Welcome to Milestone Moments, the show where
we explore the journeys that lead to success.
I'm Sheila Slick, your host and founder of Five
Milestones. In every episode, we will bring you
insights from the minds of entrepreneurs, leaders
and experts who will share not just their expertise,
but the milestone moments that have reshaped
their journeys and led to significant achievements.
So if you're looking for motivation, you're in
the right place. Subscribe now and discover the
milestones that mark the path to success. Welcome
to another episode of Milestone Moments in Business
and Leadership. I'm Sheila Slick, your host.
And joining us today is Mike Tedasco, a seasoned
expert in innovation and leadership. Mike is
currently a visiting fellow at the James Silberrod
Brown Center for Artificial Intelligence at San
Diego State University. Previously, he served
as the Senior Director of Innovation at PayPal,
where he led transformative initiatives in technology
and business strategy. With a wealth of experience
in fostering innovation and empowering future
leaders, Mike brings valuable insights on leadership,
workforce development, and the role of technology
in shaping the future. Welcome to the show, Mike.
Sheila, thank you for the kind intro. Let's try
and empower your audience today. Let's do that.
I'm excited about this chat. Me too. I don't
even know like where to start. So let's start
with PayPal, right? Because we're in an era where
innovation and AI is such a big part of our lives
and a lot of people don't know how to navigate
it or they have fear. So tell us a little bit
about what you do and what you did. Yeah. Yeah.
Well, let me let me start with PayPal and then
we'll get more on what I do today after that.
So I joined PayPal after a failed startup. I
was out of my MBA program while everybody else
was getting a job as a consultant or whatever.
I'm like. i'm gonna start a comic book company
because why not um that was literally my plan
after that and after doing that for two years
i'm like this is not getting me to where i want
to be like there was you know many successes
but like you know it's always you know a step
forward and two steps back with it and after
a couple years of doing i'm like okay I need
to find something else. I was a customer of PayPal.
That's what I was using to process my payments
on the e -commerce site that I built. And it
was very logical. I had a lot of classmates that
worked there. So when PayPal had this job on
the mobile team, this was back in 2011, I was
like, cool, mobile is exciting. There's a real
future in that and so forth. So I jumped on it.
And for whatever reason, they hired me. And my
plan was to be at the company for a year. I wound
up being there for 11 years. And the first half
was in various roles within the product world.
And I could talk more about what that means.
And the back half was running innovation. And
which was super fun. As I like to tell people,
like every Sunday night, I was basically just
excited to go to work the next day because it's
like the job was awesome. It was so exciting,
so much fun. And I just I loved it. And I just
had a wonderful 11 years there. Well, 11 years
is a long time. So let's go back to that failure
that you spoke about. And I want to bring that
up because even today, right, with AI, you have
so many people either looking to start a side
gig or wanting to go into entrepreneurship. And
I see software as a service just growing and
growing and growing and growing. And I see a
lot of founders wondering. How do I take this
to that next level? And we all know that startups
have a very high failure rate and failure isn't
always bad. So tell us a little bit about that
and how you overcame it and how you see failure
in general. Failure isn't bad as long as you
learn from it. And that's the big thing. And
I think within organizations, I think that's
often tough because failure impacts your bonus.
Failure impacts the perception that others have
with you within the company. And I'll get to
my start, but one thing that we were actually
doing at PayPal, in fact, this was right before
COVID, we were building something that was inspired
by Ben & Jerry's. Ben & Jerry's at their headquarters
out in Vermont, they actually have what's known
as a failure graveyard or an ice cream graveyard.
So in front of their headquarters, they have
like little tombstones set up for all of the
flavors of ice cream that they no longer make.
