Artificial Intelligence: Investing in Yourself | Upamanyu Ghose | TEDxHRCollege

so when I say AI what’s the first thing

so when I say AI what’s the first thing that comes to your mind

that comes to your mind

that comes to your mind Terminator iRobot any of those

Terminator iRobot any of those

Terminator iRobot any of those science-fiction movies and humanoid

science-fiction movies and humanoid

science-fiction movies and humanoid robots maybe well if it did that’s

robots maybe well if it did that’s

robots maybe well if it did that’s actually not too far from what I thought

actually not too far from what I thought

actually not too far from what I thought if AI when I joined college about

if AI when I joined college about

if AI when I joined college about two-and-a-half years ago so at that time

two-and-a-half years ago so at that time

two-and-a-half years ago so at that time I had this amazing dream that I’m going

I had this amazing dream that I’m going

I had this amazing dream that I’m going to make a perfect robot of perfect AI

to make a perfect robot of perfect AI

to make a perfect robot of perfect AI that can be just like any of you or me

that can be just like any of you or me

that can be just like any of you or me so it could be standing here giving the

so it could be standing here giving the

so it could be standing here giving the speech and you wouldn’t even know it but

speech and you wouldn’t even know it but

speech and you wouldn’t even know it but well you could save my understanding of

well you could save my understanding of

well you could save my understanding of AI was fairly limited to the movies I

AI was fairly limited to the movies I

AI was fairly limited to the movies I was watching at that time but if you

was watching at that time but if you

was watching at that time but if you don’t think of any of these movies

don’t think of any of these movies

don’t think of any of these movies that’s actually great because you’re

that’s actually great because you’re

that’s actually great because you’re already where I stand today and that’s

already where I stand today and that’s

already where I stand today and that’s after I’ve worked in the field for about

after I’ve worked in the field for about

after I’ve worked in the field for about a year so if it’s not what the science

a year so if it’s not what the science

a year so if it’s not what the science fiction movies show us then what is AI

fiction movies show us then what is AI

fiction movies show us then what is AI most of us use AI literally all the time

most of us use AI literally all the time

most of us use AI literally all the time interestingly though many of us are

interestingly though many of us are

interestingly though many of us are actually unaware that we’re interacting

actually unaware that we’re interacting

actually unaware that we’re interacting with it but if you think about it that

with it but if you think about it that

with it but if you think about it that is the point

is the point

is the point an AI is any algorithm or machine that’s

an AI is any algorithm or machine that’s

an AI is any algorithm or machine that’s designed to do a particular task but

designed to do a particular task but

designed to do a particular task but without letting us know that it’s a

without letting us know that it’s a

without letting us know that it’s a machine that’s calling the shots so if

machine that’s calling the shots so if

machine that’s calling the shots so if you’ve ever done a Google search or use

you’ve ever done a Google search or use

you’ve ever done a Google search or use Netflix movie suggestions or let’s say

Netflix movie suggestions or let’s say

Netflix movie suggestions or let’s say city on your iPhone for that matter

city on your iPhone for that matter

city on your iPhone for that matter you’ve already interacted with an AI yes

you’ve already interacted with an AI yes

you’ve already interacted with an AI yes agree it is more visible in larger

agree it is more visible in larger

agree it is more visible in larger machines like self-driven cars or

machines like self-driven cars or

machines like self-driven cars or automated industrial robots but we see

automated industrial robots but we see

automated industrial robots but we see that AI is actually not limited to just

that AI is actually not limited to just

that AI is actually not limited to just the movies it’s got a wide range and a

the movies it’s got a wide range and a

the movies it’s got a wide range and a wide range of applications so back at

wide range of applications so back at

wide range of applications so back at college I was part of a team called

college I was part of a team called

college I was part of a team called Project – and we were a bunch of

Project – and we were a bunch of

Project – and we were a bunch of undergrads really trying hard to get

undergrads really trying hard to get

undergrads really trying hard to get cars to drive themselves and not crash

cars to drive themselves and not crash

cars to drive themselves and not crash of course so we’re taking part in the

of course so we’re taking part in the

of course so we’re taking part in the challenge organized by Mahindra to build

challenge organized by Mahindra to build

challenge organized by Mahindra to build India’s first self-driving car and I was

