Understanding The Difference Between AI, ML, And DL

 I debated whether to write this piece for a long time. This was due to several factors.

At a recent AI conference, I was asked to define Artificial Intelligence. I was initially taken aback as I would never expect someone attending an AI conference to ask what the meaning of AI is.  

However, after digesting his question and trying to formulate a clear answer, I realised the meaning of AI had not been clearly communicated by the community.

After several conversations with various people, I realised that he wasn’t the only person who did not understand Artificial Intelligence (AI) and its bedfellows, Machine Learning (ML) and Deep Learning (DL). I have even conducted a survey by asking 10 friends from various backgrounds if they knew the meaning and difference of these terms. My survey yielded ten distinct responses.

In addition, I have realised that these terms are frequently used interchangeably in social media when, in fact, they are all very different things.

WHAT DO THE TERMS AI, ML AND DL MEAN? HOW DO THEY RELATE TO EACH OTHER?

This article aims to explain the terms and the differences using simple examples.

“A picture is worth a thousand words.”

Let’s start with a diagram.

The image below shows concentric circles demonstrating h

ow AI, ML and DL relate to each other. The three technologies are connected in the same way that Russian Dolls are nested; each technology is essentially a subset of the preceding technology. AI is the largest “matryoshka,” whereas DL is the smallest.

WHAT IS ARTIFICIAL INTELLIGENCE (AI)?

AI is a broad field that includes ML and DL.

There are many formal definitions available for AI. For example, the Oxford English Dictionary defines AI as: “The theory and development of computer systems able to perform tasks normally requiring human intelligence.”

Merriam-Webster on the other hand defines AI as: “A branch of computer science dealing with the simulation of intelligent behaviour in computers.”

However, one of my favourite definitions is by François Chollet, creator of Keras, who defined it in simplistic terms. He described AI as “the effort to automate intellectual tasks normally performed by humans”.

WHAT IS MACHINE LEARNING (ML)?

One of the pioneers of ML, Arthur Samuel, defined it as a “field of study that gives computers the ability to learn without being explicitly programmed”.

As shown in the diagram, ML is a subset of AI which means all ML algorithms are classified as being part of AI. However, it doesn’t work the other way and it is important to note that not all AI based algorithms are ML. This is analogous to how a square is a rectangle but not every rectangle is a square.

SO, HOW IS ML DIFFERENT TO AI?

The key difference between AI and ML is that ML allows systems to automatically learn and improve from their experiences through data without being explicitly programmed.

WHAT IS DEEP LEARNING?

DL is ML taken to the next level. It is a subset of ML that is inspired by how human brains work. Typically, when people use the term deep learning, they refer to deep artificial neural networks. DL effectively teaches computers to do what humans naturally do: learning by example.

SO, HOW IS DL DIFFERENT TO ML?

The differences between DL and ML are summarised in the table below.

	Machine Learning	Deep Learning
Data	Performs well on small to medium datasets	Performs well on large datasets
Hardware	Able to function on CPU	Requires significant computing power e.g., GPU
Features	Features need to be manually identified	Learns features automatically
Training time	Quick to train	Computationally intensive

ARTIFICIAL INTELLIGENCE:

An AI-based algorithm is created that segregates the fruits using decision logic within a rule-based engine. For example, if an apple is on the conveyor belt, a scanner would scan the label, informing the AI algorithm that the fruit is indeed an apple. Then the apple would be routed to the apple fruit tray via sorting rollers/arms.

MACHINE LEARNING:

DEEP LEARNING:

• Compied By : Pushpendra Maurya