Artificial intelligence is everywhere, and people across industries are now aware of it, but what is artificial general intelligence, and why are people beginning to talk a

Understanding Artificial General Intelligence (AGI)

Artificial intelligence is everywhere, and people across industries are now aware of it, but what is

artificial general intelligence, and why are people beginning to talk about it?

These were the exact thoughts that came to my mind when I heard of artificial general intelligence or

AGI. So, what is it, and why is this a big deal according to some?

Let's find out.

What is Artificial General Intelligence (AGI)?

Have you seen those videos or read blogs where you are warned about the evil power of artificial

intelligence and that the technology is going to take over the world and eliminate non-compliant

humans, while all you get is rather less-intelligent GPT, which is no way near threatening?

Well, that scary technology can be artificial general intelligence. As of today, the subject of artificial

general intelligence is thought to be a hypothetical form of AI that can think, process, and act like a

human. A real, conscious, self-aware, logical human.

Today, artificial general intelligence (also sometimes referred to as strong AI) is a mere concept and yet

to be created, but even the idea of AGI happening a few years, or decades from now is exciting. Imagine

if you could ask AI to do something. It just doesn't apply an algorithm to get the work done but critically

assesses the situation to ensure you get the right output—isn't that amazing?

The existing forms and models of AI are no way near to what AGI is, and AI engineers and developers

are working to make it a reality—but it might take years or decades to see it in action.

AGI Vs. AI: Are These Similar?

A lot of people around you (and me) might not understand the difference between AGI and AI—but

the fact of the matter is both these terms are confusing, at least till AGI is publicly introduced and

becomes common.

AGI, or artificial general intelligence, is a subset of AI but an advanced version of it. The AI in practice

today, or the models that are being widely used, are often trained or real-world data that has been

cleansed and refined to omit any inaccuracies and are expected to perform a single or a set of tasks.

However, there's a big limitation to achieving maximum efficiency, and that is: all these models are

often limited to a single context and cannot analyze contextual data, and hence, cannot have human-

like intelligence. It performs certain defined actions and follows the already laid out rules in the

algorithm to steer its actions and processes, which are also in a specific environment.

The case with artificial general intelligence is starkly different from what we know and understand

about AI (or weak AI). The idea of having an AGI system means that it will not necessarily have a set of

rules or pre-defined environments to function appropriately. This means it will take a more logical,

problem-based approach to arrive at a solution—and not follow some generic path already fed into

the weak AI model. This also entails that AGI is set to be more flexible, hence making it acceptable in

various industries and applications for an increased number of tasks.

What Are the Capabilities of an AGI System?

When implemented, AGI should be able to carry out a range of tasks that no current system is able to

perform. No doubt that the systems in place today are increasingly intelligent and solve a variety of

problems for humans, but they are still not at the level of human or general intelligence.

Here's some of what we can expect from an artificial general intelligence system:

• It will be able to perform/execute abstract thinking tasks, opening new doors of research.

• It will have the transfer learning capability, which means more diverse applications.

• It will be able to make decisions, not just by using an algorithm, but by using common sense.

• It will have contextual or background information, which will enable better outputs or

decision-making.

Artificial General Intelligence Examples & Use Cases

AGI isn't real yet, at least for the public. No system currently exists that works and performs with

human-like abilities. However, there are a few applications of weak or narrow AI that take it near to

what will be found in artificial general intelligence, or strong AI, with better accuracy and efficiency

and without the limitations and constraints of limited memory.

Let's have a look at some of the AGI examples and use cases:

• Fully Autonomous Vehicles

Fully autonomous vehicles or self-driving cars are a form of AI that is near to what an AGI

system will be like. These self-driving models/systems approximate or sometimes far surpass

human intelligence and depict AGI-like characteristics. The systems are pre-trained with data

to identify objects, human and non-human, and made in a way that all regulations and safety

measures are well in place.

• IBM Watson

There are some calculations (for space missions, super-complex engineering, and military-tech

purposes) that normal computers cannot handle—that's where supercomputers like IBM

Watson take the front seat and utilize their incredible power and AI capabilities to perform

those impossible calculations.

• Large Language Models

For the last couple of years, we have experienced a significant increase in the use of large

language models or LLMs. Generative Pre-trained Transformers, or GPT for short, are publicly

released models by OpenAI that reflect the incredible capability of these AI models. It is true

that these models often produce outputs that are inaccurate and very basic, but they hint at

what could be made if further advancements are made possible.

These are some use cases where artificial general intelligence can be incorporated, and if done

appropriately, it can massively impact the output and improve practical usefulness and efficiency.

Benefits of Artificial General Intelligence

One might wonder that if it is such a game-changing technology, what are the benefits of artificial

general intelligence, and why does it not have the hype it deserves?