India’s first self-driving car and I was

India’s first self-driving car and I was part of the AI division and

part of the AI division and

part of the AI division and my job was to make the car perceive the

my job was to make the car perceive the

my job was to make the car perceive the environment like a human so I’d like to

environment like a human so I’d like to

environment like a human so I’d like to share a small incident from back this

share a small incident from back this

share a small incident from back this summer when I was working over there so

summer when I was working over there so

summer when I was working over there so quick fact about me I did not know how

quick fact about me I did not know how

quick fact about me I did not know how to ride a cycle till this summer so for

to ride a cycle till this summer so for

to ride a cycle till this summer so for 20 years I’ve been doing nothing and so

20 years I’ve been doing nothing and so

20 years I’ve been doing nothing and so I finally decided okay enough is enough

I finally decided okay enough is enough

I finally decided okay enough is enough it’s high time I learned cycling I can’t

it’s high time I learned cycling I can’t

it’s high time I learned cycling I can’t have people laughing at me anymore so I

have people laughing at me anymore so I

have people laughing at me anymore so I borrowed my friends cycle and I told him

borrowed my friends cycle and I told him

borrowed my friends cycle and I told him you know teach me you really need to

you know teach me you really need to

you know teach me you really need to teach me right now

teach me right now

teach me right now so he told me some things namely I okay

so he told me some things namely I okay

so he told me some things namely I okay whatever because I was thinking okay

whatever because I was thinking okay

whatever because I was thinking okay this stuff seems simple I mean I’m

this stuff seems simple I mean I’m

this stuff seems simple I mean I’m working in the lab trying to make a car

working in the lab trying to make a car

working in the lab trying to make a car see like a human so what is this task

see like a human so what is this task

see like a human so what is this task but I learned the hard way that it

but I learned the hard way that it

but I learned the hard way that it actually wasn’t so several failures I

actually wasn’t so several failures I

actually wasn’t so several failures I injured my toe severely and I only

injured my toe severely and I only

injured my toe severely and I only learned small paths

learned small paths

learned small paths I was absolutely unable to apply them

I was absolutely unable to apply them

I was absolutely unable to apply them together so I just couldn’t cycle but

together so I just couldn’t cycle but

together so I just couldn’t cycle but after an hour or so I actually started

after an hour or so I actually started

after an hour or so I actually started cycling and at that point in the lab I

cycling and at that point in the lab I

cycling and at that point in the lab I was working on a few AI algorithms now

was working on a few AI algorithms now

was working on a few AI algorithms now when we use these algorithms when we

when we use these algorithms when we

when we use these algorithms when we train them we use something known as a

train them we use something known as a

train them we use something known as a loss function now it’s similar it’s very

loss function now it’s similar it’s very

loss function now it’s similar it’s very very simple to understand

very simple to understand

very simple to understand so as the loss decreases you realize

so as the loss decreases you realize

so as the loss decreases you realize that the machine is learning when the

that the machine is learning when the

that the machine is learning when the loss falls below a certain threshold you

loss falls below a certain threshold you

loss falls below a certain threshold you realize that okay now it’s started doing

