Week 1 - Video 1 - Introduction
By SK Collectives
Summary
## Key takeaways - **AI's Economic Impact: Trillions by 2030**: Artificial intelligence is projected to generate an additional 13 trillion US dollars in value annually by 2030, with significant impact expected beyond the software industry in sectors like retail, travel, and manufacturing. [00:50] - **AI is Narrow, Not General (Yet)**: Current AI advancements are primarily in Artificial Narrow Intelligence (ANI), which performs specific tasks, not in Artificial General Intelligence (AGI) capable of human-level versatility. Fears of 'evil killer robots' are largely unfounded given the distant timeline for AGI. [02:10], [03:20] - **AI's Reach: Few Industries Untouched**: It's challenging to identify industries where AI will not have a significant impact in the coming years, even extending to fields like hairdressing, where specialized robotics could potentially automate complex tasks. [01:22], [01:48] - **Focus on Realistic AI Capabilities**: To gain a realistic understanding of AI, it's crucial to examine both its successes and failures, rather than solely focusing on success stories, enabling more accurate judgments on technology application. [04:51], [05:03] - **Course Covers AI Basics to Strategy**: This course provides a comprehensive understanding of AI, from defining terminology and realistic capabilities to building AI teams, developing strategies, and navigating ethical considerations. [00:09], [06:17]
Topics Covered
- Is AI's true economic value shifting beyond software?
- Is any industry truly safe from AI's impact?
- Why is 'killer robot' fear based on a false premise?
- Why must we learn AI's limitations, not just its successes?
Full Transcript
welcome to a I thought everyone
AI is changing the way we work and live
and this non-technical course will teach
you how to navigate the rise of AI what
do you want to know what's behind the
buzzwords or what do you want to perhaps
use AI yourself either in the personal
context or the corporation or other
organization this course will teach you
how and if you want to understand how a
is affecting society and how you can
navigate that you also learn that from
this course in this first week we'll
start by cutting through the hype and
giving you a realistic view of what AI
really is let's get started you probably
seen news articles about how much value
a is creating according to a study by
McKinsey Global Institute a is estimated
to create an additional 13 trillion US
dollars of value annually by the year
2030
even though AI is already creating
tremendous amounts of value into
software industry a lot of the value to
be created in the future lies outside
the software industry in sectors such as
retail travel transportation
automotive materials manufacturing and
so on I should have a hard time thinking
of an industry that I don't think AI we
have a huge impact on in the next
several years my friends and I used to
challenge each other to name an industry
where we don't think AI web a huge
impact and my best example was the
hairdressing industry because you know
how to use AI robotics to automate
hairdressing but I once set this on
stage and one of my friends who is a
robotics professor was in the audience
that day and she actually stood up and
she looked at me in the eye and she said
you know Andrew most people's hairstyles
I couldn't get a robot to cut their hair
that way but she looked me and said your
hairstyle and you know that a robot can
do there is a lot of excitement but also
a lot of unnecessary hype about AI one
of the reasons for this is because AI is
actually two separate ideas almost all
the progress we are seeing in the AI too
is artificial narrow intelligence these
are a is that do one thing such as a spa
speaker or a self-driving car or AI to
do web search or air applications in
farming or in a factory these types of
AI are one-trick ponies but when you
find the appropriate trick this can be
incredibly valuable
unfortunately AI also refers to a second
concept of AGI or artificial general
intelligence that is the goal to build
AI they can do anything a human can do
or maybe even be super intelligent and
do even more things than any human can
I'm seeing tons of progress in a ni
artificially narrow intelligence and
almost no progress toward AG AI or
artificial general intelligence both of
these are worthy goals and unfortunately
the rapid progress in a ni which is
incredibly valuable that has caused
people to conclude that there's a lot of
problems in AI which is true but that
has caused people to falsely think that
there might be a lot of progress in AGI
as well which is leading to some
irrational fears about evil killer
robots coming over to take over humanity
any time now
I think AGI is an exciting golf and
research to work on but it'll take most
whole technological breakthroughs before
we get there and it may be decades or
hundreds of years or even thousands of
years away given how far away AGI is I
think there is no need to unduly worry
about it in this week you will learn
what a ni can do and how to apply them
to your problems later in this course
you also see some case studies of how
Ani these one-trick ponies can be used
to build really valuable applications
such as smart speakers and self-driving
cars in this week you will learn what is
AI you may have heard of machine
learning and the next video will teach
you what is machine learning you also
learn what is data and what types of
data are available but also what has the
data on
not valuable you learn what it is that
makes a company and a company or an AI
first company so that perhaps you can
start thinking if there are ways to
improve your company or other
organizations ability to use AI and
importantly you also learned this week
what machine learning can and cannot do
in our society newspapers as well as
research papers tend to talk only about
the success stories of machine learning
and AI and we hardly ever see any
failure stories because they just aren't
as interesting to report on but for you
to have a realistic view of what AI and
what machine learning can I cannot do I
think is important that you see examples
of both so they can make more accurate
judgments about what you may and maybe
should not try to use these technologies
for finally a lot of the recent rise of
machine learning has been driven through
the rise of deep learning sometimes also
called
neural networks in the final two
optional videos of this week you can
also see an intuitive explanation of
deep learning so that you will better
understand what they can do ask early
for a set of narrow Ani toss so that's
what you learn this week and by the end
of this week you have a sense of AI
technologies and what they can and
cannot do in the second week you learn
how these AI technologies can be used to
build valuable projects you learn what
it feels like to build an AI project as
well as what you should do to make sure
you select projects that are technically
feasible as well as valuable to you or
your business or other organization
after learning what it takes to build AI
projects in the third week you learn how
to build AI in your company in
particular if you want to take a few
steps toward making your company good at
AI you see the AI transformation
playbook and learn how to build AI teams
and also build complex AI products
finally a is having a huge impact on
society
in the fourth and final week you learn
about how a I systems can be biased and
how to diminish or eliminate such biases
you also learn how a eye is affecting
developing economies and how AI is
affecting jobs and be better able to
navigate this rise of AI for yourself
and for your organization by the end of
this four-week course you'll be more
knowledgeable and better qualified than
even the CEOs of most large companies in
terms of your understanding of AI
technology as well as your ability to
help yourself or help your company or
other organization navigate the rise of
AI and so I hope that after this course
you'll be in a position to provide
leadership to others as well as they
navigate these issues now one of the
major technology is driving the recent
rise of AI is machine learning but what
is machine learning let's take a look in
the next video
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