November 22, 2024 • 31 mins
How is AI shaping the future of medicine and education? Join us as we sit down with the father of virtual assistant, Kevin Surace, to explore how generative AI is revolutionizing medical education and practice.
Don’t miss this insightful discussion on how students and professionals can leverage AI for greater efficiency and success!
#AIInMedicine #VirtualAssistant #GenerativeAI #MedSchoolMinutes #MedicalEducation #AIRevolution #FutureOfMedicine #SaintJamesSchoolOfMedicine #AIForStudents #LearnWithAI #MedicalStudents #CaribbeanMedicalSchool #AIandAcademia #InnovationInMedicine #HealthcareAI
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
Hello and welcome to another episode of the Med
School Minutes podcast, where wediscuss what it takes to attend
and successfully complete amedical program.
This show is brought to you bySt James School of Medicine.
Here is your host, Kaushik Guha.
Speaker 2 (00:20):
Ladies and gentlemen, thank you for joining us on
another episode of Med SchoolMinutes, where we talk about
everything MD related, with afocus on international students,
specifically Caribbean students.
Today we have a veryinteresting guest.
His name is Mr Kevin Serais andhe is considered to be the
(00:41):
father of the AI assistant, orthe father of the virtual
assistant.
He is a Silicon Valleyinnovator, a serial entrepreneur
, ceo and a futurist.
He has been Inc Magazine'sEntrepreneur of the Year, a CNBC
Top Innovator of the decade anda World Economic Forum tech
(01:06):
pioneer.
His credentials go on and on,but today we're going to talk to
him about how AI is reallychanging the landscape of
education at large, as well as,more specifically, medical
education, and how students canbest leverage this.
So, without further ado, let'swelcome Mr Suresh.
(01:26):
Thank you so much for joiningus today at Med School Minutes.
So today we're going to talkabout AI, and the biggest
question is you know, when yougo online, you know you look at
Instagram threads.
I'm going to be honest AI quoteunquote experts are a dime a
(01:48):
dozen.
Could you tell us a little bitabout your background and why we
have you here and what reallymakes you an authority on AI?
Speaker 3 (01:56):
Well, look, I think everyone and their brother who
plays with ChatGPT all of asudden says they're an expert,
right?
Um, I invented the virtualassistant back in the 90s.
I've been, uh, I have 94patents.
Some of them are back here.
Uh, most of them in ai and uhspecifically applied ai.
That's very different than coreai research.
(02:17):
So there's ai research like I'mdeveloping brand new models,
like at open ai.
Those people are way smarterthan I am.
And then there's applied ai,where we take these ai, whatever
they are, all the way from the50s to today machine learning
and AI and Gen AI and say how dowe apply these to real human
problems?
Right, how do we buildsomething big around them?
That's really formidable.
(02:37):
So I think the virtualassistant is a great example of
that, where you can leverage alot of different models.
In the 90s, the models we hadwere much more simple than they
are today, but everything thatbecame Siri and Alexa and all of
that came out of my team at acompany called General Magic.
So since then I worked on AIfor HVAC, building controls,
things like that, energy savingsthat became the train energy
(03:00):
manager.
It's used in thousands andthousands of buildings today.
I've worked on these days, anAI system that finds bugs in our
software not necessarilyconsumer software, but big
enterprise systems typicalenterprise Most people won't
know might have five to 10,000applications that they manage on
(03:20):
their servers, and so youreally need AI to find all those
bugs.
Humans there's just not enoughhumans to do it.
So that's been a heavy lift.
It's been fantastic work.
Gen AI is helping in that, so Icontinue to march forward.
Speaker 2 (03:33):
As they say, Awesome and I definitely want to talk a
little bit about your TED Talk.
You do have a TED Talk.
We're going to link that whenwe put up your podcast so
everybody can see and, justgenerally speaking, I think you
definitely are an expert, butwith that, we obviously are a
(03:55):
Caribbean medical school and alarge base of our viewers are
either students who are in ourschool or students who are
looking to go into medicine ortypically, just generally
students who are interested inmedicine.
Now the big question is whenchat GPT or OpenAI came out with
this whole concept of chat GPT,there was a big buzz around it
(04:17):
and I think the buzz hasn'treally subsided yet.
If anything, we're getting usedto the buzz, getting used to
the buzz.
But in academia in particular,there seems to be a lot of
skepticism about AI.
How do you, from yourperspective, see AI changing the
world of academia in generaland maybe medicine specifically?
(04:40):
I will talk about that.
Speaker 3 (04:42):
First of all, I'm on the board of Rochester Institute
of Technology.
We have over 20,000 students,so I am very deep in these
conversations.
I've been on the board for 20years and we are an AI
powerhouse in our own right.
But of course, gen AI changes alot of things.
For example, many professorsbelieve teachers, professors etc
(05:03):
.
Believe that students shouldnot use, say, chatgpt to help
them do their work.
I say you're living in the darkages.
Of course they're going to useit, just get over yourself,
right?
So if you start creating yourcoursework and what you're
expecting, knowing that studentsare going to use this tool just
(05:23):
like they would use acalculator or Excel, well then
you start rethinking how am Igoing to use this tool, just
like they would use a calculatoror Excel?
Well then you start rethinkinghow are we going to evaluate the
knowledge these students haveand the critical thinking skills
that they're bringing to thetable?
Right, they're going to go gettheir answers from ChatGPT.
It doesn't matter, they weregoing to get their answers from
Google.
Maybe this is faster.
Whatever the case is, thepapers are going to be written
this way.
How do I, how do I evaluate?
(05:43):
Uh, for example, you know how,um, how knowledgeable they are.
So an example might be we knowthe students are going to go
home on these medical questionsand they're going to get their
answers from chat, gpt and theircopy and paste it and put it
there.
Great, in class I'm going toask each one of them, or
separately or whatever, okay,what makes this particular
(06:03):
answer right or wrong and why?
Okay, now, this is interestingbecause now we're getting into
the way we're probably going toget used to these tools in the
work environment.
Okay, and a med school, and Iknow a med school.
You've got to get doctorsthrough or nurses through that
pass their court, pass their um,you know exams, ultimately to
to to, to be able to practicemedicine.
(06:25):
But in the end, we also have toproduce doctors, nurses and
other medical workers that aregoing to work in this new world
where Gen AI is just somethingwe have, just like a calculator,
and so they are going to use it, because there's no one that
you can train at the St JamesSchool of Medicine who will know
(06:47):
every single ailment that Imight have, having just come
back from you know, sub-saharanAfrica, right, there's just no
way, because they don't see thatevery day and you can't train
them for that every day.
That's not possible, right?
Right, so they are going to usetools, and the old tools were
go to some big medical book,pull something off and try to
(07:08):
find something.
And then we kind of had Googlesearch and people have been
using that.
And now I have this thing thatcould be trained, and there are
medical versions of, say, chat,gbts.
They're fronted with a largelanguage model but behind them
we use a process called RAG tolimit their responses to be
within the medical literature.
Right, this is fascinating.
(07:30):
So you won't try to be anexpert on every possible ailment
someone has.
