjust.

633
00:30:04,831 --> 00:30:07,331
I think businesses are going
to go through that individually.

634
00:30:07,331 --> 00:30:10,898
And that's why I tell people like,
I believe that I believe this to my core,

635
00:30:11,498 --> 00:30:14,698
that in this world with algorithms and AI,

636
00:30:15,164 --> 00:30:18,598
the greatest asset
you have is trust, right?

637
00:30:18,598 --> 00:30:23,064
And then and so you can take the power
of this of the of AI and algorithms.

638
00:30:23,064 --> 00:30:25,564
And you could decide
that you want to manipulate

639
00:30:25,564 --> 00:30:28,564
and you will be successful
for a long period of time.

640
00:30:28,664 --> 00:30:33,431
But I do think the cynicism you build up,
the reaction could be so harsh that

641
00:30:33,931 --> 00:30:35,631
you could really,
especially with social media,

642
00:30:35,631 --> 00:30:37,264
set down your business pretty quickly.

643
00:30:37,264 --> 00:30:39,364
If you're not transparent
about how that happens

644
00:30:39,364 --> 00:30:41,131
and you can have a reaction
that you're not expecting.

645
00:30:41,131 --> 00:30:44,431
And then I also think how we implement
AI for not intentional

646
00:30:45,231 --> 00:30:48,798
will have some effects
that we don't anticipate.

647
00:30:48,798 --> 00:30:51,598
So even with the industrial revolution,
for example, right,

648
00:30:51,598 --> 00:30:53,964
we got to the point where
we got to a really good point in society

649
00:30:53,964 --> 00:30:56,131
and it was obviously better,
but people forget.

650
00:30:56,131 --> 00:30:58,131
We went through
two world wars, a pandemic,

651
00:30:59,598 --> 00:31:00,131
multiple

652
00:31:00,131 --> 00:31:03,331
labor, multiple labor laws
having to be put in place, child labor.

653
00:31:03,331 --> 00:31:05,864
There was a lot of things
that had to happen to make sure

654
00:31:05,864 --> 00:31:07,764
that the Industrial Revolution
was stabilized.

655
00:31:07,764 --> 00:31:11,598
People don't remember that,
where it was less demanding that with AI,

656
00:31:11,598 --> 00:31:13,231
what that's needed. That's what I think.

657
00:31:13,231 --> 00:31:17,764
I mean, you mentioned trust
and how that is obviously a big virtue

658
00:31:17,764 --> 00:31:22,064
and AI allows for it, but in a lot of ways
it doesn't allow for it

659
00:31:22,064 --> 00:31:25,098
because you can't trust anything
that comes out of AI currently.

660
00:31:25,098 --> 00:31:29,598
But but with Web3 and like,

661
00:31:29,598 --> 00:31:32,998
you know, that to me is like
the biggest opportunity is like

662
00:31:33,631 --> 00:31:38,731
bringing both of those together,
building out real trust in the ledger

663
00:31:38,731 --> 00:31:42,564
and knowing verifying actual,
you know, sources and things

664
00:31:42,898 --> 00:31:46,431
is going to be such an important piece
because trust I like to be honest.

665
00:31:46,431 --> 00:31:49,231
Like anything you see is
could be super fake now, right?

666
00:31:49,231 --> 00:31:50,298
Like HTML.

667
00:31:50,298 --> 00:31:54,131
And so we know I know lots of people
creating innovations and solutions for

668
00:31:54,131 --> 00:31:54,898
that problem.

669
00:31:55,931 --> 00:31:57,864
But I just have not awareness.

670
00:31:57,864 --> 00:32:00,731
We have to care about it. Like right now.
And people don't care about it.

671
00:32:00,731 --> 00:32:03,331
It's not a it's
not important enough for people.

672
00:32:03,331 --> 00:32:05,131
And I don't think
it will be for some time.

673
00:32:05,131 --> 00:32:07,564
So I just tell people like,

674
00:32:07,564 --> 00:32:09,664
if you want to be a business,
I think there's opportunities

675
00:32:09,664 --> 00:32:13,031
to set yourself apart, that you're taking,
that you're being intentional about.

676
00:32:13,031 --> 00:32:16,031
I think how you use AI,
that you're transparent about it

677
00:32:16,464 --> 00:32:18,298
and that you have
some human connection to it

678
00:32:18,298 --> 00:32:21,298
and that you're not necessarily
that I tell people we can't

679
00:32:21,664 --> 00:32:24,798
we can't predict the future,
but we can envision it right.

680
00:32:24,798 --> 00:32:27,798
And we can't
and we can't control algorithms.

681
00:32:27,931 --> 00:32:30,798
If we're honest, we cannot control
AI algorithms completely.

682
00:32:30,798 --> 00:32:34,831
But we can dance with them and design them
to be

683
00:32:35,131 --> 00:32:39,331
what we want to be and direct them in the
in the proper direction, 100%.

684
00:32:39,331 --> 00:32:42,331
So what I also saw
with the cycle of social media,

685
00:32:42,331 --> 00:32:45,898
when Mark Zuckerberg was put up in front
of all the ports, right.

686
00:32:45,898 --> 00:32:49,398
And then there was, Web3,
say FTX or a couple.