realize that okay now it’s started doing

realize that okay now it’s started doing what it’s intended to and I thought to

what it’s intended to and I thought to

what it’s intended to and I thought to myself you know the way I learned

myself you know the way I learned

myself you know the way I learned cycling is actually quite similar to the

cycling is actually quite similar to the

cycling is actually quite similar to the way I’m training these algorithms so

way I’m training these algorithms so

way I’m training these algorithms so after a lot of thinking I came to the

after a lot of thinking I came to the

after a lot of thinking I came to the conclusion that you know maybe AI can be

conclusion that you know maybe AI can be

conclusion that you know maybe AI can be used to understand the human brain and

used to understand the human brain and

used to understand the human brain and that is exactly what I wish to share

that is exactly what I wish to share

that is exactly what I wish to share with you today so our brain is made up

with you today so our brain is made up

with you today so our brain is made up of these cells called neurons and they

of these cells called neurons and they

of these cells called neurons and they have hundreds of billions of them now

have hundreds of billions of them now

have hundreds of billions of them now these neurons are connected to each

these neurons are connected to each

these neurons are connected to each other and the form of a complex network

other and the form of a complex network

other and the form of a complex network in the brain they receive input from

in the brain they receive input from

in the brain they receive input from organs like our eyes in yours and this

organs like our eyes in yours and this

organs like our eyes in yours and this could be anything so in a mid seen by

could be anything so in a mid seen by

could be anything so in a mid seen by the eye a sound heard by the earth or

the eye a sound heard by the earth or

the eye a sound heard by the earth or anything else now each neuron processes

anything else now each neuron processes

anything else now each neuron processes the information in a certain way and

the information in a certain way and

the information in a certain way and passes it on to the other new

passes it on to the other new

passes it on to the other new that it’s connected to now when we learn

that it’s connected to now when we learn

that it’s connected to now when we learn something there are some noodle

something there are some noodle

something there are some noodle connections that are created in the

connections that are created in the

connections that are created in the brain and as we practice it or do

brain and as we practice it or do

brain and as we practice it or do something repeatedly these connections

something repeatedly these connections

something repeatedly these connections some of them are broken some are made

some of them are broken some are made

some of them are broken some are made stronger and new connections are created

stronger and new connections are created

stronger and new connections are created so basically what I mean is when the

so basically what I mean is when the

so basically what I mean is when the brain learns to do anything it simply

brain learns to do anything it simply

brain learns to do anything it simply creates connections between neurons

creates connections between neurons

creates connections between neurons passes messages between them and that’s

passes messages between them and that’s

passes messages between them and that’s how it learns now the root of AI is

how it learns now the root of AI is

how it learns now the root of AI is something known as the artificial neural

something known as the artificial neural

something known as the artificial neural network it is inspired by the brain and

network it is inspired by the brain and

network it is inspired by the brain and hence works very similarly so it’s

hence works very similarly so it’s

hence works very similarly so it’s simply multiple layers of neurons

simply multiple layers of neurons

simply multiple layers of neurons connected to each other you give it the

connected to each other you give it the

connected to each other you give it the input from one side so this could again

input from one side so this could again

input from one side so this could again be imaged text whatever input it may be

be imaged text whatever input it may be

be imaged text whatever input it may be each of the neurons process them in a

each of the neurons process them in a

each of the neurons process them in a certain manner and you get the output

certain manner and you get the output

certain manner and you get the output from the last layer now just like we

from the last layer now just like we

from the last layer now just like we learn by experience so we do something

learn by experience so we do something

learn by experience so we do something repeatedly and then become good at it we

repeatedly and then become good at it we

repeatedly and then become good at it we train these networks similarly we train

train these networks similarly we train

train these networks similarly we train them repeatedly on thousands of data

them repeatedly on thousands of data

