Group 1 - The article discusses the limitations of Chain of Thought (CoT) reasoning in AI, highlighting its inability to break the "1Hz" barrier and suggesting that implicit reasoning may be a more suitable approach for Agentic AI [7][8][10] - Recent studies indicate that CoT may not represent true reasoning but rather a structured pattern matching, which can lead to performance degradation in tasks requiring inductive reasoning [9][10] - The high computational cost and time consumption associated with explicit reasoning make it less viable for real-time applications, necessitating a shift towards implicit reasoning that can adapt to various task complexities [10][11] Group 2 - Implicit reasoning is gaining traction as it allows for faster processing and lower costs, making it more suitable for real-time AI applications compared to the traditional "Think-before-Speaking" (TbS) model [11][12] - The article emphasizes the need for AI agents to dynamically adjust their reasoning depth and speed based on task difficulty, which is a key capability for future AI development [10][11] - Challenges remain for implicit reasoning, particularly in high-stakes scenarios where accuracy and verifiability are paramount, such as legal document analysis and medical diagnostics [13][14]

Group 1 - The core concept of the article revolves around the "Intelligence Spectrum" proposed by Eric Jang, which addresses the current "1Hz barrier" faced by AI and the prerequisites for achieving "Ultra Instinct" capabilities in AI systems [5][6][9] - Jang categorizes different types of intelligent decision-making processes along a spectrum, from "extremely slow intelligence" (e.g., plant growth) to "extremely fast intelligence" (e.g., precise movements of a hummingbird) [6][7] - Current leading LLMs like ChatGPT and Llama operate at a frequency of 1-2Hz, which is significantly slower than the natural conversational pace of humans (approximately 10Hz), leading to a mismatch in interaction speed [7][8] Group 2 - The "1-2Hz intelligence" reflects the limitations of AI in real-time interactions, resulting in a turn-based scenario where human users must wait for AI responses, exacerbating issues like hallucinations and context understanding [8][9] - Jang emphasizes that overcoming the "1Hz barrier" is not merely about increasing speed but is essential for achieving a qualitative transformation in AI capabilities, covering the entire intelligence spectrum from 0.1Hz to 50Hz [8][9] - The article discusses the dual process theory by Daniel Kahneman, illustrating how different decision frequency requirements reflect the fundamental and sometimes conflicting speed demands of various AI applications [10]