Artificial general intelligence (AGI) refers to a theoretical state in which computer systems will be to achieve or exceed human intelligence. In other words, AGI is “true” artificial intelligence as depicted in countless science fiction novels, television shows, movies, and comics.
As for the precise meaning of “AI” itself, researchers don’t quite agree on how we would recognize “true” artificial general intelligence when it appears. However, the most famous approach to identifying whether a machine is intelligent or not is known as the Turing Test or Imitation Game, an experiment that was first outlined by influential mathematician computer scientist, and cryptanalyst Alan Turing in a 1950 paper on computer intelligence. There, Turing described a three-player game in which a human “interrogator ” cannot reliably identify the human, then Turing says the machine can be said to be intelligent [1].
To complicate matters, researchers and philosophers also can’t quite agree whether we’re beginning to achieve AGI, if it’s still far off, or just totally impossible. For example, while a recent paper from Microsoft Research and OpenAI argues that Chat GPT-4 is an early form of AGI, many other researchers are skeptical of these claims and argue that they were just made for publicity [2,3].
is a field of theoretical AI research that attempts to create software with human-like intelligence and the ability to self -teach. The aim is for software to be able to perform tasks that it is not necessarily trained or developed for.
Current artificial intelligence (AI) technologies all function within a set of pre – determined parameters. For example, AI models trained in image recognition, and generation cannot build websites. AGI is a theoretical pursuit to develop AI systems that possess autonomous self-control, a reasonable degree of self-understanding, and the ability to learn new skills.
Strong AI vs. Weak AI
When researching artificial intelligence, you might have come across the terms “string” and “weak” AI. Though confusing, you likely already have a sense of what they mean.
Strong AI is essentially AI that is capable of human-level, general intelligence. In other words, it’s just another way to say “artificial general intelligence.”
Weak AI, meanwhile, refers to the narrow use of widely available AI technology, like machine learning or deep learning, to perform very specific tasks, such as playing chess, recommending songs, or steering cars. AIso known as Artificial Narrow intelligence (ANI), weak AI is essentially the kind of AI we use daily.
The 4 Types of AI
As researchers attempt to build more advanced forms of artificial intelligence, they must also begin to formulate more nuanced understandings of what intelligence or even consciousness precisely mean. In their attempt to clarify these concepts, researchers have outlined four types of artificial intelligence.
Here’s a summary of each AI type, according Professor Arend Hintze of the university of Michigan [4]:
1. Reactive machines
Reactive machines are the most basic type of artificial intelligence. Machines built in this way don’t possess any knowledge of previous events but instead only “react” to what is a result, they can only perform certain advanced tasks within a very narrow scope, such as playing chess, and are incapable of performing tasks outside of their limited context.
2. Limited memory machines
Machines with limited memory possess a limited understanding of past events. They can interact more with the world around them than reactive machines form of limited memory to make turns, observe approaching vehicles, and adjust their speed.
AI benefits and dangers
AI has a range of applications with the potential to transform how we work and our daily lives. While many of these transformations are exciting, like self-driving cars, virtual assistants, or wearable device in the healthcare industry, they also pose many challenges.
