Blog : Artificial Intelligence vs Machine Learning vs Deep Learning

Artificial Intelligence vs Machine Learning vs Deep Learning

Introduction

Artificial intelligence is the notion of producing intelligent machines that are clever. Machine Learning is a subset of artificial intelligence that aids in the development of AI-driven applications. Deep Learning is a subclass of machine learning that trains a model using massive amounts of data and advanced methods.

AI learning vs Machine Learning

AI is an umbrella term for computer software that mimics human intellect in order to accomplish complicated tasks and learn from them. Machine learning (ML) is a subsection of AI that use data-trained algorithms to create flexible models capable of performing a wide range of complicated tasks.

AI vs ML vs DL

Companies and developers all around the world are talking about embracing artificial intelligence (AI), machine learning (ML), and deep learning (DL) in this new era of technology. All of these abbreviations are often used in the realm of technology. It is critical to recognise that all of these abbreviations are part of the Artificial Intelligence (AI) umbrella.

AI is a broad field that encompasses everything related to making machines intelligent. Machine Learning (ML) is frequently used in conjunction with AI, however it is a subset of AI. An AI system that can self-learn based on an algorithm is referred to as ML. ML refers to systems that become smarter and wiser over time without human involvement. Deep Learning (DL) is a type of machine learning (ML) that is used on enormous data sets. Because intelligent behaviour necessitates extensive information, ML is used in the majority of AI projects.

1. AI (Artificial Intelligence)

Since the dawn of technology, humans have been preoccupied with automation. AI allows robots to think without the need for human interaction. It is a vast field of study in computer science. There are three types of AI systems: ANI stands for Artificial Narrow Intelligence, and it is goal-oriented and trained to execute a specific job. AGI (Artificial General Intelligence) is the ability of machines to learn, comprehend, and behave in situations where they are indistinguishable from humans. ASI (Artificial Super Intelligence) is a hypothetical AI in which robots can outperform the smartest humans in intelligence.


2. ML (machine learning)

ML is a branch of AI that use statistical learning methods to create intelligent systems. ML systems can learn and improve themselves without being explicitly coded. ML is used in recommendation algorithms on music and movie streaming services. There are three types of machine learning algorithms: supervised, unsupervised, and reinforcement learning.


3. DL (Deep Learning)

This AI subset is a strategy inspired by the way the human brain filters information. It is linked to learning through examples. DL systems assist a computer model in filtering incoming data through layers in order to forecast and categorise data. Deep Learning processes data in the same way that the human brain does. It is utilised in technologies like as self-driving automobiles. Convolutional Neural Networks, Recurrent Neural Networks, and Recursive Neural Networks are the three types of deep learning network designs.