What is Machine Intelligence? What are the Types of Machine Intelligence?

What separates humans from every other species on this planet?

The difference lies in just one word, ‘intelligence’, to the best of our knowledge – accumulated and tested over centuries by scientists and explorers. 

The level and evolution of intelligence that humans have mastered are genuinely distinct. 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’. And also highlight its relevance in our work and life – on a typical day.

So, what is intelligence? What are the types of intelligence?

Intelligence is composed of many abilities and aspects – comprehension, visualization, processing, memory, reasoning, application, and learning. And this word comes in a variety of shades. There are many kinds of intelligence. Without digging too deep, we can categorize ‘intelligence’ into some broad types: 

  • 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 here is every person has a different area of strength when we look at all these types of intelligence. For example, someone may be good at noticing nuances of tone – and hence, have musical intelligence. On the other hand, someone may be good at the ability to grow anything and explore nature – thus, born with naturalistic intelligence). 

Also, intelligence can be crystallized or fluid. If it uses previously-acquired knowledge, it is crystallized. Still, if it keeps changing and evolving into something better than before- able to apply abstract thinking for new or unfamiliar problems- it becomes fluid intelligence.

With that backdrop, let’s try to understand the new species humans have created themselves- Machines. And let’s get to know about the intelligence they have and build- machine Intelligence.

Zooming in on machine intelligence

Now let’s look at some significant types of the computer genre of intelligence. 

Cognitive computing is where sensors and algorithms help machines see and hear to get closer to some human capabilities. When a machine can make decisions based on data and models, this kind of intelligence is called artificial intelligence (AI). Artificial intelligence (AI) can be classified as,

  • Narrow (not too many human-like capabilities), 
  • General (matching human capabilities), and 
  • Super (capabilities that are better than humans)

In machine learning, models and data help machines to learn. This learning, then, allows machines to support humans in their decisions and actions. When this learning happens without human supervision, it is called unsupervised machine learning.

  • When it happens with humans in the loop, it is called supervised machine learning. 
  • And when the machine learns from feedback continuously and continuously improves itself- it uses reinforcement learning.

In supervised learning, both the input and output are defined, and the machine has to learn how to get from input to output. Here, accuracy and control get high, but it takes too much time, labeling effort, and scalability issues. In unsupervised learning, the machine must work out patterns and inferences on its own. Of course, this method can be more error-prone than supervised learning, but it is less labor-intensive.

In reinforcement learning, humans can get to insights that even they may not be aware of- provided they can allow machines some time and errors to get there.

Finally, in deep learning, a machine can mimic the human brain to some extent with its nervous topology and use of neural networks.

Conclusion

Machine learning is exploding in its reach and depth. According to Fortune Business Insights, the global machine learning market was valued at $15.44 billion in 2021 and is expected to grow to $21.17 billion by 2022 and $209.91 billion by 2029. The global AI market size was valued by Grand View Research – at $62.35 billion in 2020 and is expected to expand at a compound annual growth rate (CAGR) of 40.2 percent between 2021 and 2028. With this, you will witness many ML applications in automotive, healthcare, retail, finance, and manufacturing. 

Many AI applications are helping industries reach new levels of efficiency and revenues. We are getting closer to a world where self-driving vehicles, robot-assisted surgery, risk assessment, investment management, etc., would be everyday reality. And who knows, one day, the thing that separates humans from other species would be these machines that humans have—another proof of constant and smart human evolution.