July 28, 2025 • 15 mins
The stereotype that AI is only for tech experts is crumbling, and physical therapist Erik Lineberry is living proof. After nine years in clinical practice, Erik is making a bold career pivot into data science and AI – not because healthcare failed him, but because he sees an opportunity to bridge critical gaps between clinical practice and administrative decision-making.
What makes Erik's story particularly compelling is his pragmatic approach to learning. Rather than viewing AI as an intimidating technical challenge, he first embraced it as a solution to everyday problems. He shares how AI transformed his weekly meal planning from a multi-hour weekend chore into a task that takes mere seconds, all while maintaining personal preferences and dietary needs. This practical application demonstrates how AI can give busy professionals quality time back in their lives, making it easier to pursue further education and career growth.
Erik's journey highlights the unique advantage that domain experts bring to AI implementation. "Having that perspective of what actually happens in patient care gets lost sometimes when you just distill everything down to a spreadsheet," he explains. This clinical insight positions him to identify high-impact applications like preventative medicine, improved diagnostics, and pattern recognition that could transform healthcare delivery. Through his new blog series on AIReadyRVA.com, Erik is documenting not just his technical learning but practical AI applications anyone can use – from email organization and interior design to personal styling and vacation planning. Follow his candid, step-by-step journey and discover how your own professional expertise can find new expression in the AI landscape, regardless of your technical background. Your skills absolutely have a place in our AI-powered future.
Want to join a community of AI learners and enthusiasts? AI Ready RVA is leading the conversation and is rapidly rising as a hub for AI in the Richmond Region. Become a member and support our AI literacy initiatives.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Welcome back to Inspire AI, the podcast where we
explore how artificialintelligence is reshaping
careers, industries and the waywe think about the future.
Today's episode is for anyonewho's ever thought AI sounds
powerful, but I don't come froma tech background.
Could I actually learn this?
(00:21):
Well, let me introduce you tosomeone who proves that the
answer is a resounding yes.
Eric Lineberry is a physicaltherapist with nine years of
clinical experience, and todayhe's pivoting into the world of
data science and AI.
He's not just dabbling in tech.
(00:41):
Eric's learning Python, sql,business intelligence tools and
actively working to translatehis deep knowledge of healthcare
and insights through data.
But here's the really cool partEric isn't keeping this journey
to himself.
He's documenting it in a blogseries for AI Ready RVA, a
(01:03):
resource for non-technicalprofessionals and technical who
are curious about AI but don'tknow where to start.
So let's dive into Eric's story, one that blends science
service and a fresh approach tofuture-proofing your career,
eric, welcome.
Thank you.
Can you tell us a little bitabout yourself?
Speaker 2 (01:24):
So, like you already touched on, I'm pivoting careers
into data science and in doingso I started dabbling in AI
tools and didn't really knowwhere it would take me.
But as I started, I kind ofcame across your podcast and AI
Ready RVA and I was like, oh,this kind of all makes sense.
And AI Ready RVA.
(01:45):
And I was like, oh, this kindof all makes sense, like I'm
learning the whole.
One of the whole missions of AIReady RVA is to kind of spread
AI literacy, which I have verylittle, but like I'm picking it
up and I think it would just becool to kind of share that
process with the masses.
Speaker 1 (01:58):
Yeah, absolutely, Eric.
Can you take us back to themoment you realized you wanted
to pivot out of the physicaltherapy and into data science?
Speaker 2 (02:07):
What was going?
Speaker 1 (02:08):
through your mind.
Speaker 2 (02:10):
It was a long process .
So back, I don't know.
Pre-covid I was consideringdoing like academia.
I went as far as having a fewinterviews at PhD programs,
interview with former school ofmine to become like an associate
professor and it just neverquite fit.
I felt like I liked some of thescience aspects of it and
(02:33):
getting back into research, butnot some of like the political
aspects of it I didn't want tolike.
I kind of got to the pointwhere I had ingrained myself in
Richmond and didn't want to moveaway.
I know that feeling I just wentback to um, the clinic for a few
years, wound up in like asemi-leadership and clinical
roles.