687
00:32:49,398 --> 00:32:49,598
Right.

688
00:32:49,598 --> 00:32:51,464
But like was put up in front of of course,

689
00:32:51,464 --> 00:32:54,431
because out of like doing all the wrong
things. Right.

690
00:32:54,431 --> 00:32:57,531
That's what people listen
because they're like, holy crap.

691
00:32:57,531 --> 00:33:00,531
Like, this is major law NFT world, right?

692
00:33:00,564 --> 00:33:02,431
Got tons of lawsuits now

693
00:33:02,431 --> 00:33:06,864
because people were using
that as securities versus a utility.

694
00:33:06,864 --> 00:33:07,431
Right.

695
00:33:07,431 --> 00:33:10,231
And I think that's the way
our government has done it up to

696
00:33:10,231 --> 00:33:14,898
this point is like, you see, big use cases
and then go after everybody.

697
00:33:15,164 --> 00:33:17,831
And up to then this is I don't think
it's a good approach to either.

698
00:33:17,831 --> 00:33:18,331
But go ahead.

699
00:33:19,398 --> 00:33:19,831
It's not.

700
00:33:19,831 --> 00:33:21,931
And I think the innovator's dilemma.

701
00:33:21,931 --> 00:33:22,331
Right.

702
00:33:22,331 --> 00:33:25,164
It's kind of like,
well how much do we push?

703
00:33:25,164 --> 00:33:28,631
What can we do for innovation or
are we going to get shut down eventually.

704
00:33:28,631 --> 00:33:32,597
And that's where like a lot of growth
in Web3 was stunted for so long.

705
00:33:32,764 --> 00:33:35,764
It is still is still has been another way
that that really hurt.

706
00:33:35,797 --> 00:33:37,997
Like that's it's fact.

707
00:33:37,997 --> 00:33:40,164
But but then those people too.

708
00:33:40,164 --> 00:33:41,964
But that was my old
the old company's back there

709
00:33:41,964 --> 00:33:43,731
like that's, that's that's the truth.

710
00:33:43,731 --> 00:33:46,231
And so let me ask you this.

711
00:33:46,231 --> 00:33:49,031
When and because you've been
in an appointed role.

712
00:33:49,031 --> 00:33:49,331
Right.

713
00:33:49,331 --> 00:33:51,564
Like when you don't know enough
as a government official,

714
00:33:51,564 --> 00:33:55,664
which most, you know,
like you're getting advised, that's hard.

715
00:33:55,664 --> 00:33:59,764
It's hard to know, like what's coming down
and then the right people

716
00:33:59,764 --> 00:34:01,864
don't know where the decision makers.

717
00:34:01,864 --> 00:34:06,031
So how does a government
make decisions on policy

718
00:34:06,431 --> 00:34:08,897
without really understanding
the technology.

719
00:34:08,897 --> 00:34:11,931
Like, you know, that that is
that is a great question.

720
00:34:11,931 --> 00:34:17,297
And that's literally like the heart
of what we focus on as a midwest con,

721
00:34:17,364 --> 00:34:19,464
as a company, as value,
like one of our values

722
00:34:19,464 --> 00:34:22,464
talks about is that we talk about
as policy innovation.

723
00:34:22,531 --> 00:34:25,231
So I don't believe that, okay, does

724
00:34:25,231 --> 00:34:28,631
a government official
need to know how to program a little.

725
00:34:28,631 --> 00:34:32,997
No, but they do need to understand
the basics of how,

726
00:34:33,864 --> 00:34:38,131
how I generative AI works,
how prevalent it is.

727
00:34:38,697 --> 00:34:42,097
And they need to have a view
about emerging technology

728
00:34:42,331 --> 00:34:45,464
and, and, and the question
I ask you about, I,

729
00:34:45,964 --> 00:34:50,264
I ask a lot of public officials,
very rarely can they actually answer it

730
00:34:50,564 --> 00:34:52,031
with any thoughtfulness,
but they need to be able

731
00:34:52,031 --> 00:34:53,997
to think about these questions like,

732
00:34:53,997 --> 00:34:57,131
what's your best, worst case scenario
for emerging technology?

733
00:34:57,997 --> 00:35:01,631
Like and and what's your plan
to create the best case scenarios?

734
00:35:01,831 --> 00:35:04,697
What what's your thought about AI
and all those things and how

735
00:35:04,697 --> 00:35:09,331
we can both support innovation
and make sure we have clear policy?

736
00:35:09,564 --> 00:35:12,431
I think we're going to have to
reimagine how we do policy.

737
00:35:13,431 --> 00:35:14,797
And I don't know what that looks like.

738
00:35:14,797 --> 00:35:17,897
I know that we have to start
having education

739
00:35:18,397 --> 00:35:22,064
to our policymakers, because they're going
to have to play a role,

740
00:35:22,064 --> 00:35:23,231
and they're going to play a role.

741
00:35:23,231 --> 00:35:26,731
And they could either screw it up
massively or really empower us.

742
00:35:26,731 --> 00:35:30,031
And there's no and that's why
I call it dance with the algorithms,

743
00:35:30,031 --> 00:35:33,131
because there's not going to be
an exact system.

