I’m going to teach you guys how to teach computers so that’s not exactly a
computers so that’s not exactly a
computers so that’s not exactly a typical hobby that most of us go into
typical hobby that most of us go into
typical hobby that most of us go into it’s not like you finished class and you
it’s not like you finished class and you
it’s not like you finished class and you just go home and decide to start
just go home and decide to start
just go home and decide to start teaching computers it’s not exactly
teaching computers it’s not exactly
teaching computers it’s not exactly something we all do but for me it all
something we all do but for me it all
something we all do but for me it all started when I went on a trip to
started when I went on a trip to
started when I went on a trip to Afghanistan as a 15 year old and I came
Afghanistan as a 15 year old and I came
Afghanistan as a 15 year old and I came back and I realized that I wanted to
back and I realized that I wanted to
back and I realized that I wanted to revolutionize healthcare now that’s a
revolutionize healthcare now that’s a
revolutionize healthcare now that’s a daunting task it’s a daunting task for a
daunting task it’s a daunting task for a
daunting task it’s a daunting task for a lot of people and there’s not exactly a
lot of people and there’s not exactly a
lot of people and there’s not exactly a how-to or a wiki how that’s they going
how-to or a wiki how that’s they going
how-to or a wiki how that’s they going about it there’s no video that explains
about it there’s no video that explains
about it there’s no video that explains step by step instructions nothing
step by step instructions nothing
step by step instructions nothing especially for 15 year old me I knew
especially for 15 year old me I knew
especially for 15 year old me I knew that that’s what I wanted to do but I
that that’s what I wanted to do but I
that that’s what I wanted to do but I had no clue how I was gonna go about it
had no clue how I was gonna go about it
had no clue how I was gonna go about it until one day driven by my curiosity I
until one day driven by my curiosity I
until one day driven by my curiosity I searched something how did that
searched something how did that
searched something how did that supercomputer beat the Jeopardy world
supercomputer beat the Jeopardy world
supercomputer beat the Jeopardy world champion now in 2011 IBM released Watson
champion now in 2011 IBM released Watson
champion now in 2011 IBM released Watson a computer that had question-answering
a computer that had question-answering
a computer that had question-answering capabilities now IBM claimed that Watson
capabilities now IBM claimed that Watson
capabilities now IBM claimed that Watson was so good at answering questions that
was so good at answering questions that
was so good at answering questions that it could beat the world champions in
it could beat the world champions in
it could beat the world champions in jeopardy now Jeopardy is a pretty
jeopardy now Jeopardy is a pretty
jeopardy now Jeopardy is a pretty difficult game it’s not exactly
difficult game it’s not exactly
difficult game it’s not exactly something that people that aren’t
something that people that aren’t
something that people that aren’t exactly intelligent player do well in
exactly intelligent player do well in
exactly intelligent player do well in but for IBM to have the gusto to say
but for IBM to have the gusto to say
but for IBM to have the gusto to say that computers could beat humans
that computers could beat humans
that computers could beat humans that’s pretty atypical of them and so
that’s pretty atypical of them and so
that’s pretty atypical of them and so when the time came for Watson to go up
when the time came for Watson to go up
when the time came for Watson to go up against these humans
against these humans
against these humans Watson completely destroyed them there
Watson completely destroyed them there
Watson completely destroyed them there was not even a close shot for the humans
was not even a close shot for the humans
was not even a close shot for the humans not only did Watson beat one human it
not only did Watson beat one human it
not only did Watson beat one human it beat two of the world’s best jeopardy
beat two of the world’s best jeopardy
beat two of the world’s best jeopardy players and it beat him by a longshot
players and it beat him by a longshot
players and it beat him by a longshot and so as I’m going through the results
and so as I’m going through the results
and so as I’m going through the results I’m sort of wondering how are computers
I’m sort of wondering how are computers
I’m sort of wondering how are computers better than humans when did that
better than humans when did that
better than humans when did that when did this happen what exactly makes
when did this happen what exactly makes
when did this happen what exactly makes this computer better than a human at
this computer better than a human at
this computer better than a human at answering a question and so I’m going
answering a question and so I’m going
answering a question and so I’m going through these Ling’s I’m searching this
through these Ling’s I’m searching this