Why do they do that? Well, it serves as a couple
of things. One, it's almost ceremonious to be
able to put that out there. Like, you know, it's
like, hey, it's OK. We tried something and, you
know, it's putting it out there. And it's also
like a little bit of a reminder that it's OK
to do these things. Like we want to be a company
where that's allowed, because if you're not failing,
you're just not trying hard enough. Like, look,
if you're applying to colleges and you get into
every school that you apply to. uh you probably
should have actually tried to apply to some other
colleges maybe maybe the next year above that
or something like you know i mean for the most
part or like you're so great that you should
just apply to the one and gotten in i mean you
did something wrong in the process there like
failure is part of just everything that we do
and it's just again as long as you're learning
from that it's just a signal for everything else
so paypal we were literally making Like we one
day went to the store, we bought like these like
model train size people and all that. And we're
building a scaled down version about the size
of a large conference room table of the PayPal
campus where we're going to have QR codes of
all the different failed products of the past
with the founders. Sorry, the creators of those
products telling the story about them. And so
that was going to be our little failure graveyard
that we had there. And it was very resonant with
me. I was on a product at PayPal called PayPal
Beacon. And it was an amazing technology. It
got me into the world of patents, got me into
all this stuff. It was way, way, way ahead of
its time. If anybody goes on YouTube, type in
PayPal beacon and you could see something from
12 years ago where we were building this and
was basically a hands -free way to pay for stuff
in stores. You know, you literally didn't have
to take your phone out of your purse or your
pocket. You would walk in, it would identify
you. If you're going to a Starbucks, it could
even just see that you're pulling into the parking
lot and maybe you get the same thing every time.
And it would anticipate that through machine
learning techniques and, you know, and have your
coffee ready for you before you even walk into
the store. A lot of interesting things like that.
It wasn't the right time. Like we demoed this
at Stanford University, right up the street from
PayPal office. A lot of tech friendly people
there on University Avenue. We had relationships
with a few of the merchants on the streets. And
when I would talk to students about it, they're
like, why would I ever use my phone to buy something
in a store? That was literally the answer that
we were getting again and again in 2013. It failed.
It failed miserably. The world wasn't ready for
that. It was cool technology, but we weren't
solving a problem that people had at that time.
But, you know, if you remind people of that,
you know, if I was at PayPal today, I'd be like,
hey, remember that thing we did 10 years ago?
Why are we not doing that today? The world's
a different place. Like, can't we learn from
that and do that? Like, that's why you just don't
sweep these under the rug, act like these things
don't happen, because, you know, a lot of failure
is just timing. I mean, Apple was not the first
company that came up with a touchscreen for a
phone device and so forth. Like, you know, there
was General Magic did this in the 1990s. The
90s were not a time. The cell phone networks
were not ready for this. Like there was, you
know, I mean, it was just timing. But if you
kind of repackage that in a different time, a
failure turns into a huge success. Yeah, even
in social media, when I see TikTok, I'm thinking,
well, this was Vine like a decade ago. Vine,
like it existed and then it ceased to exist.
So I'm like, is it the algorithm? What makes
a very similar product succeed versus, you know,
the other one? And Vine, I think was from Twitter.
And so it wasn't like a little tiny. Their price,
Twitter was pretty big at the time when they
introduced Vine. Yeah, and you never know. I
mean, and that's why you have to experiment because
there isn't just one solution of, hey, this is
how I'm going to build a product that's going
to succeed. Hey, this is the type of video or
post that the algorithm is going to love that's
going to get me, you know, 100 ,000 likes or
whatever it is, whatever it is you're going like.
There's always experimentation. Frankly, that's
what makes all this stuff fun. But if you're
not experimenting, if you're just doing the same
thing and so forth, you're going to miss a lot
because the world that we're in now is changing
fast. I was teaching an AI class earlier this
week. Two sessions, a Monday session and a Wednesday
session. On Monday, I presented one deck. Wednesday
afternoon before I was teaching, I actually had
to go back and change about 10 % of all the content
that I had in there because in the last 48 hours,
the world changed enough. I'm like, oh God, that
stuff I was talking about on Monday is now out
of date. And I'm not joking. And I told the class
this, I'm like, you are actually getting different
material than on Monday. Like that's the world
that we're in. And frankly, if you're always
just assuming, hey, what we're doing is fine.
