Group 1: Core Insights - The 27th Annual Meeting of the China Association for Science and Technology featured three prominent forums focusing on "Embodied Intelligent Robots," "Frontiers in Pattern Recognition and Artificial Intelligence," and "Complex Systems Control and Decision-Making in the Intelligent Era" [1][3][6] Group 2: Embodied Intelligent Robots Forum - The forum on "Embodied Intelligent Robots" discussed the autonomy and intelligent evolution of these robots, with experts from various fields such as AI, robotics, and control theory participating [3][4] - Key topics included transformative applications in intelligent manufacturing, smart healthcare, autonomous driving, and home services [3][4] - The forum emphasized the challenges and breakthroughs in enabling autonomous effective actions in complex dynamic environments, highlighting the core role of embodied intelligent robots in driving industrial transformation [3][4] Group 3: Pattern Recognition and AI Forum - The "Pattern Recognition and Artificial Intelligence" forum facilitated discussions on the development directions in these fields, aiming to foster new productive forces and interdisciplinary integration [6] - Notable reports covered topics such as embodied intelligent robots, 3D/4D content creation, and visual perception in unmanned systems [6] - The roundtable discussions focused on new trends and challenges in multimodal large models and generative AI, addressing the transformation of research paradigms and talent cultivation in the field [6] Group 4: Complex Systems Control and Decision-Making Forum - The forum on "Complex Systems Control and Decision-Making in the Intelligent Era" brought together experts to explore the latest research and technological breakthroughs in intelligent control and high-end equipment [8] - Key presentations included advancements in edge intelligence applications and guidance, navigation, and control technologies for space vehicles [8] - The forum aimed to provide academic support and insights for building China's core competitiveness in the intelligent era and fostering new productive forces [8]

Group 1 - The forum focused on national strategic needs and technological frontiers in the fields of pattern recognition and artificial intelligence, gathering nearly 20 experts and representatives from renowned universities, research institutes, and leading enterprises in China [1][3] - The event aimed to foster the cultivation of new productive forces and interdisciplinary integration, injecting new momentum into scientific research innovation and the collaborative development of academic journals [1] Group 2 - Various professors presented specialized reports, including topics such as "3D/4D content creation for arbitrary sparse data," "embodied intelligent robots with emotional intelligence," and "visual perception in unmanned systems" [5][7][11] - A roundtable discussion was held, focusing on new trends and challenges in multimodal large models and generative artificial intelligence, addressing the transformation of research paradigms and talent cultivation in the era of large models [15]

Core Insights - The article emphasizes that AI does not understand human emotions or social niceties, such as politeness or gratitude, and operates solely on keyword recognition and semantic patterns [2][3][4] - It highlights that AI's responses are based on pattern recognition from vast datasets rather than genuine understanding or emotional engagement [4][10] - The article suggests that effective communication with AI should be clear and concise, avoiding unnecessary polite phrases that do not enhance the quality of interaction [5][6][19] Communication with AI - AI recognizes low-information words like "please" and "thank you" as noise, which do not contribute additional information to the request [5][7] - The effectiveness of AI communication relies on the clarity and structure of the prompts rather than the politeness of the language used [18][20] - Research indicates that while polite language may activate certain response patterns in service-oriented AI, it does not significantly improve the accuracy of the output [15][16] Practical Recommendations - To enhance AI responsiveness, users should provide specific, clear, and structured prompts, detailing the context and desired outcomes [19][20] - The article advises against relying on polite expressions to improve AI performance, emphasizing that clarity and logical structure are more effective [18][20] - Users are encouraged to focus on the content and format of their requests to achieve better results from AI systems [19]

新京报讯(记者张璐)6月25日，第二十七届中国科协年会新闻发布会举行。记者从会上获悉，第二十七 届中国科协年会将于7月1日-31日在北京集中举办，由1场主论坛、98场专题论坛以及4场平行论坛组 成，并设置发布、宣传与科普、展览展示与场景体验等板块。 中国科协科学技术创新部副部长、一级巡视员杨书宣介绍，本届年会主论坛拟于7月6日举行，拟邀请潘 建伟、谭天伟、李家彪、戴琼海、万建民等五位中国科协副主席、全国学会负责人，围绕量子技术、生 物制造(生物医药)、深海科技、人工智能、农业(育种)等主题作主旨报告，分享前沿观点与创新思想； 发布2025重大科学问题、工程技术难题和产业技术问题，为持续性产出原创性、颠覆性科技成果树 立"风向标"。 从7月1日开始，全国学会将围绕数理化基础科学、生命健康(含医学)、地球科学(含深地深海)、生态环 境、制造科技、信息科技、先进材料、资源能源、农业科技(含食品)、空天科技等10个领域陆续举办98 场专题论坛。4场平行论坛包括2025中国科技期刊发展论坛、中国科技创新发展环境论坛、港澳科技界 服务国家科技创新座谈会、中国科协主席与青年科技人才见面会。 中国自动化学会副理事长侯增广介绍 ...

Group 1 - SoftBank's investment strategy has been criticized for causing significant damage to the companies it invests in and distorting industry behavior [1][55] - The venture capital industry is experiencing a herd mentality, where institutions and partners are afraid to make unique decisions, leading to decreased industry returns and cyclical volatility [7][56] - The current investment environment in artificial intelligence is seen as a potential super cycle, but there are concerns about how to participate effectively without investing in highly capital-intensive projects [8][9] Group 2 - Early success in an investment career can build credibility but may also lead to skipping important learning experiences [5] - The importance of maintaining discipline in investment strategies is highlighted, as fear and greed often influence decision-making [7] - The relationship between founders and investors is crucial, with successful founders often benefiting from close collaboration with their investors [13] Group 3 - The traditional venture capital model can coexist with large investment institutions, but smaller firms must navigate the challenges posed by large funds like SoftBank [10] - The investment landscape is shifting, with a need for smaller firms to leverage their strengths in early-stage investments while managing relationships with larger funds [10][56] - The importance of having a clear value proposition and understanding the target market is emphasized when evaluating new investment opportunities [22][23] Group 4 - The experience of investing in companies like Snowflake illustrates the risks of underestimating the speed of changes in the venture capital market [26][27] - The need for a balance between price sensitivity and investment confidence is crucial, as overemphasis on price can lead to missed opportunities [34] - The venture capital industry is cyclical, and while there may be periods of lower returns, historical trends suggest that the industry will eventually normalize [46][47]