I wear a lot of hats now and Idecided that some of the
(02:56):
shortcomings of like having yourfoot in both places, as the
like way data is used and theperspectives from the clinical
side of things to theadministrative side of things,
and I felt like it would be niceto find a way to bridge that
gap and then come to find outthe data.
Science does that and it alsobrings back some of the research
(03:18):
stuff.
So doing an A-B test is just ablinded study which, like I've
read thousands of.
So I think this just makes alot of clicks for me and like a
lot of different ways it does alot of different things that I'm
already kind of doing, just ina different capacity.
Speaker 1 (03:34):
I see that's pretty powerful.
So it sounds like you justpinpointed, like what drew you
specifically to data science?
How about AI tools?
You specifically to datascience.
Speaker 2 (03:45):
How about AI tools?
What's drawing you there?
So I really hadn't picked anyup.
I think between AI got reallyaccelerated between like 2023
and now, and I've had two kidssince then, so that wasn't my
first priority.
Congrats, thank you.
But in doing my data sciencelearning, you know, like
whatever series I was doing, itwas like you should download
(04:07):
ChatGPT and integrate it inExcel and just play around with
it, and I did.
I was like, oh, this is prettycool.
And I played around with someother programs, but I really
just think it's been cool tolearn.
One of the reasons I chose thisblog series is because it has
helped me with my data sciencejourney, but it has also made me
a lot more efficient in justdaily life, which has made being
(04:28):
able to set aside time foreducation a lot easier.
So the focus of the blog andsome of my draw to AI is that it
really doesn't.
It can help you with justgetting your time back for you
and productivity.
It's just lifestyleproductivity.
Speaker 1 (04:46):
Absolutely.
That's the first thing I thinkmost people notice.
So, yeah, you just touched onyour learning journey and in the
intro we talked about yourself-teaching of Python, SQL, BI
tools, maybe some of your statsknowledge.
Tell us us what was the mostsurprising part of the learning
journey that you've been takingso far in data science or AI?
Speaker 2 (05:08):
Well, I guess two.
I'll do like two answers.
One would be like I starteddoing the data science thing and
my plan was to like get my footin the door with BI and data
analytics and that seems to bethe field that is changing the
most with AI.
So it became apparent that Ineeded to pick up the skills and
not just focus on BI tools andSQL.
(05:31):
I need to get some of thatunder my belt too.
And then, in terms of just AItools and saving me time and
this we'll talk about later butthe first blog post will be just
like a meal planning, likeroutine I created, where that
was a huge time sink for me.
It was like something I used tolove pre-kids.
And then, uh post is like justtook a lot of time out of my
(05:53):
weekend and now, um, I've likefed it all of my previous meal
plans and I can just have itlike spin them out in five
seconds on sunday afternoon andsay, ah, I don't like that one.
Out in five seconds on Sundayafternoon and say, ah, I don't
like that one, meet another one,and then we're done.
So it's just, it still pickseverything I would be picking
and I can tweak it how I want,but it went from taking a few
(06:14):
hours to a few seconds and it'sjust been great.
Speaker 1 (06:17):
Nice, yeah, I remember reading some of your
preliminary draft and youmentioned it was surprisingly
easy to incorporate AI tools.
Speaker 2 (06:27):
Yeah, that project, I think it was.
It'll be in the first blog post, but I think it was like four
or five prompts and I think ithelped that I had like a
database of a Word document ofall of my previous like things
I've done to for meal planning,but like it was eyeopening how
quick it was.
Speaker 1 (06:48):
Yeah, so.
So now you're actually writingabout the whole experience, so
tell us about your blog seriesidea and your learning journey
there.
Speaker 2 (06:56):
Yeah, so it's going to focus on like practical
applications.
So not so much of like I, datascience education, but just
being able to use that like aitools or or prompts whatever
however you want to word it foranyone can use.
So, um, starting with the mealplanning, but like other ideas
or email organization, that'sanother.
I haven't actually done thisyet, but something that I
(07:19):
typically do is every six monthsI go through and clean out the
400 emails I've just let sit inmy Gmail.
That is like my junk Gmail andI think I can speed that up
quite a bit.
From what I've personally readon AI tools, I'm looking forward
to using some of the researchand deep research tools and
seeing how that.
