Artificial Intelligence VS Machine Learning

Artificial intelligence (AI) and machine learning (ML) are often used interchangeably, but they are both actually distinct, though related, concepts.

In simplest terms, AI is computer software that mimics the ways that humans think in order to perform complex tasks, such as analyzing, reasoning, and learning. Machine learning, meanwhile, is a subset of AI that uses algorithms trained on data to produce models that can perform such complex tasks. Today, most AI is performed using machine learning, so the two terms are often used synonymously, but AI actually refers to the general concept of creating human-like cognition using computer software and systems, while ML refers to only one method of doing so.

Further in this article, I will give you detailed information on AI and ML.

What is artificial intelligence?

Artificial intelligence (AI) is computer software that mimics human cognitive abilities in order to perform complex tasks that historically could only be done by humans, such as decision making, data analysis, and language translation.

In other words, AI is code on computer systems explicitly programmed to perform tasks that require human reasoning. While automated machines and systems merely follow a set of instructions and dutifully perform them without change, AI-powered ones can learn from their interactions to improve their performance and efficiency.

AI is an umbrella term covering a variety of interrelated, but distinct, subfields. Some of the most common fields you will encounter within the broader field of artificial intelligence include:

Machine learning (ML): a subset of AI in which algorithms are trained on data sets to become machine learning models capable of performing specific tasks.

Deep learning: A subset of ML, in which artificial neural networks (AANs) that mimic the human brain are used to perform more complex reasoning tasks without human intervention.

Natural Language Processing (NLP): A subset of computer science, AI, linguistics, and ML focused on creating software capable of interpreting human communication.

Robotics: A subset of AI, computer science, and electrical engineering focused on creating robots capable of learning and performing complex tasks in real world environments.

What is machine learning?

Machine learning (ML) is a subfield of artificial intelligence focused on training machine learning algorithms with data sets to produce machine learning models capable of performing complex tasks, such as sorting images, forecasting sales, or analyzing big data.

Today, machine learning is the primary way that most people interact with AI. Some common ways that you’ve likely encountered machine learning before include:

Receiving video recommendations on an online video streaming platform.

Troubleshooting a problem online with a chatbot, which directs you to appropriate resources based on your responses.

Using virtual assistants who respond to your requests to schedule meetings in your calendar, play a specific song, or call someone.