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Artificial Intelligence – Evolution or Revolution?

From a typing machine to supercomputer, and from a human brain to neural networks, global technological evolution, though with its own set of pros and cons, has led to wonders across every industry. Now, Artificial Intelligence (AI) stands at the center of such an evolution and has become ubiquitous in applications across. Though journey of AI’s development spans across decades, heavy investments and supporting technologies in the not so recent past has enabled AI to be adapted far and wide.

AI is the ability of a digital computer — or robot/humanoid controlled by computer applications; or smart machines — to perform tasks that require human intelligence. AI stakes are high and is widely seen where characteristics of human intellectuality is required such as reasoning, discovering the meaning, generalizing, learning from past experiences etc. Nowadays, CIOs and leaders’ pursuit to accelerate the pace of change and ensuring intelligent investment resulted in the trend of diverse applications of AI. For example, medical diagnosis, computer search engines, voice or handwriting recognition, smart Assistants, self-driving cars, chatbots, robots, among others. 

Types of Artificial Intelligence

Reactive Machines

These are proficient in using its intelligence to observe and respond to the world in front of it. These machines do not have memory storage, thereby, cannot rely on past experiences to notify decision making in real-time. Reactive machines are designed to perform limited number of defined tasks; hence, it is trustworthy and reliable.

Examples include IBM-designed Chess Playing Supercomputer - Deep Blue, which defeated international grandmaster Gary Kasparov in a game; and AlphaGo by Google that defeated champion Go player Lee Sedol in 2016. However, both are incapable of evaluating future moves as they rely on neural networks and evaluate the developments of the present game; because of no memory, these cannot use past experiences to enlighten future ones. 

Limited Memory

Limited Memory Artificial Intelligence can store the past data and predicts based on information gathered for potential decisions. This AI is complex and more efficient than reactive machines. This is a cyclic process with reiterative steps that include creating training data, creating machine learning model, ability of the model to predict, ability of the model to receive feedback and ability to store the feedback data.

Theory of Mind

Theory of Mind is theoretical and a psychological term. Though we have not yet attained the technological and scientific abilities necessary to reach this level, when applied to AI, it means that the system would have the social intelligence to understand emotions. This will enable AI to gather human intentions and predict behavior, a necessary skill for AI systems to become critical adherents of human teams. 


Though this type of AI does not exist yet, this is believed to be the next and final stage of evolution of AI post the development and functioning of Theory of Mind AI — where AI systems will have a sense of human-level consciousness and understand its own existence in the world, as well as the presence and emotional state of others.

Artificial intelligence generally falls under two broad categories:  

AI is categorized into two categories: Narrow AI, and Artificial General Intelligence (AGI). 

Narrow AI

Narrow or Weak AI is a simulation of human intelligence that runs within a narrow context and is designed and trained to complete a specific task. However, Narrow AI is wrought under far more constraints and limitations than even the most basic human intelligence. A few examples of Narrow AI include:

  • Siri, Alexa and other personal assistants 
  • Self-driving cars 
  • Search engines 
  • Image recognition software 
  • Chatbots 


Often called as Strong AI, illustrates programming that can reproduce the intellectual abilities of the human brain, as we see in the movies. AGI is a machine with general intelligence and much like a human being, it can apply that intelligence to solve any problem. AGI has long been the muse of dystopian science fictions, in which super-intelligent robots overrun humanity, but experts agree it's not something we need to worry about anytime soon. Strong AI system can use fuzzy logic to apply knowledge from one domain to another and find a solution autonomously. In theory, a strong AI program should be able to pass both a Turing Test and the Chinese room test. 

Advantages and disadvantages of artificial intelligence

Because of its agility, processing speed of large amounts of data and ability to predict accurately, artificial neural networks and deep learning AI technologies are quickly evolving across the globe. However, AI has its own pros and cons and below are few:


  • Takes little time to process complex data 
  • Accurate predictions than Human  
  • Consistency in delivering the results 
  • Full scale of availability of AI-powered virtual agents  


  • Very expensive 
  • Need deep technical expertise 
  • Non availability of qualified workers to build AI tools 
  • Lack of ability to generalize from one task to another. 

Artificial Intelligence – an evolution

As AI has the capability to provide insights to businesses in their operations, businesses have been heavily investing on AI, though expensive, to perform tasks better than humans. AI tools predominantly operate quickly and accurately, particularly in repetitive detail-oriented tasks, with relatively few errors. Using machine algorithms to analyze the data and predict the actionable insights, AI has been playing vital role in day to day digital life of an average person. For instance, Google, the largest global search engine, uses machine learning to understand how people use its search engine services to access a range of online services and then improve upon them. Today's largest and most successful enterprises have been using AI to improve their operations and gain advantage over their competitors.

ACI Infotech’s AI Capabilities

Informed business leaders make optimal decisions. AI- and ML-based algorithms can contribute, by showing what's happening, why has it happened and what will happen next. The result is leaders can take the critical actions to improve operations, reduce costs, save time or boost prices, profits and productivity. 

ACI Infotech Intelligent Decisioning is an AI-driven approach that uses advanced methods and tools to transform business decision-making in operational and customer-facing processes. It helps businesses make better decisions faster, even in times of great uncertainty. ACI innovation goes beyond insights to augment and inform the choices companies need to make.