You're going to leverage thesymptoms that they're giving you
and all the background they cangive you and say what are the
possible ideas here?
Right?
So you start to use these asideators or idea generators, or
ideation.
It is very, very, very powerfulas ideation, right, and now you
(07:55):
know you do.
What a doctor does best is takethese and say, boy, let me test
for these three things.
I've never heard of two of themmyself, but we better go find
out if that's what happened here.
It's possible one of them couldkill you.
Blah, blah, blah.
Right, this is powerful, and soI look at this as a way to
allow doctors to be moreproductive, more powerful, more
(08:17):
important, because they're goingto interpret this information,
but they're going to have moreinformation instantly at their
fingertips and use theirexperience and schooling to then
interpret the best way toapproach the patient with this,
including the human sides ofthat, the EQ sides of that right
.
You come back and the patientsays, well, gee, this hurts and
(08:38):
I traveled here.
And they come back and say Ithink you have a worm in your
brain, right, there's a good anda bad way to say that.
Right, there's probably noreally excellent way to say it,
but let's let's talk about thepotential that something could
have happened like what a wormin your brain.
Right, someone's going to haveto say that to someone, or you
know you, you're facing maybeonly three months to live or
(08:59):
these sorts of things.
These are the hard things thedoctors have to do.
So I would like to see doctorsless worried about the ideation.
So I would like to see doctorsless worried about the ideation
they have a machine that doesthat, okay, it says it's
probably these five things orthese three things, or do these,
following tests and you'll findout.
And more concerned with how doI really have the time to show
empathy to this patient that I'mtreating?
(09:21):
That has maybe a serious issue,maybe not a serious issue,
maybe the family member has aserious issue, whatever, and I
think we're all going to bebetter off.
Number one.
Number two there's a shortageof doctors, so nobody needs to
worry about this.
Right, there is a shortage,there's going to continue to be
a shortage, and everyone I meanyou go into family practice.
You don't make enough money,there's not enough time in the
day.
You need these tools to giveyou some of your time back.
(09:44):
I'll give you one example.
I know you got a millionquestions, but I'll give you one
example.
Where it's being used today istaking doctor's notes, right so
throughout the day.
Why would you ever take yourown notes anymore?
Let the darn thing record, letit transcribe and let it
summarize and put it into yourepic system at the end of the
day Brilliant.
You, as a doctor, are spendingtwo hours at the end of the day
(10:06):
trying to do this from yournotes in your notebook, and now
I have a machine that does itfor me and it does it better,
just like StreamYard today.
I don't know if you're usingthis capability.
We'll transcribe everything wesaid, It'll summarize it and
it'll post it right there.
And that's work you used tohave to do at the end of the
thing for two hours, and now youdon't do it at all.
You push the button, it's done.
Maybe you'll review it and editit, or just push the button.
(10:29):
It's a summary, right?
Brilliant use of technology,brilliant use.
This is good for all themedical students.
It's the best time I'd say it'sthe best time going forward to
be in medicine.
Speaker 2 (10:39):
Oh, wow.
So you know, one of the bigcritiques that our faculty
members not just our facultymembers, but just academia in
general has about AI is that oneof the biggest principles of
medical education is lifelonglearning.
Like, the students that weproduce have to become learners
(11:00):
for the rest of their life andyou're essentially giving them
quote unquote the tools to beable to function anywhere and
learn things and adapt to theirenvironments.
Now, a big criticism about AIhas been that students are not
knowing the true principles ofresearch.
What would your response tosomething like that be?
Speaker 3 (11:25):
Well look we have lived in a changing world of
technology since the inventionof the wheel, and when the wheel
showed up, people who used tocarry stuff up on their back at
the top of the hill from theship all of a sudden could cart
it up right, and so that,fundamentally.
And then some people would say,well, what's going to happen to
their strength of their backand what?
This isn't fair.
Okay, look, Excel came out inthe late eighties.
(11:53):
If you were in finance, mostjobs in finance were pencil and
ledger book and it literallywent away.
Okay, Gen AI hit and people arealready saying no one.
Who who's going to learn towrite by hand anymore when you
have a machine that will write ablog post in 10 seconds and
it's better than the one youcould have written?
Here's my answer to that we areall going to use Gen AI to
write our blog posts.
The days of writing that byhand are just not needed.
(12:18):
I'm sorry.
The truth is, we're going totry to still teach students oh,
you need to write an essay.
They will never write anotheressay in their life.
This is a skill that's nolonger needed.
Just like we teach studentslong division, Okay, so that
they understand the fundamentalsof long division.
They do not need to ever dolong division again in their
life.
Yeah, Ever.
The last time you did longdivision in your head was, I
(12:40):
don't know, fourth grade orwhatever.
I mean these.
So we cannot believe thathumans have to have every skill
and every understanding of everyskill, because technologies
come along and take those skillsfrom us.
We don't need that skill.
So it's one thing to say.
Here's how it was done in theold days.
Like we don't learn slide rulesanymore.
It was probably a valuablething in 1952.
(13:03):
It's completely useless today.
It's a useless skill thing in1952.
It's completely useless today.
It's a useless skill.
Many of the things with all therespect to great people at your
medical school but this isacross all medical schools many
of the things we are teachingthese students today who will
come out as doctors or surgeonsor researchers perhaps, or
whatever it is they will neveruse again and actually are quite
(13:23):
antiquated.
It's just that's part of thecoursework and we have to do it.
And this is true at RIT.
We do the same thing in all ofour courses.
We look at it and go this isantiquated, but it's the thing
that's approved.
So I've got to keep teaching ituntil someone tells me to stop.
We're not doing our studentsany good doing that.
What we should be doing isembedding large language models,
transformers and other AI intoour courses and saying when you
(13:47):
leave here, you will be usingthese tools.
Here's how you best learn howto use them.
Here's how you best learn tocritically think about their
outcomes.
Right, so I might put somethings in and it comes out and
you go.
Four of these are brilliant.
I wouldn't have thought of them, and one of them is dead wrong.
I'm not going to go do that.
Right?
So you still need your criticalthinking skills Very much.
(14:08):
We need critical thinkingskills, Right, but you don't
need to remember all thisinformation and your lifelong
learning of.
I am going to somehow remember.
When someone comes in with thatsymptom, I might check for this
Useless.
There's a machine that doesthat.
Now, you don't need that skill,but you need the critical
thinking skills more than youhad before.
Right, Look at its output,right?
Speaker 2 (14:31):
Right.
Speaker 3 (14:31):
So let me switch gears a little bit and ask you
about, you know, with the adventof chat GPT, which is obviously
the most visible Gen AI modelout there and accessible it's
the best model overall that if Iwere building a legal data or a
legal interface or a medicalinterface or whatever, I would
(14:54):
use the front end of ChatGPT tohave my English interaction and
the back end I would say don'tlearn from this medical database
or medical or whatever the caseis.
Speaker 2 (15:06):
So with ChatGPT, we're looking at about Gen AI
being accessible to everybodyfor a little less than a year.
I think we're going close to ayear now.
If I'm not mistaken, yeah, ayear plus A year plus.
