hey there i'm Jabril and welcome to
crash course artificial intelligence now
I want to make sure we're starting on
the same page artificial intelligence is
everywhere it's helping banks make loans
and helping doctors diagnose patients
it's on our cell phones Auto completing
text it's the algorithm recommending
videos for you to watch after this one
AI already has a pretty huge impact on
all of our lives
so people understandably have some
polarized feelings about it
some of us imagine that AI will change
the world in positive ways it could in
car accidents because we have
self-driving cars or give the elderly
great personalized care I was worried
that AI will lead to constant
surveillance by Big Brother government
some say the automation will take all of
our jobs or the robots might try and
kill us all no we're not worried about
you John Green but but when we interact
with AI that's currently available like
Siri hey Siri is AI gonna kill us all I
don't understand to say I going to kill
us all it's clear that those are still
distant futures now to understand our
artificial intelligence might be headed
and our role in the ad revolution we
have to understand how we got to where
we are today
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if you know about artificial
intelligence mostly from movies or books
AI probably seems like this vague label
for any machine that can think like a
human fiction writers like to imagine a
more generalized AI one that can answer
any question you might have and do
anything a human can do but that's a
pretty rigid way to think about AI and
it's not super realistic sorry John
Green but you can't do all that yet a
machine is said to have artificial
intelligence if we can interpret data
potentially learn from the data and use
that knowledge to adapt and achieve
specific goals now the idea of learning
from the data is kind of a new approach
but we'll get more into that in Episode
four so let's say we load a new program
into John Green bot this program looks
at a bunch of photos of me and some of
not of me and then learns from the data
then we can show him a new photo like
this selfie of me here in the studio
filming this crash course video and
we'll see if he can recognize if the
photo is me if he can correctly
classified that new photo we can say
that John Green bot has some artificial
intelligence of course that's a very
specific input of photos and a very
specific task of classifying the photo
that's either me or not me with just
that program John the green bar can't
recognize or name anyone who isn't me he
can't navigate to places
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or hold a meaningful conversation no
just I just don't get it well would
anyone choose the bagel and have a
perfectly good doughnut right here you
are thanks John Green bye he can't do
most things that humans do which is
pretty standard for AI these days but
even with this much more limited
definition of artificial intelligence AI
still plays a huge role in our everyday
lives there are some more obvious uses
for AI like Alexa or Roomba which is
kind of like the AI from science fiction
I guess but there are also a ton of less
obvious examples when we buy something
in a big store or online we have one
type of AI deciding which and how many
items the stock and as we scroll through
Instagram a different type of AI picks
ads to show us AI helps determine how
expensive our car insurance is or
whether we get approved for a loan and
AI even affects big life decisions like
when you submit your college or job
application AI might be screening it
before a human even sees it the way AI
and automation are changing Commerce and
jobs is sort of like the Industrial
Revolution in the 18th century this
change is global some people are excited
about it and others are afraid of it but
either way we all have responsibility to
understand AI and figure out what role a
I will play in our lives the AI
revolution itself isn't even that old
the term artificial intelligence didn't
even exist a century ago it was coined
in 1956 by a computer scientist named
John McCarthy he used it to name the
Dartmouth research project on artificial
intelligence most people just call it a
Dartmouth conference for short now this
is way more than a weekend where you
listen to a few talks and maybe go to a
networking dinner back in the day
academics got together to think for a
while the conference lasted eight weeks
and got a bunch of computer scientists
cognitive psychologists and
mathematicians to join forces many of
the concepts that we'll talk about in
crash course AI like artificial neural
networks were dreamed up and developed
during this conference and in the few
years that followed what because these
excited academics were pretty optimistic
about artificial intelligence they may
have oversold it a bit for example
Marvin Minsky was a talented cognitive
scientist who was a part of the
Dartmouth conference but he had some
ridiculously wrong predictions about
technology and specifically AI in 1970
he claimed that in three to eight years
we will have a machine with the general
intelligence of an average human being
and sorry Marvin but we're not even
close to that now scientists at the
Dartmouth conference seriously
underestimated how much data and
computing power and AI would need to
solve complex real world problems
see artificial intelligence doesn't
really know anything when it's created
kind of like a human baby babies used