through these Ling’s I’m searching this weird concept of machine learning comes
weird concept of machine learning comes
weird concept of machine learning comes up every link has something to do with
up every link has something to do with
up every link has something to do with machine learning and so I asked how does
machine learning and so I asked how does
machine learning and so I asked how does machine learning work what is it and so
machine learning work what is it and so
machine learning work what is it and so the basic concept of machine learning is
the basic concept of machine learning is
the basic concept of machine learning is sort of in the named machines that can
sort of in the named machines that can
sort of in the named machines that can learn it’s a large sort of branch in
learn it’s a large sort of branch in
learn it’s a large sort of branch in computer science and what it entails is
computer science and what it entails is
computer science and what it entails is that we can feed computers a ton of data
that we can feed computers a ton of data
that we can feed computers a ton of data and we can let these computers figure
and we can let these computers figure
and we can let these computers figure out high dimensional patterns clustering
out high dimensional patterns clustering
out high dimensional patterns clustering capabilities within this data and if you
capabilities within this data and if you
capabilities within this data and if you teach it well enough these computers get
teach it well enough these computers get
teach it well enough these computers get sort of intelligent at this task and
sort of intelligent at this task and
sort of intelligent at this task and they can actually take what they’ve
they can actually take what they’ve
they can actually take what they’ve learned and apply it to new problems
learned and apply it to new problems
learned and apply it to new problems that it has never seen before so machine
that it has never seen before so machine
that it has never seen before so machine learning is this topic within computer
learning is this topic within computer
learning is this topic within computer science and there are sub branches under
science and there are sub branches under
science and there are sub branches under it there are different types of
it there are different types of
it there are different types of algorithms that machine learning uses
algorithms that machine learning uses
algorithms that machine learning uses one of the algorithms that were being
one of the algorithms that were being
one of the algorithms that were being used were called neural networks and
used were called neural networks and
used were called neural networks and they peaked my interest mainly because
they peaked my interest mainly because
they peaked my interest mainly because they were kicking human but they were
they were kicking human but they were
they were kicking human but they were better than humans at almost every task
better than humans at almost every task
better than humans at almost every task that they were being put at and they
that they were being put at and they
that they were being put at and they were consistently outperforming every
were consistently outperforming every
were consistently outperforming every other algorithm that was insane and so
other algorithm that was insane and so
other algorithm that was insane and so neural networks are modeled sort of like
neural networks are modeled sort of like
neural networks are modeled sort of like the human brain that’s where the term
the human brain that’s where the term
the human brain that’s where the term neural comes in we have neurons in our
neural comes in we have neurons in our
neural comes in we have neurons in our brain and each of these neurons do
brain and each of these neurons do
brain and each of these neurons do something they have some sort of
something they have some sort of
something they have some sort of function so that’s sort of what in your
function so that’s sort of what in your
function so that’s sort of what in your own networks do we give it a ton of data
own networks do we give it a ton of data
own networks do we give it a ton of data and it sort of sort of figures out what
and it sort of sort of figures out what
and it sort of sort of figures out what exactly needs to be looking for but I
exactly needs to be looking for but I
exactly needs to be looking for but I wondered what specifically our neural
wondered what specifically our neural
wondered what specifically our neural networks see good at and what I realize
networks see good at and what I realize
networks see good at and what I realize going through these searches and going
going through these searches and going
going through these searches and going through these links was that neural
through these links was that neural
through these links was that neural networks were really good at taking
networks were really good at taking
networks were really good at taking large amounts of data just straight
large amounts of data just straight
large amounts of data just straight number data and finding these obscure
number data and finding these obscure
number data and finding these obscure patterns that as humans we would never
patterns that as humans we would never