them repeatedly on thousands of data items to actually make them good at what

items to actually make them good at what

items to actually make them good at what they’re doing essentially strengthening

they’re doing essentially strengthening

they’re doing essentially strengthening the neural connections so if you think

the neural connections so if you think

the neural connections so if you think about it the fundamentals of AI systems

about it the fundamentals of AI systems

about it the fundamentals of AI systems and the brain are actually very similar

and the brain are actually very similar

and the brain are actually very similar but let’s take an example to get a

but let’s take an example to get a

but let’s take an example to get a clearer understanding so when you see

clearer understanding so when you see

clearer understanding so when you see this picture I’m sure most of us can

this picture I’m sure most of us can

this picture I’m sure most of us can recognize it as Jim Carrey now why do we

recognize it as Jim Carrey now why do we

recognize it as Jim Carrey now why do we do this how is it working in the brain

do this how is it working in the brain

do this how is it working in the brain so when the image from when this image

so when the image from when this image

so when the image from when this image first reaches our eye it’s broken up

first reaches our eye it’s broken up

first reaches our eye it’s broken up into several pieces and we’ve got these

into several pieces and we’ve got these

into several pieces and we’ve got these things known as receptors in the eye

things known as receptors in the eye

things known as receptors in the eye which do some sort of processing on them

which do some sort of processing on them

which do some sort of processing on them now this processing could be something

now this processing could be something

now this processing could be something as simple as finding the most important

as simple as finding the most important

as simple as finding the most important edges in the image and essentially they

edges in the image and essentially they

edges in the image and essentially they create a representation from what they

create a representation from what they

create a representation from what they find it could look something like this

find it could look something like this

find it could look something like this now this information is passed into the

now this information is passed into the

now this information is passed into the neural connections that I mentioned

neural connections that I mentioned

neural connections that I mentioned earlier and they try to make sense of

earlier and they try to make sense of

earlier and they try to make sense of the information that they are supplied

the information that they are supplied

the information that they are supplied to ultimately they come up with the

to ultimately they come up with the

to ultimately they come up with the result now since we have seen Jim Carrey

result now since we have seen Jim Carrey

result now since we have seen Jim Carrey before these noodle connections already

before these noodle connections already

before these noodle connections already exist in our brain

exist in our brain

exist in our brain they’ve already been created before so

they’ve already been created before so

they’ve already been created before so essentially when we see this picture we

essentially when we see this picture we

essentially when we see this picture we are only you

are only you

are only you lysing the connections to actually come

lysing the connections to actually come

lysing the connections to actually come to the conclusion that yeah is Jim

to the conclusion that yeah is Jim

to the conclusion that yeah is Jim Carrey in the picture now AI systems

Carrey in the picture now AI systems

Carrey in the picture now AI systems actually work very similarly we use

actually work very similarly we use

actually work very similarly we use something known as the convolutional

something known as the convolutional

something known as the convolutional neural network or CNN in short it’s

neural network or CNN in short it’s

neural network or CNN in short it’s something like this now as you can see

something like this now as you can see

something like this now as you can see from the animation it uses a sort of a

from the animation it uses a sort of a

from the animation it uses a sort of a sliding window so you can consider the

sliding window so you can consider the

sliding window so you can consider the blue as the original image and the green

blue as the original image and the green

blue as the original image and the green as a representation created by the CNN

as a representation created by the CNN

as a representation created by the CNN so essentially if you think about it

so essentially if you think about it

so essentially if you think about it when this window is sliding it’s

when this window is sliding it’s

when this window is sliding it’s actually focusing on small parts of the

actually focusing on small parts of the

actually focusing on small parts of the image so it’s sort of breaking it up

image so it’s sort of breaking it up

image so it’s sort of breaking it up into small parts just like the eye does

