Narrow Artificial Intelligence

Narrow AI is the most prevalent kind of AI today. From applications in mobile phones to the Internet to big data analytics, narrow AI is taking the world by storm.

The name stems from the fact that this kind of artificial intelligence systems are explicitly created for a single task. Owing to this narrow approach and inability to perform tasks other than the ones that are specified to them, they are also called as ‘weak’ AI. This makes their intelligence highly-focused on one task or set of tasks, allowing for further optimization and tweaking.

Artificial General Intelligence (AGI)

While narrow AI refers to where artificial intelligence has reached today, general AI refers to where it will be in the future. Also known as artificial general intelligence (AGI) and strong AI, general artificial intelligence is a type of AI that can think and function just as humans do.

Artificial Super Intelligence

Artificial super intelligence (ASI) is a term used to denote an AI that exceeds human cognition by a great extent in every possible way. This is one of the most far-off theories of artificial intelligence but is generally considered to be the eventual endgame of creating an AI.

While artificial super intelligence is still a theory at this point in time, a lot of scenarios involving it have already been envisioned. A common consensus among those in the field is that ASI will come from the exponential growth of AI algorithms, also known as ‘Intelligence Explosion’.

Intelligence explosion is a concept required for the creation of artificial super intelligence. As the name suggests, it is an explosion of intelligence from human-level, general artificial intelligence to an unthinkable level. This occurs through recursive self-improvement.

Self-improvement in AI comes in the form of learning from user input in neural networks. Recursive self-improvement, on the other hand, is the capacity of an AI system to learn from itself, at rapidly increasing levels of increasing intelligence.

To illustrate this, take the example of an AGI functioning at the level of average human intelligence. It will learn from itself, using the cognitive capabilities of an average human, to reach genius-level intelligence. However, this begins compounding, and any future learning made by the AI will be conducted at a genius-level cognitive functioning.

This accelerates at a fast pace, creating an intelligence that is smarter than itself at every step. This continues to build up quickly, until the point where intelligence explodes, and a super intelligence is born. Containing or creating a super intelligence is something that we as a human race are far from, making it an entry for sci-fi novels. For now.

This includes perceptual tasks, such as vision and language processing, along with cognitive tasks, such as processing, contextual understanding, thinking, and a more generalized approach to thinking as a whole.

While narrow AI is created as a means to execute a specific task, AGI can be broad and adaptable. The learning part of an adaptive general intelligence also has to be unsupervised, as opposed to the supervised and labeled learning that narrow AI is put through today.

AGI is still a far off reality, as the tools required to build it are not available today. Many argue that neural networks are a dependable way to create the forerunners of what can be called artificial general intelligence, but the reality of the situation is that human intelligence is still a black box.

While we as humans are beginning to decode the inner workings of our minds and brains, we are still a long way from figuring out what ‘intelligence’ means. In addition to this obstacle, the need to define ‘consciousness’ is integral to creating a general AI. This is due to the fact that an AGI needs to be ‘conscious’ and not just an algorithm or machine.

Source https://www.spiceworks.com/tech/artificial-intelligence/articles/types-of-ai/