So we’ve all heard of things like Siri, Alexa, self-driving cars, Netflix, Google,
and Instagram. In the last video, I told you the secret to the success of all of these
cool gadgets and apps – Artificial Intelligence. Wouldn’t it be cool to know how exactly
how these things work? How can Alexa understand what we’re saying and talk back to us, as
though she’s just any other human? How can a car possibly drive itself? Well, the answers
to all these questions lie in the inner workings of the many powerful branches of Artificial
Intelligence. Here’s a depiction of the primary branches of AI. Note that the intersection
of the branches depicted here is subject to interpretation, and you may see differences
in the way these are presented elsewhere. But the goal with this video is to provide
you an introduction to the basics of each of this. I’d also like you to note that
the field of AI is significantly more vast than the previous diagram, as you can see
here, but we’ll come to that in later videos.
So for AI to drive the world’s most advanced technology, it must be some kind of superpower
right? Yes, but it’s not just a single unit that runs the show. AI has hundreds of branches
that each serve different purposes and come together at the end to create something wonderful.
Its these branches that make AI a little less artificial and that much more intelligent.
The easiest way to think about it would be to compare it to a human. After all, AI machines
try to work and act just like humans. This is Steve. When Steve is born, he enters a
whole new world of strange sights and sounds. As he grows up, he starts to understand human
language and learn to communicate with others. This is one of the most basic and easy actions
for a human to grasp. But for computers? Not so easy. Well, that’s until the emergence
of AI. With Natural Language Processing, or NLP, it all changes. NLP is the branch of
AI that deals with the interaction between humans and computers. Basically, there are
two primary ways in which humans interact with computers – through text and voice.
Let’s look at text first. When the computer receives the text input, it processes it using
various techniques such as parsing, segmentation, stemming etc., which all broadly come under
this field of NLP.
Next, let’s look at voice input. When the computer receives the voice input, it captures
the audio and converts it into text. The steps we just talked about for processing text repeats.
Finally, the machine translates its response into an audio file that it plays back to the
human.
Let’s look at a few practical examples you may be familiar with. Ever used Google Translate,
Microsoft Word, Siri, or Grammarly? Well, these apps are possible thanks to Natural
Language Processing (show branch here).
Now we know that in the case of text input, NLP enabled the machine to take in a statement,
figure out its meaning, and respond back with valuable output. But in the case where the
input was voice, how did the machine actually understand the sounds coming out of a person’s
mouth? I mean humans can hear words understand the meaning and intent of those words. But
how does a computer know how to put different vowel and consonant sounds together to form
complete words and sentences in our human language? Well this takes us to our next branch
– Speech Recognition – that allows the computer to do just this. When [insert name
here] speaks, the computer is able to understand and process his words using Speech Recognition
and can output valuable information that [name] can understand. At a high level, Speech Recognition
uses a tool called a spectrogram to plot frequencies of sounds. It them compares these frequencies
to established vowel and consonant sounds to figure out what sounds the person made.
Finally, it connects these sounds together to form complete words and eventually sentences
that NLP then uses to figure out the meaning of the words. So now, you’ve learned the
fundamentals of Speech Recognition that allows the computer to understand human sounds. Now,
back to Steve. So, as Steve grows, he also learns to see
and interpret different things around him. This ability is something that most humans
take for granted. But just imagine how different life would be if we couldn’t see anything
around us or understand what they are. Well, this was the case for computers for most of
history. They could not process much of the data available, such as images and videos
of people, plants, animals, etc., making them extremely limited in their abilities. But
then came the branch of AI called computer vision that changed it all. Computer vision
gives machines the ability to acquire, process, and analyze digital images. They can then
use this information to find patterns, and make decisions. How does an iPhone unlock
itself as soon as you show it your face? Computer vision. How does a self-driving car know exactly
where to go? Computer vision. So, as you can see, computer vision is incredibly powerful
and can do amazing things.
So I’ve told you that computer vision gives a self-driving car the ability to detect objects
around it, but how does the car have the ability to drive itself, without anyone powering its
movement? This is because of the branch of robotics and autonomous systems. Autonomous
robots sense their environment by using various technologies, such as cameras, infrared and
ultrasound sensors, scanners, and microphones. Additionally, they use Computer Vision to
“see” any obstacles in their way. Just like how Steve is able to move about on his
own, these branches give the car the ability to move on its own. So this is a brief introduction
to the subfields of robotics and autonomous systems, in the AI realm.
So, we’ve seen that the Computer, using the power of NLP, Speech Recognition and Computer
Vision can intelligently process text, voice and images. Often times, with these data types,
there are also patterns that would be helpful for the computer to understand. For example,
irregularities in a medical scans could be immensely useful in early detection of potential
health issues, or perhaps detection of patterns of word usage in emails can help detect if
the email should be auto classified as spam or not. These are made possible using the
field of AI called Pattern Recognition. So, Pattern Recognition allows the machine to
recognize regularities and irreregulaties of data. And finally, onto our our last branch
of AI, arguably the most powerful one.
Now, we all know that humans have the ability to distinguish between things that are different.
For example, it is easy for us to identify a dog versus a cat. Throughout our lives,
we’ve been shown numerous images of both of these animals, so by now, we know exactly
how to tell them apart. But, until now, it’s not been so simple for a computer because
a computer didn’t have the intelligence to pinpoint exactly what differentiates between
the two enough to identify an animal given a picture that its never seen before. That
is, until the branch of Machine Learning developed. Just as a human does, Machine Learning allows
computers to learn from experience. Basically, humans can feed a computer hundreds of images
of cats and dogs, and eventually, the computer will learn how to distinguish between the
two. And over time, it gets better and better. So at a high level, this is the essence of
this large branch. So now you’ve learned about the basics o the primary subfields of
AI. As a quick summary, we have NLP, which allows computers to interact with humans;
Speech Recognition, which allows machines to understand the human sounds; Computer Vision,
which allows machines to see and process images and videos, Pattern Recognition, which allows
computers to analyze regularities and patterns, Robotics and Autonomous Systems, which allow
machines to move about on their own, and Machine Learning, which allows computers to predict
and improve themselves based on data and experience.
So now that you know the basics of AI, you are well prepared to start learning about
the branches of AI in more depth. Over the course of the next few videos, we are going
to dive into the branch of Natural Language Processing. At the end of the series, we have
an interesting project that’ll tie everything together and give you something cool to show
your friends and family, so stay tuned for that! So, whenever you are ready, you can
delve into the world of NLP by clicking on this next video. If you’ve liked the content
in this video, give it a thumbs up and comment down below what branch sounds the most interesting
to you and if you’ve ever seen something powered by that branch. If you are new here,
then make sure to subscribe and turn on notifications so you don’t miss any videos that’ll help
you on your journey towards mastering artificial intelligence. Thanks for watching, and I’ll
see you in the next one.