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What is Artificial General Intelligence (AGI)?
Artificial general intelligence (AGI) is a type of distinguished artificial intelligence (AI) that is broad in the way that human cognitive systems are broad, that can do different kinds of tasks well, and that simulates the breadth of the human intellect, rather than focusing on more specific or narrower types of tasks. Artificial general intelligence is also known as general artificial intelligence.
AGI is so far theoretical – it has not yet been achieved. The term is used to distinguish various types of artificial intelligence from each other – the terms “strong artificial intelligence” or “full artificial intelligence” are also used to discuss broader artificial intelligence goals.
There is not yet a consistent artificial general intelligence definition, as researchers have yet to agree on what non-human “general intelligence” means in real world applications. In general, however, it refers to AI systems that demonstrate a degree of autonomy and self-understanding to teach themselves to find solutions to problems that they were not programmed with initially.
Key Takeaways
- Although artificial intelligence systems are developing rapidly, true AGI is still a theoretical concept that does not yet exist in the real world.
- While AI is designed to carry out specialized tasks, AGI would use its human-like intelligence to learn and adapt to a broad range of functions, much like humans do.
- Unlike current, more basic forms of artificial intelligence, AGI would be able to understand and respond to context, reason across multiple domains, and engage in cognitive functions at a higher level.
- Scientists and engineers are using machine learning (ML), natural language processing (NLP) and brain emulation among other techniques in their attempts to achieve AGI.
- The potential emergence of real AGI raises questions about ethics, control of autonomous systems, and the potential risks to humanity.
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What Does AGI Do?
One of the big questions in artificial intelligence is to what extent machines can become intelligent and to what extent they can mirror the reasoning and perceptive capabilities of the human brain. Some debates on artificial intelligence begin with the Turing Test developed in the 20th century, which simply asks if a computer could fool a human into thinking they were communicating with another human when in fact, they were communicating with the machine.
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Other discussions on artificial intelligence go far beyond that – where some narrower or weaker forms of artificial intelligence include expert game-playing computers, computers that reference developed ontologies for conversation, and computers that give directions or other instructions.
What is artificial general intelligence in this context? Other kinds of artificial intelligence that could be called “artificial general intelligence” will exhibit behaviors that look and feel much more like the behaviors and communication methods of human beings.
If achieved, AGI would be able to mimic the human ability to learn and perform a range of tasks. This would include learning from new experiences, reasoning based on the information learned, critical thinking, and making decisions, meaning AGI systems would be able to adapt to new situations without requiring continuous reprogramming or additional training datasets.
Types of AGI
Based on the work of computer scientists such as Ben Goertzel, there are different approaches to potentially achieving AGI, which take different angles on human consciousness and how to imbue machines with human-like intelligence:
Artificial General Intelligence vs. Artificial Intelligence
What is the difference between artificial intelligence and artificial general intelligence? Artificial intelligence, as it exists today, refers to the most basic level of AI, which is categorized as weak or “narrow” AI. It is a set of technologies and applications that are designed to focus on specific tasks and functions, such as autonomous vehicles, chatbots trained by large language models (LLMs), AI writing tools, and voice-activated virtual assistants.
What AGI means is machine-based intelligence that does not rely on human programming. The difference between AI and AGI is that AGI is considered to be “strong” artificial intelligence that has the ability to learn and adapt autonomously to perform intellectual tasks it has not encountered before, as it has a much cognitive capacity as humans.
- Computer-based intelligence developed to interact with the world with human-like cognition
- Theoretical
- Human-like learning
- Demonstrates human-level reasoning and problem-solving without training or other intervention
- Computer technology that simulates human speech, comprehension, learning, and problem-solving to perform tasks
- In use
- Confined to the limits of training models
- Demonstrates human-like reasoning and problem-solving with training
5 Technologies Driving Artificial General Intelligence Research
Researchers and programmers are using several technologies and approaches to progress toward AGI.
These include:
Examples of AGI
If theoretical AGI is achieved in reality, it has potential applications in a range of industries.
General artificial intelligence examples include:
AGI would go beyond current self-driving cars that rely on maps and pre-programmed sensors to understand and respond to real-time data, enabling autonomous vehicles to explore unmapped routes and respond to hazards in real time.
AGI could analyze medical scans, test results, patient records, and genetic data to identify patterns that humans may not be able to identify to provide targeted diagnoses and tailored treatments.
AGI-powered customer service agents could analyze customer data in real time to create personalized services by anticipating potential issues, perceiving a customer’s mood, recalling details of past interactions, and communicating in an empathetic way.
AGI could optimize manufacturing processes by analyzing production data in real time to identify bottlenecks, predict equipment failures, suggest delivery routes, and recommend adjustments.
AGI Future
The future of AGI – when it might be achieved or whether it is even possible – is one of the most hotly debated aspects of artificial intelligence.
While some experts argue that it is decades away, others believe that it could be achieved much sooner.
In a paper published in 2023, researchers from Microsoft stated that OpenAI‘s ChatGPT-4 “could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system,” given the breadth and depth of its capabilities.
“Despite being purely a language model, this early version of GPT-4 demonstrates remarkable capabilities in a variety of domains and tasks, including abstraction, comprehension, vision, coding, mathematics, medicine, law, understanding of human motives and emotions, and more,” the paper states. “The combination of the generality of GPT-4’s capabilities, with numerous abilities spanning a broad swath of domains, and its performance on a wide spectrum of tasks at or beyond human-level, makes us comfortable with saying that GPT-4 is a significant step towards AGI.”
Ben Goertzel stated in a 2014 paper published in the Journal of Artificial General Intelligence that “it’s hard to make an objective, theory-independent measure of intermediate progress toward advanced AGI” because “we suspect there are many different routes to AGI, involving integration of different sorts of subsystems.”
AGI Challenges
Several technical and ethical challenges must be overcome for AGI to move from the theoretical stage to reality.
The Bottom Line
Artificial general intelligence, by definition, is the achievement of machine-based intelligence at a general level that goes beyond specific pre-programmed tasks to imitate human cognitive abilities.
While basic artificial intelligence is advancing, at this stage, AGI is a theoretical concept. There are significant challenges that will need to be overcome to achieve AGI, given the complexity of human consciousness and emotional intelligence.
AGI has the potential to solve complex problems that humans have been unable to tackle, and could have a range of uses in industries as diverse as healthcare, automotive and customer services.
However, AGI also raises significant ethical and safety concerns that must be addressed to ensure it is developed in ways that beneficial for society.