So the big question is wehaven't seen any major shifts in
education because of generativeAI.
(15:27):
It hasn't happened yet.
So from what you're telling us,it seems like we need to make
those shifts and from ourconversation, my takeaway is
that it almost seems likestudents have to be more
efficient or will have to betrained to be more efficient to
be able to use this Now.
Do you anticipate at any pointin time where our education
(15:51):
system across the board not justmedicine, but become so
advanced that a six-year-old isbeing taught?
I don't know?
Now the regular curriculumbecomes high school biology and
our college level stuff becomeshigh school biology and our
college level stuff.
Speaker 3 (16:10):
Well, I'll answer that in a couple of ways.
The first thing is thateducational systems move
glacially slow for a reason.
So things in the tech world andin the commercial world and
stuff you know, swing back andforth very, very heavily, very
quickly, right.
Technology's in, technology'sout, this and that, and
universities, in particular Kthrough 12, also move at a
(16:32):
glacially slow pace, and they'vealways moved slowly because
they don't want to bereactionary every year to the
latest thing that's happening onthe web or the latest
technology that's in over here,because it'll be out next year,
right?
So it was designed to do that.
Now the problem with that isthat technology is moving at a
(16:56):
faster pace every year than itused to, and there's lots of
reasons for that.
For instance, chatgpt wasavailable to 6 billion people on
day one because we have aninternet and we have smartphones
, so everyone worldwide couldtechnically use the free version
on day one.
What used to take 40 years tospread around the world now
takes 40 minutes, right, or 40seconds.
So the educational system isstill stuck in.
(17:17):
We'll change every decade ortwo a little and it's possible
that we're now getting to points, especially with Gen AI tools,
where they really need to changefaster and they really need to
embed this because the employersare looking for people.
So I'll give you an example.
Let's say I have a big doctor'spractice.
(17:39):
I've got, you know, 40 familydoctors in this thing right.
And I've got an opening for onenew graduate next year right.
And I interview two people.
And I interview one that says,yeah, I've heard about that Gen
AI, chat, gpt stuff, but I'venever used it.
It's probably unreliable and Iwouldn't want to do that.
(17:59):
I played with it once, but Idon't think it's a good thing.
Okay, tell me about your othermedical history and what you
came through and what youlearned in school, et cetera.
The other one comes in and sayshere's all the things I learned
in school, but one of themincluded the use of Gen AI for
my entire practice, and let metell you why that's important,
and I measured it made me 42%more productive.
I was able to summarize thingsat the end of the day, I was
(18:22):
able to diagnose things withideation that I had never
thought about before, and so I'mjust going to be your most
productive hire.
Who gets hired?
Yeah, number one number two.
Speaker 2 (18:34):
Number two definitely number two, yeah.
Speaker 3 (18:37):
So if you're watching this, you go.
You know our job as schools isto graduate people who get hired
.
That's actually yeah, that isthe.
The customer is the student andfinally, the people who hire
them, right, the hospitaldoctor's office or whatever it
is.
And so you want to make thebest, most hireable students and
(19:01):
the most hireable students, themost wanted students today,
walk in as student number two.
I know all about this stuff.
I you.
I even used it when the teachersaid don't use it, and I used
it anyway because I learned allthese other things from it and I
used it to cheat.
I learned so much more and Iwas able to critically think
through those results.
I go, I'm hired.
Do you have more like you?
(19:21):
I'll hire you.
I don't want the first one, sothink about who we're graduating
, right right.
Speaker 2 (19:26):
So I want to pinpoint something that you said how
tech tends to change and techseems to be, you know I mean
relatively speaking a littleesoteric, because you know, one
day you have Blu-ray, the otherday you have HD, another day you
have both of them and then oneof them is completely gone, et
cetera, et cetera.
Speaker 3 (19:46):
That is true.
You're going back in time about25 years because HD DVD got
killed off in its first year ortwo.
But I still have a player and Istill have some discs.
But Blu-ray won that right.
Speaker 2 (19:58):
And I still have a player and I still have some
discs, but Blu-ray won thatright and this does happen.
So, and you know, there arethings that become completely
obsolete, For example cassettes.
Nobody needs them anymore.
Nobody needs a cassette playeranymore.
In your view, Do you know?
Speaker 3 (20:09):
I have to interrupt you.
I just read an article lastweek that they're like LPs, like
vinyl.
There's a little resurgence incassettes and these certain kids
now, like they're teens, theythink it's really cool to go and
buy a cassette of Taylor Swiftand put it in a Walkman and
literally just listen to it theway it was meant to be listened
(20:29):
to, and it's become this coolthing.
There's actually someresurgence of cassettes, I kid
you not.
Speaker 2 (20:37):
Anyway, I know your point, but that's a nostalgia
factor, absolutely, and I'veseen that in LPs and vinyl
records and whatnot.
But in your opinion, do youforesee that Gen AI is
potentially replaced in the nextthree to five years with
(20:57):
something even more advancedthat is completely different
from the way Gen AI is used?
For example, I mean,hypothetically speaking, a chip
that we implant in our body thatautomatically gives us all this
information?
Again, I'm no.
Yeah.
Speaker 3 (21:13):
So let's look at it this way Look, a transformer
model is a great model of alanguage English or any other
language right.
And it's read trillions ofsentences, let's say trillions
of tokens, and therefore you canask it things relative to the
things it's read and it willcome back and give you some
interesting information aboutthat, right, that's the bottom
(21:33):
line.
So the concept of a transformeror whatever, replaces a
transformer.
It's correct, it's, it's, it's.
It's an amazing way to learneverything that's ever been
written and build a model aroundit, right?
So that's pretty interesting,right?
So I don't think that goes away.
How we interface, look, Iinvented the virtual assistant.
So I've been saying interfacewith voice since 1997 or so.
(21:55):
Voice is the most natural way,it's the fastest way to
interface with anything,including computers, including
humans, right?
You don't see me writing thingsdown, typing them and handing
them to you.
I can't type that fast, right?
I might as well talk to you andyou talk to me.
So I think we will continue tomove towards an era where more
and more of our interface to theworld is through voice.
(22:20):
When it's appropriate to usevoice, right, can't do it in a
crowded place all the time, andso you know, clearly, ultimately
there's a lot of work going onin brain-computer interface.
I, you know from what I'mseeing.
We are years and years andyears, maybe decades, away from
having a very high volume kindof interface.
Today it's like maybe you knowwe can get the A to get typed
(22:45):
out the thing you know bythinking about it right, but
it's very crude today right,we're at
a very, very, very crude level.
Someday, clearly, we're goingto, you know, implant a chip,
maybe by the end of the century,and we'll just be interfacing,
but still the transformer willhave to be there.
Right, we've got to understandthe language, understand
everything that was there, buildmodels around it.
(23:06):
So, whether it's a transformeror some other kind of neural net
, as Sam Altman said recently,everything we've done with
transformers and chat, gpt andeverything else and gemini is
paying homage to the fact thatneural nets actually worked
right.
Deep learning work period fullstop.
We weren't sure it'd work, butdeep learning, which the math
(23:28):
was kind of done in 2012, itworks, and that's all this is.
