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,
and we'll do our best to help.
And if you want to catch the next episode,
be sure to subscribe.
I'll begin by exploring the hype cycle
and how it impacts how the world talks
about artificial intelligence.
The hype cycle curve is here.
It starts with a technology trigger,
and this is when breakthroughs or new inventions happen.
For example, think about the invention of the smartphone.
People didn't really know what it was all about when it first
came on the scene.
There was a lot of rhetoric about how
the phone might replace the need for desktop and laptop
computers.
You could plug a keyboard and a screen into the phone,
and then you could just do your work.
That kind of talk resulted in this,
and it's called the peak of inflated expectations.
It's the epitome of hype, where the realities of the technology
are drowned out by hyperbole, the possibilities
are generally overstated, and the implications
are often feared.
The history of technology is littered with innovations that
fail to get past this peak.
When reality sets in, we fall into this,
the spectacularly named trough of disillusionment.
And as the name suggests, this is the reality check.
It's when one realizes that maybe
all of those grandiose ideas that you thought
were possible with the technology failed
to materialize.
And it's where people often give up,
and where what seemed to be the latest, greatest,
and hottest of ideas get consigned to the graveyard
of history.
But then some people realizing the limitations
begin to innovate around them, and they
start rising up the slope of enlightenment
to the plateau of productivity.
They develop a new innovation that works,
and they succeed with it.
For example, with the mobile phone much of the hype bubble
burst when people began to realize
it wasn't powerful enough to replace
the laptop or the desktop, or it was limited by battery life,
or things like multiple concurrent apps
could not run effectively due to resource constraints.
And all of those revolutionary ideas died.
But then some people realize that the phone
had a GPS, so applications around location,
such as navigation apps, became possible,
or even something that lets you tell someone
where you are so a driver can come and pick you up.
The idea of standing on a corner with your hand raised
in the hope that a cab might pass by and pick you up
was suddenly antiquated.
Whole new industries were born as a result of the smartphone,
and they were born by people who,
upon falling into the trough, did not give up.
They realized the realities and not the hype,
and they then turn those into a strength.
But here's a little secret.
They're not necessarily more intelligent or better
than the rest of us.
They just didn't give up when they
hit the trough of disillusionment,
and they continued along the curve.
With AI, most of the world is here today
looking up at that peak of inflated expectations.
It's blocking the way towards productivity.
So in this video series, I'm going to get you here.
Yep, you're going to be disillusioned.
And that's OK, because that's when you will understand what
AI is, what it isn't.
And maybe, just maybe, when you have a clearer understanding
of what's possible that will open you
up to developing new ideas, like these students
in India, who use machine learning on a phone
to help their families navigate air quality and pollution
issues.
Or this farmer in Japan, who didn't
have enough resources to sort out his cucumbers for sale
in the markets, so he designed and built
a machine using machine learning to do it for him.
And of course, there's this young woman
in Uganda, who harnessed the power of AI
to help farmers in her country identify and prevent
crop-destroying pests.
The possibilities are endless, and you
can have a part in this.
So please like, subscribe, and share, and most of all,
enjoy this series.
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