What is Artificial General Intelligence (AGI) and How Does It Differ from the AI We Know?

The term artificial intelligence, or AI, is everywhere these days. With AI services like ChatGPT, Gemini, and Claude making headlines, many are left wondering what kind of AI these platforms represent. You might also be curious about the true capabilities of AI and how it can be used.

In this article, we’ll explain the different types of artificial intelligence, their history, and answer the question “What is artificial general intelligence?” We'll explore its capabilities, how it differs from other AI, and the limitations that prevent AGI from becoming a reality just yet. We’ll also cover the real benefits of AI for businesses today.

What is AI, or Artificial Intelligence, and Why is it Essential Today?

While there are many definitions of artificial intelligence (AI), the main concept is the development of machines that can learn from and process data, make decisions, and act rationally, much like a human.

The central goal of AI development is to create systems that can learn independently from incoming data to solve new problems the way humans do, or even surpass human abilities. These abilities include everything from conversation and problem-solving to making decisions.

AI is also a major factor in shaping trends in software development.

The Beginnings of AI

Many people think of AI as a new phenomenon, but its origins date back further than you might expect. According to a document from the University of Washington, the concept of AI can be traced back to 1950. It was then that English mathematician Alan Turing published his paper "Computing Machinery and Intelligence," which opened with the question, "Can machines think?" This question effectively opened the door to the world of AI.

In the years that followed, AI research intensified. In 1955, the world's first AI program, Logic Theorist, was created. Later, in 1963, the Defense Advanced Research Projects Agency (DARPA), a unit of the U.S. Department of Defense, specifically funded AI research at the Massachusetts Institute of Technology (MIT).

A significant milestone occurred in 1997 when Deep Blue, a program running on a supercomputer, defeated the world's greatest chess champion at the time, Garry Kasparov. This was a major step for AI technology, opening the door for the widespread applications we see today.

How Does AI Work?

Two components are essential for AI to function: algorithms and data. Large amounts of data are fed into algorithms to recognize patterns and make predictions in a process known as training.

Once an algorithm is extensively trained, it's deployed through applications like ChatGPT or other AI tools. It continuously learns and adapts to new data, allowing the AI system to perform complex tasks like image recognition, language processing, and data analysis with increasing accuracy and effectiveness over time.

What are the Types of AI?

Different types of AI have varying capabilities and complexities in data processing. When categorized by ability, AI is generally divided into three types: Artificial Narrow Intelligence, Artificial General Intelligence, and Artificial Super Intelligence.

Artificial Narrow Intelligence (ANI)

Artificial Narrow Intelligence (ANI), or Narrow AI, is designed to perform specific, specialized tasks. This type of artificial intelligence cannot think analytically, use reason, or solve problems outside of the tasks it was trained for.

We see clear examples of ANI in action all around us, such as in-car autonomous driving systems, language translation tools, facial recognition software, and even Apple's Siri.

Artificial General Intelligence (AGI)

Artificial General Intelligence (AGI) is a theoretical form of AI that would possess human-like abilities, including analytical thinking, reasoning, and independent problem-solving without human intervention. This general AI would be able to learn, improve, and apply its knowledge across a much wider range of tasks than ANI. The development of true AGI is a long-term goal for many researchers.

Currently, no such AGI is available for public or private use, but developers are actively working to reach this point.

Artificial Super Intelligence (ASI)

Artificial Super Intelligence (ASI), or Superintelligent AI, represents a level of intelligence that surpasses human capabilities in every aspect. It would be excellent at analytical thinking, reasoning, creativity, and solving incredibly difficult problems by learning from vast amounts of data at an unprecedented speed. It is the stage of artificial intelligence that would succeed AGI.

Like AGI, ASI does not yet exist.

AGI and ASI: Current Developmental Hurdles

The path to creating AGI and ASI is filled with major challenges. Some of these include mastering language comprehension, advanced problem-solving, genuine creativity, and the ability to reason and process emotions and feelings.

Also, developing ASI requires the successful creation of Artificial General Intelligence first. A major roadblock for both is our incomplete understanding of the human brain. Research into neuroscience is constantly revealing new insights into how different parts of the brain work, which means the timeline for developing Artificial General Intelligence may extend further.

At the same time, building AI models capable of such advanced functions requires enormous computational resources. As a result, current AI technology remains in the "narrow" stage.

The Difference Between Generative AI and Other Forms of AI

The rise of Generative AI, marked by tools like ChatGPT and Gemini, has had a huge global impact and attracted a huge user base. Its ability to create new content, such as audio, images, and text, represents the latest breakthrough in the field and has the potential to drastically change how content is produced.

However, Generative AI is fundamentally different from theoretical concepts like AGI or ASI. Its limitations include a lack of true understanding, restricted applications, the potential for generating incorrect information (hallucinations), and the ability to solve problems only partially.

Generative AI also requires training on pre-existing datasets, whereas a true AGI  could learn from new experiences in real-time. Despite these differences, the advancements in Generative AI are an important step toward the future development of AGI.

The Business Advantages of AI

The adoption of AI in business is rapidly increasing. A report from Accenture revealed that 84% of executives believe they must use AI to achieve business growth. Simultaneously, AI technology can improve many different business functions.

Here are some of the main advantages of AI for businesses:

Increased Operational Effectiveness

AI's powerful data analysis capabilities can lead to more effective use of organizational resources. It can help identify new sales channels and allow employees to complete their work more effectively.

Improved Customer Experiences

AI technology is a major factor in delivering superior customer experiences. Chatbots can operate 24/7 to handle routine inquiries, while data analysis can uncover individual customer preferences to offer personalized products and services.

Reduced Errors in Operations

AI helps minimize human error by verifying data and flagging mistakes. Doing so reduces potential losses for businesses, such as in fraud detection for the financial sector or health analytics.

Data from Statista in 2023 shows that AI is most commonly used for product or service development (26%), followed by marketing (25%) and service operations (24%). A McKinsey survey found that the telecommunications and media industries had the highest AI adoption rates, followed by the technology and legal sectors.

Additionally, a 2023 analysis by Goldman Sachs predicted that the rise of AI technology will increase global economic productivity by 7%, caused by its increasing use in the business sector.

Grow Your Business Growth with AI Experts

Integrating AI into your business can yield significant positive outcomes, from improving effectiveness and reducing errors to improving management and creating new revenue streams. Companies that adopt AI early are best positioned to seize new opportunities.