I've played around that alittle bit, but I haven't
(07:41):
touched on Notebook LM or any ofthe other programs that can do
some of that.
So I'm looking forward to thatone quite a bit.
And then some like just likesilly, like basic stuff doing a
personal stylist seeing if itcan style my clothes and tell me
where to buy them.
And then something I have donea little bit of for my wife
really is interior design likeredesigning your room painting
(08:01):
the walls, you know, matching itup.
You just snap a picture and itcan actually like rework it for
you.
It's pretty incredible.
And other little thingsvacation planning and then like
a Richmond themed date nightplanner are also some ideas.
And buzz around AI browsers too.
Speaker 1 (08:20):
Yeah.
Speaker 2 (08:22):
That'll be a fun one.
There hasn't really beeninnovation in browsing in quite
a while, so that'll be too.
Yeah, that'll be a fun one.
There hasn't really beeninnovation in browsing in quite
a while, so that'll be cool.
Speaker 1 (08:27):
Correct.
Yeah, I'd love to wrap with youon that one.
So, just in terms of how you'reapproaching this personal
journey of yours switchingcareers and such and leveraging
data and tools, you're going tobe bringing something that most
data scientists don't have, andthat's domain expertise in
(08:47):
healthcare.
How do you see that playing arole in your future in data?
Speaker 2 (08:52):
Well, I mean, I think that's where I'm going to focus
most of my efforts, at least tostart.
You know it can always, it cango anywhere.
But yeah, I do have a lot ofexperience in the physical
therapy world, but also at mycurrent role, I interact with
all sorts of different medicalprofessions and I think having
that perspective of whatactually happens in patient care
(09:13):
gets lost sometimes when youjust distill everything down to
a spreadsheet or a database.
And being able to just haveperspective I, I think, makes a
big difference in anything butin data science and not getting
lost in just what a report or avisualization is telling you and
(09:33):
being able to like take it acouple steps further maybe, and
having some idea of what mightbe going on under the scenes,
like what to look for.
I think preventative medicinewould be a great route for AI,
being able to like see thingshappening before you get to the
hospital, before it's a problem.
That is a big deal and I thinkyou're already seeing that.
(09:55):
Some of like radiology andimaging, but there are many,
many ways you could do that fromlike a community health, public
health perspective that I thinkwe're just starting to do, and
then a lot of diagnosis fordifferent diseases, whether it's
orthopedic or otherwise.
Use pattern recognition right.
So it's just like you haveshoulder pain, this motion is
(10:19):
weak, you had this injury, likeyou fell and did this and like,
oh, it's probably a rotatortrufficator.
Well, there's probably otherstuff we're not looking at.
But if you fed AI like theseare all the patient records or
all the research results, whatother like signs and symptoms
are we missing?
And making diagnosis of thosethings a lot more efficient?
(10:41):
And that's a huge.
That would be a cost savingthing.
You could prevent someonehaving to get an MRI, or even
catch someone that probablyneeds to get one, that is just
slugging their way through eightweeks of physical therapy for
no reason.
You see that side of things too, but there's a huge area of
opportunity there.
Speaker 1 (11:01):
I know both of those pains physical therapy as well
as rotator cuff problems.
Yes, being an athlete, my wholelife I've experienced many of
those, it catches up to you.
Yeah, all right.
Let's say you're approachingsomebody that's in a completely
different field maybe education,construction, customer service
(11:24):
who's curious about AI buthesitant to start.
What do you say to that person?
Speaker 2 (11:30):
Well, I think I would reiterate that, like all the
time savings you can get withlike if it's not even not
related to your profession justthe practical applications that
can like just make quality oflife better and again get your
own time back when you're not atwork.
But the other thing I thinkabout a lot is I don't want to
say naysayers, but people thatmaybe think AI is a fad or it
(11:55):
can't do this, and that I justthink back to newspaper
headlines from the late 90s.
They're like the Internet'sjust never going to take off.
I mean, do you want to be thatperson?
Like you may as well give it ashot and say ai, does it take
off?
Well, you've learned a couplethings and you can move on with
your life.
But if you don't do somethingabout it now, you're going to be
, you know, old man yelling atceiling or yelling at the the
(12:17):
sky, that the internet's nevergoing to be what we think it is,
uh kind of guy.
