Artificial Intelligence (AI) vs Machine Learning (ML) vs Deep Learning (DL)

Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are three terms people use as synonyms although they don’t refer to the same things.
I will try to explain and unfold the difference between these terms

So, what’s the difference between these three concepts?

From: Towards Data Science.

The image above shows that the three concepts are strictly related. However, DL is a subset of ML, which is a subset of AI.
In this post, we’ve defined these three concepts and outlined their applications.

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, including learning, reasoning and self-correction. AI can be of two types: weak AI and strong AI. Weak Artificial Intelligence refers to an AI system developed for a specific task. Strong Artificial Intelligence is an AI system with generalized human cognitive skills.

In simpler terms, AI is the broader concept of machines being able to carry
out tasks in a way that we would consider "smart". Machine acting like human is AI.

 Application 

AI is usually adopted to solve customer service issues, inform people about the latest news along with giving them live traffic updates and weather forecast.

Real World AI Applications

• Alexa and Google Voice Assistant
• Tesla self-driving cars
• Airplane autopilot mode
• Email spam folder
• Facebook picture face-recognition
• Instagram Explore page curation

What is Machine Learning (ML)?

Machine learning (ML) is an application of Artificial Intelligence (AI) generating systems that can learn and improve without being programmed. Contrary to AI, ML concentrates on developing computer programs that access data and use it to learn for themselves.

In simpler terms, ML is an application of AI that provides system the ability to automatically learn and improve from experience without being explicitly programmed.

Application 

Machine Learning is often used to power recommendation engines that provide suggestions based on past customers’ behaviors. 

Lets Dive into an example

 I have an alexa at home, so while doing my morning exercise I ask alexa to 'play music'. 

Alexa plays the music at volume 8. But that's too loud, so I ask alexa to change the volume to 5. This happens multiple mornings, so one day when i ask alexa to change the volume, she asks 'Should I change the default volume to level 5'

Here Alexa learned from my behaviour (ML) and applied human intelligence (AI).

What is Deep Learning (DL)?

Deep Learning (DL) is a subset of Machine Learning and Artificial Intelligence. The term refers to a particular approach used for creating and training neural networks that are considered highly promising decision-making nodes.

Application

Deep Learning is used to develop highly automated systems such as self-driving cars. Through their sensors and onboard analytics, these cars can reorganise obstacle and facilitate situational awareness.

In conclusion, Artificial Intelligence, Machine Learning and Deep Learning are three different terms that need to be fully understood and used separately.