Transforming our Lives Through Robotics | Wyatt Newman | TEDxLugano

[Music]

[Music] we are experiencing a renaissance of

we are experiencing a renaissance of

we are experiencing a renaissance of robotics and artificial intelligence in

robotics and artificial intelligence in

robotics and artificial intelligence in recent years we’ve seen computers drive

recent years we’ve seen computers drive

recent years we’ve seen computers drive our cars and trucks translate and

our cars and trucks translate and

our cars and trucks translate and interpret natural languages and defeat

interpret natural languages and defeat

interpret natural languages and defeat the world’s champions of chess go and

the world’s champions of chess go and

the world’s champions of chess go and jeopardy ibm’s watson is now or soon

jeopardy ibm’s watson is now or soon

jeopardy ibm’s watson is now or soon will be the world’s leading oncology

will be the world’s leading oncology

will be the world’s leading oncology expert and the new AI is fueling the

expert and the new AI is fueling the

expert and the new AI is fueling the robot revolution in my own work i’ve

robot revolution in my own work i’ve

robot revolution in my own work i’ve been able to contribute to this

been able to contribute to this

been able to contribute to this revolution in areas including

revolution in areas including

revolution in areas including manufacturing we’re feeling is required

manufacturing we’re feeling is required

manufacturing we’re feeling is required for a mechanical assembly or grinding

for a mechanical assembly or grinding

for a mechanical assembly or grinding and in autonomous vehicles which will

and in autonomous vehicles which will

and in autonomous vehicles which will soon be commercial products offering us

soon be commercial products offering us

soon be commercial products offering us greater safety and convenience in

greater safety and convenience in

greater safety and convenience in machines that sense and interpret their

machines that sense and interpret their

machines that sense and interpret their environments with applications such as

environments with applications such as

environments with applications such as voice controlled smart wheelchairs and

voice controlled smart wheelchairs and

voice controlled smart wheelchairs and in robotic li assisted minimally

in robotic li assisted minimally

in robotic li assisted minimally invasive surgery with the promise of

invasive surgery with the promise of

invasive surgery with the promise of faster more precise operations with

faster more precise operations with

faster more precise operations with lower trauma and less risk of infection

lower trauma and less risk of infection

lower trauma and less risk of infection as well as service robots such as tour

as well as service robots such as tour

as well as service robots such as tour guides and sentries and in humanoid

guides and sentries and in humanoid

guides and sentries and in humanoid robots that can operate in domestic

robots that can operate in domestic

robots that can operate in domestic environments and can navigate over

environments and can navigate over

environments and can navigate over difficult terrains and can operate

difficult terrains and can operate

difficult terrains and can operate controls like bowels levers switches and

controls like bowels levers switches and

controls like bowels levers switches and buttons or operate power tools designed

buttons or operate power tools designed

buttons or operate power tools designed for humans or behaved as co-workers

for humans or behaved as co-workers

for humans or behaved as co-workers collaborating with humans these results

collaborating with humans these results

collaborating with humans these results from my lab and many others around the

from my lab and many others around the

from my lab and many others around the world are now emerging into new robots

world are now emerging into new robots

world are now emerging into new robots and emerging into our lives of course

and emerging into our lives of course

and emerging into our lives of course there are applications in dull

there are applications in dull

there are applications in dull monotonous and repetitive tasks but

monotonous and repetitive tasks but

monotonous and repetitive tasks but there are also new applications in tasks

there are also new applications in tasks

there are also new applications in tasks that require superhuman strength speed

that require superhuman strength speed

that require superhuman strength speed precision reliability Total Recall or

precision reliability Total Recall or

precision reliability Total Recall or unflinching focus of attention why is

unflinching focus of attention why is

unflinching focus of attention why is this happening why now and how will it

this happening why now and how will it

this happening why now and how will it change our lives as a career robot

change our lives as a career robot

change our lives as a career robot assist I’ve lived through the robot

assist I’ve lived through the robot

assist I’ve lived through the robot depression I used to advise my students

depression I used to advise my students

depression I used to advise my students don’t call yourself a robot assist you

don’t call yourself a robot assist you

don’t call yourself a robot assist you won’t get a job but in recent years I’ve

won’t get a job but in recent years I’ve

won’t get a job but in recent years I’ve seen that turned upside down my students

