MEET2026挤爆了，AI圈今年最该听的20+场演讲&对谈都在这

Core Viewpoint - The MEET2026 Smart Future Conference highlighted the rapid evolution of AI technologies, emphasizing the transition towards generative and reasoning AI, and the emergence of intelligent agents as a pivotal development in the journey towards Artificial General Intelligence (AGI) [1][5][4]. Group 1: Conference Overview - The MEET2026 conference, hosted by Quantum Bit, attracted nearly 1,500 attendees and over 3.5 million online viewers, showcasing significant interest from industry, academia, and investment circles [8]. - Key themes discussed included the integration of AI across various sectors, the importance of intelligent agents, and the belief that the next phase of AI development is imminent [5][4]. Group 2: Key Insights from Speakers - Zhang Yaqin from Tsinghua University emphasized the shift from discriminative to generative and reasoning AI, predicting that foundational models will consolidate into fewer than ten globally within the next 5-10 years, leading to an "agent internet" era [10]. - Wang Ying from Baidu highlighted the challenges users face with AI products and introduced GenFlow, a framework designed to create a universal intelligent agent that can operate across various scenarios, achieving over 1 million monthly active users [12]. - Wang Zhongyuan from the Beijing Academy of Artificial Intelligence discussed the transition from weak AI to AGI, emphasizing the need for multimodal capabilities in AI models to better understand and interact with the physical world [15]. - Qualcomm's Wan Weixing outlined the evolution of AI from perception to physical AI, focusing on the advancements in edge computing and the integration of multimodal capabilities [19]. - Amazon's Chen Xiaojian discussed the importance of building effective agents that can autonomously perform tasks, highlighting the challenges in transitioning from proof of concept to production deployment [21]. Group 3: Industry Trends and Challenges - The conference underscored the need for collaboration between technology and industry to overcome challenges in data, scenarios, and organizational coordination for AI agents [81]. - The discussions revealed a divide between general-purpose agents and specialized agents, with varying paths for development and deployment [82]. - The importance of user-friendly design in AI products was emphasized, suggesting that lowering barriers to entry is crucial for widespread adoption [93].