Artificial Intelligence (AI) and Machine Learning (ML) are two of the most well-known buzzwords in emerging technologies and are often used interchangeably. They’re helping organizations streamline processes and make better business decisions. They’re advancing nearly every industry by helping them work smarter, and they’re becoming essential technologies for businesses to maintain a competitive edge. AI is transiting from just a research topic to the early stages of enterprise adoption. Tech giants like Google and Facebook have placed huge bets on Artificial Intelligence and Machine Learning and are already using it in their products. But this is just the beginning, over the next few years, we may see AI steadily glide into one product after another.

What is Artificial Intelligence (AI)?

Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. It is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech-recognition and machine vision.

Simply put, the intelligence demonstrated by machines is known as Artificial Intelligence. Artificial Intelligence has grown to be very popular in today’s world. It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. AI manifests in a number of forms.

What is Machine Learning (ML)?

Machine learning is a subset of artificial intelligence focused on building systems that can learn from historical data, identify patterns, and make logical decisions with little to no human intervention. It is a data analysis method that automates the building of analytical models through using data that encompasses diverse forms of digital information including numbers, words, clicks and images.

Machine learning basically is a combination of multiple technologies namely artificial intelligence, data analytics, programming, etc. To put it in simple words, machine learning is a science through which you train machines, specifically computers to learn from voluminous data and predict outcomes that can solve a given problem in the best possible.

How are AI and machine learning connected?

An “intelligent” computer uses AI to think like a human and perform tasks on its own. Machine learning is how a computer system develops its intelligence.

Differences between Artificial Intelligence and Machine Learning

On a broad level, we can differentiate both AI and ML as:

“AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behaviour, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.”

1. Concept

Artificial Intelligence is a technology that enables a machine to simulate human behaviour. Machine learning is an AI subset that allows a machine to automatically learn from past data, without explicit programming.

2. Goal

AI aims to make a smart computer system, not unlike humans, that can solve complex problems. Machine learning aims to allow machines to learn from data, so that they may give an accurate output.

3. Subsets

Machine learning and deep learning are the two main subsets of AI. On the other hand, deep learning is the main subset of machine learning.

4. Scope

When it comes to scope, AI has a wider range than machine learning. AI works to create an intelligent system that can perform various complex tasks, to maximise the chances of success. Machine learning has a limited scope and deals with creating machines to perform only those specific tasks for which they have been trained. Machine learning is concerned with accuracy and patterns.

5. Categories

On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI. Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, and Reinforcement learning.

6. Applications

The main applications of AI are Siri, customer support chat-bots, online gaming, intelligent humanoid robots, etc. The main applications of machine learning are Google search algorithms, Facebook auto friend-tagging suggestions, online recommender systems, etc.

Wrapping it up

Though Machine Learning and Artificial Intelligence (AI and ML) sound different, they are closely interconnected. AI is the concept of computers being able to perform tasks in a way that we would consider ‘smart.’ While ML is the current application of AI-based machines, learning and improving through collecting Big Data. Voice assistants like Alexa, Siri, and Google Assistant are a few examples of AI-based applications. On the other hand, Netflix recommendations, Amazon Prime shopping recommendations are examples of applications of Machine Learning.

Machine Learning & AI holds a promising future for anyone who is interested in playing with data and technology. If you wish learn more about AI and ML, contact Agilis World Inc. today.