We're leveraging those deeplearning models and building out
these huge, huge, huge modelsthat are thousands, millions of
layers deep right.
Speaker 2 (23:40):
I do want to touch upon a lot of this.
Ai stuff is very intimidatingto a lot of people youngsters as
well as people who are moreadvanced in age and they keep
thinking that, oh my God, thisis like computer programming.
What sort of technical detailsor what kind of skills do you
think a person needs to have tobe able to really leverage, uh,
(24:04):
this, this information?
Number one and number two afollow-up to this question,
essentially is there is so muchI mean everything out there
seems to have ai nowadays,whether it's your phone or
whether it's even your likevacuum.
But the question is and it maynot be the real AI or generative
AI as we talk about it, but thereal question is how do you
(24:26):
sift through all thisinformation and do you need any
technical skills to be able todo that and become efficient at
using Gen AI?
Speaker 3 (24:34):
Yeah.
So look, I think there arehundreds of web applications and
mobile applications out therethat can do interesting like.
Hyperwriteai has already kindof pre-set up all kinds of
prompts for you so you don'thave to think about prompting
correctly.
But here's what I tell peoplestop playing and start doing so.
(24:56):
I do 40, 50 keynotes a year infront of audiences sometimes
5,000 people, Right and I'll askthe audience raise, raise their
, raise your hand.
If you played with somethinglike chat GBT, everybody raised
their hands.
Now, raise your hand.
If you're doing real work withit every day, everybody's hands
go down.
Like two people put their handsup, right, and then I say
that's a shame, because all ofyou are wondering gee, I wonder
(25:18):
what I can do with this.
I wonder how do I use blah,blah, blah.
Okay, you will never learn ifyou don't learn to do actual
work.
So I use these models everysingle day, all day.
I generate images, I generatediagrams, I analyze spreadsheets
, I ask it how I should reply tothis email.
I generate all kinds of contentblog posts or technical data or
(25:44):
whatever.
So I don't generate a thingwithout first asking a large
language model or a transformerright or a multimodal, Okay.
Speaker 2 (25:53):
Why.
Speaker 3 (25:54):
Because it's a better generator of content than I
will ever be.
Period it read more than I canread in my life.
I can't change that.
That's how it works, and sowhat I want to be great at is
asking the right questions andgetting the right answers, and
then going through those answersand picking out what's
important to me and how I wantto change it if I want to change
(26:16):
it at all and critically thinkabout that.
So the skills that I need goingforward the skills we all need
going forward is doing that forevery single thing during your
day.
So, for example, you could havesaid should I have Kevin Serais
on my podcast?
It will opine on that and youcan decide whether it's good or
bad, but use it as an ideator.
(26:36):
Who else should I have on mypodcast?
How might I contact them right?
What should we talk about?
What might be some of thetopics that students might be
interested in, or or professorsmight be interested in, or
teachers might be interested inright, or administration might
be interested in?
So any idea you can think of,it's an ideator next to you and
you can have 100 brain powerusing that thing, or you can sit
(27:00):
there and have one brain power,which is fine.
It's a great brain, you got agreat brain, I got a great brain
.
But the person next to me hasgot 100 brain power.
Well, how am I going to beatthem?
They got 100 brain power.
If I'm a doctor and I get 100brain power, I'm crushing the
doctor next door who's only gotone brain power, right, you need
to think of it that way, andonce you start thinking about it
(27:21):
that way, you go.
I want 100 brain power too.
Okay, then stop playing.
Get a real subscription at $20a month and use ChatGPT we use
GPT-4.0 and connect it to liveweb information and then start
really using it for every singlething you do, and within weeks
you'll go.
I'm getting really good at this.
(27:42):
Now I see the power.
Otherwise, you don't see thepower.
Speaker 2 (27:45):
I see, and so I mean the gist of it should be that
just jump in and not worry aboutwhat you already know and don't
know.
And then you know and I usechat GP for a lot of daily tasks
and I would say that, at leastin my organization, I'm probably
one of the more advanced users,so to speak.
(28:07):
But and this is a conversationI have a lot with our faculty
members it's like oh, I don'tknow how to leverage this, I
don't know how to use this, oh,I'm very intimidated by it.
It's like oh, I don't know howto leverage this, I don't know
how to use this, oh, I'm veryintimidated by it.
Speaker 3 (28:20):
Start Start at your start.
Start doing real work.
You've got to get out of theplay mode.
It's like the differencebetween playing a video game and
writing a video game right.
Playing a video game, you'renot learning anything other than
(28:43):
just playing the game.
Writing a video game game,you're learning everything about
what it takes to write a videogame.
So stop playing the video game,stop playing with chat GPD.
Get a subscription to GPT-4-0right and actually work with it
and do real and say I'm going todo five tasks today with this.
Then I'm going to do 10 thenext day.
I'm going to take every emailand have them have my response
written by gpt40 and I'm goingto edit that.
I might not accept it, I mayhave it, rewrite it.
And then you start to get goodat asking the right questions.
(29:04):
So, um, hey, I had an argumentwith my spouse this morning.
How should I reply to him orher in email?
Now that will save our marriage, trust me.
The results that come back fromthat darn thing you, you could
never beat.
You can't beat it, you can'tbeat it.
It's better than anything wecan write.
(29:25):
Why?
Because it read every singlething that's ever been written
about that subject.
Speaker 2 (29:29):
Right, right, that's amazing.
Well, thank you so much, mrSuresh.
I know we're a little pressedon time, but this conversation
for us could for me at leastcould go on forever.
There's just so much to learnfrom you and I really appreciate
it and genuinely, it's been anhonor and a pleasure to have you
on our podcast.
(29:50):
And again, thank you so muchfor the time and thank you so
much for literally laying thegroundwork for us having a
better life.
Speaker 3 (30:00):
Yes, well, I think it's.
Look, it's a great time intechnology and we've seen so
many big changes in technologythe internet, smartphones and
now generative AI.
These are huge game changersand there's more to come, so
we'll be back on the showanother time, take care.
Thanks so much for having me.
Speaker 2 (30:20):
Thank you so much, mr Sarris.
We really appreciate theinsights that you provided about
AI.
As you know, we always seehundreds, if not thousands, of
AI experts, but we're reallyhonored to be able to have a
real expert and the father ofthe virtual assistant on our
(30:41):
show tonight.
But once again, thank you somuch, mr Suresh and everybody
out there, make sure you polishup your AI skills and work on
prompt generating and promptengineering to be a more
efficient student, and alwaysremember there is no shortcut to
(31:02):
becoming an MD.
If you like the content that weproduce, please give us a like,
follow and share.
It goes a long way, especiallyfor our production team, who put
a lot of work into producingthese episodes and, if you feel
free, to download our otherepisodes from Spotify, google or
any other platform that youprefer.
Thank you so much and thank youfor your support.
Speaker 1 (31:25):
Thank you so much for tuning into our show.
We hope you enjoyed anotherepisode of Med School Minutes.
If you like our content, pleasefollow us and receive
notification when a new show isposted.
This podcast is brought to youby St James School of Medicine.