seen that turned upside down my students

seen that turned upside down my students are getting great jobs specifically for

are getting great jobs specifically for

are getting great jobs specifically for the robotics expertise from my

the robotics expertise from my

the robotics expertise from my perspective this has come about from two

perspective this has come about from two

perspective this has come about from two important changes one

important changes one

important changes one is the evolution of the new AI

is the evolution of the new AI

is the evolution of the new AI specifically deep learning and the

specifically deep learning and the

specifically deep learning and the second is a fundamental change in the

second is a fundamental change in the

second is a fundamental change in the way that we program robots let me first

way that we program robots let me first

way that we program robots let me first give you a little background on deep

give you a little background on deep

give you a little background on deep learning what is it where did it come

learning what is it where did it come

learning what is it where did it come from the foundations of deep learning

from the foundations of deep learning

from the foundations of deep learning come from brain science we all know that

come from brain science we all know that

come from brain science we all know that brains are made up of neurons

brains are made up of neurons

brains are made up of neurons interconnected with synapses and from

interconnected with synapses and from

interconnected with synapses and from there we generate all thought action

there we generate all thought action

there we generate all thought action memories perception emotions feelings

memories perception emotions feelings

memories perception emotions feelings but exactly how this is done has been a

but exactly how this is done has been a

but exactly how this is done has been a long-standing challenge neuroscientists

long-standing challenge neuroscientists

long-standing challenge neuroscientists has studied neurons down to the

has studied neurons down to the

has studied neurons down to the molecular level and we understand in

molecular level and we understand in

molecular level and we understand in detail how they communicate with release

detail how they communicate with release

detail how they communicate with release of neurotransmitters and responsiveness

of neurotransmitters and responsiveness

of neurotransmitters and responsiveness of ion channels scientists have even

of ion channels scientists have even

of ion channels scientists have even demystified the act of learning by

demystified the act of learning by

demystified the act of learning by tagging ion channels and watching their

tagging ion channels and watching their

tagging ion channels and watching their migration through dendrites in an

migration through dendrites in an

migration through dendrites in an installation into synapses this is

installation into synapses this is

installation into synapses this is watching learning under a microscope the

watching learning under a microscope the

watching learning under a microscope the physiological manifestation of learning

physiological manifestation of learning

physiological manifestation of learning a biological change you by listening to

a biological change you by listening to

a biological change you by listening to this talk are biologically changed and

this talk are biologically changed and

this talk are biologically changed and we take our knowledge of these and we

we take our knowledge of these and we

we take our knowledge of these and we wrap them up into mathematical models

wrap them up into mathematical models

wrap them up into mathematical models and we program these into computer

and we program these into computer

and we program these into computer simulations and so neurons are the

simulations and so neurons are the

simulations and so neurons are the building blocks of brains and simulated

building blocks of brains and simulated

building blocks of brains and simulated neurons are the building blocks of the

neurons are the building blocks of the

neurons are the building blocks of the new AI but it’s not enough to understand

new AI but it’s not enough to understand

new AI but it’s not enough to understand how neurons work we have to understand

how neurons work we have to understand

how neurons work we have to understand how they’re interconnected how are their

how they’re interconnected how are their

how they’re interconnected how are their synapses formed and for this we get

synapses formed and for this we get

synapses formed and for this we get knowledge from biology for example the

knowledge from biology for example the

knowledge from biology for example the horseshoe crab the horseshoe crab is an

horseshoe crab the horseshoe crab is an

horseshoe crab the horseshoe crab is an ancient creature with primitive eyes and

ancient creature with primitive eyes and

ancient creature with primitive eyes and scientists have been able to disentangle

scientists have been able to disentangle

scientists have been able to disentangle the axons from their primitive light

the axons from their primitive light

the axons from their primitive light sensors and found that they’re connected

sensors and found that they’re connected

sensors and found that they’re connected in patterns creating the equivalent of

in patterns creating the equivalent of

in patterns creating the equivalent of computing tissue that performs low-level

computing tissue that performs low-level

computing tissue that performs low-level image processing these synapses are not

image processing these synapses are not

image processing these synapses are not an accident or random these are dictated

an accident or random these are dictated

an accident or random these are dictated by the DNA of the creature because these

