Group 1 - The year 2024 is referred to as the "Year of Humanoid Robots," with predictions that emotional communication between humans and robots will become a norm in future intelligent societies [1] - The concept of machine emotions and AI companionship raises questions about the impact on human-machine interaction and relationships, as well as cultural and gender perspectives on these emotional connections [1] - The discussions highlight the potential social impacts, technological risks, and ethical issues arising from human-robot emotional interactions, prompting interdisciplinary research [1] Group 2 - The concept of machine emotions is defined and analyzed through emotional intelligence, human-machine emotions, and human-machine interaction, advocating for a limited approach to the development of machine emotions [2] - A new perspective on endowing machines with emotional capabilities is proposed based on a life-centered consciousness theory, suggesting that simulating biological homeostasis can lead to autonomous adaptability in machines [2] - Ethical reflections on human-machine emotional interactions, particularly in the context of AI resurrection technology, reveal risks such as emotional dependency and identity crises, necessitating regulatory and cultural adjustments [2] Group 3 - The philosophical discussions in affective computing often rely on idealized technical assumptions, overlooking the importance of forgetting mechanisms in creating realistic and ethical AI emotional systems [3][4] - The current challenges in affective computing include the reliance on data quality and the superficiality of emotional expressions in AI systems, which fail to capture the complexity of human emotional experiences [6] - The introduction of forgetting mechanisms is essential for enhancing the adaptability and authenticity of emotional AI, allowing systems to discard outdated emotional data [11][12] Group 4 - The proposed phenomenology-inspired human-like forgetting neural model (PHFNM) aims to integrate individual and collective forgetting processes in emotional AI systems, reflecting both natural decay and active forgetting [19][22] - The model consists of three interconnected layers: a low-dimensional emotional index layer for natural decay, a memory encoding layer for dynamic reconstruction, and an active forgetting layer for ethical regulation [23][24][25] - The PHFNM framework emphasizes the need for a balance between individual emotional memory and collective social interactions, ensuring that emotional AI systems remain relevant and ethically responsible [26][27]

Core Insights - The Guangdong-Hong Kong-Macao Greater Bay Area is positioned as a global technology innovation center, with the "Shenzhen-Hong Kong-Guangzhou" tech cluster ranking second globally in the World Intellectual Property Organization's Global Innovation Index for five consecutive years [1] - The region is witnessing significant advancements in original innovation, with collaborative efforts among research institutions leading to breakthroughs in various scientific fields [2][3] - The integration of innovation chains and industrial chains is crucial for the development of high-performance chip technology, with companies leveraging the area's robust supply chain and talent pool [4] Group 1: Technological Advancements - The Greater Bay Area is home to major scientific facilities like the China Spallation Neutron Source, enhancing research efficiency for local teams [2] - Collaborative projects between universities and research institutes in the region have led to significant discoveries in materials science and artificial intelligence [3] - The establishment of 34 joint laboratories across the Greater Bay Area is fostering regional innovation and technological breakthroughs [3] Group 2: Industry Development - The region's comprehensive electronic industry ecosystem supports the sustainable iteration of chip technology, attracting international talent and fostering collaboration [4] - Companies in the Greater Bay Area are expanding their operations and capabilities, exemplified by the growth of 博维智慧科技有限公司 from a small team in Macau to nearly 400 employees in Hengqin [7] - The area is witnessing a surge in high-tech enterprises, with 77,000 national high-tech companies contributing to a dynamic innovation landscape [7] Group 3: Talent Development - The Greater Bay Area is actively cultivating a high-level talent pool, with over 1.58 million R&D personnel and more than 150 academicians working in Guangdong [9] - Hong Kong has implemented various talent attraction initiatives, receiving over 460,000 applications since late 2022, with more than 300,000 approved [9] - Collaborative efforts among the nine cities in the Greater Bay Area aim to enhance cross-border talent mobility and create a cohesive talent ecosystem [9]