[Quick Learnings] What is the Difference Between Machine Learning and Artificial Intelligence?

[Quick Learnings] What is the Difference Between Machine Learning and Artificial Intelligence?

Machine learning is an umbrella term that covers a wide range of techniques and algorithms used to develop computer programs capable of performing tasks without being explicitly programmed. 

Machine learning can be applied in a variety of application areas, including pattern recognition, classification and data mining. In fact, machine learning has been widely used for decades in fields such as natural language processing (NLP), speech recognition, information retrieval and multimedia analytics. However, it was not until the late 1980s that researchers began developing artificial intelligence systems based on machine learning techniques.

Artificial intelligence is the study of machines with intelligent behavior – computers that can learn from experience or interact with humans or other machines intelligently using their own means rather than simply following explicit programming instructions. 

In contrast to traditional approaches to AI research which focus on building general-purpose expert systems (e.g., knowledge representation) or even autonomous robots (e.g., self-driving cars), most modern AI applications are focused on specific domains: vision/image understanding; speech/language understanding; question answering; planning and scheduling; reasoning over uncertain situations; knowledge representation (including inductive logic programming); natural language processing; robotics control/motion planning etc.. The field also includes domain-specific subfields such as computational linguistics, computational neuroscience, evolutionary computation etc.