AI on the left is struggling to answer.
ML enjoys the put-down session!
Artificial Intelligence (AI) vs. Machine Learning (ML) - Introduction
You might hear people use artificial intelligence (AI) and machine learning (ML) interchangeably, especially when discussing big data, predictive analytics, and other digital transformation topics. The confusion is understandable as artificial intelligence and machine learning are closely related. However, these trending technologies differ in several ways, including scope, applications, and more.
Increasingly, AI and ML have proliferated as businesses use them to process and analyze immense volumes of data, drive better decision-making, generate recommendations and insights in real time, and create accurate forecasts and predictions.
Source: https://cloud.google.com/learn/artificial-intelligence-vs-machine-learning
What is the theory of man vs machine?
- Humans understand the situation and respond accordingly whereas machines do not have the capability of understanding. Humans are creative and imaginative.
- They can create and invent new things but machines cannot do such types of work because they use artificial intelligence.
- Machines are operated and guided by humans.
Key Differences
While AI and ML are related, they have distinct characteristics:
Artificial Intelligence (AI)
- Broader concept of machines being able to carry out tasks in a way that we would consider "smart"
- Includes everything from rule-based systems to advanced neural networks
- Aims to create systems that can function intelligently and independently
Machine Learning (ML)
- Subset of AI that focuses on the development of systems that can learn from data
- Uses statistical methods to enable machines to improve with experience
- Currently the most practical and successful application of AI