744
00:35:33,131 --> 00:35:37,464
We're going to have to kind of be nimble,
but we're going to have to set

745
00:35:37,464 --> 00:35:41,597
some type of guidelines
and measures for what we want

746
00:35:42,331 --> 00:35:44,597
our society to be, and technology

747
00:35:44,597 --> 00:35:47,597
should be amplifying those things.

748
00:35:47,897 --> 00:35:49,097
Policymakers aren't having those thoughts.

749
00:35:49,097 --> 00:35:52,464
So being from a policy makers
point of view, like I didn't, I understand

750
00:35:52,464 --> 00:35:56,531
why they, how hard it is because they have
all these things on their brain.

751
00:35:57,297 --> 00:36:01,231
But what they don't understand is like
this is one of the most important issues

752
00:36:01,564 --> 00:36:02,064
period.

753
00:36:02,064 --> 00:36:05,897
Like it is affecting
like is affecting how we communicate.

754
00:36:06,264 --> 00:36:11,031
It's affecting racism, it's affecting
misogyny, it's affecting civil discourse.

755
00:36:11,464 --> 00:36:16,831
And it's only going to amplify
unless we figure out how we want to,

756
00:36:17,131 --> 00:36:19,864
what what we want
our principles to be around technology.

757
00:36:19,864 --> 00:36:23,031
And so I think when they
I think the problem

758
00:36:23,031 --> 00:36:26,731
with folks in elected office
is that they are

759
00:36:27,531 --> 00:36:32,364
they are they are approaching the problem
from a 20th century perspective.

760
00:36:32,397 --> 00:36:35,264
When we're in the 21st century,
that's the problem.

761
00:36:35,264 --> 00:36:39,697
Well, we got Ellen now, so let's see
what's gonna have is go interesting.

762
00:36:39,697 --> 00:36:39,997
Right.

763
00:36:39,997 --> 00:36:43,164
Like yeah that that that I have that

764
00:36:43,797 --> 00:36:48,031
that's scary too, because like you,
all other podcasts are podcasts.

765
00:36:48,031 --> 00:36:51,631
I'll just say what we don't need
is digital dictatorships either.

766
00:36:51,831 --> 00:36:53,597
Right? Because that's also scary.

767
00:36:54,831 --> 00:36:57,697
Because
but I would say that there could be, like,

768
00:36:57,697 --> 00:37:00,331
I think there's opportunities
in every situation. They'll seem.

769
00:37:00,331 --> 00:37:03,331
So I'm not one of these people
and I'm not going to get into,

770
00:37:03,931 --> 00:37:06,931
I didn't support the incoming president.

771
00:37:07,864 --> 00:37:11,731
However, there is opportunities
in everything, right?

772
00:37:11,731 --> 00:37:14,831
And so I will also not allow myself to be

773
00:37:14,831 --> 00:37:17,864
at a state of constant anger.

774
00:37:18,264 --> 00:37:22,164
I'm going to be focused and figure out,
because I think there

775
00:37:22,164 --> 00:37:23,931
will be opportunities in this moment.

776
00:37:23,931 --> 00:37:29,064
And if if something good comes out of
this, like in and Elon does, or Trump goes

777
00:37:29,064 --> 00:37:32,431
something that actually is beneficial,
I will wholeheartedly support it.

778
00:37:32,931 --> 00:37:35,231
If I feel like it's not,
I will definitely speak up.

779
00:37:35,231 --> 00:37:38,831
But my focus is not going to be
on simply reacting to someone else.

780
00:37:38,831 --> 00:37:41,097
It has to be for us.
How are we building the better future?

781
00:37:41,097 --> 00:37:43,997
And what I know is whether,
no matter who's in office,

782
00:37:43,997 --> 00:37:47,431
I don't think much is going to change
when it comes to AI and things like that.

783
00:37:47,431 --> 00:37:50,197
And I do
think we need to do more of our parts.

784
00:37:50,197 --> 00:37:53,431
I think we, you, me and the others
that are building intentionally

785
00:37:53,431 --> 00:37:56,431
in this space, like we are
the new civil rights leaders in a way,

786
00:37:56,431 --> 00:38:00,197
because we have to build the future
and the vision, the future that we want,

787
00:38:00,197 --> 00:38:03,197
and it's really participating
in this space directly.

788
00:38:03,597 --> 00:38:05,431
No, I couldn't agree with you more.

789
00:38:05,431 --> 00:38:08,431
I've had this conversation
multiple times over around like

790
00:38:08,897 --> 00:38:10,597
whoever's in the office is in the office.

791
00:38:10,597 --> 00:38:13,597
Our voices matter more now than ever
before, right?

792
00:38:13,931 --> 00:38:18,897
Especially there's there's not a lot of
us, I would say, who are in the know,

793
00:38:18,931 --> 00:38:23,031
like, you know, and I feel like blessed
and responsible at the same time.

794
00:38:23,131 --> 00:38:26,131
Exactly where it's like,
okay, if you don't speak up,

795
00:38:26,131 --> 00:38:29,397
if you're not doing these sort of podcasts
our audiences are hearing,

796
00:38:29,397 --> 00:38:30,431
my goal is to speak around

797
00:38:30,431 --> 00:38:34,231
the world, around what's happening,
because it's I want people to understand

798
00:38:34,231 --> 00:38:38,097
what's happening so that they can either
take advantage and also think

799
00:38:38,097 --> 00:38:41,764
about the implications for where
they're at in life or in business.

