What is the difference between AI and ML?
- Advanced Analytics, Data Science
- ai, data science, machine learning
- 2 min reading time
Dr. Stefan Lieder
The following quote can already help to understand what distinguishes Artificial Intelligence from Machine Learning. More details can be found in this Wiki article.
"When you're fundraising, it's artificial intelligence. When you're hiring, it's machine learning. When you're implementing, it's linear regression."
Definition Artificial Intelligence (AI)
After previous articles on Artificial Intelligence (AI) and Machine Learning (ML), it is clear that you cannot define a difference if you lack a definition.
When differentiating AI and ML, the distinction between weak and strong artificial intelligence (AI) plays a role:
Strong Artificial Intelligence
But let's take as definition of Articifical Intelligence (AI) a cognitive system equal to humans. In that case, the difference to Machine Learning (ML) is very big. ML is an informatic/mathematical method to make predictions or decisions. For an AI, ML is then at most one tool among many to act autonomously in a higher-level, more holistic system. AI could therefore make use of ML to make a decision - but not necessarily.
With weak AI
If the definition of AI is that of weak AI, both terms, AI and ML, are often actually used to describe the same thing.
The specific use case is, for example, to relieve humans of the work of classifying an e-mail as spam. An "artificial intelligence" then takes over the task of reading the e-mail and assigning it a label. But in fact, what is actually meant is the operation of the algorithm that does the classification. And this is typically an ML algorithm.
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