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What is Machine Intelligence?

AI and Machine Learning

February 19, 2025

what is machine learning

Do you ever wonder what separates humans from other species on this planet?

There is just one thing that separates us all from other living organisms: Intelligence.

Humans have mastered a distinct level and evolution of intelligence. Our ability to comprehend something, think about it, learn something, process information, apply experience, make reasonable decisions, act on a situation, and improve our ability to do it all should explain the term Intelligence. On a typical day, we can do nothing without our intelligence.

What is Intelligence? 

In simple terms, intelligence is the ability to comprehend, visualize, process, memorize, learn, and apply learning. So, this word comes in a variety of shades. Broadly, intelligence can be categorized into the following:

  • Visual/Spatial Intelligence
  • Linguistic Intelligence
  • Logical or Mathematical Intelligence
  • Kinesthetic Intelligence (aware of body parts and good at physical coordination)
  • Naturalistic Intelligence (good with environmental areas)
  • Intrapersonal Intelligence
  • Interpersonal Intelligence
  • Musical Intelligence
  • Existential Intelligence (good at deep questions and philosophy)

Most of these are self-explanatory. What is fascinating to note is that every person has a different area of strength when we consider all these types of intelligence. Furthermore, intelligence can be divided into two categories: crystallized intelligence and fluid intelligence. Pre-acquired intelligence, which remains with the human as it is, is crystallized. On the other hand, fluid intelligence keeps changing and evolving.

With that backdrop, let’s try to understand the new species humans have created for themselves: machines. So, let’s learn about their intelligence—Machine Intelligence.

Zooming to Machine Intelligence

Machine intelligence is the capability of machines to copy human cognitive intelligence, such as perceiving, learning, and making decisions, with the help of advanced algorithms and sensors. With these advanced sensors, systems can see and hear information and process it like humans to make informed decisions. This is the key characteristic of artificial intelligence.

Now, let’s look at some significant types of machine intelligence/artificial intelligence.

  1. Narrow AI

Designed to perform general tasks, narrow AI does not have general intelligence and cannot do tasks beyond its programming. Common examples include:

  • Siri, Alexa and Google Assistant
  • Recommendation algorithms of Netflix, Prime Video, Spotify
  1. General AI

This type of intelligence can understand, learn, and apply its knowledge just like human beings. Furthermore, it can adapt to unfamiliar situations and solve problems. It is a theoretical AI system that is capable of performing diverse tasks that only humans can do.

  1. Super AI

Super AI, also known as superficial AI, is the one that surpasses human intelligence in terms of creativity, problem-solving, and decision-making. In simple terms, it is a hypothetical future AI system.

  1. Reactive Machines

Reactive machines are a form of AI that only focuses on current situations and does not consider past data for actions or output. For example, computer games, like the chess-playing computer.

  1. Limited Memory AI

Most systems work on the basis of past data for making informed present decisions. For example:

  • Self-driving cars use the information stored by the sensors to make navigation decisions
  • Chatbots reply on the basis of the information they are fed 
  1. Self-Aware AI

Self-aware AI is the one that has its own consciousness to make rational decisions, like humans. It has the ability to compare the options and make wise choices. At this stage, it is completely hypothetical.

  1. Machine Learning AI

Machine learning (ML) is a subset of artificial intelligence, which learns from historical data and improves over time. Unlike other AI, it is not programmed explicitly to perform any function. This system excels at processing large datasets, including images, videos, and texts.

So, just like humans learn from their experiences and surroundings, this AI model also learns from historical data and the environment and improves over time.

There are three types of learning, as discussed below:

  1. Supervised Learning: Learning is carried out on labelled data, and the outcomes are usually known to the programmer. For example - predicting how prices on the basis of their size and location.
  2. Unsupervised Learning: In this form of learning, the system learns from its environment, and the data fed is unlabelled. The algorithm identifies the hidden patterns and clusters within the data to identify meaningful relationships within the data. For example, AI models are used for customer segmentation based on their marketing behavior, or AI models detect fraud based on anomalies in the security networks.
  3. Reinforcement Learning: This learning involves training the system to make informed decisions by interacting with its environment. The system is given feedback in the form of rewards and penalties; thus, it improves over time to gain maximum rewards.

Summing Up

Machine intelligence is there for a reason - to reduce the workload of humans and make them more efficient. They are capable of performing basic human tasks, which can allow humans to focus on critical tasks.

The market for machine intelligence and machine learning is soaring, which is creating new business opportunities in the market. According to LinkedIn’s 2024 Workforce Report, demand for Machine Learning Engineers is growing fastest globally. Thus, professionals in this domain are expected to benefit from high pay and job security in the market.

If you are also striving to make it big in the tech world, consider the comprehensive IIIT Hyderabad AI and Machine Learning course, which is designed for middle-to-senior-level tech professionals. This AI ML program by IIIT Hyderabad aims to cater to the learning needs of practitioners in the industry by providing them with a deep understanding of AI ML concepts, tools, and techniques.

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