patterns that as humans we would never realize that were really good at looking
realize that were really good at looking
realize that were really good at looking at patterns at such a different
at patterns at such a different
at patterns at such a different standpoint at high dimensions that as
standpoint at high dimensions that as
standpoint at high dimensions that as humans we just can’t comprehend and so
humans we just can’t comprehend and so
humans we just can’t comprehend and so as I’m looking through this and I’m
as I’m looking through this and I’m
as I’m looking through this and I’m thinking about this I’m
thinking about this I’m
thinking about this I’m wondering well regular data regular
wondering well regular data regular
wondering well regular data regular numeric data is cool right it works I
numeric data is cool right it works I
numeric data is cool right it works I mean obviously computers can handle it
mean obviously computers can handle it
mean obviously computers can handle it but what about images so I asked do
but what about images so I asked do
but what about images so I asked do neural networks work with images now
neural networks work with images now
neural networks work with images now here’s the thing with images you guys
here’s the thing with images you guys
here’s the thing with images you guys might not realize it or maybe you do but
might not realize it or maybe you do but
might not realize it or maybe you do but if you take a picture of me right now
if you take a picture of me right now
if you take a picture of me right now and then you take another picture of me
and then you take another picture of me
and then you take another picture of me a second later and then 100 more
a second later and then 100 more
a second later and then 100 more pictures of me a hundred seconds later
pictures of me a hundred seconds later
pictures of me a hundred seconds later it’s gonna be different every single
it’s gonna be different every single
it’s gonna be different every single time the lighting is different my facial
time the lighting is different my facial
time the lighting is different my facial expression is different and probably to
expression is different and probably to
expression is different and probably to the left or to the right it’s different
the left or to the right it’s different
the left or to the right it’s different images have no sort of how-tos of taking
images have no sort of how-tos of taking
images have no sort of how-tos of taking the same exact image every single time
the same exact image every single time
the same exact image every single time and so if we really want computers to
and so if we really want computers to
and so if we really want computers to get good at images they really need to
get good at images they really need to
get good at images they really need to be learning specifically the content
be learning specifically the content
be learning specifically the content within the image not environmental
within the image not environmental
within the image not environmental heuristics and so as I’m going through
heuristics and so as I’m going through
heuristics and so as I’m going through this neural networks are also a branch
this neural networks are also a branch
this neural networks are also a branch of machine learning but they also
of machine learning but they also
of machine learning but they also encompass a lot more there are specific
encompass a lot more there are specific
encompass a lot more there are specific types of neural networks neural networks
types of neural networks neural networks
types of neural networks neural networks that work well with images are called
that work well with images are called
that work well with images are called convolutional neural networks and
convolutional neural networks and
convolutional neural networks and essentially instead of having small
essentially instead of having small
essentially instead of having small mathematical nodes they have these
mathematical nodes they have these
mathematical nodes they have these filters so I sort of understood how
filters so I sort of understood how
filters so I sort of understood how convolutional neural networks worked I
convolutional neural networks worked I
convolutional neural networks worked I understood that they were good with
understood that they were good with
understood that they were good with images I understood that the concept of
images I understood that the concept of
images I understood that the concept of neural networks were good with
neural networks were good with
neural networks were good with extracting high dimensional pattern data
extracting high dimensional pattern data
extracting high dimensional pattern data so I wondered how exactly do you train
so I wondered how exactly do you train
so I wondered how exactly do you train it like what goes into that and so I
it like what goes into that and so I
it like what goes into that and so I asked how do you train a convolution
asked how do you train a convolution
asked how do you train a convolution your own network and this was astounding
your own network and this was astounding
your own network and this was astounding to see because it’s so similar as to how
to see because it’s so similar as to how
