artificial intelligence (AI) and machine learning (ML)
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AI & ML – The Universal Language

Are you amongst those who think that Artificial Intelligence and Machine Learning are synonymous? To correct you here, AI and ML are two different technologies that cannot be used interchangeably while talking about software. If wondering why then don’t worry we have got you covered. In this blog, we have discussed Artificial Intelligence and Machine Learning, along with their differences.


Artificial Intelligence (AI)

As the name suggests, AI is a technology that imitates human behavior to perform tasks. Alexa, Siri, Self-driving cars, and robots are some of the many examples as they do not need to be programmed, they work on their intelligence.

There are three main types of AI:

Weak AI is aimed towards performing one task. Sometimes, it is considered artificial stupidity as it has limited function. Some of the smartest considered AIs of today’s world are weak AI. For example, Chatbot and Netflix Recommendations

General AI can replicate human behavior and abilities. No doubt, with face recognition, AI is learning to categorize but general AI is far from existence in the real world.

Super AI is also referred to as artificial superintelligence. This can easily compete with the most creative human ever and might even defeat him/her. However, super AI is a long way off from existing, if not at all.

Currently, we have only Weak AI in existence, but we might have General AI shortly.


Machine Learning (ML)

Machine Learning operates on historical data. It observes a pattern of instructions and provides better suggestions for the same search in the future. The main aim of ML is to learn from history and offer reliable results.

Three major areas of ML:

Supervised Learning uses labeled input and output data.

Unsupervised Learning does not use labeled input and output data. The machine is not supervised and learns on its own.

Reinforcement Learning neither learns on its own nor does it require supervision. It learns through trial and error.


Difference between AI and ML

Now that we have gained basic knowledge about AI and ML, it will be easier to understand the difference between the two technologies.

  • AI is focused on creating a machine that can think and behave like humans but at a faster rate. On the other hand, ML is focused on the development of computer systems that can work based on past data, without humans’ intervention.
  • The former aims for success, whereas the latter focuses on accuracy.
  • The result of AI is wisdom, whereas the result of ML is knowledge.
  • AI involves creating a system that can mimic humans. ML involves creating self-learning algorithms.
  • AI gives optimal solutions, but ML gives viable solutions.
  • An example of AI is Robots, whereas the main example of ML is Google Search Algorithms.
  • AI is more complicated as it works like an application that does smart work, whereas ML is simpler as it involves just taking data and learning from it.
  • AI can work with unstructured data, but ML cannot. It can work only with structured and semi-structured data.



To sum things up, the former solves tasks that require human intelligence while the latter is a subset of artificial intelligence that solves specific tasks by learning from data and making predictions. In other words, all machine learning is AI, but all AI is not machine learning.

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