What Is Artificial General Intelligence? Definition and Examples

Key takeaways

Artificial general intelligence (AGI) is a hypothetical form of artificial intelligence (AI) in which a machine learns and thinks like a human.

• AGI works by incorporating logic into AI and machine learning processes rather than simply applying an algorithm, so that its learning and development mirror those of humans.

• Programming AGI would require the machine to develop a kind of consciousness and self-awareness that has started to appear in innovations like self-driving cars that adapt to roads and passing trucks.

• You can find aspects of AGI in AI systems used today, including language model GPTs like ChatGPT, expert systems such as those used in health care, and supercomputers, which can calculate faster than average computers.

Explore what AGI is and some examples of how you could see it implemented in real life. Afterward, if you want to learn more about AI, consider enrolling in Google's AI Essentials Specialization. In as little as a day, you’ll have the opportunity to learn how AI can help you speed up daily tasks and develop new ideas.

What is artificial general intelligence?

Artificial general intelligence is a hypothetical type of intelligent agent that has the potential to accomplish any intellectual task that humans can. In some cases, it outperforms human capabilities in ways beneficial to researchers and companies. 

Companies such as OpenAI are conducting research to advance AGI and what it means for companies, governments, and humanity alike. AGI works by incorporating logic into the AI and machine learning processes instead of just applying an algorithm, so that its learning and development mirrors that of humans.

Artificial general intelligence (AGI) vs. artificial intelligence (AI): How is AGI different from AI?

Artificial general intelligence (AGI) is theoretical, even though it is in the midst of being produced and launched, and it should be able to perform a range of intelligence without human intervention, at a human level or surpassing it, to solve problems.

On the other hand, artificial intelligence (AI) is available and in practical use today, using a combination of machine learning, deep learning, and neural networks to deliver services like chatbots and voice recognition.

AGI capabilities

AGI is essentially AI that has cognitive computing capability and the ability to gain complete knowledge of multiple subjects, the way human brains can. It does not currently exist; it is simply in the process of being researched and experimented with. If it were able to surpass human capabilities, AGI could process data sets at speeds beyond what AI is currently capable of and may be able to:

• Think abstractly

• Gather and draw from background knowledge of multiple subjects

• Exercise common sense and consciousness

• Understand cause and effect

In practice, this could include capabilities that humans have that AI does not, such as sensory perception. AGI could recognize colors and depth. Along with this are fine motor skills, like how a human reaches into their pocket to take out a wallet or cooks a meal without burning their fingers on the stove. AGI could also show creativity: Rather than generating a Renaissance painting of a cat, it could think of an idea to paint several cats wearing the clothing styles of each ethnic group in China to represent diversity. 

More than just a creative mind, painting cats wearing different Chinese dress patterns requires an understanding of different cultures, symbols, and belief systems. AGI systems would need to handle the subtle nuances of each ethnic group and create a new structure for this task using multiple algorithms at once. 

What are artificial general intelligence examples?

While AGI systems are not available just yet, some examples of artificial intelligence are already meeting or exceeding human capabilities in narrow domains. Research and experimentation are currently underway to advance AI into AGI. Some examples of AGI already present in AI systems today include:

• Self-driving cars: These cars are guided by AI to recognize that other cars, people, and things like traffic cones or barriers are in their vicinity. Self-driving cars are designed to know when a car is nearby and to react if it is too close. They are also trained to adhere to driving laws and common rules of the road.

• Language model GPT: AI systems like ChatGPT can be prompted to generate human language that mimics how humans communicate. Both the input and output for tools like ChatGPT can be flawed. They also cannot simulate human emotion the way that AGI hypothetically could.

• Expert systems: An expert system is driven by AI to simulate human judgment. A common example is a health care expert system that prescribes specific types of medicine after reading a patient’s records.

• IBM’s Watson (and other supercomputers): Supercomputers like Watson (which has fueled further advancement and innovation for IBM under watsonx) can calculate faster than the average computer. With the addition of AI, they can carry out tasks such as modeling the birth of the universe.

If AGI were to exist, these examples could surpass human intelligence. At the moment, self-driving cars require humans to be present to make decisions when the car’s AI capability does not allow it to problem-solve in ambiguous situations.

How close are we to AGI??

Today, artificial general intelligence (AGI) is merely an imagined future possibility rather than a real-world capability. While OpenAI, the company responsible for creating ChatGPT and Dall-E, claims the timeline to AGI is uncertain, it believes that by 2028, it will have systems that “can make more significant discoveries” compared to the “small discoveries” it projects for 2026 [1]. The reality is that no one knows how long it will actually take for machine intelligence to reach human-like intelligence.

Many researchers are also dubious of claims that human-level AI capable of performing a wide range of cognitive tasks is just on the horizon. For example, prominent AI researcher and Coursera co-founder Andrew Ng thinks true AGI is likely decades away [2].

Read more: The History of AI: A Timeline of Artificial Intelligence

AGI meaning for the future

In the future, though, AGI could do all this and more. While some researchers question whether it is viable or even desirable, it is likely that experts will continue working to develop AGI. AI that operates beyond human capabilities is a point of artificial superintelligence that is sometimes called singularity. 

When AI creations like ChatGPT and DALL-E were released to the general public, they were embraced by everyday users and professionals looking to generate outlines, sample prototypes, or simple lines of code. No matter how AI continues to develop, technology will likely continue to advance toward an AGI-type of cognitive computing.

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