Cloud Hosting

What Is Artificial General Intelligence (AGI)?

Artificial general intelligence (AGI) is a branch of theoretical artificial intelligence (AI) research working to develop AI with a human level of cognitive function, including the ability to self-teach. However, not all AI researchers believe that it is even possible to develop an AGI system, and the field is divided on what factors constitute and can accurately measure intelligence.

Other terms for AGI include strong AI or general AI. These theoretical forms of AI stand in contrast to weak AI, or narrow AI, which are able to perform only specific or specialized tasks within a predefined set of parameters. AGI would be able to autonomously solve a variety of complex problems across different domains of knowledge.

Given that AGI remains a theoretical concept, opinions differ as to how it might eventually be realized. According to AI researchers Ben Goertzel and Cassio Pennachin, 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 didnt know about at the time of their creation.

Because of the nebulous and evolving nature of both AI research and the concept of AGI, there are different theoretical approaches to how it could be created. Some of these include techniques such as neural networks and deep learning, while other methods propose creating large-scale simulations of the human brain using computational neuroscience.

While artificial intelligence (AI) currently encompasses a vast range of technologies and research avenues that deal with machine and computer cognition, artificial general intelligence (AGI), or AI with a level of intelligence equal to that of a human, remains a theoretical concept and research goal.

AI researcher Peter Voss defines general intelligence as having the ability to learn anything (in principle). Under his criteria, AGIs learning ability would need to be autonomous, goal-directed, and highly adaptive. AGI is generally conceptualized as being AI that has the ability to match the cognitive capacity of humans, and is categorized under the label of strong AI. (Artificial super intelligence [ASI] also sits under the strong AI category; however, it refers to the concept of AI that surpasses the function of the human brain.)

In comparison, most of the AI available at this point would be categorized as weak AI, or narrow AI, as it has been developed to focus on specific tasks and applications. Its worth noting, however, that these AI systems can still be incredibly powerful and complex, with applications ranging from autonomous vehicle systems to voice-activated virtual assistants; they merely rely on some level of human programming for training and accuracy.

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. However, Sam Altman, CEO of ChatGPT, says that ChatGPT is not even close to an AGI model.

In the future, examples of AGI applications might include advanced chatbots and autonomous vehicles, both domains in which a high level of reasoning and autonomous decision making would be required.

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:

The year when we will be able to achieve AGI (or whether we will even be able to create it at all) is a topic of much debate. Several notable computer scientists and entrepreneurs believe that AGI will be created within the next few decades:

However, the future of AGI remains an open-ended question and an ongoing research pursuit, with some scholars even arguing that AGI cannot and will never be realized. AI researcher Goertzel has explained that its difficult to objectively measure the progress toward AGI, as there are many different routes to AGI, involving integration of different sorts of subsystems and there is no thorough and systematic theory of AGI. Rather, its a patchwork of overlapping concepts, frameworks, and hypotheses that are often synergistic and sometimes mutually contradictory.

In an interview on the topic of AGIs future, Sara Hooker of research lab Cohere for AI said, It really is a philosophical question. So, in some ways, its a very hard time to be in this field, because were a scientific field.

Researchers from Microsoft and OpenAI claim that GPT-4 could be an early but incomplete example of AGI. As AGI has not yet been fully achieved, future examples of its application might include situations that require a high level of cognitive function, such as autonomous vehicle systems and advanced chatbots.

Because artificial general intelligence (AGI) is still a theoretical concept, estimations as to when it might be realized vary. Some AI researchers believe that it is impossible, while others assert that it is only a matter of decades before AGI becomes a reality.

AI encompasses a wide range of current technologies and research avenues in the field of computer science, mostly considered to be weak AI or narrow AI. Conversely, researchers in the field of AGI are working on developing strong AI, which can match the intelligence of humans.

Most researchers define AGI as having a level of intelligence that is equal to the capacity of the human brain, while artificial super intelligence (ASI) is a term ascribed to AI that can surpass human intelligence.

Researchers have differing opinions regarding when they believe AGI can be achieved, with some predicting its creation as soon as 2030 to 2050, and some believing that it is downright impossible.

The concepts of AI and AGI have long captured the human imagination, and explorations of the ideas abound in stories and science fiction. Recently, scholars have argued that even mythology dating from as far back as ancient Greece can be seen to reflect our fascination with artificial life and intelligence.

There are currently many different approaches toward creating AI that can think and learn for itself and apply its intelligence outside the bounds of a previously specified range of tasks. Due to the theoretical and multifaceted nature of this research, it is difficult to say if and when AGI might be achieved. However, if it does become a reality, one thing is certain: It will have fundamental and wide-ranging impacts across our technologies, systems, and industries.

Read this article:

Artificial General Intelligence (AGI): Definition, How It Works, and ... - Investopedia