4th industrial revolution and AI final

00:26:08
https://www.youtube.com/watch?v=XlpTZDq1Aq4

Resumen

TLDRThis course covers the fundamentals of data analysis using AI algorithms, emphasizing their essential role in today's data-driven world. Students will learn how these technologies empower analysts to handle vast data sets, enhance accuracy, and make informed decisions, which are crucial for staying competitive in the AI era. The course explores the evolution of the Industrial Revolutions, highlighting AI's transformative impact from production to consumption phases. Key topics include the differences between informatization and intelligence, the rise and development of artificial intelligence, and understanding chat GPT. Discussions will also cover anticipated job market shifts due to AI, fostering crucial skills like problem-solving, creativity, and collaboration. Additionally, the concept of singularity and the ethical considerations related to AI's future are examined. This comprehensive introduction aims to equip students with necessary skills and knowledge to navigate and thrive in the evolving world of AI and data analytics.

Para llevar

  • 🔍 Understand the role of AI in data analysis and decision-making.
  • 🛠 Explore AI's transformative impact on industries in the Fourth Industrial Revolution.
  • 📈 Learn about the evolution from informatization to intelligence.
  • 🤖 Recognize machine learning and deep learning paradigms.
  • 🧠 Grasp the concept of singularity and AI's potential surpass in human tasks.
  • 🚀 Understand chat GPT's role in language processing.
  • 💼 Analyze AI's impact on job markets and necessary skill development.
  • 🎨 Develop skills like creativity and problem-solving to complement AI.
  • 💡 Discover the key differences between traditional programming and machine learning.
  • 🌐 Assess the ethical implications and future challenges of AI development.

Cronología

  • 00:00:00 - 00:05:00

    This video introduces the importance of understanding data analysis using AI algorithms in today's AI-driven world. It emphasizes the role of data analysis in improving decision-making, accuracy, and handling large datasets efficiently. The introduction sets the stage for the course which will delve deeper into these concepts, ensuring individuals and organizations can remain competitive in this era.

  • 00:05:00 - 00:10:00

    The video discusses the impact of recommendations in commerce, using Amazon as an example of how data-driven services enhance customer purchases. It transitions into exploring traits of the fourth Industrial Revolution driven by AI, detailing how topics like the historical industrial shifts, AI evolution, and key skills for thriving in this era will be covered.

  • 00:10:00 - 00:15:00

    The content explores the fourth Industrial Revolution's focus on AI and smart systems, contrasting it with earlier revolutions centered around physical labor and power. It predicts that companies dealing in data, the new 'raw material', will succeed. The transition from informatization to intelligence, emphasizing autonomous decision-making by machines, is highlighted.

  • 00:15:00 - 00:20:00

    AI's development is traced from its inception, with key milestones like the Turing Test and advances in neural networks by figures like Jeffrey Hinton spotlighted. Real-world applications, from game-winning AI like IBM's Watson to emerging tools like Chat GPT, showcase AI's expanding capabilities and its distinction between weak and strong AI systems.

  • 00:20:00 - 00:26:08

    In concluding, the video stresses the importance of developing human-centric skills such as problem-solving, creativity, and empathy in the AI era. It highlights AI's integration across various job sectors, predicting increases in AI-related occupations and declines in others. The discussion encourages equipping oneself with collaborative and critical thinking skills to thrive alongside AI advancements.

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Mapa mental

Mind Map

Preguntas frecuentes

  • What is the main focus of this course?

    The course focuses on the fundamentals of data analysis using AI algorithms.

  • Why is understanding AI and data analytics important?

    Understanding AI and data analytics is crucial for handling large data sets efficiently, improving accuracy, and making advanced decisions.

  • What are examples of AI applications discussed in the course?

    Examples include Amazon's recommendation service, autonomous driving, and medical diagnostics.

  • What is discussed in relation to the Industrial Revolutions?

    The course discusses the transition from the first to the fourth Industrial Revolution, focusing on how AI is transforming industries.

  • How is AI impacting job markets?

    AI is expected to create new jobs in areas like data analysis, while reducing roles in clerical and secretarial fields.

  • What is the singularity in AI?

    Singularity refers to the point where AI surpasses human intelligence, potentially occurring by 2045.

  • What skills are important to develop in the AI era?