For a video version of thispodcast, please check us out on
sjsmorg slash video.
Hello and welcome to another episode of the Med
School Minutes podcast, where wediscuss what it takes to attend
and successfully complete amedical program.
This show is brought to you bySt James School of Medicine.
Here is your host, Kaushik Guha.
Speaker 2 (00:20):
Ladies and gentlemen, thank you for joining us on
another episode of Med SchoolMinutes, where we talk about
everything MD related, with afocus on international students,
specifically Caribbean students.
Today we have a veryinteresting guest.
His name is Mr Kevin Serais andhe is considered to be the
(00:41):
father of the AI assistant, orthe father of the virtual
assistant.
He is a Silicon Valleyinnovator, a serial entrepreneur
, ceo and a futurist.
He has been Inc Magazine'sEntrepreneur of the Year, a CNBC
Top Innovator of the decade anda World Economic Forum tech
(01:06):
pioneer.
His credentials go on and on,but today we're going to talk to
him about how AI is reallychanging the landscape of
education at large, as well as,more specifically, medical
education, and how students canbest leverage this.
So, without further ado, let'swelcome Mr Suresh.
(01:26):
Thank you so much for joiningus today at Med School Minutes.
So today we're going to talkabout AI, and the biggest
question is you know, when yougo online, you know you look at
Instagram threads.
I'm going to be honest AI quoteunquote experts are a dime a
(01:48):
dozen.
Could you tell us a little bitabout your background and why we
have you here and what reallymakes you an authority on AI?
Speaker 3 (01:56):
Well, look, I think everyone and their brother who
plays with ChatGPT all of asudden says they're an expert,
right?
Um, I invented the virtualassistant back in the 90s.
I've been, uh, I have 94patents.
Some of them are back here.
Uh, most of them in ai and uhspecifically applied ai.
That's very different than coreai research.
(02:17):
So there's ai research like I'mdeveloping brand new models,
like at open ai.
Those people are way smarterthan I am.
And then there's applied ai,where we take these ai, whatever
they are, all the way from the50s to today machine learning
and AI and Gen AI and say how dowe apply these to real human
problems?
Right, how do we buildsomething big around them?
That's really formidable.
(02:37):
So I think the virtualassistant is a great example of
that, where you can leverage alot of different models.
In the 90s, the models we hadwere much more simple than they
are today, but everything thatbecame Siri and Alexa and all of
that came out of my team at acompany called General Magic.
So since then I worked on AIfor HVAC, building controls,
things like that, energy savingsthat became the train energy
(03:00):
manager.
It's used in thousands andthousands of buildings today.
I've worked on these days, anAI system that finds bugs in our
software not necessarilyconsumer software, but big
enterprise systems typicalenterprise Most people won't
know might have five to 10,000applications that they manage on
(03:20):
their servers, and so youreally need AI to find all those
bugs.
Humans there's just not enoughhumans to do it.
So that's been a heavy lift.
It's been fantastic work.
Gen AI is helping in that, so Icontinue to march forward.
Speaker 2 (03:33):
As they say, Awesome and I definitely want to talk a
little bit about your TED Talk.
You do have a TED Talk.
We're going to link that whenwe put up your podcast so
everybody can see and, justgenerally speaking, I think you
definitely are an expert, butwith that, we obviously are a
(03:55):
Caribbean medical school and alarge base of our viewers are
either students who are in ourschool or students who are
looking to go into medicine ortypically, just generally
students who are interested inmedicine.
Now the big question is whenchat GPT or OpenAI came out with
this whole concept of chat GPT,there was a big buzz around it
(04:17):
and I think the buzz hasn'treally subsided yet.
If anything, we're getting usedto the buzz, getting used to
the buzz.
But in academia in particular,there seems to be a lot of
skepticism about AI.
How do you, from yourperspective, see AI changing the
world of academia in generaland maybe medicine specifically?
(04:40):
I will talk about that.
Speaker 3 (04:42):
First of all, I'm on the board of Rochester Institute
of Technology.
We have over 20,000 students,so I am very deep in these
conversations.
I've been on the board for 20years and we are an AI
powerhouse in our own right.
But of course, gen AI changes alot of things.
For example, many professorsbelieve teachers, professors etc
(05:03):
.
Believe that students shouldnot use, say, chatgpt to help
them do their work.
I say you're living in the darkages.
Of course they're going to useit, just get over yourself,
right?
So if you start creating yourcoursework and what you're
expecting, knowing that studentsare going to use this tool just
(05:23):
like they would use acalculator or Excel, well then
you start rethinking how am Igoing to use this tool, just
like they would use a calculatoror Excel?
Well then you start rethinkinghow are we going to evaluate the
knowledge these students haveand the critical thinking skills
that they're bringing to thetable?
Right, they're going to go gettheir answers from ChatGPT.
It doesn't matter, they weregoing to get their answers from
Google.
Maybe this is faster.
Whatever the case is, thepapers are going to be written
this way.
How do I, how do I evaluate?
(05:43):
Uh, for example, you know how,um, how knowledgeable they are.
So an example might be we knowthe students are going to go
home on these medical questionsand they're going to get their
answers from chat, gpt and theircopy and paste it and put it
there.
Great, in class I'm going toask each one of them, or
separately or whatever, okay,what makes this particular
(06:03):
answer right or wrong and why?
Okay, now, this is interestingbecause now we're getting into
the way we're probably going toget used to these tools in the
work environment.
Okay, and a med school, and Iknow a med school.
You've got to get doctorsthrough or nurses through that
pass their court, pass their um,you know exams, ultimately to
to to, to be able to practicemedicine.
(06:25):
But in the end, we also have toproduce doctors, nurses and
other medical workers that aregoing to work in this new world
where Gen AI is just somethingwe have, just like a calculator,
and so they are going to use it, because there's no one that
you can train at the St JamesSchool of Medicine who will know
(06:47):
every single ailment that Imight have, having just come
back from you know, sub-saharanAfrica, right, there's just no
way, because they don't see thatevery day and you can't train
them for that every day.
That's not possible, right?
Right, so they are going to usetools, and the old tools were
go to some big medical book,pull something off and try to
(07:08):
find something.
And then we kind of had Googlesearch and people have been
using that.
And now I have this thing thatcould be trained, and there are
medical versions of, say, chat,gbts.
They're fronted with a largelanguage model but behind them
we use a process called RAG tolimit their responses to be
within the medical literature.
Right, this is fascinating.
(07:30):
So you won't try to be anexpert on every possible ailment
someone has.
You're going to leverage thesymptoms that they're giving you
and all the background they cangive you and say what are the
possible ideas here?
Right?
So you start to use these asideators or idea generators, or
ideation.
It is very, very, very powerfulas ideation, right, and now you
(07:55):
know you do.
What a doctor does best is takethese and say, boy, let me test
for these three things.
I've never heard of two of themmyself, but we better go find
out if that's what happened here.
It's possible one of them couldkill you.
Blah, blah, blah.