We're not experimenting. We're not doing all
this other stuff. You are. going to miss out
on these vast quick quick changes that we're
going to start to see in our society so let's
talk a little bit about those changes i'd love
to pick your brain because i think it's more
important than ever to adapt it's disrupting
at an unprecedented pace, the technology. I personally
had heard machine learning. I don't know that
I quite understand machine learning. It's kind
of like the machine continues to learn on its
own, right? Like it's going from A to B and it'll
just keep testing how to get from A to B faster.
That's how I understand machine learning. So
if you can explain some of this AI so the general
population that's not a techie, we can understand.
And I'm not a techie either. That's a great thing
about that. Again, I started in finance and accounting
way back in the day. So that's why I love to
explain things to, as I say, normal folks like
myself who might not be engineers. So I think
there's traditional computing, and then there's
kind of artificial intelligence, machine learning,
all of these things. Those are the two buckets.
Traditional computing, you tell a very specific
code, and you say, you know, print hello world,
and the words hello world will show up on your
screen. And it goes down to binary and all this
stuff, but that's how traditional computing works.
It is going to do that 100 % of the time when
it is running that code. It is going to give
you the exact result that you were looking for.
The world that we're in with AI and machine learning
today, and specifically with large language models,
this would be ChapGPT and Claude and all those,
they work differently than that. How they work
is they're trained on a whole bunch of data.
Like imagine just all the data that's on the
internet. Every single word that's ever been
written on the internet is trained in these models.
What they're doing is they're finding patterns
in there. And they do this through something
called tokens. So it's kind of like a representative
for a word, largely speaking. And they just look
at patterns in this. So if I said to anybody,
Mary had a little blank, most people are going
to say, well, the next word should be lamb as
part of that, because we know that. That's well
known. Mary had a little lamb and so forth. The
AI model will know this too. You could type in
Mary had a little, what do you think is the next
word? And any AI model is going to return lamb,
but it's not always going to return lamb. It's
going to return it 99 % of the time or something
like that, because this is all mathematical calculations.
So, because sometimes people have, and this is
all based on what people have written in the
past. They may have written Mary had a little
Volkswagen Beetle or something or whatever it
might be. And it's just looking at these connections.
It's the next word prediction. Now, it's doing
that to the nth degree. I mean, 15 years ago,
it was revolutionary when it would predict your
next word in an email and that you could actually
do that on an iPhone. I think SwiftKey was one
of the first companies that did that. And you'd
be typing and it would say, OK, here's the next
word. This is what it's doing is saying not just
the next word, here are the next thousand words,
here are the next whatever. It's making, it has
become so much more advanced. But these are just
all mathematical probabilities. It's a mathematical
probability based on data that it's seen of what
the next word is going to be. And that at a very
basic level is how the large language models,
ChatGPT, all of those that everyone uses today,
that's how those things work. So how can we better
prepare ourselves today for the next, I don't
even know, 10 years, right? Can we just talk
maybe five years? What should we be doing as
small business owners or as professionals to
make sure that we're still relevant? Let's talk
five months even, just to be completely honest.
Let's start there. So here's what I would say.
And again, I always like to put out this disclaimer.
I don't own shares in OpenAI or Anthropic. I
intentionally don't. So I have no stake in this.
It sounds like I'm a salesperson for these companies.
There's a lot of good they do. There's a lot
of downsides in this. We could get to that later
if you want. But I just do want to preface with
this. That said, you need to be using these tools,
full stop. If you are not already using ChatGPT
or Claude or whatever it is in any of these aspects
of your business, you're falling behind. And
that's the honest truth. These models are going
to get better, but like you need to play with
them. You need to kind of understand how they
work and how they operate to see how they're
going to be able to help you out. One of the
hard things about this type of software versus
all the other software you've had before is that
the possibilities that you can do with these
models are infinite. And when most people have
infinite possibilities, they just freeze up.
They decide to do nothing. You know, Excel didn't
have that. Well, you type something in this one
and this one, and there's a formula here. You
can kind of see how things are connected to that.