    Skills like problem-solving, creativity, critical thinking, communication, and collaboration are emphasized.

  • How does machine learning differ from traditional programming?

    Machine learning allows computers to learn from data rather than following explicit instructions as in traditional programming.

  • What is the significance of chat GPT?

    Chat GPT is a language model that demonstrates AI's potential to perform human-like tasks.

  • What future challenges do experts anticipate with AI?

    Experts are considering the ethical and control issues surrounding the future development of AI.

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Desplazamiento automático:
  • 00:00:00
    hello everyone in this course we will
  • 00:00:03
    cover the fundamentals of data analysis
  • 00:00:05
    using AI algorithms
  • 00:00:08
    fundamentals of data analysis using AI
  • 00:00:11
    algorithms plays a crucial role in
  • 00:00:14
    today's data-driven world
  • 00:00:17
    understanding it empowers analysts to
  • 00:00:19
    handle large data sets efficiently
  • 00:00:22
    improve accuracy make advanced decisions
  • 00:00:26
    these skills are essential for
  • 00:00:29
    individuals and organizations seeking to
  • 00:00:31
    derive meaningful insights and stay
  • 00:00:33
    competitive in the AI driven era
  • 00:00:37
    thank you for joining us on this
  • 00:00:39
    exciting New Journey into artificial
  • 00:00:41
    intelligence and data analytics
  • 00:00:44
    we appreciate your participation
  • 00:00:48
    did you know that approximately 35 of
  • 00:00:51
    customers are more likely to make a
  • 00:00:54
    purchase thanks to Amazon's
  • 00:00:55
    recommendation service
  • 00:00:57
    Amazon collects data about your past
  • 00:01:00
    purchases search history ratings and
  • 00:01:04
    reviews
  • 00:01:05
    using Advanced Technologies like machine
  • 00:01:08
    learning and artificial intelligence
  • 00:01:10
    Amazon understands your interests and
  • 00:01:13
    preferences
  • 00:01:15
    by using your purchase history Amazon
  • 00:01:18
    recommends products that match your
  • 00:01:20
    interests and preferences
  • 00:01:23
    your feedback helps them improve their
  • 00:01:25
    recommendations making your shopping
  • 00:01:27
    experience even better
  • 00:01:30
    in this chapter we will examine the
  • 00:01:33
    characteristics of the fourth Industrial
  • 00:01:35
    Revolution era driven by AI technology
  • 00:01:38
    such as Amazon's recommendation services
  • 00:01:42
    we will explore how we should respond to
  • 00:01:45
    this rapidly changing landscape
  • 00:01:48
    in this chapter we will cover five
  • 00:01:51
    topics as follows
  • 00:01:54
    firstly we will discuss Industrial
  • 00:01:57
    Revolution from first to Fourth
  • 00:02:00
    next we will explore the difference
  • 00:02:03
    between informatization and intelligence
  • 00:02:07
    we will then examine the artificial
  • 00:02:09
    intelligence
  • 00:02:12
    next we will take a look at chat GPT
  • 00:02:16
    finally we will explore key skills you
  • 00:02:19
    should develop in AI era
  • 00:02:22
    by the end of the section students
  • 00:02:25
    should be able to explain followings
  • 00:02:28
    to understand the differences among the
  • 00:02:31
    four industrial revolutions it is
  • 00:02:33
    important to explore
  • 00:02:36
    who generated wealth in each Revolution
  • 00:02:38
    and make predictions about the winners
  • 00:02:40
    in the fourth Industrial Revolution
  • 00:02:43
    additionally knowledge about the concept
  • 00:02:46
    and evolution of AI understanding of the
  • 00:02:50
    concept of singularity
  • 00:02:52
    and the differences between traditional
  • 00:02:55
    programming machine learning and deep
  • 00:02:57
    learning are crucial
  • 00:03:00
    being able to explain Chad GPT and the
  • 00:03:03
    skills students should develop in the
  • 00:03:05
    age of AI are also important
  • 00:03:08
    let's dive into our first topic the
