What Is Artificial General Intelligence?

Artificial general intelligence (AGI) is a hypothetical form of artificial intelligence in which a machine can learn and think like a human. For this to be possible, AGI would need self-awareness and consciousness, so it could solve problems, adapt to its surroundings and perform a broader range of tasks that it wasn’t initially trained to do.

If artificial general intelligence (sometimes called strong AI) sounds like sci-fi, that’s because it still is. Existing forms of AI haven’t quite reached the level of AGI — but developers are still working to make it a reality.

“AGI doesn’t exist today in the way we think about it,” Wayne Chang, cofounder of Digits, told Built In. “However, the speed of innovation towards AGI is accelerating. In its ideal state, AGI would perform tasks that are identical to or surpass those that a human would perform.”

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What Could Artificial General Intelligence Do?

Current forms of AI are able to master a specific task they’re programmed to undertake. AGI, in theory, takes this capability a step further, adapting to unfamiliar situations it was never trained to handle. This opens the door for many more applications:  

• Healthcare: AGI could analyze massive volumes of patient data to identify at-risk patients, predict future diseases and design personalized treatments.
• Education: AGI could curate a unique curriculum for students based on their individual academic performance and learning style.
• Customer service: AGI could use past calls and demographic info to tailor service to each customer, anticipate questions and take proactive measures before issues occur.   
• Finance: AGI could compile information to enhance the accuracy of financial models, predict market behavior and execute informed trades based on real-time insights.
• Self-driving cars: AGI could collect real-time information (on weather, traffic patterns, etc.) from sensors and make instant adjustments to adapt to various scenarios.  
• Programming: AGI could understand coding logic to not only generate code, but also make recommendations and design entire functions to fulfill particular needs.  
• Manufacturing: AGI could process large amounts of data gathered from sensors to predict machine issues and alert teams before equipment breaks down.

AGI vs. AI: What’s the Difference? 

AGI is a subcategory of AI, and the former can be seen as an upgraded version of the latter. 

• Artificial intelligence is often trained on data to perform specific tasks or a range of tasks limited to a single context. Many forms of AI rely on algorithms or pre-programmed rules to guide their actions and learn how to operate in a certain environment.
• Artificial general intelligence, on the other hand, is able to reason and adapt to new environments and different types of data. So instead of depending on predetermined rules to function, AGI embraces a problem-solving and learning approach — similar to humans.

Types of Artificial Intelligence

Artificial general intelligence is considered one of the three main types of AI. 

Weak AI (Narrow AI)

Two subsets of AI fall under the weak AI category: reactive machines and limited memory machines. Reactive machines can react to immediate stimuli, but cannot store or learn from memories of past actions. Limited memory machines can store past information to improve their performance over time. As a result, weak AI can only perform a limited range of tasks. 

Strong AI (Artificial General Intelligence)

AGI is also referred to as strong AI, which can replicate human intelligence. When strong AI learns how to complete one task, it can take this knowledge and apply it to other tasks. Strong AI can then take on challenges it was never trained for, demonstrating the kind of advanced problem-solving and adaptability associated with humans.  

Artificial Superintelligence (ASI)

Artificial superintelligence is a theoretical form of AI that would be able to learn at a rapid rate to the point where it surpasses the abilities of humans. ASI is seen as the technology necessary to develop self-aware AI. In this state, AI would be able to act according to its own will and disregard instructions or its intended purpose. 

While AI tools today mostly belong to the weak AI category, some believe we are inching closer toward achieving artificial general intelligence.   

Examples of Artificial General Intelligence

While artificial general intelligence doesn’t exist, the following examples show that AGI may not be that far off. 

ChatGPT-4o 

ChatGPT-4o builds on the foundation laid by previous GPT models, with the goal of realizing “more natural human-computer interaction.” The model can process text, visuals and audio and respond via text or its own voice to sustain in humanlike conversations. 

IBM Watson

IBM Watson made waves when it won Jeopardy! in 2011, defeating two of the show’s most renowned champions. The suite of Watson tools can now be used to sift through data, glean insights, anticipate user needs and more. 

Self-Driving Cars

Many cars include autonomous features, like Honda’s traffic jam feature that can adapt to crowded conditions on the road. Meanwhile, Waymo’s autonomous ride-hailing service demonstrates complete autonomy while transporting customers. 

