The age of AI is already upon us with overwhelmed information and funding sailing the sector to improvement.

Almost six decades back, the term 'artificial intelligence' was coined for a summer conference at Dartmouth University, organised by a young computer scientist named John McCarthy. Their ambiguous project to create a computer that could use language, form abstractions and concepts, and solve problems marked the beginning of technology. From there, humans are rushing to artificial general intelligence (AGI) today.

Artificial intelligence is defined as the capability to which a machine can exhibit intelligent characteristics. The technology is conquering every industry and is invading people's everyday life. The age of AI is already upon us with overwhelmed information in form of big data. Because of the constant flow of information on AI, it is becoming increasingly difficult to pinpoint what exactly AI is. We have travelled through Narrow AI for a long time and are on a race to reach General AI. As we talk about general AI, two theories on General AI are making their rounds across tech medium. One is based on fear of a dystopian future where super-intelligent robots take over the world by wiping off humankind, as portrayed in science fiction movies. The other theory is on an optimistic note where artificial intelligence and humans go hand in hand to accomplish every process. Let us take a look back at the path we travelled and the opportunities that will unfold in the future.

What is Narrow AI?

Artificial Narrow Intelligence (ANI) also known as 'weak AI' is defined as a specific type of AI in which a technology outperforms humans in some very narrowly defined task. Narrow AI is particularly programmed to perform a single work such as checking the weather, playing chess, analyse raw data content, facial recognition, speech detection, driving a car, searching on internet, etc.

Even though these machines look intelligent for the current trends, they only operate under a narrow set of constraints and limitations. That is why this type of AI is commonly referred to as weak AI. Narrow AI doesn't mimic or replicate human intelligence; it merely simulates human behaviour based on a narrow range of parameters and contexts. Narrow AI has been through a lot of unsuccessful attempts in the past decades. Machine learning and deep learning are some of the technologies that fuelled more innovation into the sector powering narrow AI. Some of the examples of narrow AI are,

• Google search

• Virtual assistants like Siri by Apple, Alexa by Amazon and Cortana by Microsoft

• Facial recognition tools and software like Clearview

• Recommendation systems that use analysis to suggest products, movies, songs, etc from previous lists

• Spam filters that keep email inboxes clean

What is General AI?

Artificial General Intelligence (AGI) also known as 'strong AI' allows a machine to apply knowledge and skills in different contexts. This more closely mirrors human intelligence by providing opportunities for autonomous learning and problem-solving. In other words, AGI can successfully perform any intellectual task that a human being can. This is the sort of AI that sci-fi movies portray.

The current systems are slowly updating to be something more than narrow AI. Today, machines are able to perform tasks faster than humans. Unfortunately, machines are not up to the mark where they think strategically, abstract, and tap into their thoughts and make decisions accordingly. This type of intelligence that replicates a human's way of thinking and coming to a solution is where we are headed. Strong AI uses a theory of mind AI framework, which refers to the ability to discern needs, emotions, beliefs and thought processes of other intelligent entitles. The human brain is taken as a model to create general AI. However, the lack of comprehensive knowledge on the functionalities of the human brain has researchers struggling to replicate basic functions of sight and movement.

Technology: Through narrow AI and on the path to reach general AI

In the early 1950s when technology came to existence, people thought that it will only take a few years to crack general AI. They imagined that designing a machine that can perform a single task is easy. It started well with Georgetown experiment in 1954 which was able to partially translate around 60 sentences from Russian to English. This marked a milestone in technology history and put up people's hope.

The tech world went into rough weather when proposals and projects were abandoned during the so-called AI winter. The period between 1970 and 1980 made people lose their hope, and at one stage they thought it would be impossible to build an intelligent machine. From such worse stance, the digital innovation recovered for good.

Simply put, Narrow AI is where we have been and General AI is where we are headed to. The digital era is further fuelled with more easy-to-go features like smartphones, computational power, internet connectivity and more similar services. A high level of development is made in the AI sector with investments pouring in from all industries. As mentioned in the World Economic Forum, "AI is no longer about a machine playing chess. AI is on the street driving our cars, call centres talking to customers, drafting and reviewing legal documents with immaculate precision, it is even trading using indices derived from satellite imagery." With such level of improvement and heavy funding, researches could further intensify the researches and drive us to the so-called 'General AI' soon.