  • 00:03:11
    fourth Industrial Revolution
  • 00:03:14
    this revolution is all about making
  • 00:03:17
    machines and objects smarter or
  • 00:03:19
    intelligence with AI playing a major
  • 00:03:22
    role
  • 00:03:23
    we have experienced four industrial
  • 00:03:26
    revolutions
  • 00:03:28
    the first and second revolutions
  • 00:03:31
    replaced human physical labor with steam
  • 00:03:34
    and Electric Power
  • 00:03:36
    however the focus of the third and
  • 00:03:38
    fourth revolutions has shifted towards
  • 00:03:41
    using computers and AI to replace office
  • 00:03:43
    workers
  • 00:03:45
    in today's era of the fourth Industrial
  • 00:03:48
    Revolution AI connects and makes the
  • 00:03:51
    almost entire business process from
  • 00:03:54
    production to consumption smarter or
  • 00:03:57
    intelligent
  • 00:03:58
    in the fourth Industrial Revolution
  • 00:04:01
    looking at examples from the past can
  • 00:04:04
    help us predict which companies may be
  • 00:04:06
    successful in markets
  • 00:04:08
    let's consider the previous industrial
  • 00:04:11
    revolutions for insight
  • 00:04:14
    during the first Industrial Revolution
  • 00:04:17
    companies that supplied wool which is
  • 00:04:20
    used to make fabric earn substantial
  • 00:04:22
    profits
  • 00:04:24
    in the Second Industrial Revolution
  • 00:04:27
    companies that provided petroleum
  • 00:04:29
    necessary for machines and cars became
  • 00:04:32
    wealthy
  • 00:04:34
    in the third Industrial Revolution
  • 00:04:36
    companies supplying computer components
  • 00:04:39
    and software greatly benefited
  • 00:04:42
    from this we observe that companies
  • 00:04:45
    involved in producing raw materials or
  • 00:04:48
    components rather than final products
  • 00:04:51
    were able to make more money due to less
  • 00:04:53
    intense competition
  • 00:04:55
    for example iron ore providers are more
  • 00:04:59
    advantageous compared to blacksmiths
  • 00:05:02
    applying a similar line of thinking in
  • 00:05:05
    the era of the fourth Industrial
  • 00:05:07
    Revolution it is predicted that
  • 00:05:09
    companies gathering and analyzing data
  • 00:05:13
    which acts as the raw material for
  • 00:05:16
    intelligent Technologies would generate
  • 00:05:18
    significant profits
  • 00:05:21
    the third and fourth industrial
  • 00:05:23
    revolutions can be characterized by
  • 00:05:25
    informatization and intelligence
  • 00:05:27
    respectively
  • 00:05:30
    informatization focuses on optimizing
  • 00:05:33
    existing processes while intelligence
  • 00:05:35
    emphasizes intelligent technologies that
  • 00:05:38
    make decisions directly
  • 00:05:41
    for example self-driving cars and chat
  • 00:05:44
    Bots are examples of intelligence where
  • 00:05:47
    they can operate without human
  • 00:05:49
    involvement
  • 00:05:50
    the difference between informatization
  • 00:05:53
    and intelligence lies in who is the
  • 00:05:55
    decision maker
  • 00:05:57
    the objective of the third Industrial
  • 00:06:00
    Revolution was to use computer systems
  • 00:06:02
    to assist humans in decision making
  • 00:06:05
    in contrast the goal of the fourth
  • 00:06:08
    Industrial Revolution is to enable
  • 00:06:10
    machines or objects to make autonomous
  • 00:06:13
    decisions without human intervention
  • 00:06:16
    thus in the era of the fourth Industrial
  • 00:06:19
    Revolution it is expected that there
  • 00:06:22
    will be an increase in the development
  • 00:06:24
    of smart devices
  • 00:06:26
    and systems that can work on their own
  • 00:06:29
    and make decisions without much human
  • 00:06:31
    involvement
  • 00:06:33
    in the fourth Industrial Revolution
  • 00:06:36
    computers and objects are connected
  • 00:06:38
    through Networks
  • 00:06:40
    this allows them to learn from each
  • 00:06:42
    other and make decisions without human
  • 00:06:45
    intervention
