let’s travel back in time for a moment to 2007 george w bush was president
to 2007 george w bush was president
to 2007 george w bush was president Rihanna’s Umbrella topped the Billboard
Rihanna’s Umbrella topped the Billboard
Rihanna’s Umbrella topped the Billboard charts v Harry Potter movie had just
charts v Harry Potter movie had just
charts v Harry Potter movie had just been released and reality star Kim
been released and reality star Kim
been released and reality star Kim Kardashian had yet to rise to prominence
Kardashian had yet to rise to prominence
Kardashian had yet to rise to prominence somehow 2007 can feel both like it was a
somehow 2007 can feel both like it was a
somehow 2007 can feel both like it was a million years ago and like it was just
million years ago and like it was just
million years ago and like it was just yesterday but what you might not realize
yesterday but what you might not realize
yesterday but what you might not realize was that in 2007 one major invention
was that in 2007 one major invention
was that in 2007 one major invention catalyzed a shift in the way we live
catalyzed a shift in the way we live
catalyzed a shift in the way we live work and play of course on June 29 2007
work and play of course on June 29 2007
work and play of course on June 29 2007 the iPhone was released now the iPhone
the iPhone was released now the iPhone
the iPhone was released now the iPhone was not the first smartphone invented
was not the first smartphone invented
was not the first smartphone invented Steve Jobs didn’t invent the technology
Steve Jobs didn’t invent the technology
Steve Jobs didn’t invent the technology he just came out with the form factor
he just came out with the form factor
he just came out with the form factor that was most widely adopted and say
that was most widely adopted and say
that was most widely adopted and say Qualcomm employee I would be remiss if I
Qualcomm employee I would be remiss if I
Qualcomm employee I would be remiss if I didn’t mention the Qualcomm CDMA
didn’t mention the Qualcomm CDMA
didn’t mention the Qualcomm CDMA smartphone released in 1999 teen 99 or
smartphone released in 1999 teen 99 or
smartphone released in 1999 teen 99 or the much more recognizable and popular
the much more recognizable and popular
the much more recognizable and popular blackberry released the same year but it
blackberry released the same year but it
blackberry released the same year but it was the iPhone that began that laid the
was the iPhone that began that laid the
was the iPhone that began that laid the seeds for a foundation of change now a
seeds for a foundation of change now a
seeds for a foundation of change now a plot if you have a smartphone with you
plot if you have a smartphone with you
plot if you have a smartphone with you right now
a plot again if you’ve used your
a plot again if you’ve used your smartphone today to navigate to the
smartphone today to navigate to the
smartphone today to navigate to the speeder store your ticket or summon
speeder store your ticket or summon
speeder store your ticket or summon transportation so I’m certainly not
transportation so I’m certainly not
transportation so I’m certainly not bringing to your attention anything you
bringing to your attention anything you
bringing to your attention anything you don’t already know you’re aware you have
don’t already know you’re aware you have
don’t already know you’re aware you have a smartphone as do all of your friends
a smartphone as do all of your friends
a smartphone as do all of your friends and family but what you might not fully
and family but what you might not fully
and family but what you might not fully grasp is just how quickly and
grasp is just how quickly and
grasp is just how quickly and ubiquitously we’ve adopted this
ubiquitously we’ve adopted this
ubiquitously we’ve adopted this technology in just nine years we’ve
technology in just nine years we’ve
technology in just nine years we’ve gotten to the point where over 65
gotten to the point where over 65
gotten to the point where over 65 percent of adult Americans use a
percent of adult Americans use a
percent of adult Americans use a smartphone if that number seems low to
smartphone if that number seems low to
smartphone if that number seems low to you it’s because among college-educated
you it’s because among college-educated
you it’s because among college-educated and young adults that percentage is much
and young adults that percentage is much
and young adults that percentage is much higher in fact we were able to adopt
higher in fact we were able to adopt
higher in fact we were able to adopt this technology so quickly and so
this technology so quickly and so
this technology so quickly and so universally that we’ve catalyzed a shift
universally that we’ve catalyzed a shift
universally that we’ve catalyzed a shift in the way we do business we’ve shifted
in the way we do business we’ve shifted
in the way we do business we’ve shifted our economy to the on demand or sharing
our economy to the on demand or sharing
our economy to the on demand or sharing economy the on demand or sharing economy
economy the on demand or sharing economy
economy the on demand or sharing economy is a model in which goods and services
is a model in which goods and services
is a model in which goods and services are traded on the basis of access rather
are traded on the basis of access rather
are traded on the basis of access rather than ownership this means for
than ownership this means for
than ownership this means for participating in collaborative
participating in collaborative
participating in collaborative consumption where someone will rent out
consumption where someone will rent out
consumption where someone will rent out or sell something they’re not using to
or sell something they’re not using to
or sell something they’re not using to their peers whether it’s their car their
their peers whether it’s their car their
their peers whether it’s their car their house and item or even their time rather