by the DNA of the creature because these

by the DNA of the creature because these synaptic values perform useful

synaptic values perform useful

synaptic values perform useful computations and we learned more from

computations and we learned more from

computations and we learned more from the Nobel prize-winning work of Hubel

the Nobel prize-winning work of Hubel

the Nobel prize-winning work of Hubel and Wiesel studying the visual cortex of

and Wiesel studying the visual cortex of

and Wiesel studying the visual cortex of the cat they found more of these innate

the cat they found more of these innate

the cat they found more of these innate connections among neurons notably there

connections among neurons notably there

connections among neurons notably there are collections of neurons in the retina

are collections of neurons in the retina

are collections of neurons in the retina that can detect light dark changes like

that can detect light dark changes like

that can detect light dark changes like the horseshoe crab and these bits

the horseshoe crab and these bits

the horseshoe crab and these bits project onto deeper neurons that

project onto deeper neurons that

project onto deeper neurons that assemble these into line segments at

assemble these into line segments at

assemble these into line segments at different displacements and angles and

different displacements and angles and

different displacements and angles and these project onto deep

these project onto deep

these project onto deep so to assemble them into geometric

so to assemble them into geometric

so to assemble them into geometric patterns and so we see not only are

patterns and so we see not only are

patterns and so we see not only are there patterns of connections at

there patterns of connections at

there patterns of connections at synapses but there’s also an

synapses but there’s also an

synapses but there’s also an organization by layers of abstraction so

organization by layers of abstraction so

organization by layers of abstraction so we’ve learned more about how at least

we’ve learned more about how at least

we’ve learned more about how at least ensembles of neurons are connected

ensembles of neurons are connected

ensembles of neurons are connected together but are we ready to build

together but are we ready to build

together but are we ready to build brains maybe we get insight and

brains maybe we get insight and

brains maybe we get insight and inspiration from biologists studying the

inspiration from biologists studying the

inspiration from biologists studying the behavior of creatures an example is the

behavior of creatures an example is the

behavior of creatures an example is the ghost crab the ghost crab has a behavior

ghost crab the ghost crab has a behavior

ghost crab the ghost crab has a behavior in that it lives in a burrow in the sand

in that it lives in a burrow in the sand

in that it lives in a burrow in the sand and emerges periodically to enter the

and emerges periodically to enter the

and emerges periodically to enter the sea if you chase it it runs quickly to

sea if you chase it it runs quickly to

sea if you chase it it runs quickly to the sanctuary of its burrow it appears

the sanctuary of its burrow it appears

the sanctuary of its burrow it appears to have a strong reflex for

to have a strong reflex for

to have a strong reflex for self-preservation and good strategies

self-preservation and good strategies

self-preservation and good strategies for survival but if while the crab is

for survival but if while the crab is

for survival but if while the crab is out you cover its burrow at the metal

out you cover its burrow at the metal

out you cover its burrow at the metal plate and when it really chase it it

plate and when it really chase it it

plate and when it really chase it it runs towards its burrow and it stops on

runs towards its burrow and it stops on

runs towards its burrow and it stops on top of the plate and at this point you

top of the plate and at this point you

top of the plate and at this point you can just walk over and pick it up and so

can just walk over and pick it up and so

can just walk over and pick it up and so although the ghost crab has a biological

although the ghost crab has a biological

although the ghost crab has a biological brain it reveals itself to be

brain it reveals itself to be

brain it reveals itself to be indistinguishable from a robot it has a

indistinguishable from a robot it has a

indistinguishable from a robot it has a program which is normally effective but

program which is normally effective but

program which is normally effective but it has no room for creativity or

it has no room for creativity or

it has no room for creativity or innovation and so we’re embolden to try

innovation and so we’re embolden to try

innovation and so we’re embolden to try to build our primitive brains and we put

to build our primitive brains and we put

to build our primitive brains and we put together what we’ve learned our

together what we’ve learned our

together what we’ve learned our knowledge of neurons in simulations

knowledge of neurons in simulations

knowledge of neurons in simulations patterns of interconnections in synapses

patterns of interconnections in synapses

patterns of interconnections in synapses and layers of abstraction and these form