  • 00:06:46
    this means that in certain areas the
  • 00:06:49
    responsibility for decision-making
  • 00:06:51
    shifts from humans to intelligent
  • 00:06:54
    machines or objects
  • 00:06:56
    the fourth Industrial Revolution is
  • 00:06:59
    often compared to a dish called bibimbap
  • 00:07:03
    in this analogy Big Data The Internet of
  • 00:07:07
    Things iot an AI are like different
  • 00:07:09
    ingredients that make up bibimbap
  • 00:07:13
    just as different ingredients come
  • 00:07:15
    together to create a delicious bibimbap
  • 00:07:18
    these Technologies combine to drive the
  • 00:07:21
    fourth Industrial Revolution
  • 00:07:23
    countries and companies that can
  • 00:07:25
    effectively integrate these ingredients
  • 00:07:28
    and create innovative solutions will
  • 00:07:31
    become the winners of the fourth
  • 00:07:33
    Industrial Revolution
  • 00:07:36
    in this chapter we will examine
  • 00:07:38
    artificial intelligence
  • 00:07:42
    the term AI was first used by John
  • 00:07:45
    McCarthy a computer scientist in 1956.
  • 00:07:50
    A.I which stands for artificial
  • 00:07:53
    intelligence is all about teaching
  • 00:07:55
    computers to act smart like humans
  • 00:07:59
    it uses special computer programs called
  • 00:08:02
    algorithms to help machines understand
  • 00:08:04
    information learn from it and make
  • 00:08:07
    decisions
  • 00:08:09
    some cool examples of AI in action or
  • 00:08:12
    alphago Watson Chad GPT and many more
  • 00:08:17
    the key milestones in the development of
  • 00:08:20
    AI are as follows
  • 00:08:23
    in 1950 Alan Turing mentioned the Turing
  • 00:08:27
    test
  • 00:08:29
    this test is like a game where a person
  • 00:08:32
    talks to both a machine and a human
  • 00:08:34
    without knowing who is who
  • 00:08:37
    if the person can't tell which one is
  • 00:08:39
    the machine based on their conversation
  • 00:08:41
    then the machine is considered to have
  • 00:08:44
    passed the test
  • 00:08:46
    it's a way to check if a machine can
  • 00:08:48
    talk like a human
  • 00:08:50
    don't you think that Chad GPT is better
  • 00:08:53
    than humans when you talk to it
  • 00:08:56
    in 2006 Professor Jeffrey Hinton made
  • 00:09:00
    improvements to computer systems called
  • 00:09:02
    Deep neural networks
  • 00:09:05
    these systems are like the human brain
  • 00:09:07
    and can understand and work with data
  • 00:09:10
    in 2012 Alex Krish husky did something
  • 00:09:14
    exciting by using deep learning along
  • 00:09:17
    with GPS to get better at recognizing
  • 00:09:19
    images
  • 00:09:21
    this made computers really good at
  • 00:09:24
    figuring out what's in a picture
  • 00:09:26
    then in 2020 Chad GPT came along
  • 00:09:32
    please take a moment to briefly read the
  • 00:09:35
    history of AI development Illustrated in
  • 00:09:38
    this slide
  • 00:09:39
    we have already reviewed the key
  • 00:09:41
    developments of AI in the previous slide
  • 00:09:45
    this slide shows the competition between
  • 00:09:48
    humans and AI
  • 00:09:51
    in 1996 IBM Watson won against the world
  • 00:09:56
    chess champion
  • 00:09:57
    in 2011 IBM Watson became the champion
  • 00:10:02
    in the popular U.S quiz show Jeopardy
  • 00:10:04
    defeating the other human champions
  • 00:10:08
    then in 2016 it made a big splash by
  • 00:10:12
    beating the world champion go player Lee
  • 00:10:15
    settle
  • 00:10:16
    in 2023 Chad GPT became widely used
  • 00:10:21
    serving as a smart personal assistant
  • 00:10:25
    from these examples we can see that AI
  • 00:10:28
    is rapidly entering areas that were once
  • 00:10:31
    only for humans
  • 00:10:33
    this speed is expected to increase even
  • 00:10:36
    more in the future
  • 00:10:39
    there are two types of AI weak and
  • 00:10:42
    strong AI
  • 00:10:44
    weak AI refers to AI systems designed
  • 00:10:47
    for specific tasks Unlimited in their
  • 00:10:50