So that's kind of where I wouldjust try it.
Speaker 1 (12:25):
Just dive in Yep.
Yeah, all right.
So you discovered AI Ready RVAwhile searching for resources.
Why do you think communitieslike this are so important?
Speaker 2 (12:38):
I think, obviously with all the positives, you can
look at that we've kind oftalked about with health care
certainly a lot of negatives andI think a lot of it would be
further stratifying some likesocioeconomic statuses, right.
And if you don't uplift thecommunity around you to try to
keep things even, I think youcan foresee a future where
(13:02):
things do get much worse, topheavy, which is already a
complaint that a lot of peoplehave about the US and economics
in general.
So it's really important thatif we're going to have these
tools to try to make sure thatit is as equitable as possible
across all of our communities.
Speaker 1 (13:21):
Yeah, that's exactly right.
So, before we wrap up, I wantto highlight something important
Eric's not just learning forhimself.
He's turning his experienceinto a resource.
His blog on AIReadyRVAcom iswritten specifically for people
who feel overwhelmed by AI andwant an honest, step-by-step
(13:41):
view of what learning itactually looks like.
So, eric, in conclusion, wheredo you see yourself in one to
two years?
Speaker 2 (13:52):
What's the vision you're working toward?
To be working probably still inhealthcare, but in data science
, data analytics and using AItools and just data tools to
again uplift everyone right.
Try to tie all this togetherand make things more efficient
in healthcare.
There's so many ways you can dothat.
(14:13):
So, whether it's with ahealthcare organization or a
public health organization, justtrying to get healthcare to
function a little better.
Speaker 1 (14:21):
Yeah, that's beautiful.
It's very inspirational how youput that.
Thank you for sharing.
So, folks, whether you're aphysical therapist, a teacher,
an analyst or an entrepreneur,your skills absolutely have a
place in the AI powered future,and if Eric's story resonated
with you, you're in luck.
(14:42):
So head on over toAIReadyRVAcom board slash blog
to follow Eric's learningjourney as he shares his tools,
takeaways and lessons learned inreal time.
Start where you are, use whatyou know and let curiosity lead
the way.
Thank you again, eric.
Speaker 2 (15:02):
Yeah, thank you.
Thanks for having me and thanksfor giving the opportunity.
Appreciate it.
Speaker 1 (15:07):
All right, everyone.
Until next time, stay curious,stay focused and keep learning.
Welcome back to Inspire AI, the podcast where we
explore how artificialintelligence is reshaping
careers, industries and the waywe think about the future.
Today's episode is for anyonewho's ever thought AI sounds
powerful, but I don't come froma tech background.
Could I actually learn this?
(00:21):
Well, let me introduce you tosomeone who proves that the
answer is a resounding yes.
Eric Lineberry is a physicaltherapist with nine years of
clinical experience, and todayhe's pivoting into the world of
data science and AI.
He's not just dabbling in tech.
(00:41):
Eric's learning Python, sql,business intelligence tools and
actively working to translatehis deep knowledge of healthcare
and insights through data.
But here's the really cool partEric isn't keeping this journey
to himself.
He's documenting it in a blogseries for AI Ready RVA, a
(01:03):
resource for non-technicalprofessionals and technical who
are curious about AI but don'tknow where to start.
So let's dive into Eric's story, one that blends science
service and a fresh approach tofuture-proofing your career,
eric, welcome.
Thank you.
Can you tell us a little bitabout yourself?
Speaker 2 (01:24):
So, like you already touched on, I'm pivoting careers
into data science and in doingso I started dabbling in AI
tools and didn't really knowwhere it would take me.
But as I started, I kind ofcame across your podcast and AI
Ready RVA and I was like, oh,this kind of all makes sense.
And AI Ready RVA.
(01:45):
And I was like, oh, this kindof all makes sense, like I'm
learning the whole.
One of the whole missions of AIReady RVA is to kind of spread
AI literacy, which I have verylittle, but like I'm picking it
up and I think it would just becool to kind of share that
process with the masses.
Speaker 1 (01:58):
Yeah, absolutely, Eric.