Right, this is powerful, and soI look at this as a way to
allow doctors to be moreproductive, more powerful, more
(08:17):
important, because they're goingto interpret this information,
but they're going to have moreinformation instantly at their
fingertips and use theirexperience and schooling to then
interpret the best way toapproach the patient with this,
including the human sides ofthat, the EQ sides of that right
.
You come back and the patientsays, well, gee, this hurts and
(08:38):
I traveled here.
And they come back and say Ithink you have a worm in your
brain, right, there's a good anda bad way to say that.
Right, there's probably noreally excellent way to say it,
but let's let's talk about thepotential that something could
have happened like what a wormin your brain.
Right, someone's going to haveto say that to someone, or you
know you, you're facing maybeonly three months to live or
(08:59):
these sorts of things.
These are the hard things thedoctors have to do.
So I would like to see doctorsless worried about the ideation.
So I would like to see doctorsless worried about the ideation
they have a machine that doesthat, okay, it says it's
probably these five things orthese three things, or do these,
following tests and you'll findout.
And more concerned with how doI really have the time to show
empathy to this patient that I'mtreating?
(09:21):
That has maybe a serious issue,maybe not a serious issue,
maybe the family member has aserious issue, whatever, and I
think we're all going to bebetter off.
Number one.
Number two there's a shortageof doctors, so nobody needs to
worry about this.
Right, there is a shortage,there's going to continue to be
a shortage, and everyone I meanyou go into family practice.
You don't make enough money,there's not enough time in the
day.
You need these tools to giveyou some of your time back.
(09:44):
I'll give you one example.
I know you got a millionquestions, but I'll give you one
example.
Where it's being used today istaking doctor's notes, right so
throughout the day.
Why would you ever take yourown notes anymore?
Let the darn thing record, letit transcribe and let it
summarize and put it into yourepic system at the end of the
day Brilliant.
You, as a doctor, are spendingtwo hours at the end of the day
(10:06):
trying to do this from yournotes in your notebook, and now
I have a machine that does itfor me and it does it better,
just like StreamYard today.
I don't know if you're usingthis capability.
We'll transcribe everything wesaid, It'll summarize it and
it'll post it right there.
And that's work you used tohave to do at the end of the
thing for two hours, and now youdon't do it at all.
You push the button, it's done.
Maybe you'll review it and editit, or just push the button.
(10:29):
It's a summary, right?
Brilliant use of technology,brilliant use.
This is good for all themedical students.
It's the best time I'd say it'sthe best time going forward to
be in medicine.
Speaker 2 (10:39):
Oh, wow.
So you know, one of the bigcritiques that our faculty
members not just our facultymembers, but just academia in
general has about AI is that oneof the biggest principles of
medical education is lifelonglearning.
Like, the students that weproduce have to become learners
(11:00):
for the rest of their life andyou're essentially giving them
quote unquote the tools to beable to function anywhere and
learn things and adapt to theirenvironments.
Now, a big criticism about AIhas been that students are not
knowing the true principles ofresearch.
What would your response tosomething like that be?
Speaker 3 (11:25):
Well look we have lived in a changing world of
technology since the inventionof the wheel, and when the wheel
showed up, people who used tocarry stuff up on their back at
the top of the hill from theship all of a sudden could cart
it up right, and so that,fundamentally.
And then some people would say,well, what's going to happen to
their strength of their backand what?
This isn't fair.
Okay, look, Excel came out inthe late eighties.
(11:53):
If you were in finance, mostjobs in finance were pencil and
ledger book and it literallywent away.
Okay, Gen AI hit and people arealready saying no one.
Who who's going to learn towrite by hand anymore when you
have a machine that will write ablog post in 10 seconds and
it's better than the one youcould have written?
Here's my answer to that we areall going to use Gen AI to
write our blog posts.
The days of writing that byhand are just not needed.
(12:18):
I'm sorry.
The truth is, we're going totry to still teach students oh,
you need to write an essay.
They will never write anotheressay in their life.
This is a skill that's nolonger needed.
Just like we teach studentslong division, Okay, so that
they understand the fundamentalsof long division.
They do not need to ever dolong division again in their
life.
Yeah, Ever.
The last time you did longdivision in your head was, I
(12:40):
don't know, fourth grade orwhatever.
I mean these.
So we cannot believe thathumans have to have every skill
and every understanding of everyskill, because technologies
come along and take those skillsfrom us.
We don't need that skill.
So it's one thing to say.
Here's how it was done in theold days.
Like we don't learn slide rulesanymore.
It was probably a valuablething in 1952.
(13:03):
It's completely useless today.
It's a useless skill thing in1952.
It's completely useless today.
It's a useless skill.
Many of the things with all therespect to great people at your
medical school but this isacross all medical schools many
of the things we are teachingthese students today who will
come out as doctors or surgeonsor researchers perhaps, or
whatever it is they will neveruse again and actually are quite
(13:23):
antiquated.
It's just that's part of thecoursework and we have to do it.
And this is true at RIT.
We do the same thing in all ofour courses.
We look at it and go this isantiquated, but it's the thing
that's approved.
So I've got to keep teaching ituntil someone tells me to stop.
We're not doing our studentsany good doing that.
What we should be doing isembedding large language models,
transformers and other AI intoour courses and saying when you
(13:47):
leave here, you will be usingthese tools.
Here's how you best learn howto use them.
Here's how you best learn tocritically think about their
outcomes.
Right, so I might put somethings in and it comes out and
you go.
Four of these are brilliant.
I wouldn't have thought of them, and one of them is dead wrong.
I'm not going to go do that.
Right?
So you still need your criticalthinking skills Very much.
(14:08):
We need critical thinkingskills, Right, but you don't
need to remember all thisinformation and your lifelong
learning of.
I am going to somehow remember.
When someone comes in with thatsymptom, I might check for this
Useless.
There's a machine that doesthat.
Now, you don't need that skill,but you need the critical
thinking skills more than youhad before.
Right, Look at its output,right?
Speaker 2 (14:31):
Right.
Speaker 3 (14:31):
So let me switch gears a little bit and ask you
about, you know, with the adventof chat GPT, which is obviously
the most visible Gen AI modelout there and accessible it's
the best model overall that if Iwere building a legal data or a
legal interface or a medicalinterface or whatever, I would
(14:54):
use the front end of ChatGPT tohave my English interaction and
the back end I would say don'tlearn from this medical database
or medical or whatever the caseis.
Speaker 2 (15:06):
So with ChatGPT, we're looking at about Gen AI
being accessible to everybodyfor a little less than a year.
I think we're going close to ayear now.
If I'm not mistaken, yeah, ayear plus A year plus.
So the big question is wehaven't seen any major shifts in
education because of generativeAI.
(15:27):
It hasn't happened yet.
So from what you're telling us,it seems like we need to make
those shifts and from ourconversation, my takeaway is
that it almost seems likestudents have to be more
efficient or will have to betrained to be more efficient to
be able to use this Now.
Do you anticipate at any pointin time where our education
(15:51):
system across the board not justmedicine, but become so
advanced that a six-year-old isbeing taught?
I don't know?
Now the regular curriculumbecomes high school biology and
our college level stuff becomeshigh school biology and our
college level stuff.