    abilities such as Google Translator
  • 00:10:53
    on the other hands strong AI refers to
  • 00:10:57
    AI systems that possess general
  • 00:10:59
    intelligence and can understand and
  • 00:11:01
    perform tasks like a human
  • 00:11:04
    it's like having an AI system that can
  • 00:11:06
    think and learn just like we do
  • 00:11:09
    when people talk about AI they usually
  • 00:11:13
    mean machines learning and processing
  • 00:11:15
    information like humans
  • 00:11:18
    machine learning is a way to implement
  • 00:11:20
    AI using various methods to find
  • 00:11:23
    meaningful information from data
  • 00:11:26
    deep learning is a specific type of
  • 00:11:29
    machine learning that mimics the human
  • 00:11:31
    brain using artificial neural networks
  • 00:11:34
    you will learn about machine learning
  • 00:11:37
    and deep learning techniques such as
  • 00:11:39
    clustering and classification throughout
  • 00:11:42
    the semester
  • 00:11:44
    traditional programming and machine
  • 00:11:46
    learning are quite different from each
  • 00:11:48
    other
  • 00:11:49
    in traditional programming we have to
  • 00:11:52
    tell the computer exactly what to do
  • 00:11:54
    step by step
  • 00:11:57
    for example if we wanted to clean a room
  • 00:12:00
    we have to explicitly instruct it to
  • 00:12:02
    remove dust first and then mop the floor
  • 00:12:06
    it's like giving a computer a detailed
  • 00:12:09
    guideline to follow
  • 00:12:11
    but in machine learning it works
  • 00:12:14
    differently
  • 00:12:16
    instead of giving Specific Instructions
  • 00:12:19
    we show the computer lots of videos of
  • 00:12:21
    successful and unsuccessful cleaning
  • 00:12:25
    it learns by watching these examples and
  • 00:12:28
    figuring out its own way of cleaning
  • 00:12:30
    it's like teaching a computer by showing
  • 00:12:33
    it how things are done
  • 00:12:35
    the computer learns from these videos
  • 00:12:38
    and starts to recognize patterns
  • 00:12:41
    it finds out what works and what doesn't
  • 00:12:45
    this way it can make its own decisions
  • 00:12:48
    and perform tasks without us
  • 00:12:52
    there are also differences between
  • 00:12:54
    machine learning and deep learning
  • 00:12:57
    in machine learning we humans have to
  • 00:13:01
    tell the computer about specific
  • 00:13:02
    features that help it recognize
  • 00:13:04
    something
  • 00:13:06
    for example we might explain to the
  • 00:13:09
    computer that cats have certain eye
  • 00:13:11
    shapes or nose structures
  • 00:13:13
    eye shapes are called features
  • 00:13:17
    then the computer learns to identify
  • 00:13:19
    cats based on these given features
  • 00:13:23
    it's like giving the computer some Clues
  • 00:13:25
    to recognize cats
  • 00:13:28
    now in deep learning things work a bit
  • 00:13:32
    differently
  • 00:13:33
    we provide the computer with a bunch of
  • 00:13:36
    cat images and the computer figures out
  • 00:13:39
    the important features of cats all by
  • 00:13:41
    itself
  • 00:13:43
    it learns to extract the features that
  • 00:13:46
    are relevant for identifying cats from
  • 00:13:48
    the images
  • 00:13:50
    let's take a look at Deep learning in
  • 00:13:52
    more detail
  • 00:13:54
    deep learning is a type of Computer
  • 00:13:57
    Learning that tries to imitate how our
  • 00:13:59
    brains work
  • 00:14:01
    it uses interconnected Parts kind of
  • 00:14:04
    like the neurons in our brains to
  • 00:14:06
    process information and learn from it
  • 00:14:09
    the Deep part means there are many
  • 00:14:12
    layers that help the computer understand
  • 00:14:14
    complicated stuff
  • 00:14:17
    it's like teaching a computer to learn
  • 00:14:19
    and think a bit like our own brains do
  • 00:14:23
    machine learning is being used in
  • 00:14:25
    various Fields as follows
  • 00:14:29
    first is the image classification it's
  • 00:14:32
