What Is AGI vs. AI: What’s the Difference?

Key takeaways

While AI is typically task-specific, AGI aims to demonstrate autonomous, human-like intelligence across multiple areas. 

• Although AGI is not yet in use, it could help solve the complex problems currently challenging world leaders, such as climate change and disease prevention. 

• AI helps automate tasks and solve problems that previously required human intelligence. 

• You can use generative AI to replicate text, images, and videos with incredible accuracy. 

Discover the differences between AGI and AI, the implications and potential applications of each, and how technology would need to advance to reach AGI. Afterward, if you’re ready to build essential skills to excel in an AI role, enroll in IBM’s AI Foundations for Everyone Specialization. Beginner-friendly, this program covers natural language processing, 

deep learning, machine learning software, data science, and more. 

What is AGI?

AGI is a theoretical concept that describes an AI that can control itself autonomously and perform a wide range of basic tasks like an average human can. For example, an AGI agent teaching a class could analyze each learner’s needs and adapt the material accordingly. It could also present the material in an engaging and interesting way, much like a skilled elementary school teacher would. 

An AGI agent in an autonomous vehicle could weigh several variables at once and make quick decisions based on the changing needs of the road. It would do this much like a human driver, but with an enhanced ability to stay focused and make lightning-fast calculations. 

Sam Altman, the chief executive officer (CEO) of the AI company OpenAI, said AGI would be the “equivalent of a median human that you could hire as a coworker. They could do anything you’d be happy with a remote coworker doing, just behind a computer [1].” You could reasonably expect a remote coworker to figure out how to do a task within the scope of their job, even if they had never been trained on that task. If a remote worker didn’t know how to do something, they would use what they know to seek out the information they need to complete the new task. AGI would function in much the same way with the same or potentially better efficiency and accuracy. 

Does any AGI exist yet?

Although AGI is not yet in use, it has theoretical applications in many different fields that could have a profound impact on humanity. Using intelligence modeled after but potentially superior to our own, AGI could help solve the complex problems currently challenging world leaders, such as climate change and curing disease. AGI could also help revolutionize human productivity through automation and optimizing processes. A few industries that AGI could impact include: 

• Software development

• Self-driving vehicles

• Health care

• Education

• Manufacturing

• Financial services

• Scientific research

Is ChatGPT AGI?

No, ChatGPT is not AGI. While it marks a big leap in natural language processing (NLP), ChatGPT still lacks the autonomy and adaptability needed to qualify as AGI. True AGI also necessitates interaction with the physical world, which falls beyond ChatGPT’s current capabilities. 

Disadvantages of AGI

The potential advantages that AGI could bring to humanity are so large that it can be difficult to conceptualize. The potential disadvantages of AGI could be just as significant. Potential disadvantages of the technology may include: 

• AGI removing itself from the control of human managers

• AGI developing unsafe goals or goals that run counter to human goals

• AGI with bias

• Inadequate management and regulation of AGI

• Existential risks to humanity

While many thinkers and AI philosophers disagree on exactly how much or in exactly which circumstances AGI could pose an existential risk to humanity, a thought experiment by Oxford philosopher Nick Bostrom, sometimes referred to as “the paperclip maximizer,” explores some of the common concerns [2]. 

The experiment is as follows: Suppose you created an AGI model with the instruction to maximize the production of paper clips. With no overriding set of ethical or moral principles, the AGI might go to great lengths, including destroying the Earth and all humans, to obtain the maximum amount of resources with which to create paper clips. Bostrom and others in the field say developing AGI must happen with careful consideration of ethics. 

What is AI?

AI is a technology that allows computers and robots to perform tasks and learn in a similar way to how human brains learn a specific skill. Philosophers and storytellers have been imagining independent robots for as long as people have been capable of telling stories. AI, as humanity knows it today, has steadily progressed since the 1950s. 

What is AI used for?

Individuals and organizations can use AI to automate tasks and solve problems that previously required human intelligence. Nearly all industries could benefit from AI because AI is an adaptable technology that you can apply to many issues. For example, you can use AI for:

• Product recommendation systems

• Virtual personal assistants

• Robotics in manufacturing, health care, or space exploration

• Facial recognition

• Predictive analytics

• Data analysis

• Analysis of the translation of written or spoken language

• Generation of text, images, or video

Unlike AGI, which could theoretically learn to do any task that the average human could do, the AI you might use today is a narrow or weak type of AI. This means the AI can only accomplish the tasks that programmers and developers train it to perform. You can use an AI model to play a game of chess, a different type of AI to write a paragraph, and a third AI model to recommend what movie you could stream next. However, you can’t use a single AI to complete all of those tasks (except in a circumstance where researchers trained an AI to do those three things). Although it’s difficult to define exactly what constitutes AGI, the ability to learn tasks when a programmer hasn’t trained the algorithm to accomplish those tasks is a key marker. 

How close are we to artificial general intelligence?

Despite the impressive capabilities of AI, the technology you can access today would need to greatly improve to advance to the level of AGI, meaning we are not yet close to AGI becoming a reality. Generative AI can replicate text, images, and videos with incredible accuracy, but it cannot create genuinely original ideas; it can only make predictions based on training data. AI technology can compute and respond to natural human language, but it struggles when confronted with challenges such as accents or background noise that humans can easily interpret. These and other limitations of AI illustrate that researchers would need to solve many more problems in AI before we reach AGI. 

Read more: What Is a Generative AI Learning Path?

What is AGI vs. AI? Future implications

While some computer scientists argue that we can never reach AGI, others argue that computers could move beyond the ability of human minds between 2030 and 2050. Whether AI researchers and computer scientists can ever bring AGI out of the realm of science fiction and into the modern world is unknown, but it would require advances in computer vision, natural language processing, deep learning, generative AI, and robotics, among other areas. 

In the future, governments may do more to regulate AI development and applications in order to attempt to control the release or development of AGI. Regulation also might occur around privacy issues raised by AI and AGI. To successfully gain the potential benefits AGI could offer, researchers and policymakers need to be thoughtful about human goals and the ethics of AI. 

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