house and item or even their time rather
house and item or even their time rather than the b2c business models of the past
than the b2c business models of the past
than the b2c business models of the past mobile applications have enabled trusted
mobile applications have enabled trusted
mobile applications have enabled trusted c2c transactions or consumer to consumer
let’s take a moment and talk about the
let’s take a moment and talk about the economic conditions that made this shift
economic conditions that made this shift
economic conditions that made this shift possible the on-demand
possible the on-demand
possible the on-demand economic revolution didn’t become
economic revolution didn’t become
economic revolution didn’t become possible because the kind of consumers
possible because the kind of consumers
possible because the kind of consumers who were willing to pay extra for
who were willing to pay extra for
who were willing to pay extra for convenience and on-demand services got
convenience and on-demand services got
convenience and on-demand services got smartphones those kind of consumers had
smartphones those kind of consumers had
smartphones those kind of consumers had already had them for a few years it was
already had them for a few years it was
already had them for a few years it was when everyone had a smartphone they were
when everyone had a smartphone they were
when everyone had a smartphone they were so abit with us that even low-income
so abit with us that even low-income
so abit with us that even low-income individuals had one that these services
individuals had one that these services
individuals had one that these services became popular second of all these
became popular second of all these
became popular second of all these services didn’t rise to popularity until
services didn’t rise to popularity until
services didn’t rise to popularity until 2009 2010 shortly after the traditional
2009 2010 shortly after the traditional
2009 2010 shortly after the traditional economy came crashing down following the
economy came crashing down following the
economy came crashing down following the Great Recession of 2009 both high
Great Recession of 2009 both high
Great Recession of 2009 both high skilled and low skilled workers alike
skilled and low skilled workers alike
skilled and low skilled workers alike found it difficult to find meaningful
found it difficult to find meaningful
found it difficult to find meaningful labor when you think about rideshare it
labor when you think about rideshare it
labor when you think about rideshare it doesn’t just enable on-demand access to
doesn’t just enable on-demand access to
doesn’t just enable on-demand access to transportation it enables an on-demand
transportation it enables an on-demand
transportation it enables an on-demand income something that was becoming
income something that was becoming
income something that was becoming increasingly valuable for this kind of
increasingly valuable for this kind of
increasingly valuable for this kind of economic model to work not only did both
economic model to work not only did both
economic model to work not only did both sides of the equation
sides of the equation
sides of the equation have to have access to this technology
have to have access to this technology
have to have access to this technology but they both had to see a value
but they both had to see a value
but they both had to see a value proposition in providing it so that’s
proposition in providing it so that’s
proposition in providing it so that’s where we stood just a few years ago
where we stood just a few years ago
where we stood just a few years ago smartphones were rapidly approaching
smartphones were rapidly approaching
smartphones were rapidly approaching their peak penetration and there existed
their peak penetration and there existed
their peak penetration and there existed a gap in the economy people were willing
a gap in the economy people were willing
a gap in the economy people were willing to pay for goods and services and people
to pay for goods and services and people
to pay for goods and services and people demanded them but there existed nothing
demanded them but there existed nothing
demanded them but there existed nothing to connect them fast forward to the
to connect them fast forward to the
to connect them fast forward to the present and online marketplaces have
present and online marketplaces have
present and online marketplaces have become abundant and the on-demand
become abundant and the on-demand
become abundant and the on-demand economy is thriving so where do we stand
economy is thriving so where do we stand
economy is thriving so where do we stand today especially with respect to machine
today especially with respect to machine
today especially with respect to machine learning and artificial intelligence we
learning and artificial intelligence we
learning and artificial intelligence we find ourselves on the precipice of the
find ourselves on the precipice of the
find ourselves on the precipice of the next economic revolution the shift to
next economic revolution the shift to
next economic revolution the shift to the automated economy one half of the
the automated economy one half of the
the automated economy one half of the rideshare value proposition is the
rideshare value proposition is the
rideshare value proposition is the supply side and labor is extremely
supply side and labor is extremely
supply side and labor is extremely expensive and volatile when we go back
expensive and volatile when we go back
expensive and volatile when we go back to what if instead of using your phone
to what if instead of using your phone
to what if instead of using your phone to summon someone to take you to your
to summon someone to take you to your
to summon someone to take you to your destination the car could take you there
destination the car could take you there
destination the car could take you there itself what if we cut out the middleman
itself what if we cut out the middleman