Can you take us back to themoment you realized you wanted
to pivot out of the physicaltherapy and into data science?
Speaker 2 (02:07):
What was going?
Speaker 1 (02:08):
through your mind.
Speaker 2 (02:10):
It was a long process .
So back, I don't know.
Pre-covid I was consideringdoing like academia.
I went as far as having a fewinterviews at PhD programs,
interview with former school ofmine to become like an associate
professor and it just neverquite fit.
I felt like I liked some of thescience aspects of it and
(02:33):
getting back into research, butnot some of like the political
aspects of it I didn't want tolike.
I kind of got to the pointwhere I had ingrained myself in
Richmond and didn't want to moveaway.
I know that feeling I just wentback to um, the clinic for a few
years, wound up in like asemi-leadership and clinical
roles.
I wear a lot of hats now and Idecided that some of the
(02:56):
shortcomings of like having yourfoot in both places, as the
like way data is used and theperspectives from the clinical
side of things to theadministrative side of things,
and I felt like it would be niceto find a way to bridge that
gap and then come to find outthe data.
Science does that and it alsobrings back some of the research
(03:18):
stuff.
So doing an A-B test is just ablinded study which, like I've
read thousands of.
So I think this just makes alot of clicks for me and like a
lot of different ways it does alot of different things that I'm
already kind of doing, just ina different capacity.
Speaker 1 (03:34):
I see that's pretty powerful.
So it sounds like you justpinpointed, like what drew you
specifically to data science?
How about AI tools?
You specifically to datascience.
Speaker 2 (03:45):
How about AI tools?
What's drawing you there?
So I really hadn't picked anyup.
I think between AI got reallyaccelerated between like 2023
and now, and I've had two kidssince then, so that wasn't my
first priority.
Congrats, thank you.
But in doing my data sciencelearning, you know, like
whatever series I was doing, itwas like you should download
(04:07):
ChatGPT and integrate it inExcel and just play around with
it, and I did.
I was like, oh, this is prettycool.
And I played around with someother programs, but I really
just think it's been cool tolearn.
One of the reasons I chose thisblog series is because it has
helped me with my data sciencejourney, but it has also made me
a lot more efficient in justdaily life, which has made being
(04:28):
able to set aside time foreducation a lot easier.
So the focus of the blog andsome of my draw to AI is that it
really doesn't.
It can help you with justgetting your time back for you
and productivity.
It's just lifestyleproductivity.
Speaker 1 (04:46):
Absolutely.
That's the first thing I thinkmost people notice.
So, yeah, you just touched onyour learning journey and in the
intro we talked about yourself-teaching of Python, SQL, BI
tools, maybe some of your statsknowledge.
Tell us us what was the mostsurprising part of the learning
journey that you've been takingso far in data science or AI?
Speaker 2 (05:08):
Well, I guess two.
I'll do like two answers.
One would be like I starteddoing the data science thing and
my plan was to like get my footin the door with BI and data
analytics and that seems to bethe field that is changing the
most with AI.
So it became apparent that Ineeded to pick up the skills and
not just focus on BI tools andSQL.
(05:31):
I need to get some of thatunder my belt too.
And then, in terms of just AItools and saving me time and
this we'll talk about later butthe first blog post will be just
like a meal planning, likeroutine I created, where that
was a huge time sink for me.
It was like something I used tolove pre-kids.
And then, uh post is like justtook a lot of time out of my
(05:53):
weekend and now, um, I've likefed it all of my previous meal
plans and I can just have itlike spin them out in five
seconds on sunday afternoon andsay, ah, I don't like that one.
Out in five seconds on Sundayafternoon and say, ah, I don't
like that one, meet another one,and then we're done.
So it's just, it still pickseverything I would be picking
and I can tweak it how I want,but it went from taking a few
(06:14):
hours to a few seconds and it'sjust been great.
Speaker 1 (06:17):
Nice, yeah, I remember reading some of your
preliminary draft and youmentioned it was surprisingly
easy to incorporate AI tools.
Speaker 2 (06:27):
Yeah, that project, I think it was.
It'll be in the first blog post, but I think it was like four
or five prompts and I think ithelped that I had like a
database of a Word document ofall of my previous like things
I've done to for meal planning,but like it was eyeopening how
quick it was.