to see because it’s so similar as to how we as humans are learning you give a
we as humans are learning you give a
we as humans are learning you give a convolutional neural network a ton of
convolutional neural network a ton of
convolutional neural network a ton of data and this data is labeled so a given
data and this data is labeled so a given
data and this data is labeled so a given Network a picture of an orange a picture
Network a picture of an orange a picture
Network a picture of an orange a picture of an apple another picture of an orange
of an apple another picture of an orange
of an apple another picture of an orange another picture of an apple and I’ll do
another picture of an apple and I’ll do
another picture of an apple and I’ll do this a couple million times and I’ll
this a couple million times and I’ll
this a couple million times and I’ll tell the network here’s an image and
tell the network here’s an image and
tell the network here’s an image and guess what you think this image might be
guess what you think this image might be
guess what you think this image might be and it’ll take a guess yeah apple or
and it’ll take a guess yeah apple or
and it’ll take a guess yeah apple or orange and if it’s wrong I tell it hey
orange and if it’s wrong I tell it hey
orange and if it’s wrong I tell it hey go back and sort of figure out where you
go back and sort of figure out where you
go back and sort of figure out where you made your mistake tweak it so that if I
made your mistake tweak it so that if I
made your mistake tweak it so that if I were to give you the same exact image
were to give you the same exact image
were to give you the same exact image you wouldn’t get it wrong and if it was
you wouldn’t get it wrong and if it was
you wouldn’t get it wrong and if it was right it would hardwire that the
right it would hardwire that the
right it would hardwire that the knowledge that it’s been taught sort of
knowledge that it’s been taught sort of
knowledge that it’s been taught sort of like the brain trial-and-error you get a
like the brain trial-and-error you get a
like the brain trial-and-error you get a math problem wrong you go back you
math problem wrong you go back you
math problem wrong you go back you figure out what you did wrong with it
figure out what you did wrong with it
figure out what you did wrong with it and then you continue but I I wondered
and then you continue but I I wondered
and then you continue but I I wondered what exactly within the network are you
what exactly within the network are you
what exactly within the network are you training the stuff gets super complex
training the stuff gets super complex
training the stuff gets super complex like is it just is it literally just a
like is it just is it literally just a
like is it just is it literally just a network is that a bunch of code like
network is that a bunch of code like
network is that a bunch of code like what exactly are you training with the
what exactly are you training with the
what exactly are you training with the within a convolutional neural network
within a convolutional neural network
within a convolutional neural network and I asked what is a convolutional
and I asked what is a convolutional
and I asked what is a convolutional filter that’s the stuff inside of it and
filter that’s the stuff inside of it and
filter that’s the stuff inside of it and so these filters are sort of like
so these filters are sort of like
so these filters are sort of like Instagram filters Instagram filters make
Instagram filters Instagram filters make
Instagram filters Instagram filters make us look happier and make us look more
us look happier and make us look more
us look happier and make us look more energetic sometimes they make me look
energetic sometimes they make me look
energetic sometimes they make me look like I took my picture and good lighting
like I took my picture and good lighting
like I took my picture and good lighting when actuality I took it in the bathroom
when actuality I took it in the bathroom
when actuality I took it in the bathroom and dark but these filters aren’t making
and dark but these filters aren’t making
and dark but these filters aren’t making us look good they’re looking for
us look good they’re looking for
us look good they’re looking for specific features they’re looking for
specific features they’re looking for
specific features they’re looking for edges are looking for corners filters
edges are looking for corners filters
edges are looking for corners filters that are later on in the network are
that are later on in the network are
that are later on in the network are looking at colors and specific objects
looking at colors and specific objects
looking at colors and specific objects if you were to peer within a
if you were to peer within a
if you were to peer within a convolutional neural network that was
convolutional neural network that was
convolutional neural network that was trained to recognize cats and dogs
trained to recognize cats and dogs
trained to recognize cats and dogs the last convolutional filter is
the last convolutional filter is
the last convolutional filter is actually looking at a cat it’s looking
actually looking at a cat it’s looking
