Artificial General Intelligence or AGI refers to AI systems with human-like cognitive abilities across a wide range of tasks, capable of learning and adapting to new situations without specific training.

Unlike narrow AI, which is designed for specific tasks, AGI aims to replicate the general problem-solving capabilities of the human brain.

What is AGI?

• Artificial general intelligence (AGI) is a theoretical pursuit in the field of artificial intelligence (AI) research that is working to develop AI with a human level of cognition. 
• AGI is considered strong AI (compared to weak AI, which can function only within a specific set of parameters).
• Strong AI, like AGI, would theoretically be self-teaching and able to carry out a general range of tasks autonomously.
• AGI research is still evolving, and researchers are divided on both the approach(es) necessary to achieve AGI and the predicted timeline for its eventual creation.

AI researchers Ben Goertzel and Cassio Pennachin say, “‘general intelligence’ does not mean exactly the same thing to all researchers.” However, “loosely speaking,” AGI refers to “AI systems that possess a reasonable degree of self-understanding and autonomous self-control, and have the ability to solve a variety of complex problems in a variety of contexts, and to learn to solve new problems that they didn’t know about at the time of their creation.”

Examples of Artificial General Intelligence (AGI) 

Because AGI remains a developing concept and field, it is debatable whether any current examples of AGI exist. Researchers from Microsoft, in tandem with OpenAI, claim that GPT-4 “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system.” This is due to its “mastery of language” and its ability to “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting” with capabilities that are “strikingly close to human-level performance.”8 However, Sam Altman, CEO of ChatGPT, says that ChatGPT is not even close to an AGI model.

Types of Artificial General Intelligence (AGI) Research 

Computer scientists and artificial intelligence researchers continue to develop theoretical frameworks and work on the unsolved problem of AGI. Goertzel has defined several high-level approaches that have emerged in the field of AGI research and categorizes them as follows:

• Symbolic: A symbolic approach to AGI holds the belief that symbolic thought is “the crux of human general intelligence” and “precisely what lets us generalize most broadly.”
• Emergentist: An emergentist approach to AGI focuses on the idea that the human brain is essentially a set of simple elements (neurons) that self-organize complexly in reaction to the experience of the body. In turn, it might follow that a similar type of intelligence might emerge from re-creating a similar structure.
• Hybrid: As the name suggests, a hybrid approach to AGI sees the brain as a hybrid system in which many different parts and principles work together to create something in which the whole is greater than the sum of its parts. By nature, hybrid AGI research varies widely in its approaches.
• Universalist: A universalist approach to AGI centers on “the mathematical essence of general intelligence” and the idea that once AGI is solved in the theoretical realm, the principles used to solve it can be scaled down and used to create it in reality.

Where are we headed?

“We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google’s PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4’s performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions.” Sébastien Bubeck

Risks of AGI

1. Existential Threats: AGI could surpass human intelligence, potentially leading to scenarios where it acts in ways that are harmful to humanity.
2. Ethical Concerns: Issues around control, alignment with human values, and decision-making authority pose significant ethical challenges.
3. Economic Disruption: AGI could lead to massive job displacement and economic inequality if not managed properly.
4. Security Risks: AGI systems could be misused for malicious purposes, including cyber-attacks and autonomous weapons.
5. Loss of Human Autonomy: Over-reliance on AGI could erode human decision-making capabilities and autonomy.

These risks necessitate careful consideration and robust governance frameworks to ensure AGI development benefits humanity while mitigating potential downsides.

Source-
What is AGI? – Artificial General Intelligence Explained – Amazon AWS https://aws.amazon.com/what-is/artificial-general-intelligence/

Source – https://www.investopedia.com/artificial-general-intelligence-7563858#toc-what-is-artificial-general-intelligence-agi