into small parts just like the eye does

into small parts just like the eye does it and then it processes these various

it and then it processes these various

it and then it processes these various parts to actually come up with some

parts to actually come up with some

parts to actually come up with some valuable information now this is the

valuable information now this is the

valuable information now this is the first layer the output of the first

first layer the output of the first

first layer the output of the first layer of a CNN and something that I

layer of a CNN and something that I

layer of a CNN and something that I design the network does a very simple

design the network does a very simple

design the network does a very simple task it’s just supposed to identify if

task it’s just supposed to identify if

task it’s just supposed to identify if Jim Carrey is there in a picture or not

Jim Carrey is there in a picture or not

Jim Carrey is there in a picture or not and as you see from this representation

and as you see from this representation

and as you see from this representation although it might not exactly match in

although it might not exactly match in

although it might not exactly match in the representation in case of di both

the representation in case of di both

the representation in case of di both the systems follow fundamentally the

the systems follow fundamentally the

the systems follow fundamentally the same rule your first breaking it up into

same rule your first breaking it up into

same rule your first breaking it up into small parts then you’re processing them

small parts then you’re processing them

small parts then you’re processing them creating representations and encoding

creating representations and encoding

creating representations and encoding them with various information and

them with various information and

them with various information and finally trying to make sense of this so

finally trying to make sense of this so

finally trying to make sense of this so till now what I explained were examples

till now what I explained were examples

till now what I explained were examples of how AI was inspired by the brain so

of how AI was inspired by the brain so

of how AI was inspired by the brain so now that we’ve established the

now that we’ve established the

now that we’ve established the similarity between the two let’s dive

similarity between the two let’s dive

similarity between the two let’s dive into the actual interesting part that’s

into the actual interesting part that’s

into the actual interesting part that’s how a I can be used to decode the brain

how a I can be used to decode the brain

how a I can be used to decode the brain so today we use MRI scans to actually

so today we use MRI scans to actually

so today we use MRI scans to actually understand a lot about the brain and

understand a lot about the brain and

understand a lot about the brain and doctors and neuroscientists all over the

doctors and neuroscientists all over the

doctors and neuroscientists all over the world are using this this method to

world are using this this method to

world are using this this method to actually find out various things

actually find out various things

actually find out various things one example is something known as the

one example is something known as the

one example is something known as the brain age now the brain age is

brain age now the brain age is

brain age now the brain age is essentially just the level of maturity

essentially just the level of maturity

essentially just the level of maturity that your brain has reached and this can

that your brain has reached and this can

that your brain has reached and this can often differ from your actual physical

often differ from your actual physical

often differ from your actual physical age and that is essential because the

age and that is essential because the

age and that is essential because the difference between the brain age and

difference between the brain age and

difference between the brain age and your physical age can actually explain

your physical age can actually explain

your physical age can actually explain the onset of several medical conditions

the onset of several medical conditions

the onset of several medical conditions in the brain

in the brain

in the brain like dementia so I was recently reading

like dementia so I was recently reading

like dementia so I was recently reading a research paper on this and I’d like to

a research paper on this and I’d like to

a research paper on this and I’d like to share its findings with you

share its findings with you

share its findings with you so traditionally if you analyze these

so traditionally if you analyze these

so traditionally if you analyze these scans they need to be first pre

scans they need to be first pre

scans they need to be first pre processed very heavily and when I say

processed very heavily and when I say

processed very heavily and when I say pre process I mean remove all non brain

pre process I mean remove all non brain

pre process I mean remove all non brain tissue so we can focus just on the brain

tissue so we can focus just on the brain

tissue so we can focus just on the brain then they are analyzed by scientists