Speaker 1 (06:48):
Yeah, so.
So now you're actually writingabout the whole experience, so
tell us about your blog seriesidea and your learning journey
there.
Speaker 2 (06:56):
Yeah, so it's going to focus on like practical
applications.
So not so much of like I, datascience education, but just
being able to use that like aitools or or prompts whatever
however you want to word it foranyone can use.
So, um, starting with the mealplanning, but like other ideas
or email organization, that'sanother.
I haven't actually done thisyet, but something that I
(07:19):
typically do is every six monthsI go through and clean out the
400 emails I've just let sit inmy Gmail.
That is like my junk Gmail andI think I can speed that up
quite a bit.
From what I've personally readon AI tools, I'm looking forward
to using some of the researchand deep research tools and
seeing how that.
I've played around that alittle bit, but I haven't
(07:41):
touched on Notebook LM or any ofthe other programs that can do
some of that.
So I'm looking forward to thatone quite a bit.
And then some like just likesilly, like basic stuff doing a
personal stylist seeing if itcan style my clothes and tell me
where to buy them.
And then something I have donea little bit of for my wife
really is interior design likeredesigning your room painting
(08:01):
the walls, you know, matching itup.
You just snap a picture and itcan actually like rework it for
you.
It's pretty incredible.
And other little thingsvacation planning and then like
a Richmond themed date nightplanner are also some ideas.
And buzz around AI browsers too.
Speaker 1 (08:20):
Yeah.
Speaker 2 (08:22):
That'll be a fun one.
There hasn't really beeninnovation in browsing in quite
a while, so that'll be too.
Yeah, that'll be a fun one.
There hasn't really beeninnovation in browsing in quite
a while, so that'll be cool.
Speaker 1 (08:27):
Correct.
Yeah, I'd love to wrap with youon that one.
So, just in terms of how you'reapproaching this personal
journey of yours switchingcareers and such and leveraging
data and tools, you're going tobe bringing something that most
data scientists don't have, andthat's domain expertise in
(08:47):
healthcare.
How do you see that playing arole in your future in data?
Speaker 2 (08:52):
Well, I mean, I think that's where I'm going to focus
most of my efforts, at least tostart.
You know it can always, it cango anywhere.
But yeah, I do have a lot ofexperience in the physical
therapy world, but also at mycurrent role, I interact with
all sorts of different medicalprofessions and I think having
that perspective of whatactually happens in patient care
(09:13):
gets lost sometimes when youjust distill everything down to
a spreadsheet or a database.
And being able to just haveperspective I, I think, makes a
big difference in anything butin data science and not getting
lost in just what a report or avisualization is telling you and
(09:33):
being able to like take it acouple steps further maybe, and
having some idea of what mightbe going on under the scenes,
like what to look for.
I think preventative medicinewould be a great route for AI,
being able to like see thingshappening before you get to the
hospital, before it's a problem.
That is a big deal and I thinkyou're already seeing that.
(09:55):
Some of like radiology andimaging, but there are many,
many ways you could do that fromlike a community health, public
health perspective that I thinkwe're just starting to do, and
then a lot of diagnosis fordifferent diseases, whether it's
orthopedic or otherwise.
Use pattern recognition right.
So it's just like you haveshoulder pain, this motion is
(10:19):
weak, you had this injury, likeyou fell and did this and like,
oh, it's probably a rotatortrufficator.
Well, there's probably otherstuff we're not looking at.
But if you fed AI like theseare all the patient records or
all the research results, whatother like signs and symptoms
are we missing?
And making diagnosis of thosethings a lot more efficient?
(10:41):
And that's a huge.
That would be a cost savingthing.
You could prevent someonehaving to get an MRI, or even
catch someone that probablyneeds to get one, that is just
slugging their way through eightweeks of physical therapy for
no reason.
You see that side of things too, but there's a huge area of
opportunity there.
Speaker 1 (11:01):
I know both of those pains physical therapy as well
as rotator cuff problems.
Yes, being an athlete, my wholelife I've experienced many of
those, it catches up to you.
Yeah, all right.
