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  • 00:00

    SPEAKER: It's hard to escape news
    SPEAKER: It's hard to escape news

  • 00:01

    about artificial intelligence nowadays.
    about artificial intelligence nowadays.

  • 00:04

    From new discoveries in medicine and science,
    From new discoveries in medicine and science,

  • 00:06

    to gaming, to enhanced experiences
    to gaming, to enhanced experiences

  • 00:08

    on our phones, laptops, and even our cars, excitement about AI
    on our phones, laptops, and even our cars, excitement about AI

  • 00:13

    is everywhere.
    is everywhere.

  • 00:14

    But what is AI?
    But what is AI?

  • 00:16

    In my time working with it, teaching students, companies,
    In my time working with it, teaching students, companies,

  • 00:20

    governments, and developers, the single most helpful lesson has
    governments, and developers, the single most helpful lesson has

  • 00:24

    always been helping people understand what AI is,
    always been helping people understand what AI is,

  • 00:27

    and just as importantly what it isn't.
    and just as importantly what it isn't.

  • 00:30

    In this series, we'll take a journey
    In this series, we'll take a journey

  • 00:32

    to explore artificial intelligence,
    to explore artificial intelligence,

  • 00:34

    along with machine learning and deep learning.
    along with machine learning and deep learning.

  • 00:36

    We'll cut through the hype, and we'll
    We'll cut through the hype, and we'll

  • 00:38

    help you understand what it's really all about.
    help you understand what it's really all about.

  • 00:40

    You don't need to be a programmer or a mathematician.
    You don't need to be a programmer or a mathematician.

  • 00:43

    You don't even need a tech background.
    You don't even need a tech background.

  • 00:46

    And if you have any questions along the way,
    And if you have any questions along the way,

  • 00:48

    just go ahead and leave a comment down below,
    just go ahead and leave a comment down below,

  • 00:50

    and we'll do our best to help.
    and we'll do our best to help.

  • 00:51

    And if you want to catch the next episode,
    And if you want to catch the next episode,

  • 00:53

    be sure to subscribe.
    be sure to subscribe.

  • 00:55

    I'll begin by exploring the hype cycle
    I'll begin by exploring the hype cycle

  • 00:58

    and how it impacts how the world talks
    and how it impacts how the world talks

  • 01:00

    about artificial intelligence.
    about artificial intelligence.

  • 01:02

    The hype cycle curve is here.
    The hype cycle curve is here.

  • 01:04

    It starts with a technology trigger,
    It starts with a technology trigger,

  • 01:06

    and this is when breakthroughs or new inventions happen.
    and this is when breakthroughs or new inventions happen.

  • 01:09

    For example, think about the invention of the smartphone.
    For example, think about the invention of the smartphone.

  • 01:12

    People didn't really know what it was all about when it first
    People didn't really know what it was all about when it first

  • 01:15

    came on the scene.
    came on the scene.

  • 01:16

    There was a lot of rhetoric about how
    There was a lot of rhetoric about how

  • 01:18

    the phone might replace the need for desktop and laptop
    the phone might replace the need for desktop and laptop

  • 01:20

    computers.
    computers.

  • 01:21

    You could plug a keyboard and a screen into the phone,
    You could plug a keyboard and a screen into the phone,

  • 01:23

    and then you could just do your work.
    and then you could just do your work.

  • 01:25

    That kind of talk resulted in this,
    That kind of talk resulted in this,

  • 01:28

    and it's called the peak of inflated expectations.
    and it's called the peak of inflated expectations.

  • 01:31

    It's the epitome of hype, where the realities of the technology
    It's the epitome of hype, where the realities of the technology

  • 01:34

    are drowned out by hyperbole, the possibilities
    are drowned out by hyperbole, the possibilities

  • 01:38

    are generally overstated, and the implications
    are generally overstated, and the implications

  • 01:40

    are often feared.
    are often feared.

  • 01:42

    The history of technology is littered with innovations that
    The history of technology is littered with innovations that

  • 01:45

    fail to get past this peak.
    fail to get past this peak.

  • 01:47

    When reality sets in, we fall into this,
    When reality sets in, we fall into this,

  • 01:50

    the spectacularly named trough of disillusionment.
    the spectacularly named trough of disillusionment.