    about teaching computers to see and
  • 00:14:35
    understand different types of images
  • 00:14:38
    second is the language applications it's
  • 00:14:41
    about using AI to understand and process
  • 00:14:44
    human language like talking to Virtual
  • 00:14:47
    assistants or translating languages
  • 00:14:50
    third one is autonomous driving it's
  • 00:14:53
    about creating self-driving cars that
  • 00:14:56
    can recognize and respond to pedestrians
  • 00:14:59
    and road signs
  • 00:15:01
    fourth one is medical Fields it's about
  • 00:15:04
    using AI to help doctors analyze X-rays
  • 00:15:07
    and diagnose cancer more accurately
  • 00:15:10
    now ai is widely adopted in almost all
  • 00:15:14
    Industries to increase productivity and
  • 00:15:17
    efficiency
  • 00:15:19
    let's take a look at some interesting
  • 00:15:21
    applications of AI in our life
  • 00:15:24
    AI painter is a tool that uses AI to
  • 00:15:27
    create artwork
  • 00:15:29
    it can imitate different Artistic Styles
  • 00:15:32
    and even replicate famous paintings
  • 00:15:36
    for example if you ask to draw a picture
  • 00:15:39
    in the style of Van Gogh it will be
  • 00:15:42
    drawn as if it were painted by Van Gogh
  • 00:15:45
    by learning from a large amount of art
  • 00:15:48
    data AI painter can generate unique and
  • 00:15:51
    Visually appealing pieces
  • 00:15:54
    Cafe X wants to make getting coffee easy
  • 00:15:57
    and fun while still making sure it
  • 00:15:59
    tastes great
  • 00:16:01
    you can order using a machine or your
  • 00:16:03
    phone
  • 00:16:05
    robots make the coffee by grinding the
  • 00:16:08
    beans Brewing it and adding milk or
  • 00:16:11
    other things
  • 00:16:12
    at Cali Burger they have a special robot
  • 00:16:16
    Chef that can do lots of cooking tasks
  • 00:16:19
    it can grill burger patties put the
  • 00:16:22
    ingredients together and even flip the
  • 00:16:24
    burgers
  • 00:16:26
    the robot Chef follows exact recipes and
  • 00:16:29
    instructions that are saved in its
  • 00:16:31
    system so the burgers always turn out
  • 00:16:34
    the same taste
  • 00:16:36
    in the future or even now humans are
  • 00:16:39
    expected to coexist with AI
  • 00:16:43
    futurist Ray Kurzweil in his book The
  • 00:16:47
    Singularity is near predicts that by
  • 00:16:49
    2045 AI will surpass human capabilities
  • 00:16:54
    this point where AI surpasses human
  • 00:16:58
    intelligence is referred to as
  • 00:17:00
    singularity
  • 00:17:02
    please note that experts are still
  • 00:17:04
    discussing and studying the concept of
  • 00:17:06
    Singularity and when it might happen
  • 00:17:09
    there is no clear answer yet and it's an
  • 00:17:12
    ongoing topic of research and debate
  • 00:17:16
    when do you think the singularity will
  • 00:17:18
    occur
  • 00:17:20
    AI is seen as a good thing by experts
  • 00:17:23
    like Ray Kurzweil Bill Gates and Mark
  • 00:17:26
    Zuckerberg
  • 00:17:28
    they believe it will make our lives
  • 00:17:30
    better instead of taking over
  • 00:17:33
    AI can improve how we work learn get
  • 00:17:36
    health care and communicate
  • 00:17:39
    they think AI can be useful and
  • 00:17:41
    meaningful to lots of people
  • 00:17:44
    but they also know there are challenges
  • 00:17:46
    to tackle
  • 00:17:49
    they want to make sure AI is used in the
  • 00:17:51
    right way and doesn't cause problems
  • 00:17:55
    Elon Musk and Stephen Hawking are
  • 00:17:57
    worried about AI
  • 00:18:00
    musk thinks it's more dangerous and
  • 00:18:03
    could even destroy civilization
  • 00:18:06
    he wants rules and regulations to
  • 00:18:09
    control it
  • 00:18:11
    Hawking agrees and says it could be the
  • 00:18:13
    worst thing ever unless we control it
  • 00:18:17
    they both want us to be careful and
  • 00:18:19
    responsible with AI
  • 00:18:21
    in conclusion AI will make our lives
  • 00:18:24
    easier and more productive but we need