There are just unlimited possibilities with what
you can do with these models. So what I always
tell people, start with your personal life. If
you're not familiar, just like literally. Make
it your default search engine. Take a company
like Perplexity, make that your default search
engine. It's an AI model. It's great. And you
will find, oh, you can ask much more elaborate
questions. You will be able to do this. You'll
be able to do all these other things instead
of searching in Google as you traditionally did
in a way that's much more advanced. Sign up for
the $20 a month ChatGPT version and you can get
something called Advanced Voice Mode. It's amazing.
I use it all the time. I use it for driving in
the car to school. I will have it question my
kids have a test or something. And I'll say,
hey, my daughter has a test, fifth grade level,
U .S. history, Revolutionary War, ask increasingly
difficult questions, make a multiple choice,
have her answer them, go. And we'll do that and
we'll have it going through the speakers in the
car and it'll just start asking these questions
for that. Whatever you want to do. I will go
on long walks with it. Ask it questions. Brainstorm
things. Think about what's on my to -do list
or there's a problem I'm trying to work through.
And the great thing is it transcribes everything.
So I can even say at the end, hey, can you summarize
everything we talked about? Can you give me just
the key takeaways of everything that we discussed
as part of this? And it will bring all of that
together in one place. Again, it's, you know,
or you're a small business owner. You get a bunch
of contracts coming in. One of my favorite things
to do whenever I get a contract, I'll throw that
into something like Claude and I'll say, hey,
I just got this contract. Is there anything unusual
in this? Is there anything that is not custom
in this contract or out of the ordinary? And
it knows that kind of stuff pretty well and might
say, well, this is a little bit weird, but like,
yeah, for the most part, this is a pretty standard
contract. I'm like, great. Now, if this was like
a $10 million contract I'm going to sign, I am
probably going to hire a lawyer, but. For most
things, like to get an answer in 30 seconds on
that, like that's pretty incredible. Like, OK,
I'm not going to read through that. I'm going
to do this. If it doesn't, you know, if I'm concerned,
I might throw it through a couple different models.
I might ask ChatGPT and Claude and Grok and whatever
the exact same question and just kind of triangulate
and see, does anybody notice anything wrong here?
But like, those are all things you can start
to do. And again, the problem is it's infinite
things you can do. And that's why you just have
to start working for that with them and find
out what is the best thing for you and dealing
with these models and how it's going to help
you most. Because these are just tools for us
to use. So that's the now. And where do you see
this in five years? The only job that I know
that's going to exist in five years is a solopreneur.
That when I talk to students two years ago, when
I was at, you know, talking to students that
were graduating, I would say to them, hey, just
learn these AI tools. It's 2023. Learn these
tools and you're going to go in there and your
coworkers are going to look at you like a god
because you're able to do all these magical things
in a fraction of the time that they can. Like
right now in coding, for example, if you're not
using AI to code, like I. I don't know what to
even say because it's just going to be that much
more difficult. It's not perfect. But the new
Gemini that Google has put out, we were doing
this just last night in our class. We had people
coding up games that they were playing within
three minutes. And they were just putting in
prompts. This is vibe coding. They're just talking
in English. They're doing this. They're seeing
that. And they're seeing the magic behind this.
Now, it's not as complex as a game that you're
going to pay $30, $40, $50 for or something like
that. but it's something and it's customized.
Like somebody was actually making a game. She
was making a game for her boyfriend. She's like,
oh my God, he's going to love this. Like, and
it was like, oh, it was super personal. Like
you can do that kind of stuff now. All of these
tools, sorry, I'm getting totally sidetracked,
Sheila. I mean, I get excited about this. What
was the question again? Bring me back. You had
me like in a daze, just learned it. No, it was,
where do you see it in five years? Yeah, five
years from now. Sorry, sorry. Solopreneur, that's
where I was going. Thank you. But when I talk
to these students today, I say like, you are
going, I mean, you already have the concept of
AI agents and these work decently well. And the
difference between like chat GPT and an agent
is effectively an agent. You're just going to
give like high level guidelines and say something
like, Hey, I need you to research the Minneapolis
market for me on. Houses that are under the Zillow
value within 10 miles of this location, within
this kind of school district, and they have no
pink inside the house. Whatever it is, something
like that. There is no way you could do that
with a search query. And to actually do that
would take a ton of time. But these AI agents
can do that. And probably within 30 minutes,
they would take... two days of work come back
to you and say like, okay, here are the results.