and layers of abstraction and these form

and layers of abstraction and these form what are called

what are called

what are called deep neural networks now the trick to

deep neural networks now the trick to

deep neural networks now the trick to getting useful computations have it out

getting useful computations have it out

getting useful computations have it out of a deep neural network is to discover

of a deep neural network is to discover

of a deep neural network is to discover good synaptic weights like the horseshoe

good synaptic weights like the horseshoe

good synaptic weights like the horseshoe crab the process of this discovery is

crab the process of this discovery is

crab the process of this discovery is called deep learning now we knew about

called deep learning now we knew about

called deep learning now we knew about many of these discoveries much earlier

many of these discoveries much earlier

many of these discoveries much earlier but they were never successful until

but they were never successful until

but they were never successful until recently and part of the reason is this

recently and part of the reason is this

recently and part of the reason is this discovery of good synaptic values

discovery of good synaptic values

discovery of good synaptic values requires intensive computations and

requires intensive computations and

requires intensive computations and we’ve been helped recently by the

we’ve been helped recently by the

we’ve been helped recently by the emergence of new computing hardware

emergence of new computing hardware

emergence of new computing hardware notably the graphical processing unit or

notably the graphical processing unit or

notably the graphical processing unit or GPU these were originally developed for

GPU these were originally developed for

GPU these were originally developed for computer gaming but they were found to

computer gaming but they were found to

computer gaming but they were found to be effective for the intensive

be effective for the intensive

be effective for the intensive computations for discovery of synapses a

computations for discovery of synapses a

computations for discovery of synapses a second critically important development

second critically important development

second critically important development was the emergence of big data we all

was the emergence of big data we all

was the emergence of big data we all know that companies such as Facebook

know that companies such as Facebook

know that companies such as Facebook Amazon and Google are amassing huge

Amazon and Google are amassing huge

Amazon and Google are amassing huge repositories of labeled information and

repositories of labeled information and

repositories of labeled information and the ease of gathering data over the

the ease of gathering data over the

the ease of gathering data over the Internet

Internet

Internet leads to the creation of new

leads to the creation of new

leads to the creation of new repositories springing up around the

repositories springing up around the

repositories springing up around the world and this is essential for training

world and this is essential for training

world and this is essential for training the new networks because they still

the new networks because they still

the new networks because they still learn very slowly we require both

learn very slowly we require both

learn very slowly we require both intensive computations and literally

intensive computations and literally

intensive computations and literally millions of examples but the results

millions of examples but the results

millions of examples but the results have been stunning now computers can

have been stunning now computers can

have been stunning now computers can interpret images semantically they can

interpret images semantically they can

interpret images semantically they can say that as a pedestrian that is a

say that as a pedestrian that is a

say that as a pedestrian that is a bicyclist that is a car that is my Road

bicyclist that is a car that is my Road

bicyclist that is a car that is my Road and this is necessary for effective

and this is necessary for effective

and this is necessary for effective autonomous vehicles or for robots

autonomous vehicles or for robots

autonomous vehicles or for robots behaving intelligently in factories or

behaving intelligently in factories or

behaving intelligently in factories or in homes applications of deep learning

in homes applications of deep learning

in homes applications of deep learning are springing up everywhere facial

are springing up everywhere facial

are springing up everywhere facial recognition recognition of emotions

recognition recognition of emotions

recognition recognition of emotions interpretation of natural languages even

interpretation of natural languages even

interpretation of natural languages even patent searches and an avalanche of new

patent searches and an avalanche of new

patent searches and an avalanche of new applications on the horizon and these

applications on the horizon and these

applications on the horizon and these dramatically better brains are spurring

dramatically better brains are spurring

dramatically better brains are spurring the rise of the robots the second

the rise of the robots the second

the rise of the robots the second important development for the rise of

important development for the rise of

important development for the rise of robots was a fundamental change in how

robots was a fundamental change in how

robots was a fundamental change in how we program them as built into the robot

we program them as built into the robot

we program them as built into the robot operating system or Ross in my career

operating system or Ross in my career

operating system or Ross in my career I’ve seen decades of robot projects that

I’ve seen decades of robot projects that

I’ve seen decades of robot projects that started from scratch and invested all of