  • 01:54

    And as the name suggests, this is the reality check.
    And as the name suggests, this is the reality check.

  • 01:57

    It's when one realizes that maybe
    It's when one realizes that maybe

  • 01:59

    all of those grandiose ideas that you thought
    all of those grandiose ideas that you thought

  • 02:01

    were possible with the technology failed
    were possible with the technology failed

  • 02:04

    to materialize.
    to materialize.

  • 02:05

    And it's where people often give up,
    And it's where people often give up,

  • 02:08

    and where what seemed to be the latest, greatest,
    and where what seemed to be the latest, greatest,

  • 02:11

    and hottest of ideas get consigned to the graveyard
    and hottest of ideas get consigned to the graveyard

  • 02:14

    of history.
    of history.

  • 02:15

    But then some people realizing the limitations
    But then some people realizing the limitations

  • 02:19

    begin to innovate around them, and they
    begin to innovate around them, and they

  • 02:21

    start rising up the slope of enlightenment
    start rising up the slope of enlightenment

  • 02:24

    to the plateau of productivity.
    to the plateau of productivity.

  • 02:26

    They develop a new innovation that works,
    They develop a new innovation that works,

  • 02:29

    and they succeed with it.
    and they succeed with it.

  • 02:30

    For example, with the mobile phone much of the hype bubble
    For example, with the mobile phone much of the hype bubble

  • 02:33

    burst when people began to realize
    burst when people began to realize

  • 02:36

    it wasn't powerful enough to replace
    it wasn't powerful enough to replace

  • 02:37

    the laptop or the desktop, or it was limited by battery life,
    the laptop or the desktop, or it was limited by battery life,

  • 02:41

    or things like multiple concurrent apps
    or things like multiple concurrent apps

  • 02:43

    could not run effectively due to resource constraints.
    could not run effectively due to resource constraints.

  • 02:46

    And all of those revolutionary ideas died.
    And all of those revolutionary ideas died.

  • 02:49

    But then some people realize that the phone
    But then some people realize that the phone

  • 02:52

    had a GPS, so applications around location,
    had a GPS, so applications around location,

  • 02:55

    such as navigation apps, became possible,
    such as navigation apps, became possible,

  • 02:58

    or even something that lets you tell someone
    or even something that lets you tell someone

  • 03:00

    where you are so a driver can come and pick you up.
    where you are so a driver can come and pick you up.

  • 03:03

    The idea of standing on a corner with your hand raised
    The idea of standing on a corner with your hand raised

  • 03:06

    in the hope that a cab might pass by and pick you up
    in the hope that a cab might pass by and pick you up

  • 03:08

    was suddenly antiquated.
    was suddenly antiquated.

  • 03:11

    Whole new industries were born as a result of the smartphone,
    Whole new industries were born as a result of the smartphone,

  • 03:14

    and they were born by people who,
    and they were born by people who,

  • 03:16

    upon falling into the trough, did not give up.
    upon falling into the trough, did not give up.

  • 03:19

    They realized the realities and not the hype,
    They realized the realities and not the hype,

  • 03:22

    and they then turn those into a strength.
    and they then turn those into a strength.

  • 03:25

    But here's a little secret.
    But here's a little secret.

  • 03:27

    They're not necessarily more intelligent or better
    They're not necessarily more intelligent or better

  • 03:29

    than the rest of us.
    than the rest of us.

  • 03:30

    They just didn't give up when they
    They just didn't give up when they

  • 03:32

    hit the trough of disillusionment,
    hit the trough of disillusionment,

  • 03:34

    and they continued along the curve.
    and they continued along the curve.

  • 03:36

    With AI, most of the world is here today
    With AI, most of the world is here today

  • 03:39

    looking up at that peak of inflated expectations.
    looking up at that peak of inflated expectations.

  • 03:42

    It's blocking the way towards productivity.
    It's blocking the way towards productivity.

  • 03:44

    So in this video series, I'm going to get you here.
    So in this video series, I'm going to get you here.

  • 03:48

    Yep, you're going to be disillusioned.
    Yep, you're going to be disillusioned.