While I might not be able to answer the latter part of the question, I can certainly list some of the

probable benefits of artificial general intelligence against real-world problems and what could be

achieved if AGI becomes a reality. Let's have a look:

• Cure of Chronic Illnesses

Scientists, for a long time, have been trying to find practical and effective cures for multiple

chronic illnesses like cancer. This will be a huge stride toward making a better and safer world.

• Expedited Space Exploration

Space exploration is often hindered by a plethora of limitations, but with the advent of artificial

general intelligence, it could be made possible, and who knows, we might be able to

experience something revolutionary.

• End to Global Warming

Global warming is among the world's most pressing concerns. The practical use of AGI could

be the gateway to devise intelligent, practically viable, and effective policies to reduce the

global carbon footprint, adopt more sustainable practices across different sectors, and put an

end to global warming—which is now a looming threat.

Technologies Contributing to AGI Research

It is now established that AGI is still a work in progress, but there are a few technologies that are aiding

scientists and researchers in taking small but concrete steps toward a full-fledged AGI system. Below

are a few of the emerging technologies commonly used for this purpose:

• Deep Learning

Deep learning is among the emerging technologies that contribute to AGI research. It studies

raw data and forms conclusions based on that through neural networks. It usually has multiple

layers that are used to decipher and understand complex relationships. There are many

incredible systems in place, built by AI experts, that are able to understand text, audio, images,

and video data and process various other types of information.

• Generative AI

Generative AI, also commonly known as Gen AI or generative artificial intelligence, is part of

deep learning. This technology has seen stark improvement in adoption and distribution over

the past few years. It works by classifying and understanding data and producing unique

outputs, including texts, images, code, audio, and videos. Generative AI models are trained

with massive amounts of data, allowing them to cater to a variety of queries that are similar

to human-generated content and have some form of intelligence. However, because of its

limitations and its generative nature, the outputs are not always factually correct.

• Natural Language Processing

NLP, or natural language processing, is exactly what the name suggests. It is a type of AI that

enables systems or models to comprehend and then generate human-like content or human

language. It uses machine learning and computational linguistics to understand and make

sense of data and build contextual relationships. NLP is fuelling the research for AGI in multiple

ways.

• Computer Vision

For the analysis of visual and spatial data, computer vision is the right technology. The

technology now has widespread applications, including self-driving vehicles that process and

analyze real-time camera feeds and steer the vehicles clear of any obstacles or apply breaks

on time. Computer vision is also widely implemented in multiple factories, mainly to ensure

worker safety in critical areas, analyze equipment effectiveness, and at conveyor belts for

classification of different objects based on their color, size, and other factors.

• Robotics

Although robotics is not directly linked to the ongoing AGI research, robotic process

automation is a significant application of the AGI system, where organizations can build

complete plants through specific mechanical systems that intelligently perform physical

movements. For example, an AGI-powered robotic arm could perform tasks that are not

currently automated, especially the ones requiring physical human touch. The sensory

perception and manipulation capabilities of AGI could transform that.

Challenges in AGI Research

Like every other research, scientists and researchers face certain challenges in developing an ideal AGI

system. These challenges include:

• Sensory Perception

Sensory perception today is not possible through machines or software. However, AGI aims to

solve this issue. It is among the biggest challenges faced by researchers to solve the sensory

perception issue and interact with the outside world or objects. Apart from the robotic

capabilities and maneuverability, the system must also be able to perceive information like

humans. Today's technology needs significant advancement before we can use machines to

perform sensory tasks.

• Form Connections

The weak or narrow AI models are limited because of the data they are trained on and cannot

transfer the expertise of one domain to another—while humans can very often do that. This

challenge of having to draw connections and transfer the knowledge of one domain to

another, as well as the ability to give accurate results, even when the input is from unfamiliar

data, is hindering scientists from making great strides.

• Emotional Intelligence

Another challenge in developing artificial general intelligence is the incorporation of human

emotions or emotional intelligence. The ability to function as humans and possess

characteristics is a blocker in building an artificial general intelligence system. The ability to

respond based on emotions, among other factors, and not only text-based linguistic datasets,

makes this technology stand out—however, it has yet to be built.

Ethical Considerations and the Future of Artificial General Intelligence

One thing is for sure—the benefits of artificial general intelligence are incredible and far-reaching, but

there's also a flip side to it. AGI should be approached with caution. While AGI is immensely useful, it

can act as a two-edged sword if not managed and regulated properly.

The challenges we face with current AI technologies hint at even greater risks with the emergence of

artificial superintelligence or strong AI—surpassing common human intellect. Without proper

regulation, we may confront AI systems perpetuating harmful biases and making decisions contrary to

human ethics.

The control (or the lack of it) over AGI raises questions about power dynamics. While AGI holds

immense potential across various industries, it's important for organizations and leaders to prioritize

ethical considerations in its development. Ensuring that AGI and other AI technologies are geared

towards useful and beneficial purposes should be a primary focus before widespread adoption.