their senses to perceive the world and
their bodies to interact with it and
they learn from the consequences of
their actions my baby niece might put a
strawberry in her mouth and decide that
it's tasty and then she might put plate
on her mouth and decide that it's gross
babies experience millions of these data
gathering events as they learn to speak
walk think and not eat play-doh now most
kinds of artificial intelligence don't
have things like senses a body or a
brain that can automatically judge a lot
of different things like a human baby
does modern AI systems are just programs
and machines so we need to give an AI a
lot of data plus we have to label the
data with whatever information the AI is
trying to learn like whether food tastes
good to humans and then the AI needs a
powerful enough computer to make sense
of all the data all of this just wasn't
available in 1956 back then an AI could
made me tell the difference between a
triangle and a circle but it definitely
can recognize my face in the photo like
John Green bot did earlier so until
about 2010 or so the field was basically
frozen and what's called the AI winter
still there were a lot of changes in the
last half a century that led us to the
AI revolution as a friend once said
history reminds us that revolutions are
not so much events as they are processes
the AI revolution didn't begin with a
sing
vents idea or invention we got to where
we are today because of lots of small
decisions and two big developments in
computing the first development was a
huge increase in computing power and how
fast computers could process data to see
just how huge let's go to the
thought-bubble
during the Dartmouth conference in 1956
the most advanced computer was the IBM
709 T it filled a whole room stored data
on basically giant cassette tapes and
took instructions using paper punch
cards every second
the IBM 709 T could do about 200,000
operations but if you tried to do that
it would take you fifty five and a half
hours assuming you did one operation per
second and took no breaks that's right
not even for snacks at the time this was
enough computing power to help with the
US Air Force ballistic missile warning
system but AI needs to do a lot more
computations with a lot more data the
street of a computer is linked to the
number of transistors it has to do
operations every two years or so since
1956 engineers have doubled the number
of transistors that can fit in the same
amount of space so computers have gotten
much faster when the first iPhone was
released in 2007 it could do about 400
million operations per second but 10
years later apple says the iPhone tins
processor can do about 600 billion
operations per second that's like having
the computing power of over a thousand
original iPhones in your pocket for all
the Nerds out there listen you're right
it's not quite that simple we're just
talking about flops here and a modern
supercomputer which does computational
functions like the IBM 709 T did can do
over 30 quadrillion operations per
second to put it another way a program
that would have taken a modern
supercomputer one second to compute
would have taken the IBM 709 T 4750
three years thanks thought-bubble
so computers started to have enough
computing power to mimic certain brain
functions with artificial intelligence
in 2005 and that's when the AI winter
started to show signs of thawing but it
doesn't really matter if you have a
powerful computer unless you also have a
lot of data for it to
the second development that kicked off
the AI revolution is something that
you're using right now the Internet in
social media in the past 20 years our
world has become much more
interconnected whether you live stream
from your phone or just use a credit
card we're all participating in the
modern world every time you upload a
photo click a link tweet a hashtag tweet
without a hashtag like a video on
YouTube tag a friend on Facebook argue
on reddit post on tik-tok our EP vine
support a Kickstarter campaign buy
snacks on Amazon call uber from a party
and basically anything that generates
data even when we do something that
seems like it's offline like applying
for a loan to buy a new car or using a
password at the airport those datasets
end up in a bigger system the AI
revolution is happening now because we
have this wealth of data and the
computing power to make sense of it and
I get it the idea that we're generating
a bunch of data but don't always know
how why or if it's being used by
computer programs can be kind of
overwhelming but through crash course AI
we want to learn how artificial
intelligence works because it's
impacting our lives in huge ways and
that impact to only continue to grow
with knowledge we can make small
decisions to help guide the AI
revolution instead of feeling like we're
riding on a roller coaster we didn't
even sign up for we're creating the
future of artificial intelligence
together every single day which i think
is pretty cool next time we'll start to
dive into technical ideas like
supervised unsupervised and
reinforcement learning and we'll discuss
what makes a machine learning algorithm
good see you then thanks to PBS for
sponsoring crash course AI if you want
to help keep crash course free for
everyone forever you can join our
community on patreon and if you don't
learn more about how computers got so
fast check out our video on Moore's Law
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you
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