itself what if we cut out the middleman entirely and use automation to provide
entirely and use automation to provide
entirely and use automation to provide services
one example of artificial intelligence
one example of artificial intelligence is Siri at this point you’ve all likely
is Siri at this point you’ve all likely
is Siri at this point you’ve all likely used or seen someone use Siri to access
used or seen someone use Siri to access
used or seen someone use Siri to access data and in a lot of ways series very
data and in a lot of ways series very
data and in a lot of ways series very intelligent she can understand humans
intelligent she can understand humans
intelligent she can understand humans the way humans speak using
the way humans speak using
the way humans speak using colloquialisms or idioms and she has a
colloquialisms or idioms and she has a
colloquialisms or idioms and she has a bunch of built-in jokes when you ask her
bunch of built-in jokes when you ask her
bunch of built-in jokes when you ask her an opinion based question she’ll respond
an opinion based question she’ll respond
an opinion based question she’ll respond with a humorous quip or sarcastic pun as
with a humorous quip or sarcastic pun as
with a humorous quip or sarcastic pun as we continue to interact with Siri in
we continue to interact with Siri in
we continue to interact with Siri in more complex ways this anthropomorphize
more complex ways this anthropomorphize
more complex ways this anthropomorphize an artificial intelligent robot we begin
an artificial intelligent robot we begin
an artificial intelligent robot we begin to expect more and more from her and it
to expect more and more from her and it
to expect more and more from her and it is this expectation and comfort with
is this expectation and comfort with
is this expectation and comfort with this technology that will drive us into
this technology that will drive us into
this technology that will drive us into the automated revolution everything you
the automated revolution everything you
the automated revolution everything you do on your device your smartphone tablet
do on your device your smartphone tablet
do on your device your smartphone tablet or computer is data beat to be collected
or computer is data beat to be collected
or computer is data beat to be collected when we use the same device the same way
when we use the same device the same way
when we use the same device the same way for an extended period of time the
for an extended period of time the
for an extended period of time the computer or device can begin to
computer or device can begin to
computer or device can begin to recognize our patterns and predict our
recognize our patterns and predict our
recognize our patterns and predict our next move this is called longitudinal
next move this is called longitudinal
next move this is called longitudinal data so even today when I get my car
data so even today when I get my car
data so even today when I get my car after work my phone usually has a
after work my phone usually has a
after work my phone usually has a notification waiting for me it tells me
notification waiting for me it tells me
notification waiting for me it tells me the traffic between my office and my
the traffic between my office and my
the traffic between my office and my home so every day between around 5:00
home so every day between around 5:00
home so every day between around 5:00 and 6:00 p.m. it knows I’m gonna get in
and 6:00 p.m. it knows I’m gonna get in
and 6:00 p.m. it knows I’m gonna get in my car and make the same commute and it
my car and make the same commute and it
my car and make the same commute and it tells me the same thing every day
tells me the same thing every day
tells me the same thing every day traffic is heavy expect delays another
traffic is heavy expect delays another
traffic is heavy expect delays another famous example of artificial
famous example of artificial
famous example of artificial intelligence is IBM’s Watson Watson
intelligence is IBM’s Watson Watson
intelligence is IBM’s Watson Watson famously beat the world’s best chess
famously beat the world’s best chess
famously beat the world’s best chess player at his own game chess is a finite
player at his own game chess is a finite
player at his own game chess is a finite game though each move creates a finite
game though each move creates a finite
game though each move creates a finite series of possible other moves and so
series of possible other moves and so
series of possible other moves and so forth
forth
forth and the machines ability to see the
and the machines ability to see the
and the machines ability to see the entire board and see every option is
entire board and see every option is
entire board and see every option is incredible in some ways in this context
incredible in some ways in this context
incredible in some ways in this context it makes sense that the machine is
it makes sense that the machine is
it makes sense that the machine is smarter than humans because it isn’t
smarter than humans because it isn’t
smarter than humans because it isn’t bound by the confines of human memory
bound by the confines of human memory
bound by the confines of human memory and capacity but what a lot of consumers
and capacity but what a lot of consumers
and capacity but what a lot of consumers fail to understand is that the machine
fail to understand is that the machine
fail to understand is that the machine isn’t understanding it’s just parsing
isn’t understanding it’s just parsing
isn’t understanding it’s just parsing through options
through options
through options the next best move Watson’s brand of
the next best move Watson’s brand of
the next best move Watson’s brand of interfacial intelligence took an extra
interfacial intelligence took an extra
interfacial intelligence took an extra step though when it challenged jeopardy
step though when it challenged jeopardy
step though when it challenged jeopardy Victor’s Ken Jennings and Brad Rutter at
Victor’s Ken Jennings and Brad Rutter at
