Home > Posts > Artificial Intelligence > Difference Between AI and Machine Learning

Difference Between AI and Machine Learning

Artificial intelligence is the creation of cooperation and interaction between human and machine. It is a technology for the service of humanity and for the convenience of humans to handle many activities in their daily life through machines. Machine learning is a sub-technology of artificial intelligence that makes the machine with time evolve, learn, observe, analyze and give results for all of this.

Machine Learning (ML) is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning using rules to reach approximate or definite conclusions and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision.

Difference Between AI and Machine Learning

Machine Learning

ML is based on a neural network which is a system of hardware and/or software patterned after the operation of neurons in the human brain. the neural network is built for training and learning, it relies on certain factors of importance to determine the probable outcome of a situation and needs to be programmed by humans first. the following steps are the definition of ML.

  • ML stands for Machine Learning which is defined as the acquisition of knowledge or skill.
  • The aim is to increase accuracy, but it does not care about success.
  • It is a simple concept machine takes data and learn from data.
  • The goal is to learn from data on a certain task to maximize the performance of machine on this task.
  • It allows the system to learn new things from data.
  • It involves creating self-learning algorithms.
  • It will go for the only solution for that whether it is optimal or not.
  • ML leads to knowledge.

Some of the machine learning applications

  • Image Recognition. 
  • Speech Recognition. 
  • Medical Diagnosis. 
  • Statistical Arbitrage. 
  • Learning Associations. 
  • Classification.
  • Prediction. 
  • Extraction.

Artificial Intelligence

AI includes a considerable measure of technology advances, Machine learning is only one of them. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider smart.  the following steps are the definition of AI.

  • Intelligence is defined acquisition of knowledge intelligence is defined as an ability to acquire and apply knowledge.
  • The aim is to increase the chance of success and not accuracy.
  • It works like a computer program that does smart work.
  • The goal is to simulate natural intelligence to solve a complex problem.
  • AI is decision making.
  • It leads to developing a system to mimic human to respond behave in a circumstances.
  • AI will go for finding the optimal solution.
  • AI leads to intelligence or wisdom.

Some of the artificial intelligence applications

  • Knowledge reasoning.
  • Planning.
  • Machine learning.
  • Natural language processing.
  • Computer vision.
  • Robotics.
  • Artificial general intelligence.
error: Content is protected !!