Speaker 3 (16:10):
Well, I'll answer that in a couple of ways.
The first thing is thateducational systems move
glacially slow for a reason.
So things in the tech world andin the commercial world and
stuff you know, swing back andforth very, very heavily, very
quickly, right.
Technology's in, technology'sout, this and that, and
universities, in particular Kthrough 12, also move at a
(16:32):
glacially slow pace, and they'vealways moved slowly because
they don't want to bereactionary every year to the
latest thing that's happening onthe web or the latest
technology that's in over here,because it'll be out next year,
right?
So it was designed to do that.
Now the problem with that isthat technology is moving at a
(16:56):
faster pace every year than itused to, and there's lots of
reasons for that.
For instance, chatgpt wasavailable to 6 billion people on
day one because we have aninternet and we have smartphones
, so everyone worldwide couldtechnically use the free version
on day one.
What used to take 40 years tospread around the world now
takes 40 minutes, right, or 40seconds.
So the educational system isstill stuck in.
(17:17):
We'll change every decade ortwo a little and it's possible
that we're now getting to points, especially with Gen AI tools,
where they really need to changefaster and they really need to
embed this because the employersare looking for people.
So I'll give you an example.
Let's say I have a big doctor'spractice.
(17:39):
I've got, you know, 40 familydoctors in this thing right.
And I've got an opening for onenew graduate next year right.
And I interview two people.
And I interview one that says,yeah, I've heard about that Gen
AI, chat, gpt stuff, but I'venever used it.
It's probably unreliable and Iwouldn't want to do that.
(17:59):
I played with it once, but Idon't think it's a good thing.
Okay, tell me about your othermedical history and what you
came through and what youlearned in school, et cetera.
The other one comes in and sayshere's all the things I learned
in school, but one of themincluded the use of Gen AI for
my entire practice, and let metell you why that's important,
and I measured it made me 42%more productive.
I was able to summarize thingsat the end of the day, I was
(18:22):
able to diagnose things withideation that I had never
thought about before, and so I'mjust going to be your most
productive hire.
Who gets hired?
Yeah, number one number two.
Speaker 2 (18:34):
Number two definitely number two, yeah.
Speaker 3 (18:37):
So if you're watching this, you go.
You know our job as schools isto graduate people who get hired
.
That's actually yeah, that isthe.
The customer is the student andfinally, the people who hire
them, right, the hospitaldoctor's office or whatever it
is.
And so you want to make thebest, most hireable students and
(19:01):
the most hireable students, themost wanted students today,
walk in as student number two.
I know all about this stuff.
I you.
I even used it when the teachersaid don't use it, and I used
it anyway because I learned allthese other things from it and I
used it to cheat.
I learned so much more and Iwas able to critically think
through those results.
I go, I'm hired.
Do you have more like you?
(19:21):
I'll hire you.
I don't want the first one, sothink about who we're graduating
, right right.
Speaker 2 (19:26):
So I want to pinpoint something that you said how
tech tends to change and techseems to be, you know I mean
relatively speaking a littleesoteric, because you know, one
day you have Blu-ray, the otherday you have HD, another day you
have both of them and then oneof them is completely gone, et
cetera, et cetera.
Speaker 3 (19:46):
That is true.
You're going back in time about25 years because HD DVD got
killed off in its first year ortwo.
But I still have a player and Istill have some discs.
But Blu-ray won that right.
Speaker 2 (19:58):
And I still have a player and I still have some
discs, but Blu-ray won thatright and this does happen.
So, and you know, there arethings that become completely
obsolete, For example cassettes.
Nobody needs them anymore.
Nobody needs a cassette playeranymore.
In your view, Do you know?
Speaker 3 (20:09):
I have to interrupt you.
I just read an article lastweek that they're like LPs, like
vinyl.
There's a little resurgence incassettes and these certain kids
now, like they're teens, theythink it's really cool to go and
buy a cassette of Taylor Swiftand put it in a Walkman and
literally just listen to it theway it was meant to be listened
(20:29):
to, and it's become this coolthing.
There's actually someresurgence of cassettes, I kid
you not.
Speaker 2 (20:37):
Anyway, I know your point, but that's a nostalgia
factor, absolutely, and I'veseen that in LPs and vinyl
records and whatnot.
But in your opinion, do youforesee that Gen AI is
potentially replaced in the nextthree to five years with
(20:57):
something even more advancedthat is completely different
from the way Gen AI is used?
For example, I mean,hypothetically speaking, a chip
that we implant in our body thatautomatically gives us all this
information?
Again, I'm no.
Yeah.
Speaker 3 (21:13):
So let's look at it this way Look, a transformer
model is a great model of alanguage English or any other
language right.
And it's read trillions ofsentences, let's say trillions
of tokens, and therefore you canask it things relative to the
things it's read and it willcome back and give you some
interesting information aboutthat, right, that's the bottom
(21:33):
line.
So the concept of a transformeror whatever, replaces a
transformer.
It's correct, it's, it's, it's.
It's an amazing way to learneverything that's ever been
written and build a model aroundit, right?
So that's pretty interesting,right?
So I don't think that goes away.
How we interface, look, Iinvented the virtual assistant.
So I've been saying interfacewith voice since 1997 or so.
(21:55):
Voice is the most natural way,it's the fastest way to
interface with anything,including computers, including
humans, right?
You don't see me writing thingsdown, typing them and handing
them to you.
I can't type that fast, right?
I might as well talk to you andyou talk to me.
So I think we will continue tomove towards an era where more
and more of our interface to theworld is through voice.
(22:20):
When it's appropriate to usevoice, right, can't do it in a
crowded place all the time, andso you know, clearly, ultimately
there's a lot of work going onin brain-computer interface.
I, you know from what I'mseeing.
We are years and years andyears, maybe decades, away from
having a very high volume kindof interface.
Today it's like maybe you knowwe can get the A to get typed
(22:45):
out the thing you know bythinking about it right, but
it's very crude today right,we're at
a very, very, very crude level.
Someday, clearly, we're goingto, you know, implant a chip,
maybe by the end of the century,and we'll just be interfacing,
but still the transformer willhave to be there.
Right, we've got to understandthe language, understand
everything that was there, buildmodels around it.
(23:06):
So, whether it's a transformeror some other kind of neural net
, as Sam Altman said recently,everything we've done with
transformers and chat, gpt andeverything else and gemini is
paying homage to the fact thatneural nets actually worked
right.
Deep learning work period fullstop.
We weren't sure it'd work, butdeep learning, which the math
(23:28):
was kind of done in 2012, itworks, and that's all this is.
We're leveraging those deeplearning models and building out
these huge, huge, huge modelsthat are thousands, millions of
layers deep right.
Speaker 2 (23:40):
I do want to touch upon a lot of this.
Ai stuff is very intimidatingto a lot of people youngsters as
well as people who are moreadvanced in age and they keep
thinking that, oh my God, thisis like computer programming.
What sort of technical detailsor what kind of skills do you
think a person needs to have tobe able to really leverage, uh,
(24:04):
this, this information?