Victor’s Ken Jennings and Brad Rutter at their own game jeopardy is an incredibly
their own game jeopardy is an incredibly
their own game jeopardy is an incredibly complex game which requires a really
complex game which requires a really
complex game which requires a really deep understanding of the English
deep understanding of the English
deep understanding of the English language including jokes and puns Watson
language including jokes and puns Watson
language including jokes and puns Watson didn’t have access to the Internet
didn’t have access to the Internet
didn’t have access to the Internet instead it use deep learning and some
instead it use deep learning and some
instead it use deep learning and some downloaded data to sort through the
downloaded data to sort through the
downloaded data to sort through the clues using after it learned this
clues using after it learned this
clues using after it learned this excessive data
excessive data
excessive data Watson displayed its most probable
Watson displayed its most probable
Watson displayed its most probable answer on the game signaling device and
answer on the game signaling device and
answer on the game signaling device and handily beat its human competitors we’re
handily beat its human competitors we’re
handily beat its human competitors we’re now at the point that not only two
now at the point that not only two
now at the point that not only two machines beat the humans at machine-like
machines beat the humans at machine-like
machines beat the humans at machine-like games but machines can beat humans at an
games but machines can beat humans at an
games but machines can beat humans at an inherently human game the machine is
inherently human game the machine is
inherently human game the machine is actually kind of kicking our ass so
let’s talk about some ways where this
let’s talk about some ways where this technology will disrupt our daily life
technology will disrupt our daily life
technology will disrupt our daily life and years to come the self-driving car
and years to come the self-driving car
and years to come the self-driving car is an innovation that science fiction is
is an innovation that science fiction is
is an innovation that science fiction is predicting been predicting for years and
predicting been predicting for years and
predicting been predicting for years and I’ll be the first to tell you it’s not a
I’ll be the first to tell you it’s not a
I’ll be the first to tell you it’s not a matter of if it’s when driving is a
matter of if it’s when driving is a
matter of if it’s when driving is a really arduous and inefficient task for
really arduous and inefficient task for
really arduous and inefficient task for humans to complete it relies on a vast
humans to complete it relies on a vast
humans to complete it relies on a vast amount of human skill judgment and
amount of human skill judgment and
amount of human skill judgment and reflex human mistakes can cause vast
reflex human mistakes can cause vast
reflex human mistakes can cause vast delays and massive injuries
another challenge that the self-driving
another challenge that the self-driving car presents is the determination of a
car presents is the determination of a
car presents is the determination of a hierarchy when you’re driving there are
hierarchy when you’re driving there are
hierarchy when you’re driving there are often situations that arise where you
often situations that arise where you
often situations that arise where you have to make a split-second decision
have to make a split-second decision
have to make a split-second decision deciding what the best move will be for
deciding what the best move will be for
deciding what the best move will be for you next things can happen such as
you next things can happen such as
you next things can happen such as there’s a biker in the road if you
there’s a biker in the road if you
there’s a biker in the road if you swerve to hit it you’ll fall into a
swerve to hit it you’ll fall into a
swerve to hit it you’ll fall into a ditch and possibly injure yourself as a
ditch and possibly injure yourself as a
ditch and possibly injure yourself as a human we make these decisions really
human we make these decisions really
human we make these decisions really quickly and we don’t always make the
quickly and we don’t always make the
quickly and we don’t always make the right one but what is the right decision
right one but what is the right decision
right one but what is the right decision when it comes down to self-driving cars
when it comes down to self-driving cars
when it comes down to self-driving cars that answer will be programmed into the
that answer will be programmed into the
that answer will be programmed into the computer raising a lot of ethical
computer raising a lot of ethical
computer raising a lot of ethical questions unlike chess where there are
questions unlike chess where there are
questions unlike chess where there are rules that everyone follows in driving
rules that everyone follows in driving
rules that everyone follows in driving there are no rules there’s an infinite
there are no rules there’s an infinite
there are no rules there’s an infinite possibility of things that could happen
possibility of things that could happen
possibility of things that could happen an item can follow up a pickup truck a
an item can follow up a pickup truck a
an item can follow up a pickup truck a deer could run out into the road or
deer could run out into the road or
deer could run out into the road or someone could run a red light what’s the
someone could run a red light what’s the
someone could run a red light what’s the best move as we move forward with this
best move as we move forward with this
best move as we move forward with this technology this and many similar
technology this and many similar
technology this and many similar questions we’ll have to find the answer
questions we’ll have to find the answer
questions we’ll have to find the answer to another place where machines can cut
to another place where machines can cut