then they are analyzed by scientists

then they are analyzed by scientists neuroscientists doctors and we finally

neuroscientists doctors and we finally

neuroscientists doctors and we finally arrive at a result but with the advent

arrive at a result but with the advent

arrive at a result but with the advent of AI there’s actually a simpler method

of AI there’s actually a simpler method

of AI there’s actually a simpler method so you just take the raw scan throw it

so you just take the raw scan throw it

so you just take the raw scan throw it into an artificial neural network and

into an artificial neural network and

into an artificial neural network and you get the same result and the main

you get the same result and the main

you get the same result and the main point to be noted here is the first

point to be noted here is the first

point to be noted here is the first method takes about 24 hours the AI

method takes about 24 hours the AI

method takes about 24 hours the AI method takes a few seconds so

method takes a few seconds so

method takes a few seconds so essentially if you see what’s happening

essentially if you see what’s happening

essentially if you see what’s happening over here is AI is enabling us to easily

over here is AI is enabling us to easily

over here is AI is enabling us to easily extract information from the brain not

extract information from the brain not

extract information from the brain not go into all that hassle ultimately come

go into all that hassle ultimately come

go into all that hassle ultimately come up with the same result and allowing us

up with the same result and allowing us

up with the same result and allowing us to focus on more important problems like

to focus on more important problems like

to focus on more important problems like understanding the brain another

understanding the brain another

understanding the brain another interesting use of AI can be understood

interesting use of AI can be understood

interesting use of AI can be understood by considering the work of a

by considering the work of a

by considering the work of a psychologist so what is he doing he’s

psychologist so what is he doing he’s

psychologist so what is he doing he’s using AI to create a model of the brain

using AI to create a model of the brain

using AI to create a model of the brain he’s teaching this model how to read and

he’s teaching this model how to read and

he’s teaching this model how to read and what he intends to do is learn from the

what he intends to do is learn from the

what he intends to do is learn from the model how it is understanding the

model how it is understanding the

model how it is understanding the various characters making sense out of

various characters making sense out of

various characters making sense out of it and use this finding on people who

it and use this finding on people who

it and use this finding on people who have dyslexia so essentially he’s trying

have dyslexia so essentially he’s trying

have dyslexia so essentially he’s trying to solve the problem in humans by doing

to solve the problem in humans by doing

to solve the problem in humans by doing experiments on an AI model and this can

experiments on an AI model and this can

experiments on an AI model and this can be applied to any field what I mean is

be applied to any field what I mean is

be applied to any field what I mean is AI can be used as a modeling tool for

AI can be used as a modeling tool for

AI can be used as a modeling tool for the brain and we can conduct our own

the brain and we can conduct our own

the brain and we can conduct our own experiments to find out the various

experiments to find out the various

experiments to find out the various problems that occur now I come to the

problems that occur now I come to the

problems that occur now I come to the most exciting example of AI actually

most exciting example of AI actually

most exciting example of AI actually helping human brain development and that

helping human brain development and that

helping human brain development and that is an algorithm called alphago alphago

is an algorithm called alphago alphago

is an algorithm called alphago alphago was an algorithm designed by a company

was an algorithm designed by a company

was an algorithm designed by a company called deep mind now this was designed

called deep mind now this was designed

called deep mind now this was designed to play the game of Go Go is a very very

to play the game of Go Go is a very very

to play the game of Go Go is a very very complex Chinese board game now when I

complex Chinese board game now when I

complex Chinese board game now when I say complex I mean at any point of time

say complex I mean at any point of time

say complex I mean at any point of time it has more number of legal

it has more number of legal

it has more number of legal than the number of atoms in the universe

than the number of atoms in the universe

than the number of atoms in the universe so if the universe has about 10 to the

so if the universe has about 10 to the

so if the universe has about 10 to the power of 8 the atoms which is 1 followed

power of 8 the atoms which is 1 followed

power of 8 the atoms which is 1 followed by 80 zeroes go at any point of time has