800
00:38:41,764 --> 00:38:42,897
Right.

801
00:38:42,897 --> 00:38:45,597
So I couldn't agree with you more.

802
00:38:45,597 --> 00:38:46,597
I think it's interesting.

803
00:38:46,597 --> 00:38:51,431
One of the things that also scares me,
and I'm trying to think about both sides

804
00:38:51,431 --> 00:38:54,864
of the perspective here,
because a lot of the work we do is more on

805
00:38:54,864 --> 00:38:57,964
the automation data
and genetic, all this stuff.

806
00:38:57,964 --> 00:39:00,064
And then there's the whole robotic side,
right?

807
00:39:00,064 --> 00:39:02,897
And with Elon saying by 20,

808
00:39:02,897 --> 00:39:06,297
I think 2040
that we're going to have more humanoids

809
00:39:06,297 --> 00:39:10,264
than humans on the planet, scares
the shit out of me a little bit. Rob.

810
00:39:10,264 --> 00:39:13,297
I know the
I know the little bit of things,

811
00:39:13,897 --> 00:39:16,997
you know, and like,
you know know policy is should it's

812
00:39:18,797 --> 00:39:21,864
like, whoa, that's crazy.

813
00:39:21,864 --> 00:39:26,564
But that's that's the way the world, like,
you know, the world and it's,

814
00:39:27,630 --> 00:39:29,830
and again,
I think we'll learn some lessons.

815
00:39:29,830 --> 00:39:30,764
You know what?

816
00:39:30,764 --> 00:39:34,830
I will not we're we're always wrong
when we when we predict the future.

817
00:39:35,230 --> 00:39:35,864
Yeah.

818
00:39:35,864 --> 00:39:38,730
But I just say, what I do
believe is that there are lessons

819
00:39:38,730 --> 00:39:40,797
to be learned from the past,
not to lean on them.

820
00:39:40,797 --> 00:39:44,597
And I do think there's going to be
there's a lot that hasn't been addressed

821
00:39:44,597 --> 00:39:46,564
and that we haven't
thought about, with this.

822
00:39:46,564 --> 00:39:50,430
So, and that's why, you know,
understanding this technology is not

823
00:39:50,430 --> 00:39:53,164
there's not there's no opting out,
you know, just say like we can

824
00:39:53,164 --> 00:39:55,764
you can't put your head in the sand
and just say, I'm

825
00:39:55,764 --> 00:39:58,697
not going to adopt the technology
because you will get left behind.

826
00:39:58,697 --> 00:40:00,930
You will not be able
to build your business.

827
00:40:00,930 --> 00:40:03,964
You won't be able to participate
in society.

828
00:40:04,630 --> 00:40:08,797
There is no option other than adopting
the technology, learning

829
00:40:08,797 --> 00:40:10,230
and then figuring out
how you make it better.

830
00:40:10,230 --> 00:40:12,264
I mean, that's what I tell people.

831
00:40:12,264 --> 00:40:14,030
Yeah,
I think from a practical perspective,

832
00:40:14,030 --> 00:40:14,864
just because I'm

833
00:40:14,864 --> 00:40:17,997
sure we have a lot of entrepreneurs
on this, on this, in your community.

834
00:40:17,997 --> 00:40:18,664
Right.

835
00:40:18,664 --> 00:40:21,964
Think about like this, your technology
stack

836
00:40:21,964 --> 00:40:25,797
that you normally have for operations
or marketing everything.

837
00:40:25,797 --> 00:40:28,164
There's going to be a whole new technology
stack, right?

838
00:40:28,164 --> 00:40:30,030
I mean, able technology stack.

839
00:40:30,030 --> 00:40:32,530
It's actually something I get asked
probably the most.

840
00:40:32,530 --> 00:40:34,864
Rob is like, what do I use for this?
What do I use for that?

841
00:40:34,864 --> 00:40:37,530
So it's like, is it like,
what's the best tools

842
00:40:37,530 --> 00:40:40,830
ten x 15 x your productivity or whatever
it may be?

843
00:40:40,830 --> 00:40:43,764
And I think it's something that everyone
needs to start to think about,

844
00:40:43,764 --> 00:40:47,664
because there's one thing of creating
custom and unique things which, you know,

845
00:40:47,664 --> 00:40:50,697
depending on where you are in business
and what your goals are

846
00:40:50,697 --> 00:40:53,097
and all the things,
there's lots of opportunity there.

847
00:40:53,097 --> 00:40:57,564
But there's another just being because I
it's like a big buzzword right now.

848
00:40:57,564 --> 00:40:58,630
At the end of the day,

849
00:40:58,630 --> 00:41:01,330
everybody's going to be running
an intelligent business, right?

850
00:41:01,330 --> 00:41:02,730
Like that's really what this is.

851
00:41:02,730 --> 00:41:07,164
So it's about, you know,
what are those two ChatGPT is great,

852
00:41:07,164 --> 00:41:08,497
but it's not the end all be all.