actually looking at a cat it’s looking for a whole facial description of a cat
for a whole facial description of a cat
for a whole facial description of a cat which is intense because we didn’t
which is intense because we didn’t
which is intense because we didn’t explicitly tell it this is what a cat is
explicitly tell it this is what a cat is
explicitly tell it this is what a cat is we just let it figure it out after
we just let it figure it out after
we just let it figure it out after hundreds of thousands of images and so I
hundreds of thousands of images and so I
hundreds of thousands of images and so I also wondered because this stuff relates
also wondered because this stuff relates
also wondered because this stuff relates so much to the brain our convolutional
so much to the brain our convolutional
so much to the brain our convolutional neural networks sort of like the visual
neural networks sort of like the visual
neural networks sort of like the visual cortex in our brain and it was
cortex in our brain and it was
cortex in our brain and it was interesting to see that they’re almost
interesting to see that they’re almost
interesting to see that they’re almost exactly the same instead of these
exactly the same instead of these
exactly the same instead of these filters we have layers of neurons in our
filters we have layers of neurons in our
filters we have layers of neurons in our brain and these neurons are picking up
brain and these neurons are picking up
brain and these neurons are picking up on the most minut details if I were to
on the most minut details if I were to
on the most minut details if I were to show you a 90 degree angle on this
show you a 90 degree angle on this
show you a 90 degree angle on this screen there are specific neurons in
screen there are specific neurons in
screen there are specific neurons in your brain that are going to fire
your brain that are going to fire
your brain that are going to fire because they just recognize that 90
because they just recognize that 90
because they just recognize that 90 degree angle but then if I show off an
degree angle but then if I show off an
degree angle but then if I show off an 89 degree angle those neurons aren’t
89 degree angle those neurons aren’t
89 degree angle those neurons aren’t going to fire and it set another set of
going to fire and it set another set of
going to fire and it set another set of neurons are going to fire because our
neurons are going to fire because our
neurons are going to fire because our brains are so adept at taking these
brains are so adept at taking these
brains are so adept at taking these really small minut details and figuring
really small minut details and figuring
really small minut details and figuring it out
it out
it out understand
understand
understand that this is a corner and this is an
that this is a corner and this is an
that this is a corner and this is an edge and this is a 90-degree angle and
edge and this is a 90-degree angle and
edge and this is a 90-degree angle and this isn’t so as I’m going through this
this isn’t so as I’m going through this
this isn’t so as I’m going through this I sort of have this idea these networks
I sort of have this idea these networks
I sort of have this idea these networks are really good with patterns with data
are really good with patterns with data
are really good with patterns with data and so my next question was about breast
and so my next question was about breast
and so my next question was about breast cancer
cancer
cancer I wondered why is breast cancer so hard
I wondered why is breast cancer so hard
I wondered why is breast cancer so hard to diagnose and when I later found out
to diagnose and when I later found out
to diagnose and when I later found out was that there are a ton of markers for
was that there are a ton of markers for
was that there are a ton of markers for breast cancer for a human for a
breast cancer for a human for a
breast cancer for a human for a radiologist a pathologist or a doctor to
radiologist a pathologist or a doctor to
radiologist a pathologist or a doctor to look at an image an x-ray there are over
look at an image an x-ray there are over
look at an image an x-ray there are over 10 to 20 features that they need to be
10 to 20 features that they need to be
10 to 20 features that they need to be looking for but they need to look for it
looking for but they need to look for it
looking for but they need to look for it within the whole image and they’re not
within the whole image and they’re not
within the whole image and they’re not exactly clustered together these are
exactly clustered together these are
exactly clustered together these are things like shape and size and
things like shape and size and
things like shape and size and jaggedness of whatever they’re looking
jaggedness of whatever they’re looking
jaggedness of whatever they’re looking at and so it’s pretty hard to diagnose
at and so it’s pretty hard to diagnose
at and so it’s pretty hard to diagnose because the difference between a tumor
because the difference between a tumor
because the difference between a tumor that’s cancerous and could actually be
that’s cancerous and could actually be
that’s cancerous and could actually be fatal
fatal