by 80 zeroes go at any point of time has

by 80 zeroes go at any point of time has a maximum of 10 to the power of 10,000

a maximum of 10 to the power of 10,000

a maximum of 10 to the power of 10,000 170 moves which is 1 followed by 10,000

170 moves which is 1 followed by 10,000

170 moves which is 1 followed by 10,000 170 zeroes so I’m sure we understand why

170 zeroes so I’m sure we understand why

170 zeroes so I’m sure we understand why it’s going to be unreasonable to design

it’s going to be unreasonable to design

it’s going to be unreasonable to design an algorithm that will try out all

an algorithm that will try out all

an algorithm that will try out all possible moves and then pick the best

possible moves and then pick the best

possible moves and then pick the best out of it

out of it

out of it hence deepmind designed alphago to play

hence deepmind designed alphago to play

hence deepmind designed alphago to play just like a human and that is very

just like a human and that is very

just like a human and that is very essential because now that it works like

essential because now that it works like

essential because now that it works like a human we can actually analyze the

a human we can actually analyze the

a human we can actually analyze the decision pathways to understand how

decision pathways to understand how

decision pathways to understand how decision-making goes on in our own

decision-making goes on in our own

decision-making goes on in our own brains now when this algorithm was put

brains now when this algorithm was put

brains now when this algorithm was put up against the world champion lee sedol

up against the world champion lee sedol

up against the world champion lee sedol it beat him four out of five times in

it beat him four out of five times in

it beat him four out of five times in fact in one of the games in the 37th

fact in one of the games in the 37th

fact in one of the games in the 37th move that was played by alphago it

move that was played by alphago it

move that was played by alphago it completely baffled lee and he had no

completely baffled lee and he had no

completely baffled lee and he had no idea what to do however let’s focus on

idea what to do however let’s focus on

idea what to do however let’s focus on the one game that lee actually won so in

the one game that lee actually won so in

the one game that lee actually won so in this game in the 78th move lee played

this game in the 78th move lee played

this game in the 78th move lee played such a move that he in turn confused

such a move that he in turn confused

such a move that he in turn confused alphago and mind you he confused an AI

alphago and mind you he confused an AI

alphago and mind you he confused an AI algorithm which is a great

algorithm which is a great

algorithm which is a great accomplishment so after the tournament

accomplishment so after the tournament

accomplishment so after the tournament he expressed that through this through

he expressed that through this through

he expressed that through this through playing alphago he had actually been

playing alphago he had actually been

playing alphago he had actually been opened to new ideas to be able to think

opened to new ideas to be able to think

opened to new ideas to be able to think creatively and had a new insight into

creatively and had a new insight into

creatively and had a new insight into the game and ever since then he’s never

the game and ever since then he’s never

the game and ever since then he’s never lost a single game and go so one could

lost a single game and go so one could

lost a single game and go so one could consider the 4 out of 5 losses as an

consider the 4 out of 5 losses as an

consider the 4 out of 5 losses as an early sign of machines asserting their

early sign of machines asserting their

early sign of machines asserting their superiority but I believe it needs to be

superiority but I believe it needs to be

superiority but I believe it needs to be looked at differently I believe that

looked at differently I believe that

looked at differently I believe that without the thirty-seventh move there

without the thirty-seventh move there

without the thirty-seventh move there would have never been the 70th move what

would have never been the 70th move what

would have never been the 70th move what I mean is what is AI enabling us to do

I mean is what is AI enabling us to do

I mean is what is AI enabling us to do it’s enabling us to think more

it’s enabling us to think more

it’s enabling us to think more creatively to improve the way we think

creatively to improve the way we think

creatively to improve the way we think and hence providing a path to augment

and hence providing a path to augment

and hence providing a path to augment our own natural intelligence at the end

our own natural intelligence at the end

our own natural intelligence at the end of the day now I still believe that the

of the day now I still believe that the

of the day now I still believe that the human brain is the most elegant

human brain is the most elegant

human brain is the most elegant intelligent system to ever exist

intelligent system to ever exist

intelligent system to ever exist yes AI does is superior than us in a

yes AI does is superior than us in a

yes AI does is superior than us in a certain tasks currently but our brain is

certain tasks currently but our brain is

certain tasks currently but our brain is far more superior in various other tasks

far more superior in various other tasks

far more superior in various other tasks and our objective is to take this

and our objective is to take this

and our objective is to take this natural intelligence to its pinnacle to

natural intelligence to its pinnacle to

natural intelligence to its pinnacle to take it to its absolute height and AI

take it to its absolute height and AI

take it to its absolute height and AI proves a very very promising path to

proves a very very promising path to

proves a very very promising path to that point so what we want to establish

that point so what we want to establish

that point so what we want to establish is a symbiotic relation between man and

is a symbiotic relation between man and

is a symbiotic relation between man and machine so we make machine smarter make

machine so we make machine smarter make

machine so we make machine smarter make them explore domains that we can’t and

them explore domains that we can’t and

them explore domains that we can’t and then we take the information learnt by

then we take the information learnt by

then we take the information learnt by them to improve what we are best at

them to improve what we are best at

them to improve what we are best at thinking and inventing so we don’t want

thinking and inventing so we don’t want

thinking and inventing so we don’t want a situation where it’s man versus

a situation where it’s man versus

a situation where it’s man versus machine what’s ideal is man plus machine

machine what’s ideal is man plus machine

machine what’s ideal is man plus machine versus problems so if you think about it

versus problems so if you think about it

versus problems so if you think about it when you invest in AI you’re technically

when you invest in AI you’re technically

when you invest in AI you’re technically investing in yourself thank you

investing in yourself thank you

investing in yourself thank you [Applause]