It’s very common to hear the terms “machine learning” and “artificial intelligence” thrown around in the wrong context. It’s an easy mistake to make, as they are two separate but similar concepts that are closely related. With that said, it’s important to note that machine learning, or ML, is a subset of artificial intelligence, or AI.
To understand these two concepts better, let’s first define each one:
Many definitions of artificial intelligence have popped up over the years, which is one of the reasons it can seem somewhat complicated or confusing. But in its simplest form, AI is a field that combines computer science and robust datasets to achieve effective problem-solving.
Today’s field of artificial intelligence includes sub-fields like machine learning and deep learning, which involve AI algorithms that make predictions or classifications based on input data.
AI is sometimes broken down into different types, such as weak AI or strong AI. Weak AI, which is also referred to as Narrow AI or Artificial Narrow Intelligence (ANI), is AI that has been trained to perform specific tasks. It is the most apparent form of AI in our daily lives, enabling applications like Apple’s Siri and autonomous vehicles.
Continue reading: https://www.unite.ai/machine-learning-vs-artificial-intelligence-key-differences/
To understand these two concepts better, let’s first define each one:
- Artificial Intelligence (AI): AI is any software or processes that are designed to mimic human thinking and process information. AI includes a wide range of technologies and fields like computer vision, natural language processing (NLP), autonomous vehicles, robotics, and finally, machine learning. AI enables devices to learn and identify information to solve problems and extract insights.
- Machine Learning (ML): Machine learning is a subset of AI, and it is a technique that involves teaching devices to learn information given to a dataset without human interference. Machine learning algorithms can learn from data over time, improving the accuracy and efficiency of the overall machine learning model. Another way of looking at it is that machine learning is the process that AI undergoes when performing AI functions.
Many definitions of artificial intelligence have popped up over the years, which is one of the reasons it can seem somewhat complicated or confusing. But in its simplest form, AI is a field that combines computer science and robust datasets to achieve effective problem-solving.
Today’s field of artificial intelligence includes sub-fields like machine learning and deep learning, which involve AI algorithms that make predictions or classifications based on input data.
AI is sometimes broken down into different types, such as weak AI or strong AI. Weak AI, which is also referred to as Narrow AI or Artificial Narrow Intelligence (ANI), is AI that has been trained to perform specific tasks. It is the most apparent form of AI in our daily lives, enabling applications like Apple’s Siri and autonomous vehicles.
Continue reading: https://www.unite.ai/machine-learning-vs-artificial-intelligence-key-differences/