fatal versus a tumor that’s non cancerous and
versus a tumor that’s non cancerous and
versus a tumor that’s non cancerous and is really just gonna sit there there’s
is really just gonna sit there there’s
is really just gonna sit there there’s almost that much of change there’s not
almost that much of change there’s not
almost that much of change there’s not that much for them to be looking for so
that much for them to be looking for so
that much for them to be looking for so I wanted to quantify that it’s hard to
I wanted to quantify that it’s hard to
I wanted to quantify that it’s hard to diagnose but how hard is it and so I
diagnose but how hard is it and so I
diagnose but how hard is it and so I asked what is the misdiagnosis rate so
asked what is the misdiagnosis rate so
asked what is the misdiagnosis rate so I’m scrolling through this and I’m
I’m scrolling through this and I’m
I’m scrolling through this and I’m looking at stats and it looks like as
looking at stats and it looks like as
looking at stats and it looks like as many as 31 percent of women are being
many as 31 percent of women are being
many as 31 percent of women are being misdiagnosed 31 percent that means that
misdiagnosed 31 percent that means that
misdiagnosed 31 percent that means that 31 percent of women are being told that
31 percent of women are being told that
31 percent of women are being told that the tumors they have are cancerous when
the tumors they have are cancerous when
the tumors they have are cancerous when they’re not actually we’re more fatally
they’re not actually we’re more fatally
they’re not actually we’re more fatally they’re being told that the tumors they
they’re being told that the tumors they
they’re being told that the tumors they have are not cancerous when they
have are not cancerous when they
have are not cancerous when they actually are 31 percent of women are
actually are 31 percent of women are
actually are 31 percent of women are fighting for their lives they’re
fighting for their lives they’re
fighting for their lives they’re grappling with this reality that there’s
grappling with this reality that there’s
grappling with this reality that there’s a foreign object within their body that
a foreign object within their body that
a foreign object within their body that their body has turned against themselves
their body has turned against themselves
their body has turned against themselves and 31 percent of them are being told
and 31 percent of them are being told
and 31 percent of them are being told they’re wrong that it’s off that’s 31
they’re wrong that it’s off that’s 31
they’re wrong that it’s off that’s 31 percent of woman that could be saved
percent of woman that could be saved
percent of woman that could be saved because especially with cancer the
because especially with cancer the
because especially with cancer the earlier you detect it the higher the
earlier you detect it the higher the
earlier you detect it the higher the likelihood you have of beating it so
likelihood you have of beating it so
likelihood you have of beating it so we’re robbing 31% of women
we’re robbing 31% of women
we’re robbing 31% of women from the chance of living so I’m
from the chance of living so I’m
from the chance of living so I’m thinking about this and it’s astounding
thinking about this and it’s astounding
thinking about this and it’s astounding because as I’m going through this the 31
because as I’m going through this the 31
because as I’m going through this the 31 percent is a big number but bigger than
percent is a big number but bigger than
percent is a big number but bigger than that is the astounding number of threads
that is the astounding number of threads
that is the astounding number of threads that I’m looking at that talked about
that I’m looking at that talked about
that I’m looking at that talked about how they were misdiagnosed and now
how they were misdiagnosed and now
how they were misdiagnosed and now there’s stage for an invasive those are
there’s stage for an invasive those are
there’s stage for an invasive those are big words you don’t have to be a doctor
big words you don’t have to be a doctor
big words you don’t have to be a doctor to realize that that doesn’t sound good
to realize that that doesn’t sound good
to realize that that doesn’t sound good and so I wanted to build an accurate
and so I wanted to build an accurate
and so I wanted to build an accurate solution something that could help these
solution something that could help these
solution something that could help these people but I didn’t want it to be
people but I didn’t want it to be
people but I didn’t want it to be expensive so I asked are mammograms
expensive so I asked are mammograms
expensive so I asked are mammograms cheap I wanted to build a solution that
cheap I wanted to build a solution that
cheap I wanted to build a solution that was cost effective for people all around
was cost effective for people all around
was cost effective for people all around the world and what I realized was that
the world and what I realized was that
the world and what I realized was that mammograms are usually covered under
mammograms are usually covered under
mammograms are usually covered under health insurance but if they’re not most
