A Playful Exploration of single AI Agent

Dive into the world of AI agents, where it’s still unclear whether these systems could only imitate limited human actions or possibly develop their own unique intelligence. AI agents have moved beyond mere routine tasks and now tackles complex challenges that are quite remarkable. Are these agents mini versions of us, ‘learning’ through trial and error, or are they merely tools meant to augment our abilities? Or they might even surpass our intelligence one day!

For now, let’s set aside these big questions. Instead, we’ll use a fun and playful exploration of human behaviour to better understand these AI agents.

Imagine a young boy sent to a grocery store to pick up something for his mother. The boy doesn’t act randomly; he formulates a plan based on available tools, short-term memory of the context and task, as well as his long-term memory of locations and past experiences. As he proceed, feedback from the environment helps him adjust and refine the plan. This iterative process of planning, receiving feedback, and adapting closely reflects the fundamental functions of an AI agent.

Now, imagine he has started school and is beginning to learn math. Each day, he returns home with homework, tackling each problem as he did simpler tasks in his younger years. You might notice he needs some guidance to solve the problems accurately. Experimenting with different teaching methods, such as offering examples of similar problems, advising him to think slowly through each step, or demonstrating problem-solving techniques, you gradually find some effective ways to aid him, enhancing his ability to solve problems. This resembles how varied prompts can improve the performance and perspective of an LLM agent.

Although humans and AI agents share some similarities, they differ in their approaches to complex tasks. Unlike agents, humans not only plan but also mentally simulate these plans, envisioning potential outcomes beforehand. This ability to mentally model scenarios, whether mapping out a path to a certain location or anticipating dialogue in an important meeting, is crucial for finding optimal plans. However, this process also places a computational burden on agents. Thus, for agents to excel, they must possess the ability to simulate plans and ability to determine when to employ them.

Another key difference lies in our capacity to evolve our knowledge. Humans can grasp abstract concepts or extract them from our experiences, enabling us to effectively tackle new real-world challenges. For AI agents to reach higher levels of intelligence, they may need to integrate a comprehensive world model, including the abilities to extract abstract knowledge and apply them in unseen situations. This integration could also enable these agents to autonomously build new tools to extend their capabilities.

Furthermore, our brain development is closely linked to our senses, providing crucial information that shapes our intelligence. Unlike humans, AI agents, particularly large language models (LLMs), operate solely in digital environments, processing text-based inputs. Their potential to reach advanced intelligence levels remains uncertain. Achieving human-like intelligence may require these agents to perceive and interact in the physical world. Until then, enhancing their abilities through multi-modal integration — adding capabilities for processing images, audio, and video — could improve their understanding and problem-solving in complex tasks.

Furthermore, humans develop their own principles and philosophies. Coupled with our diverse knowledge base, we often approach problems differently. This diversity promotes optimal convergence and progress as a whole. Collaborative efforts between humans and AI agents, as well as among AI agents themselves, amplify their effectiveness in addressing complex tasks. The challenge lies in cultivating diversity among AI agents.

While debates continue on whether AI agents can achieve Artificial General Intelligence (AGI), it’s clear that there is still much room for improvement. Nevertheless, AI and AI agents are improving rapidly. Recognising this, it is crucial that we use these technologies wisely to augment our abilities, addressing complex challenges more efficiently. Through responsible and innovative utilisation, we can unlock their potential to contribute to building a better, more effective world.