Artificial Intelligence and Machine Learning are two emerging concepts which are playing a very crucial role since the Covid pandemic hit us. Both technologies are being used to study the new virus, test potential medical treatments, analyse impact on public health and so on. 

Today we look more in detail about two important technologies which are changing the way we look and perceive things and revolutionize the entire paradigm of industries, not just IT. We look at artificial intelligence and Machine learning and understand the difference between them , the purpose for which they are deployed and how they work etc.

About Artificial Intelligence  

Artificial intelligence is part of computer science which mimics human intelligence. And as its name suggests it means human made thinking power. Artificial intelligence is a technology which can help us to create intelligent systems which can simulate human intelligence. These systems are not pre-programmed but they use such algorithms such as reinforcement learning and deep learning neural networks. 

IBM Deep Blue which beat chess grandmaster Garry Kasparov in 1996 and Google DeepMind’s AlphaGo , which beat Sedol at Go in 2016 are all examples of narrow AI – skilled at one specific task. Based on its capabilities AI can be classified into below types – Artificial Narrow intelligence (ANI) or Weak AI, Artificial General intelligence (AGI) or General AI and Artificial Super Intelligence (ASI) or strong AI. Currently we are working on weak and General AI. The future of AI is strong AI which is going to be more intelligent than humans.

Applications of Artificial Intelligence 

• Map services
• Recommendation engines such as Amazon, Spotify , Netflix etc. 
• Robotics such as Drones, Sophia the robot
• Health care industry such as medical diagnosis, prognosis, precision surgery
• Autonomous systems such as autopilot, self-driving cars
• Research – drug discovery
• Financials – Stock market predictions 

About Machine Learning   

Machine learning is a subset of Artificial intelligence, in very simple words machines take data and learn for themselves. It is the most wanted and promising tool in the AI domain. ML systems can apply knowledge and training from large data sets , speech recognition, object recognition, facial recognition and many such tasks. ML allows systems to learn and recognize patterns and make predictions instead of hardcoding instructions for tasks completion.

In simple terms Machine learning can be defined as a subset of artificial intelligence which enables systems to learn from past data or experiences without being pre-coded with a specific set of instructions.  Machine learning requires the use of massive amount of structured and semi-structured data to perform predictions based on that data. ML can be divided into three types – supervised learning, reinforcement learning and unsupervised learning. ML is used at various places such as online recommendation systems for google search algorithm, email spam filtering, Facebook auto friend tagging suggestion etc. 

Applications of Machine Learning 

• Regression (Prediction)
• Classification (lesser number of classes , with less data)
• Control systems – Drones

Comparison Table: Artificial Intelligence vs Machine Learning

Below table summarizes the differences between the two terms:

FUNCTION	ARTIFICIAL INTELLIGENCE	MACHINE LEARNING
Definition	Artificial intelligence technology enables machine to simulate human behaviour	It is a subset of AI which let a machine to automatically learn from past data without any pre-coded instructions
Origin	Origin around year 1950	Origin around year 1960
Purpose	Make smart computer systems to solve complex problems like human beings	ML is used to allow systems to learn from data so that we can get accurate output without manual intervention
	It focuses on maximizing chances of success	It focuses on accuracy and patterns
Objective	Learning, reasoning and self-correction	Learning and self-correction when new data is introduced
Components	Artificial intelligence is subset of data science	Machine learning is subset of artificial intelligence and data science
Scope	Wide range of scope	Limited scope
Applications	Siri, customer support using catboats, expert system, online game playing, intelligent humanoid robot etc.	Online recommendation system, Google search algorithms, Facebook Auto friend suggestion, optical character recognition, web security, imitation learning etc.
Data types	Deals with structured, semi structured and unstructured data	Deals with structured and semi-structured data
Examples of algorithm	Q Learning, Actor critic methods, REINFORCE etc.	Linear regression, Logistics regression, K means clustering, Decision trees etc.

Download the comparison table: Artificial Intelligence vs Machine Learning

Conclusion

AI and ML are often confused terms but AI is a simulation of natural intelligence at par with humans and ML is an application of AI to give systems the ability to learn and understand things without any hard coded programming instructions. They evolve as they learn.

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