How Far Are We From AGI? This paper explores the current state and future trajectory of Artificial General Intelligence (AGI), aiming to foster a collective understanding and stimulate broader discussions among researchers and practitioners. AGI, capable of efficiently and effectively performing diverse real-world tasks akin to human intelligence, represents a significant milestone in AI evolution. While existing works have highlighted recent AI advancements, they lack a comprehensive discussion of AGI's definitions, goals, and development trajectory. This paper addresses pivotal questions regarding our proximity to AGI and the strategies necessary for its realization through extensive surveys, discussions, and original perspectives. The paper begins by articulating the required capability frameworks for AGI, integrating internal, interface, and system dimensions. As AGI realization demands advanced capabilities and strict constraints, necessary alignment technologies are discussed to harmonize these factors. The paper emphasizes the importance of responsibly approaching AGI by defining key AGI progression levels, establishing an evaluation framework to assess the current state, and outlining a roadmap for achieving AGI. It also outlines existing challenges and potential pathways toward AGI in multiple domains, providing tangible insights into AI's widespread impact. The paper is structured into several sections, starting with an introduction to AGI, followed by discussions on AGI internal components (perception, reasoning, memory, metacognition), interface components (digital, physical, and intelligence interfaces), system components (challenges, model architectures, training, inference, cost, platforms, future systems), alignment techniques, and a roadmap for responsibly approaching AGI. Case studies illustrate the current development of early-stage AGI in various fields, highlighting the potential of AI in science, visual intelligence, world models, decentralized AI, coding, robotics, and human-AI collaboration. The paper concludes by emphasizing the importance of responsible AI development, ethical considerations, and the need for explainable and transparent AGI systems. It also highlights the challenges and future directions for AGI, including the need for advanced reasoning abilities, dynamic reasoning across domains, ethical and efficient planning, and the ability to understand context, infer causality, and apply advanced logical planning. The paper underscores the importance of addressing hallucination, uncertainty assessment, ambiguity handling, and social reasoning to ensure AGI systems are reliable, safe, and capable of interacting effectively with humans and other agents.How Far Are We From AGI? This paper explores the current state and future trajectory of Artificial General Intelligence (AGI), aiming to foster a collective understanding and stimulate broader discussions among researchers and practitioners. AGI, capable of efficiently and effectively performing diverse real-world tasks akin to human intelligence, represents a significant milestone in AI evolution. While existing works have highlighted recent AI advancements, they lack a comprehensive discussion of AGI's definitions, goals, and development trajectory. This paper addresses pivotal questions regarding our proximity to AGI and the strategies necessary for its realization through extensive surveys, discussions, and original perspectives. The paper begins by articulating the required capability frameworks for AGI, integrating internal, interface, and system dimensions. As AGI realization demands advanced capabilities and strict constraints, necessary alignment technologies are discussed to harmonize these factors. The paper emphasizes the importance of responsibly approaching AGI by defining key AGI progression levels, establishing an evaluation framework to assess the current state, and outlining a roadmap for achieving AGI. It also outlines existing challenges and potential pathways toward AGI in multiple domains, providing tangible insights into AI's widespread impact. The paper is structured into several sections, starting with an introduction to AGI, followed by discussions on AGI internal components (perception, reasoning, memory, metacognition), interface components (digital, physical, and intelligence interfaces), system components (challenges, model architectures, training, inference, cost, platforms, future systems), alignment techniques, and a roadmap for responsibly approaching AGI. Case studies illustrate the current development of early-stage AGI in various fields, highlighting the potential of AI in science, visual intelligence, world models, decentralized AI, coding, robotics, and human-AI collaboration. The paper concludes by emphasizing the importance of responsible AI development, ethical considerations, and the need for explainable and transparent AGI systems. It also highlights the challenges and future directions for AGI, including the need for advanced reasoning abilities, dynamic reasoning across domains, ethical and efficient planning, and the ability to understand context, infer causality, and apply advanced logical planning. The paper underscores the importance of addressing hallucination, uncertainty assessment, ambiguity handling, and social reasoning to ensure AGI systems are reliable, safe, and capable of interacting effectively with humans and other agents.