853
00:41:08,497 --> 00:41:10,797
There's so much so much more out there.

854
00:41:10,797 --> 00:41:15,664
So anyway, I, I just think that's a really
important thing for any entrepreneur

855
00:41:15,664 --> 00:41:19,430
or even any business leader to start
to think about is what is our AI enabled

856
00:41:19,730 --> 00:41:23,830
tech stack, and how is that going to help,
you know, amplify our productivity,

857
00:41:23,997 --> 00:41:26,930
our experiences,
our customer support, etc., etc.?

858
00:41:26,930 --> 00:41:29,797
Yeah, I mean, I, totally agree.

859
00:41:29,797 --> 00:41:31,864
And how you just
made me think about this is,

860
00:41:33,097 --> 00:41:35,230
I would probably ask a business owner

861
00:41:35,230 --> 00:41:38,230
or a government official
or a nonprofit or whoever,

862
00:41:39,030 --> 00:41:42,030
what is, repeatable, scalable process

863
00:41:42,597 --> 00:41:45,430
that you have for your best practices?

864
00:41:45,430 --> 00:41:48,897
What is what is the repeatable,
scalable process that you have for

865
00:41:49,964 --> 00:41:52,964
things that you that that are going
wrong in your business to improve?

866
00:41:53,330 --> 00:41:55,797
And then I would ask a third question,
how can I be

867
00:41:55,797 --> 00:41:59,697
used to help and amplify
the first two questions?

868
00:41:59,697 --> 00:42:00,430
Right.

869
00:42:00,430 --> 00:42:03,064
Because you got to really think about
like there's

870
00:42:03,064 --> 00:42:07,030
there's nothing that I can't help
you do better.

871
00:42:07,030 --> 00:42:07,830
When you think

872
00:42:07,830 --> 00:42:11,997
about the current pain points you have
and the things that you do well,

873
00:42:12,130 --> 00:42:15,397
it can both amplify
the things you do extremely well,

874
00:42:15,930 --> 00:42:19,730
and it can minimize the pain points
you have for things you do poorly.

875
00:42:20,030 --> 00:42:25,264
So really thinking about what those things
are specifically and thinking about how

876
00:42:25,864 --> 00:42:29,364
AI applies to those things will save you

877
00:42:29,364 --> 00:42:32,730
so much time, money,
and make you more money.

878
00:42:33,364 --> 00:42:37,464
So I tell people to, to to learn
by doing experiment as much as possible.

879
00:42:37,797 --> 00:42:40,664
Is there any tools that you like,
one or 2 or 3 tools that you use?

880
00:42:40,664 --> 00:42:41,897
And you you highly recommend that?

881
00:42:41,897 --> 00:42:44,897
I want to ask you
a couple wrap up questions, man.

882
00:42:45,297 --> 00:42:49,230
I mean, obviously the ChatGPT world
and but it's not just that for me.

883
00:42:49,230 --> 00:42:51,930
I look at like Claude,
I use Claude, I use perplexity.

884
00:42:51,930 --> 00:42:56,097
It really depends on if I'm more research
driven stuff or complexity.

885
00:42:56,097 --> 00:42:59,097
Right. Which I use for research a lot.

886
00:42:59,097 --> 00:43:02,830
I mean, I'm a I'm a podcaster too,
so I use opus clips, which is like,

887
00:43:03,030 --> 00:43:05,830
I just want you to understand
if you use opus clips of you really,

888
00:43:05,830 --> 00:43:06,930
I use opus clips.

889
00:43:06,930 --> 00:43:09,064
Okay. Just this is again perspective.

890
00:43:09,064 --> 00:43:10,530
Not too long ago.

891
00:43:10,530 --> 00:43:13,597
This is like not too long ago
to create a clip.

892
00:43:14,530 --> 00:43:15,464
I have a podcast.

893
00:43:15,464 --> 00:43:17,330
I don't get it for five years

894
00:43:18,297 --> 00:43:21,564
and you're
like, you had to literally get the video.

895
00:43:21,564 --> 00:43:26,064
Somebody had to transcribe your podcast
said this was a year and a half ago.

896
00:43:26,064 --> 00:43:27,864
A lot too long ago
was a year and a half ago.

897
00:43:27,864 --> 00:43:29,230
It wasn't a long time ago.

898
00:43:29,230 --> 00:43:30,097
This opus clips.

899
00:43:30,097 --> 00:43:33,797
You put your entire episode in
and you can prompt for like,

900
00:43:33,964 --> 00:43:35,664
you know, I want engaging moments,

901
00:43:35,664 --> 00:43:37,530
I want some funny moments,
I want this and the other.

902
00:43:37,530 --> 00:43:39,497
And all of a sudden 25 clips come in.

903
00:43:39,497 --> 00:43:43,930
And not only that, it's like between
one minute and five, you can be precise,

904
00:43:44,064 --> 00:43:47,230
you can go in and edit it,
you can add different parts of the script.

905
00:43:47,230 --> 00:43:48,730
It is to me.

906
00:43:48,730 --> 00:43:51,597
And actually funny,
I just reached out the CEO to the CEO

907
00:43:51,597 --> 00:43:54,330
because I really want to talk to you
because I feel like one, I,

908
00:43:54,330 --> 00:43:57,297
I feel like there's some products out,
but those are products

909
00:43:57,297 --> 00:44:01,297
that I want to amplify to my community
because they're done well.