And you look over those results. It might only
be 90, 95 % accurate, but it's going to save
you a ton of time with that. This is growing
exponentially right now. Taking what I described
there, you would be able to then apply this kind
of agent concept to just about anything. It's
like, hey, this file, or actually you could probably
even say within a couple of years, hey, in my
email are all of the receipts I have for invoices
that I've received over the last year. I want
you to go through my email, find all of those.
categorize them in proper categories, put them
into our accounting ledger and go ahead and do
a first draft of my taxes. That's probably a
year or so away, maybe two years, like literally
what I just described there. So that's why when
I tell students now, the only job that I know
that's going to exist in five years, it's probably
something like, you know, a solopreneur. The
example I gave last night is like, say your passion
is golf course maintenance. Like you can build
a piece of custom software that is going to specifically
serve, you know, the maintenance needs of golf
courses. Like nobody is probably building that
software today. It's too hard, too difficult,
too whatever to do. You can do that. You could
package that. You could customize that and you
could sell it to, you know. a fraction of the
golf courses across the US, you'd be hyper -focused
on serving their needs. If anything goes wrong,
and this is one of the key things, because if
something goes wrong, like if they built that
themselves, if something goes wrong, they're
not going to call Sam Altman at OpenAI and say,
hey, Sam, this is broken. Like they got to figure
it out. The agent's got to figure it out. Often
people want to have, and that's not going to
change. People are going to want to have a human
at some point in the loop to talk about. And
that's why I really believe like a solopreneur
who is hyper -focused on building a solution
for a specific customer set is going to be the
one business that I know is going to exist five
years from now. Everything else is kind of up
in the air. What about physical robots? So even
that same golf course, it needs the grass cut
and the computer, that little AI agent can't
cut the grass. How far are we from seeing more
robots taking over some of the actual labor involved
in some of these sessions? Sheila, I'm going
to show my age here. My first house that my wife
and I bought was in 2004. And this was in Ohio.
And there was a company called Friendly Robotics.
They were based out of Israel. And I had them
shipped to me a grass cutting robot in 2004.
So this was over 20 years ago. I actually had
one of these. As you can imagine, this was like
in Cincinnati, Ohio in the suburbs. I was the
weird guy on the street because I had a grass
cutting robots while everyone else was pushing
their things. I would hit a button and the thing
would just go kind of like a Roomba out there.
It didn't do a great job, but this is also 20
some years ago. Fast forward to just last week,
I was at NVIDIA's GTC, which is their big conference
that they have here in San Jose, like 25 ,000
people there. I could not even tell you the amount
of different robots that I saw there. All of
these companies building these robots and so
forth. Figure Tesla with Optimus. You know, there
was a Disney robot that Jensen Wong, the CEO
of NVIDIA, had on stage. There's a lot coming
in robotics, for sure. It's a little bit further
off than the software side because there's some
more risks to robots. You know, if the robot
falls on somebody or whatever. Like there was
a company called Nightscope. They're still around.
They had a security robot. Several years ago
at the Stanford Mall, the security robot rolled
over a kid's arm. Like the kid was lying behind
the robot or something. They didn't plan for
that. That's hard. But that's also a real problem
to have that. There's much less risk in software
than there is with robots. So robots will come.
You know, I would say if you're in something
that really requires non -repetitive physical
work in some way, that's hard. I was talking
to a founder recently who was working on a robot
that would be doing stuff like cleaning. And
he was telling me how hard it is to get the thing
to fold sheets, like to make a bed. Super difficult.