to another place where machines can cut out human labor is in delivery right now
out human labor is in delivery right now
out human labor is in delivery right now you can have food or items delivered by
you can have food or items delivered by
you can have food or items delivered by a human in a car or on a bike or you
a human in a car or on a bike or you
a human in a car or on a bike or you know any number of other transportation
know any number of other transportation
know any number of other transportation methods depending on where you live but
methods depending on where you live but
methods depending on where you live but in the next few years we’re going to
in the next few years we’re going to
in the next few years we’re going to expect to see drones take over this task
expect to see drones take over this task
expect to see drones take over this task a drone is an artificially intelligent
a drone is an artificially intelligent
a drone is an artificially intelligent robot that can use sensors to create a
robot that can use sensors to create a
robot that can use sensors to create a 3d model of its environment can use then
3d model of its environment can use then
3d model of its environment can use then use a trajectory to navigate through
use a trajectory to navigate through
use a trajectory to navigate through this environment and arrive at its
this environment and arrive at its
this environment and arrive at its destination as drone technology evolves
destination as drone technology evolves
destination as drone technology evolves there will be no needs for humans in
there will be no needs for humans in
there will be no needs for humans in this equation anymore lastly I’m going
this equation anymore lastly I’m going
this equation anymore lastly I’m going to talk about another place where
to talk about another place where
to talk about another place where machine labor can take over humans food
machine labor can take over humans food
machine labor can take over humans food preparation for years robots were able
preparation for years robots were able
preparation for years robots were able to complete any number of repetitive
to complete any number of repetitive
to complete any number of repetitive tasks over and over but when it needs to
tasks over and over but when it needs to
tasks over and over but when it needs to use artificial intelligence is when it
use artificial intelligence is when it
use artificial intelligence is when it needs to create custom made to order
needs to create custom made to order
needs to create custom made to order items like for example start out how to
items like for example start out how to
items like for example start out how to San Francisco momentum machines created
San Francisco momentum machines created
San Francisco momentum machines created a robot that can prepare a custom
a robot that can prepare a custom
a robot that can prepare a custom made-to-order burger at restaurant
made-to-order burger at restaurant
made-to-order burger at restaurant quality with fast food prices and speed
this is a pretty exciting proposition
this is a pretty exciting proposition but it’s not without controversy
co-founder Alexandra Sparta Costa said
co-founder Alexandra Sparta Costa said it himself this machine is not meant to
it himself this machine is not meant to
it himself this machine is not meant to make our employees more efficient it’s
make our employees more efficient it’s
make our employees more efficient it’s meant to completely obvious them we
meant to completely obvious them we
meant to completely obvious them we could debate the ethics of this
could debate the ethics of this
could debate the ethics of this statement ad nauseam and believe me it
statement ad nauseam and believe me it
statement ad nauseam and believe me it will be in the next few years but what
will be in the next few years but what
will be in the next few years but what history has shown us is that when
history has shown us is that when
history has shown us is that when technology can make humans work can make
technology can make humans work can make
technology can make humans work can make Goods be produced faster and cheaper it
Goods be produced faster and cheaper it
Goods be produced faster and cheaper it will prevail Google CEO sundar pichai
will prevail Google CEO sundar pichai
will prevail Google CEO sundar pichai said it himself machine learning is a
said it himself machine learning is a
said it himself machine learning is a core transformative way in which we’re
core transformative way in which we’re
core transformative way in which we’re rethinking everything we’re doing so
rethinking everything we’re doing so
rethinking everything we’re doing so what exactly sets humans apart from
what exactly sets humans apart from
what exactly sets humans apart from machines it’s our ability to think for
machines it’s our ability to think for
machines it’s our ability to think for ourselves to fully and truly understand
ourselves to fully and truly understand
ourselves to fully and truly understand the world around us and to behave
the world around us and to behave
the world around us and to behave rationally and at times irrationally
rationally and at times irrationally
rationally and at times irrationally just as we saw smartphones penetrate the
just as we saw smartphones penetrate the
just as we saw smartphones penetrate the economy and it shift the way we do
economy and it shift the way we do
economy and it shift the way we do business into the on-demand sharing
business into the on-demand sharing
business into the on-demand sharing model we can expect to have see machine
model we can expect to have see machine
model we can expect to have see machine learning have similar results nine years
learning have similar results nine years
learning have similar results nine years ago the iPhone was released where will
ago the iPhone was released where will
ago the iPhone was released where will we be in nine more thank you
”
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