Paul Lin ⁽³⁾

Abstract: This article explores reasoning techniques in large language models, revealing how these AI systems have evolved from simple text prediction to complex logical thinking abilities, including chain-of-thought, self-verification, and other key methods, as well as current challenges.

Abstract: Agentic AI perception refers to an autonomous system’s ability to sense, interpret, and act upon its environment using sensors, data inputs, and machine learning.

Unlike passive AI tools (e.g., chatbots), Agentic AI systems actively collect real-time data (e.g., visual, auditory, textual), extract meaningful insights, and execute tasks without constant human intervention.

Abstract: Agentic AI ushers in a significant AI leap. Its shift from passivity to activity unlocks vast industry potential. With features like environmental perception and self - learning, it powers diverse applications. As tech advances, it'll be more embedded in daily life, enhancing efficiency.

However, we must grapple with ethics and control. How can we ensure AI acts ethically? Who's accountable for its decisions? Answering these is key for its beneficial growth.