I mean, if you really think about how precise
that is and he's like that to him is the holy
grail is to be able to actually make a bed for
that. And, you know, and, you know, because there's
just so many variables in that and have it do
it somewhat efficiently and not just take like
a half hour to make a bed. Those robots will
get that, but that's probably a little bit further
away. That probably is like. five plus years
away to like get to that level it will happen
in our lifetimes not as quickly as some of the
things that are more software related so since
you have evangelized creativity to employees
of every nation what is one effective technique
that you can recommend to spark innovation in
our everyday work So here's one thing I believed
when I was at PayPal. It became our slogan, something
that I believe strongly to this day. We are all
innovators. Everyone can innovate is what we
would always say. And it didn't matter what your
function was, what your background was. We are
innovators by just like the nature of us as part
of our species. This is how we got to where we're
at today in society. The key to innovation often
is just having. The freedom to make mistakes,
as we talked about before, and even just the
constraints or even the incentives around creating
an environment of innovation. If you're not going
to be rewarded for this, if you're going to be
knocked for failing or for whatever it might
be, there is not going to be creativity. I think
Maya Angelou has a quote saying that we're all
creative people until the age of eight when we
basically had it. knocked out of us, beaten out
of us, or whatever the quote is from her. And
like, you think about that, like schools often
do that. I mean, it's always like, there's an
answer. There's one right answer. Like, you know,
there's, you know, not all teachers are like
that, but a lot of just the regiments of school
and so forth does that. And look, I think that's
good to have in life, but I think it's, there's
also time for creativity. And so one thing I
would recommend, actually, let me, I'll tell
a story. In fact, somebody I used to know at
PayPal, this guy was straight out of college.
I was running innovation. One of the things in
the innovation we did was file patents. And he
was like, well, I want a patent. Like, that seems
cool. I want to be able to do that. So what he
did was he put aside 30 minutes every day to
just come up with ideas for stuff. And he would
actually do this while watching episodes of The
Office. That was like his mental thing. I think
he had seen the office many times. So it was
almost mindless for him. So he would put on the
office. It was kind of chill time. He had a notebook
and he would just write down ideas. And, you
know, at the end of that 30 minutes, he would
send a few to me. He's like, hey, I got anything
here. From what I remember, like, I think the
first 10. 15 things I'm like no no this is not
it like like more of this less of this more of
this less of this more of this like okay okay
and he just kept iterating again and again and
again just through each part of the process and
had you know sort of a coach in me to just kind
of like give little Little tweaks of guidance,
but he's stuck with it. He's persistent. A lot
of innovation is just being persistent with something,
to be completely honest. But, you know, he did
this for probably months and he got his first
patent. And you know what? He kind of started
to unlock the code of that. I think within probably
six months of starting... He had actually filed
like 15, 20 patents that have been granted since
by the U .S. Patent Trademark Office. Within
like a year from the point he kind of figured
it out that next year, he was just able to do
all these amazing things. And it comes from just
persistence. So, you know, finding a way, like
prioritizing it, setting some time aside where
he can actually do that, prioritizing that work,
getting a little bit better every time. Like
if you're not making, you know, 1 % improvements
in what you're doing, then it's not going to
be helpful. Put all of those things together
and you got somebody who is, you know, able to
do his goal and much more within a relatively
short amount of time. Consistency. Persist. Yeah.
Yes, absolutely. Absolutely. Well, so what is
your next milestone? My next milestone? Wow.
The thing I'm working on right now, and I'm almost
finished, I'm super excited about, I'm actually
writing a series of children's books. And for
me, so I have a publisher, they're going to release
those in late 2026. So they're quite some time
out, but they've been a little bit of a, they
go deep into the sciences. So it's actually,
they're fables about the periodic table. It is
literally called Periodic Fables is part of that.
And there are three different stories they're
going to release. And for me, that's going to
be a huge, exciting thing, being a published
author in an area that I'm not a chemist by any
stretch. So I had to learn a lot through that.
