NAI vs GAI vs SAI: What does the future of Artificial Intelligence Look Like?

By | December 18, 2019
Artificial Intelligence
Artificial Intelligence

When Alan Turing first introduced the idea about machines having the ability to think way back in 1950, the whole concept seemed quite far-fetched at that time. The term AI was first introduced by John McCarthy, an American Computer Scientist and Cognitive Reasoning specialist, in 1956. Without a doubt, this concept was one of the most significant turning points in the field of Computer Science.

Artificial Intelligence can be broadly defined as

“Artificial Intelligence refers to the machine having humanlike intelligence i.e., Machines exhibiting the same visual, speech, and cognitive abilities like that of a human. It is about making machines smart enough so that they can make their own decisions.”   

Millions of dollars of research being conducted by tech giants like Facebook, Google, Amazon, etc. There have been remarkable advancements and breakthroughs in the field of AI, and the pace of these innovations is expected to grow exponentially in the upcoming years.

AI has helped add value to business all over the world. From increased customer engagement to automating everyday tasks such as Social and Digital Marketing campaigns, AI has become the new face of every Marketing Strategy.

Based on the AI technologies that we have so far and the ones that are expected to be potentially the “Next Thing” in AI, Artificial Intelligence can be classified into three types.

1. ANI: Artificial Narrow Intelligence

2. AGI: Artificial General Intelligence 

3. ASI: Artificial Super Intelligence       

Artificial Narrow Intelligence (ANI):

Also referred to as Weak Intelligence, Narrow AI is as far as humanity has managed to go so far. All the AI innovations that currently exist in our time fall under Narrowly Intelligent Machines. 

The basic idea behind Narrow AI is a System or a Program that is developed to do a single task. These AI machines gather information from a single data source and give you real-time output as far as it falls under the specified data set.

These machines are also referred to as Single Domain machines. When it comes to taking care of a single task efficiently like predicting the weather or playing chess, Narrow AI is good enough to take care of that. But when it comes to handling data and information that is outside the domain of that System, Narrow AI fails to manage or even process that. 

Some examples of Narrow AI are Siri, Google Assistant, Google Translate, Speech recognition systems, etc. No matter how intelligent these machines seem to be, they are nowhere close to exhibiting humanlike intelligence and decision-making capabilities. They just do what they are programmed to do I .e. They don’t have the same cognitive abilities like that of a human.   

Benefits of ANI:    

Although Artificial Narrow Intelligence falls under the Weak AI category, it still is a tremendous technological breakthrough that has had significant implications for all kinds of fields and businesses.

·ANI systems can process data at a much faster rate thus allowing you to be efficient and productive

·ANI systems promote better healthcare by enabling doctors to Make Data-Driven Decisions

·ANI has seeped into our personal lives as well i.e., and Speech Recognition Systems will enable you to be more productive with your Mundane Tasks like ordering food or searching for a particular piece of information 

·ANI is the necessary foundation for advanced AI concepts like General and Super Artificial Intelligence

AI-based self-driving cars and traffic systems would provide a more organized way of dealing with essential to advanced level traffic issues and so much more. These are just some of the benefits that the world is currently enjoying thanks to the breakthroughs that are happening in ANI.

Problems with ANI: 

  • ANI is data-dependent. You can’t make an ANI machine smart unless you feed it already existing data related to the problem domain and train it to some extent. The amount of training data would have a direct impact on the performance of an ANI system.
  • Performance Gets affected by small changes in the System 
  • ANI Machines can’t make decisions in a Humanlike Manner
  • The Scope of Output is limited 

For the latest news about the scope of ANI and recent AI innovations, visit ConceptBB. 

Artificial General Intelligence (AGI):

AGI is also referred to as Strong Intelligence. AGI machines can think, act, and behave as humans do. Although we have made machines that can process data at a much faster rate than humans do but still unlike humans, these machines can’t think abstractly, and they don’t have their cognitive reasoning faculties.

This is what AGI strives to achieve. These machines are expected to adapt to uncertainty and make informed decisions just the way we humans do.  

AGI: The New Face of AI

AGI focuses on the transfer of learning from one domain to another. It is about making machines smart enough so that they can tackle complex problems in a stochastic environment with limited resources. 

AGI is going to be the future of AI. Although it seems like AGI still has a long way to go but considering the technological breakthroughs that have happened in what like the last 100 years, there is no telling when we might get to see an AGI machine exhibiting the same cognitive abilities like that of a human.

The main challenge with AGI is that research institutions are not prioritizing it. ANI has given proven results for businesses and private organizations, so they are focusing their efforts on exploring ANI technologies. But over the last few years, we have seen a significant shift in these trends, and we are expecting a substantial breakthrough in AGI as well.    

Artificial Super Intelligence (ASI):

Artificial Super Intelligence is what you have seen in Science Fiction Movies like Terminator and I Robot. Is this concept just fiction? Futuristic Scientists would beg to differ. 

ASI refers to a machine having intelligence that far exceeds that of a human being in virtually all areas of performance. From decision making to creativity as well as wisdom and problem solving, these machines would be better at everything that humans. ASI might seem a bit farfetched from now. Still, then again, considering the technological breakthroughs that have happened over the last few decades, we can expect the era of ASI to be just around the corner. 

Biography: Jack Connor, a technical and entertainer researcher and have to write many entertaining, and professional blogs like Project FreeTv content, and AI (Artificial Intelligence)