Understanding Fundamentals of Artificial Intelligence

Posted By :Rajat Soni |30th July 2021


Artificial intelligence (AI) refers to machines or computer programs that can learn to execute jobs that typically need intelligence and are carried out by humans. 

"The mainstream view in psychology identifies human intelligence not as a single capacity or cognitive process, but rather as a set of discrete components," says Jack Copeland. Learning, reasoning, problem-solving, vision, and various other aspects of intelligence have been the subject of AI research. 

The different types of Artificial Intelligence:


Weak AI: Artificial Narrow Intelligence (ANI) allows computers to outperform humans in some particular tasks (For example, IBM Watson)

Strong AI: Artificial General Intelligence (AGI) is the ability of a machine to perform the same intellectual tasks as a human being. 

Artificial Super-Intelligence (ASI): When a machine's intelligence exceeds that of the world's brightest and most gifted human minds put together, that forms a superior super-intelligence. 


It can also be divided into four types: 


  • Reactive Machines merely react to a stimulus without learning from prior experiences or improving with practice (for example, IBM Deep Blue). 
  • Limited Memory can retain and use data for a brief period of time but cannot add them to a library of experiences (for example Self Driving Cars).
  • Theory of Mind, machines that duplicate our mental models, including ideas, emotions, and memories, are known as the Theory of Mind.
  • Self-Awareness, sometimes known as conscious robots, is a science fiction concept.

We can see how AI has a wide range of applications and how many of them are currently in use in our hands or our daily lives: virtual assistants, translators, eCommerce or social media suggestions, chatbots, and so on. 


This is only the beginning, yet it's already moving at full speed! 


Looking into the future, it's evident that AI will transform businesses, industries, countries, and the entire globe; it's up to us to imagine how we want it to be and make the correct decisions now. 


Agentive Technology: Artificial Intelligence (AI) should complement humanity, providing us with the means to eliminate work and perform it independently. 

Centaurs: Because of the complementarity of capabilities, it is proved that the total of IA and Humans is better than IA alone.

Multiplicity: The partnership of Artificial Intelligence and Amplified Intelligence (human + artificial) is the key to success.

AI Superpowers: Dr. Kai-Fu incorporates variables like compassion, love, and empathy while putting AI at the core.


Artificial Intelligence is primarily based on two pillars: 


Symbolic Learning and Machine Learning


The first pillar was the basis upon which everything was built, but since the development of Machine Learning, specifically Deep Learning, all efforts have been focused on the second.

Machine Learning is a system capable of handling large amounts of data, creating models that successfully classify them, and then making predictions with new data.


Types of learning: 


Supervised learning: It is taught with training data and contains both inputs and desirable outputs.

Unsupervised learning: Only non-tagged or classed input data is included, and common elements are detected.

Reinforcement learning: Rather than focusing on results, attempts to maintain a balance between the two.

Exploration — New Knowledge — Exploitation — Current knowledge.

Learning models: There are many learning models such as basic regression (linear, logistic), classification (neural networks, naive Bayes, random forest), cluster analysis (k-means, anomaly detection)


I hope you find this article informative and that it will help you in your quest to learn more about Artificial Intelligence. 


About Author

Rajat Soni

Rajat is working as Front-End developer, having good knowledge of HTML5, CSS3, Bootstrap 4, Javascript and React JS. He loves listening to music and learn about new technologies.

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