started from scratch and invested all of

started from scratch and invested all of their resources only to recreate results

their resources only to recreate results

their resources only to recreate results of the past we were not building on

of the past we were not building on

of the past we were not building on foundations we were not making progress

foundations we were not making progress

foundations we were not making progress by reinventing the wheel we’re not

by reinventing the wheel we’re not

by reinventing the wheel we’re not protecting our advances and reusing them

protecting our advances and reusing them

protecting our advances and reusing them at integrating them with others and Ross

at integrating them with others and Ross

at integrating them with others and Ross has changed all of this by bringing

has changed all of this by bringing

has changed all of this by bringing modern software engineering techniques

modern software engineering techniques

modern software engineering techniques to robots ross was innovated at

to robots ross was innovated at

to robots ross was innovated at Stanford’s artificial intelligence lab

Stanford’s artificial intelligence lab

Stanford’s artificial intelligence lab and was nurtured for nine years by

and was nurtured for nine years by

and was nurtured for nine years by Google and it’s now emerged as the de

Google and it’s now emerged as the de

Google and it’s now emerged as the de facto standard robot programming

facto standard robot programming

facto standard robot programming environment around the world I was not a

environment around the world I was not a

environment around the world I was not a founder of Ross but I am a convert I’m a

founder of Ross but I am a convert I’m a

founder of Ross but I am a convert I’m a user a contributor a teacher an

user a contributor a teacher an

user a contributor a teacher an evangelist most recently I’ve also

evangelist most recently I’ve also

evangelist most recently I’ve also written a textbook in pursuit of my

written a textbook in pursuit of my

written a textbook in pursuit of my desire to train and recruit the next

desire to train and recruit the next

desire to train and recruit the next generation of robot assists the number

generation of robot assists the number

generation of robot assists the number of robots the variety of robots using

of robots the variety of robots using

of robots the variety of robots using Ross is exploding old robots are being

Ross is exploding old robots are being

Ross is exploding old robots are being converted to Ross new robots are born

converted to Ross new robots are born

converted to Ross new robots are born with Ross the existence of Ross has led

with Ross the existence of Ross has led

with Ross the existence of Ross has led to the creation of new robot startup

to the creation of new robot startup

to the creation of new robot startup companies and Ross has spread throughout

companies and Ross has spread throughout

companies and Ross has spread throughout the world in academia in industry in

the world in academia in industry in

the world in academia in industry in research labs and now we’re seeing

research labs and now we’re seeing

research labs and now we’re seeing experts in Tokyo in Edinburgh in

experts in Tokyo in Edinburgh in

experts in Tokyo in Edinburgh in Cleveland who

Cleveland who

Cleveland who contributing their expertise in modules

contributing their expertise in modules

contributing their expertise in modules like Lego blocks that can be assembled

like Lego blocks that can be assembled

like Lego blocks that can be assembled in new novel systems in California in

in new novel systems in California in

in new novel systems in California in Australia and in China and for the first

Australia and in China and for the first

Australia and in China and for the first time we’re able to create robots that

time we’re able to create robots that

time we’re able to create robots that are more sophisticated than any one

are more sophisticated than any one

are more sophisticated than any one person or anyone research group could do

person or anyone research group could do

person or anyone research group could do in a lifetime

in a lifetime

in a lifetime dramatically better robots are coming

dramatically better robots are coming

dramatically better robots are coming out and we can expect dramatic changes

out and we can expect dramatic changes

out and we can expect dramatic changes in our life one of the things we expect

in our life one of the things we expect

in our life one of the things we expect will make a difference is jobs a recent

will make a difference is jobs a recent

will make a difference is jobs a recent McKinsey study estimated that half of

McKinsey study estimated that half of

McKinsey study estimated that half of all human labor can be replaced by a

all human labor can be replaced by a

all human labor can be replaced by a robot or machine enabled with artificial

robot or machine enabled with artificial

robot or machine enabled with artificial intelligence they also identified over

intelligence they also identified over

intelligence they also identified over 70 professions in which 90% of human

70 professions in which 90% of human

70 professions in which 90% of human content can be eliminated ranging from

content can be eliminated ranging from

content can be eliminated ranging from stock pickers to truck drivers a recent

stock pickers to truck drivers a recent

stock pickers to truck drivers a recent study showed that loss of manufacturing

study showed that loss of manufacturing

study showed that loss of manufacturing jobs in the United States was

jobs in the United States was

jobs in the United States was attributable to automation not

attributable to automation not

attributable to automation not outsourcing robots are taking our

outsourcing robots are taking our

outsourcing robots are taking our manufacturing jobs and it’s not just in

manufacturing jobs and it’s not just in

manufacturing jobs and it’s not just in manufacturing it’s across the spectrum

manufacturing it’s across the spectrum

manufacturing it’s across the spectrum for example in logistics like Amazon

for example in logistics like Amazon

for example in logistics like Amazon automated distribution centers or in

automated distribution centers or in

automated distribution centers or in design with 3d printers in home

design with 3d printers in home

design with 3d printers in home automation in security and defense

automation in security and defense

automation in security and defense agriculture and food health care energy

agriculture and food health care energy

agriculture and food health care energy Elon Musk warns that there will be fewer

Elon Musk warns that there will be fewer

Elon Musk warns that there will be fewer and fewer jobs that a robot cannot do

and fewer jobs that a robot cannot do

and fewer jobs that a robot cannot do better than he human and Stephen Hawking

better than he human and Stephen Hawking

better than he human and Stephen Hawking worries that there will only be jobs for