health insurance but if they’re not most
health insurance but if they’re not most developing countries have these machines
developing countries have these machines
developing countries have these machines because they’ve been in existence for so
because they’ve been in existence for so
because they’ve been in existence for so long and so that’s exactly what I did I
long and so that’s exactly what I did I
long and so that’s exactly what I did I took what I learned in computer science
took what I learned in computer science
took what I learned in computer science and machine learning in pattern
and machine learning in pattern
and machine learning in pattern recognition and I applied it to medicine
recognition and I applied it to medicine
recognition and I applied it to medicine to help try to make impact to go towards
to help try to make impact to go towards
to help try to make impact to go towards that goal of revolutionising healthcare
that goal of revolutionising healthcare
that goal of revolutionising healthcare but what I realized along the way was
but what I realized along the way was
but what I realized along the way was that there are just some things that you
that there are just some things that you
that there are just some things that you can’t search for the passion the
can’t search for the passion the
can’t search for the passion the motivation the human element the thing
motivation the human element the thing
motivation the human element the thing that wakes us up that keeps us going
that wakes us up that keeps us going
that wakes us up that keeps us going these are things that no company no
these are things that no company no
these are things that no company no curriculum no teacher not even your
curriculum no teacher not even your
curriculum no teacher not even your parents can tell you these are things
parents can tell you these are things
parents can tell you these are things that you have to go out into the real
that you have to go out into the real
that you have to go out into the real world and explore and find for me I was
world and explore and find for me I was
world and explore and find for me I was going to Afghanistan and realizing that
going to Afghanistan and realizing that
going to Afghanistan and realizing that there were people suffering because the
there were people suffering because the
there were people suffering because the quality of health care they were
quality of health care they were
quality of health care they were receiving was dictated by the amount of
receiving was dictated by the amount of
receiving was dictated by the amount of money that they had health care is the
money that they had health care is the
money that they had health care is the industry that keeps us living it keeps
industry that keeps us living it keeps
industry that keeps us living it keeps us going we have dreams we have
us going we have dreams we have
us going we have dreams we have motivations we want to get things done
motivations we want to get things done
motivations we want to get things done we have goals we want to we want to grow
we have goals we want to we want to grow
we have goals we want to we want to grow up
up
up but when healthcare the industry that is
but when healthcare the industry that is
but when healthcare the industry that is supposed to keep us living is dictated
supposed to keep us living is dictated
supposed to keep us living is dictated by money by wealth by these material
by money by wealth by these material
by money by wealth by these material things are our lives really immaterial
things are our lives really immaterial
things are our lives really immaterial is it fair to tell someone that was born
is it fair to tell someone that was born
is it fair to tell someone that was born into a situation so
into a situation so
into a situation so poverty in a thorough country like
poverty in a thorough country like
poverty in a thorough country like Afghanistan where I’m from but because
Afghanistan where I’m from but because
Afghanistan where I’m from but because you were born into poverty your life
you were born into poverty your life
you were born into poverty your life doesn’t matter as much compared to the
doesn’t matter as much compared to the
doesn’t matter as much compared to the person that has more money has more
person that has more money has more
person that has more money has more wealth has more influence is that fair
wealth has more influence is that fair
wealth has more influence is that fair that was a question I grappled with I
that was a question I grappled with I
that was a question I grappled with I realized that this was against every
realized that this was against every
realized that this was against every bone in my body but this experience I
bone in my body but this experience I
bone in my body but this experience I went out of my comfort zone I left the
went out of my comfort zone I left the
went out of my comfort zone I left the privilege of living in Chicago the
privilege of living in Chicago the
privilege of living in Chicago the privilege of being able to go to the
privilege of being able to go to the
privilege of being able to go to the doctor and understand that I was going
doctor and understand that I was going
