Difference between Artificial intelligence and Machine learning

Difference between Artificial intelligence and Machine learning

Artificial Intelligence and Machine Learning are the two most important, hyped and interchangeably used words in the market right now. They have become a part of our daily lives,  but does that mean everyone understands it well? No, there still exists a lot of confusion between what exactly is Artificial Intelligence and Machine Learning. So, today we are going to look into their respective meanings and the vast differences. 

What is Artificial Intelligence and Machine Learning?

Artificial Intelligence

Artificial Intelligence is a computer science field where computer systems are made to mimic human intelligence and actions better than what humans perform now. The words ‘Artificial’ and ‘Intelligence’ simply implies using technology to make a man-made thinking power and intelligent systems which can stimulate human intelligence. 

AI does not need any pre-programming, instead, it uses algorithms which can efficiently work using their own intelligence. It includes Machine Learning algorithms like deep learning neural networks, reinforcement learning algorithms and more. It is used in multiple places like Google, Siri, Chess and more.

Based on abilities, Artificial Intelligence can be categorised into three types:

  • Weak AI
  • General AI
  • Strong AI

Machine Learning 

Machine Learning, on the other hand is extracting knowledge from the data i.e. it enables a computer system to make some decisions and make predictions based on pre-stored historical data. It uses a massive amount of structured and semi-structured data to give predictions and generate accurate results.  

Machine Learning operates on algorithms which learn on it’s own,using the historical data. It works for specific domains and platforms. For example. If we are creating a machine learning program to detect cat images, it will only give results for cat images unless we provide new data like a dog image. Then, it will become unresponsive. 

Machine Learning can be categorised into three types:

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning

Related Post- A Step by Step Guide: How to Hire a Mobile App Development Company

Applications 

Artificial Intelligence

Artificial Intelligence has proved to be a game changer in the business sector. Today businesses across the globe are deploying AI in at least one of their segments. Let’s quickly have a look at some of the applications of Artificial Intelligence

1. Chatbots

AI-powered chatbots in particular are actually benefiting businesses by reducing the job openings. They are always delivering smart and flexible analytics through text message conversations on mobile devices using different interfaces. This saves a huge chunk of time earlier people used to spend in collecting data for business users. But, now they can spend the same time planning for the growth of the company in the near future. 

2. HRM (Human Resource Management)

AI has impacted the HR sector in a massive way and for the most simplest of reasons, firstly being, there is tons of data to manage and secondly HR is the most integral part of any company yet they have to deal with a lot of work pressure. With AI in place, now HR’s can automate a huge part of the work and contribute quality time to hiring good employees and spending time in person necessary for a good work environment. 

Machine Learning 

Just like AI, let’s have a quick look at Machine Learning in action.

  1. Pinterest

I am pretty sure most people know this one. Machine Learning is used for improved content search/discovery. Whether you’re a regular on this or new, it’s quite simple to browse on Pinterest, how? It’s main function is to curate existing data. For example, if you browse a particular type of decor idea, it will show you tons of similar content from all the regions and so on.

  1. Facebook Chatbot Army

Facebook messenger is the most experimental chatbots testing laboratory. On facebook even a fairly new startup can set up their chatbot system to leverage the benefits and reap high results and profits. Not only this, AI is also used to filter out spam and poor quality content. 

Difference between AI and Machine Learning

Artificial IntelligenceMachine Learning
AI is a technology which enables the machine to clone human behaviour.ML is a subset of AI, and it allows a machine to automatically learn from the previously stored data. 
AI aims at making smart computer systems which can solve complex problems like humans.Whereas, ML aims at giving accurate output and predictions. 
Machine Learning and Deep Learning are the two subsets of AI.Deep Learning is the main subset of ML.
AI has a wide scope.ML has limited scope. 
AI works towards creating systems which can solve and perform complex activities.While, ML works towards creating machines that can perform the trained tasks efficiently. 
AI focuses on optimum chances of increasing the level of success.ML focuses on accuracy and patterns. 
AI deals with learning, reasoning and self-correction.ML deals with learning and self-correction when introduced to new data. 
AI works smartly works as a computer program.ML works as a concept helping the machine learn from data. 
AI works on Structured, Unstructured and Semi-Structured data. ML works on Structured and Semi-Structured data. 
Applications: Online gaming, Customer Support, Siri, Intelligent humanoid robot etc.Applications: Google search algorithms, Facebook auto friend tagging suggestions etc. 

I hope now that we have reached the end of the blog, you all have a better understanding of what exactly AI and ML are, and about their respective differences along with their applications. Both have varied uses with a few similarities. So, next time make sure to use the right term at the right place!

About the author

Director @Anyalpha, a Top Software Development Company offering  Mobile App Development and Website Development Services to Businesses & Startups.

Leave a Reply

Your email address will not be published. Required fields are marked *