  • 00:18:27
    to keep it under control
  • 00:18:30
    let's talk about a GPT
  • 00:18:34
    GPT or generative pre-trained
  • 00:18:37
    Transformer is a fancy type of computer
  • 00:18:40
    program that's really good at creating
  • 00:18:42
    human-like text
  • 00:18:44
    it learns from a lot of examples and can
  • 00:18:47
    generate responses that make sense based
  • 00:18:50
    on what you say
  • 00:18:52
    when you chat with GPT it understands
  • 00:18:55
    what you're saying and tries to give you
  • 00:18:57
    helpful answers
  • 00:18:59
    it's been trained on lots of different
  • 00:19:02
    texts so it knows how to put things
  • 00:19:04
    together in a way that sounds natural
  • 00:19:07
    chat GPT is a large-scale language model
  • 00:19:11
    developed by openai while Bard is
  • 00:19:14
    developed by Google AI
  • 00:19:17
    both models provide similar
  • 00:19:19
    functionalities
  • 00:19:22
    GPT can do lots of things with language
  • 00:19:25
    like making up sentences understanding
  • 00:19:28
    what you say
  • 00:19:30
    filling and missing parts of a text
  • 00:19:32
    translating between languages and giving
  • 00:19:35
    you a shorter version of a long text
  • 00:19:39
    chat GPT is still under development but
  • 00:19:42
    it has already shown a lot of potential
  • 00:19:46
    here are some details about the Chad GPT
  • 00:19:49
    version history
  • 00:19:51
    chat GPT 1.0 released in November 2018
  • 00:19:58
    chat GPT 3.5
  • 00:20:01
    released in November 2022
  • 00:20:05
    chat GPT 4.0 released in March 2023
  • 00:20:11
    it is expected that the Chad GPT version
  • 00:20:14
    development will continue
  • 00:20:17
    to conclude this chapter let's discuss
  • 00:20:20
    the essential skills students must
  • 00:20:22
    cultivate to thrive in the AI era
  • 00:20:26
    right now there are many AI analysis
  • 00:20:29
    tools being developed and used
  • 00:20:32
    these tools make it possible for people
  • 00:20:35
    without coding or statistics knowledge
  • 00:20:37
    to do data analysis
  • 00:20:40
    we predict that in the future Ai and
  • 00:20:43
    data analysis tools will become even
  • 00:20:45
    easier to use and more powerful
  • 00:20:48
    this course is not just for computer
  • 00:20:51
    science students but for students from
  • 00:20:53
    different Majors like tourism and
  • 00:20:56
    sociology
  • 00:20:57
    I believe that by combining your domain
  • 00:21:00
    knowledge with the AI skills you'll
  • 00:21:02
    learn this semester you can create new
  • 00:21:05
    knowledge and greatly increase
  • 00:21:06
    productivity
  • 00:21:08
    AI technology is used everywhere in all
  • 00:21:12
    fields and industries
  • 00:21:14
    not knowing about AI is like not being
  • 00:21:17
    able to read or write
  • 00:21:19
    it's that important
  • 00:21:22
    there are three distinct types of
  • 00:21:24
    knowledge that can be categorized
  • 00:21:26
    information retrieval knowledge
  • 00:21:29
    application and knowledge creation
  • 00:21:32
    AI has already surpassed humans in the
  • 00:21:35
    domain of information retrieval where it
  • 00:21:38
    can quickly and accurately find and
  • 00:21:40
    process vast amounts of data
  • 00:21:43
    however when it comes to applying
  • 00:21:46
    knowledge and making contextual
  • 00:21:48
    decisions humans still possess an
  • 00:21:51
    advantage
  • 00:21:52
    additionally humans have the unique
  • 00:21:55
    ability to generate new knowledge and
  • 00:21:57
    think creatively
  • 00:21:59
    therefore to survive in the era of AI
  • 00:22:03
    you should cultivate human abilities
  • 00:22:05
    such as creativity and empathy which are
  • 00:22:08
    unique to us
  • 00:22:10
    let's look at how AI is changing our job
  • 00:22:13
    market
  • 00:22:15
    according to the world economic forum's
  • 00:22:18
    future of jobs report 2023 there will be
  • 00:22:22
    new job opportunities in fields like Ai