910
00:44:01,297 --> 00:44:04,230
And, you know, the people that are in
it are in it to win it.

911
00:44:04,230 --> 00:44:05,230
Yeah. Right. Yeah.

912
00:44:05,230 --> 00:44:10,697
And that to me is it's such a, because,
I got another one for you to go for.

913
00:44:11,130 --> 00:44:13,330
No, but I have you use notebook alum.

914
00:44:13,330 --> 00:44:14,197
Oh, yeah.

915
00:44:14,197 --> 00:44:17,564
The one that brings everything together
and makes your podcast like it's free.

916
00:44:17,564 --> 00:44:18,130
That's free.

917
00:44:18,130 --> 00:44:20,797
And when I talk about that,
because that's, like, the coolest thing.

918
00:44:20,797 --> 00:44:20,964
Yeah.

919
00:44:20,964 --> 00:44:24,497
Like, no, just literally for my questions
with you today,

920
00:44:24,497 --> 00:44:27,497
I use notebook
LM like literally I did that,

921
00:44:27,797 --> 00:44:31,130
put it together, pull the sources together
and help me organize it.

922
00:44:31,130 --> 00:44:35,763
And what what normally takes me who used
to take me hours to prepare for a podcast.

923
00:44:36,197 --> 00:44:36,897
It takes me now.

924
00:44:36,897 --> 00:44:38,830
I've done it for a lot of time,
so that's all.

925
00:44:38,830 --> 00:44:41,597
I also have some knowledge, but.

926
00:44:41,597 --> 00:44:45,097
And now what used to take me three hours
probably takes me 20 minutes

927
00:44:45,097 --> 00:44:46,963
of prep, right?

928
00:44:46,963 --> 00:44:47,597
Probably.

929
00:44:47,597 --> 00:44:50,897
And it's starting to get less
because that is like no big deal.

930
00:44:51,030 --> 00:44:54,030
You're just able to pull any source
in, it'll organize it for you,

931
00:44:54,030 --> 00:44:56,663
put the notes together for you,
you can ask the question and it's free.

932
00:44:57,863 --> 00:45:00,963
It's just amazing, like
the amount of tools that are out there.

933
00:45:00,963 --> 00:45:06,030
So I recommend people to experiment, pay
for some of the stuff, even with ChatGPT

934
00:45:06,163 --> 00:45:10,530
pay for the to pay the $20 a month
and then do some of the other stuff.

935
00:45:10,530 --> 00:45:13,530
If you have anything like accounting
processes.

936
00:45:14,430 --> 00:45:15,763
You know, something I've done is you.

937
00:45:15,763 --> 00:45:18,430
Because I'm not great at processes,
but you have to be to scale businesses.

938
00:45:18,430 --> 00:45:20,263
But I started creating processes,

939
00:45:20,263 --> 00:45:23,263
writing it down, then
using GPT to help with other stuff I did,

940
00:45:23,463 --> 00:45:26,230
and then dictating that
and then using ChatGPT

941
00:45:26,230 --> 00:45:28,463
or something else
to come up with better results

942
00:45:28,463 --> 00:45:30,663
and making sure that I'm creating standard
operating procedures.

943
00:45:30,663 --> 00:45:34,563
I mean, this can really
you are literally hurting yourself

944
00:45:34,563 --> 00:45:36,297
by not adopting the new technology.

945
00:45:36,297 --> 00:45:38,830
So all right, a couple of things
I want to get to you at the end,

946
00:45:38,830 --> 00:45:39,897
kind of rapid fire questions.

947
00:45:39,897 --> 00:45:42,563
Now, these are hard questions.

948
00:45:42,563 --> 00:45:44,497
Yeah. Always true. People are all right.

949
00:45:44,497 --> 00:45:45,497
I say things like that.

950
00:45:45,497 --> 00:45:47,663
And I know you're just.

951
00:45:47,663 --> 00:45:48,030
All right.

952
00:45:48,030 --> 00:45:51,197
What's an important truth you have that
very few people agree with you on?

953
00:45:52,830 --> 00:45:55,830
Oh, important truth.

954
00:45:56,130 --> 00:45:57,930
Integrity is everything.

955
00:45:57,930 --> 00:45:58,863
Whatever that that is.

956
00:45:58,863 --> 00:46:00,630
Integrity is my number one value.

957
00:46:00,630 --> 00:46:02,997
I feel like if you're going to
do something, say something.

958
00:46:02,997 --> 00:46:04,763
Do it.

959
00:46:04,763 --> 00:46:06,330
But it's really hard to do.

960
00:46:06,330 --> 00:46:07,430
It's a really hard to do.

961
00:46:07,430 --> 00:46:09,530
Keep integrity with yourself
and with others.

962
00:46:09,530 --> 00:46:12,197
So to me, it's it's the source of truth.

963
00:46:12,197 --> 00:46:14,097
Integrity. Yeah.

964
00:46:14,097 --> 00:46:17,497
You know, I say the truth is simple, and
life is simple is just not easy, right?

965
00:46:17,497 --> 00:46:18,197
It's just like.