worries that there will only be jobs for

worries that there will only be jobs for the most exceptional humans but

the most exceptional humans but

the most exceptional humans but throughout modern history has been

throughout modern history has been

throughout modern history has been predicted the technological advances

predicted the technological advances

predicted the technological advances would lead to massive job layoffs and

would lead to massive job layoffs and

would lead to massive job layoffs and historically this has not been true and

historically this has not been true and

historically this has not been true and the 1800s the Luddites protested

the 1800s the Luddites protested

the 1800s the Luddites protested automation in the textile industry by

automation in the textile industry by

automation in the textile industry by smashing weaving machines but ultimately

smashing weaving machines but ultimately

smashing weaving machines but ultimately these machines increased employment in

these machines increased employment in

these machines increased employment in the industry and increased wages overall

the industry and increased wages overall

the industry and increased wages overall the Industrial Revolution elevated the

the Industrial Revolution elevated the

the Industrial Revolution elevated the lives of the common worker in the 20th

lives of the common worker in the 20th

lives of the common worker in the 20th century United States we began with 40%

century United States we began with 40%

century United States we began with 40% of our workforce involved in farming and

of our workforce involved in farming and

of our workforce involved in farming and with introduction of technology this

with introduction of technology this

with introduction of technology this fell to 2% by the end of the century but

fell to 2% by the end of the century but

fell to 2% by the end of the century but there was not a massive jobs collapse

there was not a massive jobs collapse

there was not a massive jobs collapse instead there was jobs growth there was

instead there was jobs growth there was

instead there was jobs growth there was wealth increases we largely moved into

wealth increases we largely moved into

wealth increases we largely moved into manufacturing including in sectors that

manufacturing including in sectors that

manufacturing including in sectors that had been undreamed-of in the past and

had been undreamed-of in the past and

had been undreamed-of in the past and the introduction of computer into

the introduction of computer into

the introduction of computer into business was predicted to lead to

business was predicted to lead to

business was predicted to lead to massively

massively

massively and certainly businesses became more

and certainly businesses became more

and certainly businesses became more efficient but there were not massive

efficient but there were not massive

efficient but there were not massive layoffs there was increase in employment

layoffs there was increase in employment

layoffs there was increase in employment and increased salaries today you can’t

and increased salaries today you can’t

and increased salaries today you can’t run a business without a computer and

run a business without a computer and

run a business without a computer and the existence of the computer is made

the existence of the computer is made

the existence of the computer is made startups easier and as we lost our

startups easier and as we lost our

startups easier and as we lost our manufacturing jobs we gained new jobs in

manufacturing jobs we gained new jobs in

manufacturing jobs we gained new jobs in the service sector to a large extent we

the service sector to a large extent we

the service sector to a large extent we gave up dull dirty and dangerous

gave up dull dirty and dangerous

gave up dull dirty and dangerous manufacturing jobs for knowledge workers

manufacturing jobs for knowledge workers

manufacturing jobs for knowledge workers and so we have reason to believe there

and so we have reason to believe there

and so we have reason to believe there will not be a robot apocalypse but a

will not be a robot apocalypse but a

will not be a robot apocalypse but a robot utopia a world where robots do all

robot utopia a world where robots do all

robot utopia a world where robots do all of the dirty dull and dangerous work for

of the dirty dull and dangerous work for

of the dirty dull and dangerous work for us and that humans working together with

us and that humans working together with