It was just wonderful just going through that
whole process. And to me, life is a bunch of
these little experiments where you learn stuff
and you bring it to other things in life. And
I just love that. So I guess that's my next milestone.
You had done comic books. That's how we began
the conversation. How is it different than comic
books? And what are you going to apply from that
failure of the comic book to the children's book?
Such a good question. So the comic book business,
I wasn't actually creating. I'm not an artist
either. I'm not an engineer. I'm not an artist.
I'm just a jack of all trades, master of none
is basically what I am. But what I was actually
building back in 2009, it was called SketchMaven.
It was a marketplace for comic book artwork.
So it was a place where artists could actually
come, sell their artwork and so forth, and people
would buy them and so forth as part of that.
But one of the things I learned just, and frankly,
spending a lot of time in this world was just
like layout, design. I've looked at... Thousands,
tens of thousands, hundreds of thousands, maybe,
I don't know, of comic pages in my lifetime.
And just understanding the layout, how to tell
a story, things like the passage of time within
a comic book. I think in the great book, if anybody's
interested, Scott McCloud's Understanding Comics.
It's probably came out in the 90s. But, you know,
I remember this so well, like McLeod talks about,
like, literally the space that you have in between
panels conveys different things to the audience,
you know, and so that actually might convey more
of a passage of time versus less and all these
things. It's a completely different and unique
art form that, you know, nobody out there has
mastered. There are so many different techniques.
There are different cultural perceptions in this
world. And for me, yeah, I think just spending
a lot of time with artists, with people in this
world has given me a whole appreciation that
I'm trying to, as a writer, convey some of that
to the wonderful artists that I'm working with
on the piece. Interesting. Well, it was a marketplace.
I love the chemistry because so many kids struggle
with science or chemistry. I did. I surely did.
I love math and I love technology. And in the
sciences, it's not my forte, right? So I'd probably
be a great candidate to perhaps try the periodic
fables to see if they stick with me, where my
daughter right now is getting a PhD in integrative
biology. And I'm like, whoa. Yeah, I'm constantly
reminding her. And I'm like. The key is to be
able to explain to me what you do, what you're
studying and the effects and just the basics.
And, you know, when did I study the periodic
table? I think I was in 10th grade. Well, I mean,
and that's something that comes over time. And
I think Richard Feynman. scientist has a quote
about this of like you know mastery of a subject
is being able to explain that to anybody you
know and that is one of the things large language
models do amazingly well you could put a document
into something like google's notebook lm and
say hey I don't get this. This is a white paper
about dark matter or something like that. I don't
understand any of this. Explain this to me as
if I was in sixth grade. And it could do that.
And you're like, okay, I think I get it. Now
let's do ninth grade. Let's do that. And that's
one of the wonderful things about AI tools is
they're infinitely patient. You can just keep
on doing this with them until you really get
it at the level that you're comfortable with
as well. And that's a technique I still use all
the time. I was just asking it the other day.
about, wait, what was I asking about? I asked
it about how things work all the time. I was
asking about how toilets work the other day because
I was like, oh, I actually really don't know
how a toilet works. And you know, it's almost
embarrassing, but I'm like, I don't know. And
I was even asking it the other day, how does
a calculator work? I have no idea. You just push
numbers in there and somehow it gives you the
answer. Well, how does that actually happen?
For people who are curious and gosh, like I hope
everybody out there is curious. That's why you're
listening to this pod and watching it and you're
learning. You want to learn more. You want to
make yourself better. Like for people who are
infinitely curious, like these tools are amazing
to be able to use to just ask questions about
like, I'll be walking around and I'll see something
like that looks industrial. I'm like, what the
heck is that thing? I'll take a picture of it
and say, what is this? Is this like for water?
What does it do? And I'll explain it to you.
Like, it's great. Well, thank you so much for
joining me today, Mike. Pleasure. Pleasure, Sheila.
No, it's great having you. Great conversation.
And thank you all for tuning in to another episode
of Milestone Moments in Business and Leadership.
Until next time.