966
00:46:18,197 --> 00:46:20,863
It's like it's just the truth.

967
00:46:20,863 --> 00:46:22,963
All right.

968
00:46:22,963 --> 00:46:26,630
You have a committee of three,
living or dead, advising you on life.

969
00:46:26,630 --> 00:46:28,563
Who would these three people be and why?

970
00:46:28,563 --> 00:46:31,230
My dad, he passed was 23.

971
00:46:31,230 --> 00:46:33,897
I have so many questions for him. Hands
down.

972
00:46:33,897 --> 00:46:36,830
Wow. You would ask him right
now, you're thinking, oh, my God.

973
00:46:36,830 --> 00:46:38,730
I mean, I would ask him
so many business questions.

974
00:46:38,730 --> 00:46:39,797
So many life questions.

975
00:46:39,797 --> 00:46:42,063
I feel like he was a community builder.

976
00:46:42,063 --> 00:46:42,997
He was a business owner.

977
00:46:42,997 --> 00:46:47,163
Like he him and I, we would have wrapped
on every part of my life.

978
00:46:47,163 --> 00:46:47,763
Robert.

979
00:46:47,763 --> 00:46:50,730
Like, he was so insightful, like,
you know, and I was one thing

980
00:46:50,730 --> 00:46:51,630
you could think you wanted.

981
00:46:51,630 --> 00:46:53,663
You want to tell him right now?
What would you tell him?

982
00:46:53,663 --> 00:46:57,397
I'm staring at his picture,
and I'm just like, how he's influenced me.

983
00:46:57,397 --> 00:46:59,297
And he's the reason I do what I do.

984
00:46:59,297 --> 00:47:02,430
And like, for me,
it's like I'm building his legacy.

985
00:47:02,797 --> 00:47:05,630
Because he was an incredible human.

986
00:47:05,630 --> 00:47:08,830
His life was too short,
and I'm just trying to keep going.

987
00:47:08,830 --> 00:47:11,830
What he started, and hopefully amplify it.

988
00:47:11,897 --> 00:47:14,430
I'm sure he's proud of you. Yeah.
Thank you.

989
00:47:14,430 --> 00:47:16,130
Thank you so much. Yeah.

990
00:47:16,130 --> 00:47:18,397
Who are your other two? My other two.

991
00:47:20,130 --> 00:47:21,830
I would

992
00:47:21,830 --> 00:47:24,830
Michelle, Michelle Obama, I,

993
00:47:24,863 --> 00:47:27,930
I think her perspective on life

994
00:47:28,263 --> 00:47:30,297
personally and professionally,

995
00:47:30,297 --> 00:47:33,297
her resilience and all the things
that she's done and accomplish,

996
00:47:33,297 --> 00:47:37,630
I just want some very strong
females around me

997
00:47:37,930 --> 00:47:40,797
that will push me in ways
that I've never been pushed before, and

998
00:47:40,797 --> 00:47:44,363
I just appreciate her honesty
and transparency.

999
00:47:45,330 --> 00:47:49,430
And just what she continues to show up
and how she shows up in this world.

1000
00:47:49,430 --> 00:47:52,430
So that would be definitely number two.

1001
00:47:53,897 --> 00:47:56,897
Number three, that's a hard one for me.

1002
00:47:58,163 --> 00:47:59,730
Doesn't have to be three weakest
opportunities.

1003
00:47:59,730 --> 00:48:00,797
Two is two.

1004
00:48:00,797 --> 00:48:01,897
I can't do two.

1005
00:48:01,897 --> 00:48:03,997
And I want to come back to it
because, you know,

1006
00:48:03,997 --> 00:48:06,030
I here's the one that actually
I would love somebody.

1007
00:48:06,030 --> 00:48:08,130
And I don't know, that's
what I have to think about. Who,

1008
00:48:09,430 --> 00:48:09,830
but someone

1009
00:48:09,830 --> 00:48:13,763
who in the emerging technology
space would be really interesting.

1010
00:48:13,763 --> 00:48:16,763
And I don't know if it's Mark.

1011
00:48:17,130 --> 00:48:21,130
Because, I mean, you shouldn't
discriminate, obviously.

1012
00:48:21,530 --> 00:48:26,263
Sam Altman
I think it would be really amazing,

1013
00:48:26,263 --> 00:48:30,697
intriguing and scary to understand
what's going on in his brain.

1014
00:48:30,697 --> 00:48:35,263
And I'm very good at interviewing and
just getting into some deep conversations.

1015
00:48:35,363 --> 00:48:38,363
We're going to project
that that you're going to get him on a.

1016
00:48:38,363 --> 00:48:41,030
And the reason
why is if we want to be leaders

1017
00:48:41,030 --> 00:48:42,297
and have voices in the space,

1018
00:48:42,297 --> 00:48:45,263
like you have to understand
where people are coming from.

1019
00:48:45,263 --> 00:48:49,497
And he such a unique perspective
and so much depth.

1020
00:48:51,063 --> 00:48:54,130
And you want to hear both
sides, the extreme sides and the sides.

1021
00:48:54,130 --> 00:48:57,463
And then that allows you
to actually create informed decisions.