doctor and understand that I was going to be okay and I saw that there were
to be okay and I saw that there were
to be okay and I saw that there were woman mothers cradling their sons in
woman mothers cradling their sons in
woman mothers cradling their sons in hopes in fear that a doctor would come
hopes in fear that a doctor would come
hopes in fear that a doctor would come by that the line that stood in front of
by that the line that stood in front of
by that the line that stood in front of them the one that grasps corners and
them the one that grasps corners and
them the one that grasps corners and blocks of the city that it would be
blocks of the city that it would be
blocks of the city that it would be shortened so if their little baby
shortened so if their little baby
shortened so if their little baby could have a chance to grow up to keep
could have a chance to grow up to keep
could have a chance to grow up to keep going it stood against everything I
going it stood against everything I
going it stood against everything I believed in instead against it and it
believed in instead against it and it
believed in instead against it and it shook me and so I came back and I
shook me and so I came back and I
shook me and so I came back and I realized that that was something that I
realized that that was something that I
realized that that was something that I wanted to fix these things you can’t
wanted to fix these things you can’t
wanted to fix these things you can’t find them in a classroom you can’t find
find them in a classroom you can’t find
find them in a classroom you can’t find them sitting behind a computer searching
them sitting behind a computer searching
them sitting behind a computer searching for something you have to go out you
for something you have to go out you
for something you have to go out you have to explore you have to find the
have to explore you have to find the
have to explore you have to find the thing that matters to you I’m blessed to
thing that matters to you I’m blessed to
thing that matters to you I’m blessed to be able to wake up every morning and
be able to wake up every morning and
be able to wake up every morning and know that I’m happy that I’m content
know that I’m happy that I’m content
know that I’m happy that I’m content with the work that I’m doing life is
with the work that I’m doing life is
with the work that I’m doing life is worth a lot more than money it’s worth a
worth a lot more than money it’s worth a
worth a lot more than money it’s worth a lot more than what we placed on it in
lot more than what we placed on it in
lot more than what we placed on it in these developing countries people can’t
these developing countries people can’t
these developing countries people can’t control what they’re born into and they
control what they’re born into and they
control what they’re born into and they can’t really control where even how they
can’t really control where even how they
can’t really control where even how they might end but they can control
might end but they can control
might end but they can control everything that happens in the middle
everything that happens in the middle
everything that happens in the middle and sometimes we get lucky we’re a lot
and sometimes we get lucky we’re a lot
and sometimes we get lucky we’re a lot luckier because we’re born into a place
luckier because we’re born into a place
luckier because we’re born into a place where we can do more and it’s our
where we can do more and it’s our
where we can do more and it’s our responsibility as humans forget forget
responsibility as humans forget forget
responsibility as humans forget forget that it’s them these are our brothers or
that it’s them these are our brothers or
that it’s them these are our brothers or sisters these are people that we see on
sisters these are people that we see on
sisters these are people that we see on the news and we just assume oh it’s
the news and we just assume oh it’s
the news and we just assume oh it’s someone else
someone else
someone else that country but no these are real
that country but no these are real
that country but no these are real people that have families that have
people that have families that have
people that have families that have goals and motivations just like us and
goals and motivations just like us and
goals and motivations just like us and so I want to ask you the audience the
so I want to ask you the audience the
so I want to ask you the audience the people sitting here you guys want to
people sitting here you guys want to
people sitting here you guys want to make bold moves that’s why you’re here
make bold moves that’s why you’re here
make bold moves that’s why you’re here you’re in support of that ideology what
you’re in support of that ideology what
you’re in support of that ideology what exactly is it that you want to search
exactly is it that you want to search
exactly is it that you want to search for go out do something find something
for go out do something find something
for go out do something find something worth searching for thank you
worth searching for thank you
worth searching for thank you [Applause]
[Applause]
[Applause] you
you
you [Applause]
”
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