Let's say you're approachingsomebody that's in a completely
different field maybe education,construction, customer service
(11:24):
who's curious about AI buthesitant to start.
What do you say to that person?
Speaker 2 (11:30):
Well, I think I would reiterate that, like all the
time savings you can get withlike if it's not even not
related to your profession justthe practical applications that
can like just make quality oflife better and again get your
own time back when you're not atwork.
But the other thing I thinkabout a lot is I don't want to
say naysayers, but people thatmaybe think AI is a fad or it
(11:55):
can't do this, and that I justthink back to newspaper
headlines from the late 90s.
They're like the Internet'sjust never going to take off.
I mean, do you want to be thatperson?
Like you may as well give it ashot and say ai, does it take
off?
Well, you've learned a couplethings and you can move on with
your life.
But if you don't do somethingabout it now, you're going to be
, you know, old man yelling atceiling or yelling at the the
(12:17):
sky, that the internet's nevergoing to be what we think it is,
uh kind of guy.
So that's kind of where I wouldjust try it.
Speaker 1 (12:25):
Just dive in Yep.
Yeah, all right.
So you discovered AI Ready RVAwhile searching for resources.
Why do you think communitieslike this are so important?
Speaker 2 (12:38):
I think, obviously with all the positives, you can
look at that we've kind oftalked about with health care
certainly a lot of negatives andI think a lot of it would be
further stratifying some likesocioeconomic statuses, right.
And if you don't uplift thecommunity around you to try to
keep things even, I think youcan foresee a future where
(13:02):
things do get much worse, topheavy, which is already a
complaint that a lot of peoplehave about the US and economics
in general.
So it's really important thatif we're going to have these
tools to try to make sure thatit is as equitable as possible
across all of our communities.
Speaker 1 (13:21):
Yeah, that's exactly right.
So, before we wrap up, I wantto highlight something important
Eric's not just learning forhimself.
He's turning his experienceinto a resource.
His blog on AIReadyRVAcom iswritten specifically for people
who feel overwhelmed by AI andwant an honest, step-by-step
(13:41):
view of what learning itactually looks like.
So, eric, in conclusion, wheredo you see yourself in one to
two years?
Speaker 2 (13:52):
What's the vision you're working toward?
To be working probably still inhealthcare, but in data science
, data analytics and using AItools and just data tools to
again uplift everyone right.
Try to tie all this togetherand make things more efficient
in healthcare.
There's so many ways you can dothat.
(14:13):
So, whether it's with ahealthcare organization or a
public health organization, justtrying to get healthcare to
function a little better.
Speaker 1 (14:21):
Yeah, that's beautiful.
It's very inspirational how youput that.
Thank you for sharing.
So, folks, whether you're aphysical therapist, a teacher,
an analyst or an entrepreneur,your skills absolutely have a
place in the AI powered future,and if Eric's story resonated
with you, you're in luck.
(14:42):
So head on over toAIReadyRVAcom board slash blog
to follow Eric's learningjourney as he shares his tools,
takeaways and lessons learned inreal time.
Start where you are, use whatyou know and let curiosity lead
the way.
Thank you again, eric.
Speaker 2 (15:02):
Yeah, thank you.
Thanks for having me and thanksfor giving the opportunity.
Appreciate it.
Speaker 1 (15:07):
All right, everyone.
Until next time, stay curious,stay focused and keep learning.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
New Heights with Jason & Travis Kelce
Football’s funniest family duo — Jason Kelce of the Philadelphia Eagles and Travis Kelce of the Kansas City Chiefs — team up to provide next-level access to life in the league as it unfolds. The two brothers and Super Bowl champions drop weekly insights about the weekly slate of games and share their INSIDE perspectives on trending NFL news and sports headlines. They also endlessly rag on each other as brothers do, chat the latest in pop culture and welcome some very popular and well-known friends to chat with them. Check out new episodes every Wednesday. Follow New Heights on the Wondery App, YouTube or wherever you get your podcasts. You can listen to new episodes early and ad-free, and get exclusive content on Wondery+. Join Wondery+ in the Wondery App, Apple Podcasts or Spotify. And join our new membership for a unique fan experience by going to the New Heights YouTube channel now!
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.