Artificial intelligence and machine learning are two aspects of computer science that are related. These two technologies are the most common when it comes to developing intelligent systems.
Even though these are two connected technologies that are often used interchangeably, they are nevertheless two different words in some situations.
Artificial intelligence is a branch of computer science that aims to create a computer system that can think like a person. It is made up of the terms “artificial” and “intelligence,” which together mean “human-made thought capacity.” As a result, we can describe it as a technology that allows us to build intelligent systems that can simulate human intelligence.
Artificial intelligence systems do not need to be pre-programmed; instead, they employ algorithms that operate in conjunction with their intelligence. ML algorithms’ primary examples include Reinforcement learning algorithms and deep learning neural networks. Siri, AI in chess, Google’s AlphaGo, and other applications of AI are all examples.
AI can be divided into three categories based on its capabilities:
- Weak AI
- General AI
- Strong AI
We are currently operating with both poor and general AI. Strong AI is the future AI, and it is predicted that it will be more intelligent than humans.
The goal of machine learning is to extract information from data. Machine learning is a branch of artificial intelligence that allows computers to learn from previous data or experiences without being specifically programmed.
Without being precisely programmed, machine learning allows a computer system to make predictions or make decisions based on historical data. Machine learning makes use of a large number of structured and semi-structured data for a machine learning model to produce accurate results or make predictions on the basis of it.
ML is based on an algorithm that learns on its own with the help of historical data. It only works for specific domains; for example, if we create a machine learning model to detect dog pictures, it will only return results for dog pictures; however, if we include new data, such as a cat picture, it will become unresponsive. Machine learning is used in various applications, including online recommender systems, Google search algorithms, email spam filters, and Facebook auto friend tagging suggestions, among others.
It is divided into three categories:
- Supervised learning
- Reinforcement learning
- Unsupervised learning
Artificial Intelligence vs. Machine Learning
- Artificial intelligence (AI) is a technology that allows machines to mimic human behavior. On the other hand, machine learning is a subset of AI that allows a machine to learn from past data without having to program it directly.
- AI aims to create an intelligent computer system that can solve complex problems in the same way humans can. The aim of machine learning, on the other hand, is to enable machines to learn from data so that they can produce accurate results.
- In AI, we create intelligent systems that can perform any task the same way a person can. In ML, on the other hand, we use data to teach machines how to perform a specific task and provide an accurate result.
- The two major subsets of AI are machine learning and deep learning. Machine learning includes deep learning as a branch.
- AI has a wide variety of applications. Machine learning, on the other hand, has restricted use.
- AI is attempting to develop an autonomous machine capable of performing a variety of complex tasks. On the other hand, machine learning aims to build computers that can only perform the tasks for which they have been programmed.
- The AI system is concerned with increasing the likelihood of success. Machine learning, on the other hand, is primarily concerned with precision and patterns.
- Siri, customer service through catboats, Expert Systems, online gameplay, intelligent humanoid robots, and other AI applications are among the most popular. Machine learning’s key implementations, on the other hand, include online recommender systems, Google search algorithms, and Facebook auto friend tagging recommendations, among others.
- Weak AI, General AI, and Strong AI are the three types of AI that can be classified based on their capabilities. On the other hand, machine learning is categorized into three types: supervised learning, unsupervised learning, and reinforcement learning.
- Learning, thinking, and self-correction are all aspects of AI. When presented with new data, ML involves learning and self-correction.
- Structured, semi-structured, and unstructured data are all dealt with by AI. ML, on the other hand, works with structured and semi-structured data.