In today’s fast-evolving tech landscape, understanding the difference between Machine Learning (ML) and Artificial Intelligence (AI) is crucial. While often used interchangeably, they serve different purposes. Let’s break it down!

🌟 Machine Learning (ML):

• ML is the process of acquiring knowledge from data. 📊
  Machine learning involves feeding large amounts of data into algorithms that learn from it. The system improves over time based on patterns it recognizes in the data.

• ML learns from data to perform just one task. 🎯
  Unlike AI, which can handle multiple tasks, ML typically focuses on improving performance in a single area—like recognizing objects in images or predicting future trends.

• The goal of ML is to acquire knowledge. 💡
  ML systems continuously learn from data, refining their models to become more accurate and efficient.

🌟 Artificial Intelligence (AI):

• AI is the process of applying that knowledge. 🧠
  Artificial intelligence uses knowledge gained (from ML or other sources) to make decisions or solve complex problems. It’s about taking action based on learning.

• AI imitates natural intelligence to do many tasks. 🤖
  AI systems can perform a variety of tasks that would require human intelligence, such as driving cars, diagnosing diseases, or managing smart homes.

• The goal of AI is to attain wisdom. 🎓
  AI seeks to achieve human-like decision-making abilities by continuously processing and analyzing vast amounts of information.

Want to learn more about cutting-edge technology? Stay connected with Gleez Technologies for more insights! 💻