  • 03:50

    And that's OK, because that's when you will understand what
    And that's OK, because that's when you will understand what

  • 03:53

    AI is, what it isn't.
    AI is, what it isn't.

  • 03:55

    And maybe, just maybe, when you have a clearer understanding
    And maybe, just maybe, when you have a clearer understanding

  • 03:58

    of what's possible that will open you
    of what's possible that will open you

  • 04:00

    up to developing new ideas, like these students
    up to developing new ideas, like these students

  • 04:04

    in India, who use machine learning on a phone
    in India, who use machine learning on a phone

  • 04:06

    to help their families navigate air quality and pollution
    to help their families navigate air quality and pollution

  • 04:09

    issues.
    issues.

  • 04:10

    Or this farmer in Japan, who didn't
    Or this farmer in Japan, who didn't

  • 04:12

    have enough resources to sort out his cucumbers for sale
    have enough resources to sort out his cucumbers for sale

  • 04:15

    in the markets, so he designed and built
    in the markets, so he designed and built

  • 04:17

    a machine using machine learning to do it for him.
    a machine using machine learning to do it for him.

  • 04:20

    And of course, there's this young woman
    And of course, there's this young woman

  • 04:22

    in Uganda, who harnessed the power of AI
    in Uganda, who harnessed the power of AI

  • 04:24

    to help farmers in her country identify and prevent
    to help farmers in her country identify and prevent

  • 04:28

    crop-destroying pests.
    crop-destroying pests.

  • 04:30

    The possibilities are endless, and you
    The possibilities are endless, and you

  • 04:32

    can have a part in this.
    can have a part in this.

  • 04:34

    So please like, subscribe, and share, and most of all,
    So please like, subscribe, and share, and most of all,

  • 04:37

    enjoy this series.
    enjoy this series.

  • 04:38

    [MUSIC PLAYING]
    [MUSIC PLAYING]

All verb
escape
/əˈskāp/

word

To not to be noticed or remembered by someone

AI and the Gartner Hype Cycle

13,671 views

Intro:

SPEAKER: It's hard to escape news. about artificial intelligence nowadays.. From new discoveries in medicine and science,. to gaming, to enhanced experiences. on our phones, laptops, and even our cars, excitement about AI
is everywhere.. But what is AI?. In my time working with it, teaching students, companies,
governments, and developers, the single most helpful lesson has
always been helping people understand what AI is,. and just as importantly what it isn't.. In this series, we'll take a journey. to explore artificial intelligence,. along with machine learning and deep learning.. We'll cut through the hype, and we'll. help you understand what it's really all about.. You don't need to be a programmer or a mathematician.
You don't even need a tech background.. And if you have any questions along the way,. just go ahead and leave a comment down below,.

Video Vocabulary

/ikˈsplôr/

verb

To travel to a place to discover more about it.

/THro͞o/

adjective adverb preposition

continuing or valid to final destination. expressing movement into one side and out of other side of opening etc.. moving in one side and out of other side of.

/imˈpôrtntlē/

adverb

In an important way;.

/ikˈsītmənt/

noun

feeling of great enthusiasm and eagerness.

/ˈkwesCH(ə)n/

noun other verb

sentence worded or expressed so as to elicit information. What you ask about; issues. To have or express concerns or uncertainty.

/ˌəndərˈstand/

verb

To know the meaning of language, what someone says.

/ˈhelpiNG/

noun verb

portion of food served to one person at one time. To make something better or less difficult.

/ˈmedəsən/

noun

Science of preventing, treating, or curing disease.

/ˈtēCHiNG/

noun verb

The act of helping people learn. To help someone learn or do something.

/dəˈskəv(ə)rē/

noun other

action or process of discovering or being discovered. Learning some things for the first time.

/ˈlərniNG/

noun verb

Act of getting knowledge. To get knowledge or skills by study or experience.

/ˈprōˌɡramər/

noun

person who writes computer programs.

noun other verb

action of one object striking another. Acts or forces of one thing hitting something else. To affect someone or something greatly.

/ˈwərkiNG/

adjective noun verb

having paid employment. action of doing work. To be functioning properly, e.g. a car.

/inˈteləjəns/

adjective noun

Of the spying services; acting in secrecy. Ability to learn things or to consider situations.