Number one and number two afollow-up to this question,
essentially is there is so muchI mean everything out there
seems to have ai nowadays,whether it's your phone or
whether it's even your likevacuum.
But the question is and it maynot be the real AI or generative
AI as we talk about it, but thereal question is how do you
(24:26):
sift through all thisinformation and do you need any
technical skills to be able todo that and become efficient at
using Gen AI?
Speaker 3 (24:34):
Yeah.
So look, I think there arehundreds of web applications and
mobile applications out therethat can do interesting like.
Hyperwriteai has already kindof pre-set up all kinds of
prompts for you so you don'thave to think about prompting
correctly.
But here's what I tell peoplestop playing and start doing so.
(24:56):
I do 40, 50 keynotes a year infront of audiences sometimes
5,000 people, Right and I'll askthe audience raise, raise their
, raise your hand.
If you played with somethinglike chat GBT, everybody raised
their hands.
Now, raise your hand.
If you're doing real work withit every day, everybody's hands
go down.
Like two people put their handsup, right, and then I say
that's a shame, because all ofyou are wondering gee, I wonder
(25:18):
what I can do with this.
I wonder how do I use blah,blah, blah.
Okay, you will never learn ifyou don't learn to do actual
work.
So I use these models everysingle day, all day.
I generate images, I generatediagrams, I analyze spreadsheets
, I ask it how I should reply tothis email.
I generate all kinds of contentblog posts or technical data or
(25:44):
whatever.
So I don't generate a thingwithout first asking a large
language model or a transformerright or a multimodal, Okay.
Speaker 2 (25:53):
Why.
Speaker 3 (25:54):
Because it's a better generator of content than I
will ever be.
Period it read more than I canread in my life.
I can't change that.
That's how it works, and sowhat I want to be great at is
asking the right questions andgetting the right answers, and
then going through those answersand picking out what's
important to me and how I wantto change it if I want to change
(26:16):
it at all and critically thinkabout that.
So the skills that I need goingforward the skills we all need
going forward is doing that forevery single thing during your
day.
So, for example, you could havesaid should I have Kevin Serais
on my podcast?
It will opine on that and youcan decide whether it's good or
bad, but use it as an ideator.
(26:36):
Who else should I have on mypodcast?
How might I contact them right?
What should we talk about?
What might be some of thetopics that students might be
interested in, or or professorsmight be interested in, or
teachers might be interested inright, or administration might
be interested in?
So any idea you can think of,it's an ideator next to you and
you can have 100 brain powerusing that thing, or you can sit
(27:00):
there and have one brain power,which is fine.
It's a great brain, you got agreat brain, I got a great brain
.
But the person next to me hasgot 100 brain power.
Well, how am I going to beatthem?
They got 100 brain power.
If I'm a doctor and I get 100brain power, I'm crushing the
doctor next door who's only gotone brain power, right, you need
to think of it that way, andonce you start thinking about it
(27:21):
that way, you go.
I want 100 brain power too.
Okay, then stop playing.
Get a real subscription at $20a month and use ChatGPT we use
GPT-4.0 and connect it to liveweb information and then start
really using it for every singlething you do, and within weeks
you'll go.
I'm getting really good at this.
(27:42):
Now I see the power.
Otherwise, you don't see thepower.
Speaker 2 (27:45):
I see, and so I mean the gist of it should be that
just jump in and not worry aboutwhat you already know and don't
know.
And then you know and I usechat GP for a lot of daily tasks
and I would say that, at leastin my organization, I'm probably
one of the more advanced users,so to speak.
(28:07):
But and this is a conversationI have a lot with our faculty
members it's like oh, I don'tknow how to leverage this, I
don't know how to use this, oh,I'm very intimidated by it.
It's like oh, I don't know howto leverage this, I don't know
how to use this, oh, I'm veryintimidated by it.
Speaker 3 (28:20):
Start Start at your start.
Start doing real work.
You've got to get out of theplay mode.
It's like the differencebetween playing a video game and
writing a video game right.
Playing a video game, you'renot learning anything other than
(28:43):
just playing the game.
Writing a video game game,you're learning everything about
what it takes to write a videogame.
So stop playing the video game,stop playing with chat GPD.
Get a subscription to GPT-4-0right and actually work with it
and do real and say I'm going todo five tasks today with this.
Then I'm going to do 10 thenext day.
I'm going to take every emailand have them have my response
written by gpt40 and I'm goingto edit that.
I might not accept it, I mayhave it, rewrite it.
And then you start to get goodat asking the right questions.
(29:04):
So, um, hey, I had an argumentwith my spouse this morning.
How should I reply to him orher in email?
Now that will save our marriage, trust me.
The results that come back fromthat darn thing you, you could
never beat.
You can't beat it, you can'tbeat it.
It's better than anything wecan write.
(29:25):
Why?
Because it read every singlething that's ever been written
about that subject.
Speaker 2 (29:29):
Right, right, that's amazing.
Well, thank you so much, mrSuresh.
I know we're a little pressedon time, but this conversation
for us could for me at leastcould go on forever.
There's just so much to learnfrom you and I really appreciate
it and genuinely, it's been anhonor and a pleasure to have you
on our podcast.
(29:50):
And again, thank you so muchfor the time and thank you so
much for literally laying thegroundwork for us having a
better life.
Speaker 3 (30:00):
Yes, well, I think it's.
Look, it's a great time intechnology and we've seen so
many big changes in technologythe internet, smartphones and
now generative AI.
These are huge game changersand there's more to come, so
we'll be back on the showanother time, take care.
Thanks so much for having me.
Speaker 2 (30:20):
Thank you so much, mr Sarris.
We really appreciate theinsights that you provided about
AI.
As you know, we always seehundreds, if not thousands, of
AI experts, but we're reallyhonored to be able to have a
real expert and the father ofthe virtual assistant on our
(30:41):
show tonight.
But once again, thank you somuch, mr Suresh and everybody
out there, make sure you polishup your AI skills and work on
prompt generating and promptengineering to be a more
efficient student, and alwaysremember there is no shortcut to
(31:02):
becoming an MD.
If you like the content that weproduce, please give us a like,
follow and share.
It goes a long way, especiallyfor our production team, who put
a lot of work into producingthese episodes and, if you feel
free, to download our otherepisodes from Spotify, google or
any other platform that youprefer.
Thank you so much and thank youfor your support.
Speaker 1 (31:25):
Thank you so much for tuning into our show.
We hope you enjoyed anotherepisode of Med School Minutes.
If you like our content, pleasefollow us and receive
notification when a new show isposted.
This podcast is brought to youby St James School of Medicine.
For a video version of thispodcast, please check us out on
sjsmorg slash video.
Popular Podcasts
Cold Case Files: Miami
Joyce Sapp, 76; Bryan Herrera, 16; and Laurance Webb, 32—three Miami residents whose lives were stolen in brutal, unsolved homicides. Cold Case Files: Miami follows award‑winning radio host and City of Miami Police reserve officer Enrique Santos as he partners with the department’s Cold Case Homicide Unit, determined family members, and the advocates who spend their lives fighting for justice for the victims who can no longer fight for themselves.
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.