AlphaFold 3

Designed by Google DeepMind, AlphaFold 3 doesn’t just predict protein structure but can also predict the structures of life’s building blocks, including DNA and RNA. This makes it possible to generate models of various molecular structures and accelerate drug development.

AI Music Generators

AI music generators are beginning to compete with human musicians, producing songs that generate plenty of buzz online. For example, Suno can supplement AI-generated lyrics with vocals and instrumentals, crafting all the elements of a song on its own. 

Benefits of Artificial General Intelligence

The development of AI technology is progressing in leaps and bounds. Artificial general intelligence might not be here today, but its arrival will transform daily life in countless ways: 

• Increased productivity: AGI could adapt to new tasks and roles, saving teams from having to repeatedly train it and freeing up workers to handle other challenges.  
• Enhanced problem-solving: AGI could use its advanced computing power to address global issues like climate change, widespread disease and supply-chain needs. 
• Faster healthcare: AGI could quickly diagnose diseases and design new treatments, resulting in faster and more personalized healthcare. 
• In-depth interaction: AGI could offer sharp insights and sound advice, becoming a more active collaborator and even taking on roles like mentor.  
• Original creativity: AGI could use flexible thinking to craft its own movie scripts, songs, videos and other creative works with little to no prompting. 

This transformation will mean huge benefits for society. Artificial general intelligence will be able to scan all preexisting information available in places like the internet to solve some of the world’s most pressing problems. 

“AI has many positive uses now but has enormous future potential,” Amruth Laxman, co-founder of 4Voice, told Built In. “It could, in the future, find a cure for chronic illnesses like cancer or resolve issues like overburdened utility infrastructure.”

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Risks of Artificial General Intelligence

For all its potential benefits, artificial general intelligence doesn’t come without risks. Already, AI is challenging our perception of the world and what makes us human, and AGI could come with even more consequences:  

• Ethical questions: There’s reason to question whether AI can understand human ethics, so humans may have to confront an AI that doesn’t follow human ethical standards.
• Social inequities: AGI requires the kind of capital and resources only large corporations have, concentrating even more power in the hands of a few businesses.  
• Lack of legal safeguards: Laws still lag behind weak AI, so AGI would likely have no legal limits and could potentially be used for malicious purposes.    
• Job losses: The development of an AI that can mimic and surpass human abilities may trigger fears of job losses due to automation.

Within weak AI, issues have already arisen where embedded systems have been built with biased data. This can result in AI making erroneous or, at worst, discriminatory decisions. 

“Existing attempts at large AI models are trained with unfiltered and unreviewed data,” Chang said. “Because of this, a major concern is biased data, which can in turn compound within the systems and be exaggerated through the models.”

Artificial general intelligence does come with its dangers. But as long as the humans at the wheel have good intentions, Arnold Liwanag, chief technology officer at AI company Tealbook, isn’t worried.

“AI is a tool,” Liwanag said. “The risk is only as great as the intent people have when using these tools.”

Future of Artificial General Intelligence

According to a TIME article, some forecasters predict AGI could exist as early as 2030, while many others don’t foresee AGI being achieved until decades later at the earliest. But forms of advanced AI continue to bring the field closer to AGI, with Google DeepMind’s AlphaGeometry 2 being seen as an AGI milestone due to its performance on Olympiad math questions and OpenAI claiming it is close to building AI that can reason.   

If AGI is ever realized, it would mean AI that could act on abstract thinking, common sense, background knowledge, transfer learning and cause and effect. This would open up the possibilities for numerous industries. AGI could perform surgeries in the medical field and bring about autonomous cars in the automotive industry. Complex tasks and workflows would become AI-powered, saving organizations time and money. More ambitious views of AGI even envision it helping humans address large-scale problems like climate change.

Of course, concerns remain about artificial general intelligence being developed without any laws or policies that could hold companies accountable. Researchers have responded by calling for “ethical frameworks and governance mechanisms” to keep the technology in check. Regulations for current AI technologies are also on the horizon, with the EU AI Act being rolled out in the coming years.     

Steps taken to monitor weak AI could open the door for more robust AI policies that can better prepare society for AGI and even more intelligent forms of AI. Governments and societies may then want to take proactive measures to ensure AI organizations prioritize the common good, so people can enjoy the benevolent aspects of self-aware AI and a higher quality of life.   

“Cognitive power is going to flow from sentience,” computer scientist and AI researcher Selmer Bringsjord previously told Built In. “And when power is available and not sufficiently controlled — self-controlled or controlled by others — really, really bad things can happen.”

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