  • 00:22:25
    and machine learning data analysis and
  • 00:22:28
    digital transformation
  • 00:22:30
    jobs like AI Specialists and data
  • 00:22:33
    analysts are expected to increase by
  • 00:22:36
    around 40 by 2027.
  • 00:22:39
    however some jobs like clerical and
  • 00:22:43
    secretarial roles including bank tellers
  • 00:22:46
    and data entry clerks are predicted to
  • 00:22:49
    decline rapidly due to AI
  • 00:22:52
    here are the top 10 jobs that are
  • 00:22:54
    expected to grow the fastest and decline
  • 00:22:57
    the fastest in the next five years
  • 00:23:00
    to become a recognized talent in the era
  • 00:23:04
    of AI it is essential for students to
  • 00:23:07
    cultivate the following five abilities
  • 00:23:10
    1. problem solving students need to
  • 00:23:14
    learn how to identify and solve problems
  • 00:23:17
    this means being able to identify issues
  • 00:23:21
    and find solutions that work
  • 00:23:23
    2. creativity it is the ability to think
  • 00:23:27
    of new and original things
  • 00:23:30
    it's important for students to think in
  • 00:23:33
    unique and imaginative ways and come up
  • 00:23:35
    with fresh ideas
  • 00:23:38
    free critical thinking it is the ability
  • 00:23:41
    to analyze and evaluate information in a
  • 00:23:44
    logical way
  • 00:23:46
    4. communication it is the skill of
  • 00:23:49
    expressing ideas and thoughts
  • 00:23:51
    effectively
  • 00:23:53
    students should be able to clearly
  • 00:23:55
    convey their messages and understand
  • 00:23:57
    others perspectives using appropriate
  • 00:24:00
    language and listening actively
  • 00:24:03
    5. collaboration it is the ability to
  • 00:24:07
    work well with others
  • 00:24:10
    it involves cooperating communicating
  • 00:24:13
    and contributing as part of a team to
  • 00:24:15
    achieve shared goals
  • 00:24:18
    we are living in a society where we
  • 00:24:21
    compete with AI
  • 00:24:22
    in his book The World is Flat in 2000
  • 00:24:26
    Thomas Friedman noted the increasing
  • 00:24:29
    competition between students from China
  • 00:24:31
    and job seekers in the United States
  • 00:24:35
    this highlights the growing
  • 00:24:37
    globalization of the world
  • 00:24:40
    in today's rapidly advancing world of AI
  • 00:24:43
    it is crucial for us to find ways to
  • 00:24:46
    protect our jobs from being taken over
  • 00:24:48
    by AI
  • 00:24:50
    I hope today's lecture has offered some
  • 00:24:53
    guidance on how to navigate this
  • 00:24:55
    challenge
  • 00:24:56
    I will summarize what we have learned
  • 00:24:59
    about Industrial Revolution and AI
  • 00:25:02
    looking back at the past raw material
  • 00:25:05
    and component producers earned higher
  • 00:25:08
    profits than final product manufacturers
  • 00:25:11
    in the age of the fourth Industrial
  • 00:25:14
    Revolution companies that collect and
  • 00:25:16
    analyze data would generate wealth
  • 00:25:20
    AI involves computers performing tasks
  • 00:25:23
    that typically require human
  • 00:25:25
    intelligence
  • 00:25:27
    traditional programming involves
  • 00:25:30
    Specific Instructions while machine
  • 00:25:32
    learning allows computers to learn from
  • 00:25:34
    data
  • 00:25:36
    deep learning uses neural networks for
  • 00:25:39
    complex information processing
  • 00:25:42
    ularity suggests AI surpassing human
  • 00:25:46
    intelligence
  • 00:25:48
    chat GPT has the potential to
  • 00:25:51
    significantly impact our way of working
  • 00:25:53
    in the office
  • 00:25:55
    as we conclude this chapter it is
  • 00:25:58
    important to emphasize the cultivation
  • 00:26:00
    of human abilities such as creativity
  • 00:26:03
    and empathy in the age of AI
  • 00:26:06
    thanks for your listening
Etiquetas
  • AI
  • Data Analysis
  • Industrial Revolution
  • Machine Learning
  • Deep Learning
  • Chat GPT
  • Singularity
  • AI Applications
  • AI Skills
  • Ethics