1022
00:48:57,463 --> 00:49:01,397
I, I just for him, you know,
make an AI agent out of his brain.

1023
00:49:02,097 --> 00:49:02,330
He's.

1024
00:49:03,397 --> 00:49:05,030
Yeah, it's a good idea.

1025
00:49:05,030 --> 00:49:06,163
There you go.

1026
00:49:06,163 --> 00:49:08,997
Hey, hey, Chad, it's ag Sam Altman.

1027
00:49:08,997 --> 00:49:11,997
Okay, well,

1028
00:49:12,197 --> 00:49:13,197
all right, final question.

1029
00:49:13,197 --> 00:49:16,197
What's your what
what's your theme and slogan in life?

1030
00:49:16,863 --> 00:49:19,163
Impact and profit?

1031
00:49:19,163 --> 00:49:19,697
It's.

1032
00:49:19,697 --> 00:49:22,163
Yeah, I have many,
but that one has stuck with me.

1033
00:49:22,163 --> 00:49:26,330
I just feel like for everything I do,
I want to make sure

1034
00:49:26,330 --> 00:49:29,530
I'm adding a ton of value
and making a crazy amount of impact.

1035
00:49:29,930 --> 00:49:34,097
And I think you can do that
by living a really sustainable life.

1036
00:49:34,097 --> 00:49:34,597
Life.

1037
00:49:34,597 --> 00:49:38,563
And you can do that and add more value
and more impact when you do have that.

1038
00:49:38,563 --> 00:49:42,430
And I feel like in the entrepreneurial
world, in the nonprofit world,

1039
00:49:42,630 --> 00:49:45,863
in the government world,
a lot of people don't have that stability.

1040
00:49:45,863 --> 00:49:47,397
And I think a lot. So that's

1041
00:49:47,397 --> 00:49:51,030
always been my mantra when I help people
create sustainable businesses.

1042
00:49:51,163 --> 00:49:54,763
But I'm thinking AI and opportunities,
it's impact and profit, right?

1043
00:49:55,263 --> 00:49:56,097
Yeah.

1044
00:49:56,097 --> 00:49:57,030
It's about like,

1045
00:49:57,030 --> 00:50:00,163
the truth about innovation
and talk about this like in terms of like

1046
00:50:00,796 --> 00:50:03,796
what's happening, what needs to happen,
how people need to be framing.

1047
00:50:03,796 --> 00:50:04,430
It's one of those things

1048
00:50:04,430 --> 00:50:09,330
that's been in my brain because, like you,
I see the patterns connecting

1049
00:50:09,330 --> 00:50:12,630
and what and what and how
and how we need to be thinking about

1050
00:50:13,496 --> 00:50:16,830
business innovation and growth
in order to make sure

1051
00:50:17,596 --> 00:50:21,863
that, you know, that we're well positioned
as a and that businesses are,

1052
00:50:21,863 --> 00:50:24,996
but also the communities that normally are
well positioned are well positioned.

1053
00:50:24,996 --> 00:50:27,663
But anyway,
I want to think about that. Why?

1054
00:50:27,663 --> 00:50:29,130
You know what I mean?

1055
00:50:29,130 --> 00:50:31,096
It's definitely
I have to write it like I have,

1056
00:50:31,096 --> 00:50:32,963
like I was going to write everything
on the unique method

1057
00:50:32,963 --> 00:50:35,663
before the repositioning,
but now I'm like everything,

1058
00:50:35,663 --> 00:50:37,030
this is the future of business.

1059
00:50:37,030 --> 00:50:38,796
Like I need to be known for that.

1060
00:50:38,796 --> 00:50:42,930
Like it is an important thing
for me is like I see things and so do you.

1061
00:50:42,930 --> 00:50:45,596
So I'm also let's do it.

1062
00:50:45,596 --> 00:50:49,096
I want to use that as an ability
to get paid internationally.

1063
00:50:49,096 --> 00:50:51,663
And speaking. Yeah. That's we, we,
we share that.

1064
00:50:51,663 --> 00:50:52,530
We need to think about that.

1065
00:50:52,530 --> 00:50:54,563
Let's, let's, let's let's do it.

1066
00:50:54,563 --> 00:50:57,363
See my Alexander, who's also going to be,

1067
00:50:57,363 --> 00:50:59,930
a feature speaker at Midwest Con 2025,

1068
00:51:01,063 --> 00:51:01,496
also the

1069
00:51:01,496 --> 00:51:05,596
co-founder of DC startup
a Tech Week, also co-founder of Virgin

1070
00:51:05,596 --> 00:51:09,663
I building agents and helping midsize
businesses learn how to implement AI.

1071
00:51:09,663 --> 00:51:10,830
It's been such a pleasure.

1072
00:51:10,830 --> 00:51:12,696
I can't wait to talk more with you.

1073
00:51:12,696 --> 00:51:14,896
I will be in DC next week by the way.

1074
00:51:14,896 --> 00:51:17,896
So for connecting back
if you have time and

1075
00:51:18,930 --> 00:51:21,430
love everything you're doing
and let's continue to build.

1076
00:51:21,430 --> 00:51:23,163
Awesome. Thank you for having me.

1077
00:51:23,163 --> 00:51:25,396
This is an awesome conversation.
Thank you so much.