AGI, Simply Explained

When people normally talk about Artificial Intelligence (AI), they typically mean AI tools that are becoming increasingly commonplace, such as LLM chatbots like ChatGPT or AI agents such as GitHub Copilot.

These tools are all an effort that leads us to Artificial General Intelligence (AGI), which refers to AI systems that can understand, learn, and perform tasks that we would normally expect only a human would be able to do.

Although there are indeed many AI agents available nowadays, they are typically built to be good at one specific task or function.

AGI, on the other hand, would theoretically be flexible enough to switch between many different tasks while also being smart enough to adapt learned patterns from one task to solve another.

To paint a broader picture, imagine if the same AI that could beat a grandmaster in chess could then also help optimize your calendar, construct recipes based on the ingredients in your pantry, and even provide therapeutic comfort when you type your feelings out to it as a chat.

This broad applicability is why we consider AGI to be considered “general” intelligence. In theory, it would be able to understand, improvise, and learn across a span of topics, much more like humans do.

So, is this just science fiction? Or is it our inevitable future? Well, we don’t fully know yet. Although the rise of AI has been exponential in recent years, AGI’s feasibility is still a large question—can AI really replace humans?

Today, researchers are exploring several avenues to develop AGI, such as scaling up powerful AI models (like ChatGPT), arguing that consistent development of their neural networks may allow these models to acquire more general human abilities.

• A community-made sample timeline of our progression towards AGI can be found here. There are some nice visuals and explanations!

Others are aiming to design neural networks that follow the structure of the human brain, aiming to allow models to make connections the same way humans do, increasing the scope for transferable knowledge.

Some believe that AGI will develop to its true potential only when we let AI models interact with the physical world as robots.

Well, what’s holding us back from entering the new era of intelligent robots coexisting with humans? Simply put, although AI agents are incredibly useful and have sped up many processes, they simply are not consistently smart.