us and that humans working together with robots increase the value of human

robots increase the value of human

robots increase the value of human labour increased productivity and

labour increased productivity and

labour increased productivity and increased wealth and we will still need

increased wealth and we will still need

increased wealth and we will still need doctors therapists poets writers

doctors therapists poets writers

doctors therapists poets writers researchers teachers musicians composers

researchers teachers musicians composers

researchers teachers musicians composers comedians actors athletes dancers and

comedians actors athletes dancers and

comedians actors athletes dancers and artists and countless others who elevate

artists and countless others who elevate

artists and countless others who elevate and enrich our lives that we can expect

and enrich our lives that we can expect

and enrich our lives that we can expect with our newfound wealth we’ll be able

with our newfound wealth we’ll be able

with our newfound wealth we’ll be able to enjoy these arts and entertainment

to enjoy these arts and entertainment

to enjoy these arts and entertainment and travel and leisure robots will

and travel and leisure robots will

and travel and leisure robots will become our laborers and also our

become our laborers and also our

become our laborers and also our assistants and our advisors our servants

assistants and our advisors our servants

assistants and our advisors our servants and our Guardians

and our Guardians

and our Guardians and our companions robots will become

and our companions robots will become

and our companions robots will become commonplace and indispensable in our

commonplace and indispensable in our

commonplace and indispensable in our lives and this will give birth to a new

lives and this will give birth to a new

lives and this will give birth to a new basic industry and generate millions of

basic industry and generate millions of

basic industry and generate millions of jobs involved in the creation of ever

jobs involved in the creation of ever

jobs involved in the creation of ever more capable machines tomorrow’s robot

more capable machines tomorrow’s robot

more capable machines tomorrow’s robot assists will face a fundamental grand

assists will face a fundamental grand

assists will face a fundamental grand challenge to create robots in our image

challenge to create robots in our image

challenge to create robots in our image but that ultimately surpass human

but that ultimately surpass human

but that ultimately surpass human strength speed precision intelligence

strength speed precision intelligence

strength speed precision intelligence and most importantly compassion and

and most importantly compassion and

and most importantly compassion and ethics addressing this grand challenge

ethics addressing this grand challenge

ethics addressing this grand challenge will require a collaboration among

will require a collaboration among

will require a collaboration among contributors with greater

contributors with greater

contributors with greater multidisciplinary breadth than any time

multidisciplinary breadth than any time

multidisciplinary breadth than any time in history of course we’ll need more

in history of course we’ll need more

in history of course we’ll need more engineers and computer scientists but

engineers and computer scientists but

engineers and computer scientists but we’ll also need philosophers linguists

we’ll also need philosophers linguists

we’ll also need philosophers linguists psychologists psychiatrists neuro

psychologists psychiatrists neuro

psychologists psychiatrists neuro scientists biologists skill experts and

scientists biologists skill experts and

scientists biologists skill experts and countless more knowledge workers the

countless more knowledge workers the

countless more knowledge workers the result of this grand challenge will be a

result of this grand challenge will be a

result of this grand challenge will be a transformational elevation of human life

transformational elevation of human life

transformational elevation of human life and so yes the robot revolution is here

and so yes the robot revolution is here

and so yes the robot revolution is here but it’s not to be feared but to be

but it’s not to be feared but to be

but it’s not to be feared but to be embraced as our hope for the future

embraced as our hope for the future

embraced as our hope for the future thank you

thank you

thank you [Applause]