Please welcome to stage Dr. . Heather Jung. [Applause] I like looking at art, whether it's in museums, outside the classroom, or at home organizing my kids' room.Here are some I found from my kids. They're cute. Yeah.Bring back many happy memories. But more importantly, they make us feel a burst of energy, a burst of imagination, creativity and emotion. We all hold on to these precious moment and we take the same energy into our professional life.My professional career is in computer science. I'm a CS facul ...

据悉，大会共设置150余场专题论坛，涵盖人工智能基础模型、机器学习理论与机理、面向人工智 能的数据管理和治理、强化学习与推理等9个主题领域，涉及人工智能、大数据、云计算等热点领域。 （记者 郭晓龙） 23日，2025中国计算机大会在黑龙江省哈尔滨市开幕。本届大会以"数智赋能，无限可能"为主题， 由中国计算机学会主办，哈尔滨工程大学和哈尔滨工业大学承办，旨在探讨数字智能技术的前沿进展与 未来趋势，推动计算技术与经济社会深度融合。 ...

Core Insights - The article discusses the urgent need for advanced network infrastructure to support large language model training and data center security in the context of rapid advancements in intelligent computing and future networks [2][3]. Group 1: Research Achievements - The research group led by Assistant Professor Liu Guyue from Peking University has made significant contributions, with five high-level papers accepted at ACM SIGCOMM 2025, making it the highest-publishing research group from a university this year [2][3]. - The acceptance rate for SIGCOMM 2025 was only 16.1%, with 461 submissions and only 74 accepted [2]. Group 2: Key Research Papers - **InfiniteHBD**: Proposes a transceiver-centered high-bandwidth domain architecture that overcomes scalability and fault tolerance issues in large model training, achieving a cost reduction to 31% of NVL-72 and nearly zero GPU waste [6][8]. - **DNSLogzip**: Introduces a novel approach for fast and high-ratio compression of DNS logs, reducing storage costs by approximately two-thirds, saving up to $163,000 per month per DNS service node [11][12]. - **BiAn**: A framework based on large language models for intelligent fault localization in production networks, reducing root cause identification time by 20.5% and improving accuracy by 9.2% [13][14]. - **MixNet**: A runtime reconfigurable optical-electrical network structure for distributed mixture-of-experts training, enhancing network cost efficiency by 1.2 to 2.3 times under various bandwidth conditions [15][18]. - **Mazu**: A high-speed encrypted traffic anomaly detection system implemented on programmable switches, successfully protecting over ten million servers and detecting malicious traffic with approximately 90% accuracy [19][22]. Group 3: Overall Impact - The five research outcomes collectively form a comprehensive technological loop across architecture, data, operations, and security, driving the efficient, reliable, and intelligent development of next-generation network systems [3].

Research Findings - Promotional language in academic papers correlates with higher average ratings, suggesting presentation impacts perception [5][10][11] - The research analyzed approximately 16,000 papers from venues like ICLR to study the impact of hype [5] - AI model "spaCy" was used to analyze word context and connotation, improving accuracy in identifying promotional language [8][9] AI's Role and Impact - AI serves as a collaborator and amplifier, enhancing human capabilities rather than replacing them [2][17][18] - AI enables more in-depth analysis of data, leading to further investigations and observations [16] - The future of work involves collaboration between humans and AI, leveraging their respective strengths [19] Implications for Academia and Industry - Presentation of ideas is crucial, even if the idea itself is innovative [11][14] - AI can detect subtle nuances in language, potentially identifying double meanings and implications [15] - Focus should be on how AI can improve and humanize work, rather than fearing job displacement [20][21]

Core Insights - The job market for computer science graduates is experiencing a significant downturn, with unemployment rates rising to 6.1%, nearly double that of philosophy graduates at 3.2% [1] - The traditional perception of computer science as a secure career path is being challenged, as the employment rate for graduates from elite institutions has dropped from 80% to 70% in just two years [1] - In contrast, philosophy graduates are seeing stable employment rates between 75% and 90%, with average salaries increasing significantly over time [7][10] Group 1: Challenges in Computer Science - The influx of experienced candidates from layoffs in tech companies is intensifying competition for entry-level positions, making it difficult for new graduates to secure jobs [3] - Major tech companies are applying for H-1B visas while simultaneously laying off thousands of engineers, creating a disconnect between claims of talent shortages and actual hiring practices [3] - The rise of artificial intelligence is reshaping the job landscape, with companies using AI as a justification for layoffs rather than as a productivity tool [3][5] Group 2: Employment Trends - Global tech layoffs have exceeded 151,000 last year, with 22,000 positions cut in the early months of this year alone, including significant layoffs at major firms like Microsoft and Intel [5] - The number of computer science degrees awarded has more than doubled in the past decade, leading to an oversupply of graduates compared to available job opportunities [5] - The job market is shifting towards roles that require advanced skills in AI, data engineering, and cybersecurity, rather than traditional programming positions [11][12] Group 3: Opportunities in Philosophy - Philosophy graduates are finding diverse employment opportunities in education, public administration, and cultural sectors, with a notable demand for their critical thinking and analytical skills [7][8] - The integration of philosophy with digital humanities and cross-cultural studies is enhancing the employability of philosophy graduates in a globalized job market [10] - Philosophy graduates are increasingly entering the civil service, leveraging their skills in policy research and administration [8] Group 4: Future of Employment - The job market is evolving, with a growing emphasis on skills and project experience over formal educational credentials, as seen in the decreasing number of job postings requiring a degree [10][12] - Companies like IBM and Google are removing degree requirements for many positions, focusing instead on practical skills [10] - The demand for complex problem-solving skills is rising, indicating a shift away from basic coding tasks towards roles that require system design and ethical considerations in technology [12][13]

Core Points - The 2025 China Computer Conference (CNCC2025) will be held from October 22 to 25 in Harbin, Heilongjiang Province, with the theme "Digital Intelligence Empowerment, Infinite Possibilities" [1] - The conference aims to enhance the influence of the computer field in China and promote regional digital economic development [3][5] Event Overview - The conference will feature over 10,000 square meters of exhibition space, open to the public for free, marking a significant expansion in scale and depth [3] - A total of 19 invited reports, 3 main forums, and 154 specialized forums will be organized, focusing on various aspects of digital economy and AI [5][6] Key Participants - Notable speakers include academicians from various prestigious institutions and industry leaders, such as Sumi Helal from the University of Bologna and C. Mohan from Hong Kong Baptist University [5] - The forums will cover themes like "Digital Economy," "Large Model Development," and "Embodied Intelligence," with prominent experts leading discussions [5][6] Organizational Efforts - Harbin Engineering University and Harbin Institute of Technology are collaborating on the event's preparations, including venue setup and volunteer coordination [9][12] - The organizing committee emphasizes high standards in service and emergency management to ensure a successful conference [9][12] Media Engagement - The press conference attracted various media outlets, indicating strong interest and engagement from the media regarding the conference's significance [13][16]

Core Insights - Yoshua Bengio has been recognized as the world's most cited scientist across all fields, achieving a total citation count of over 973,655, with 698,008 citations in the last five years [4][5][6] - The top 10 list of highly cited scientists includes prominent figures in computer science, with four of them being key contributors to the field of artificial intelligence [7][8] Group 1: Yoshua Bengio - Yoshua Bengio is a Turing Award winner and a leading figure in deep learning, holding the top position in citation metrics globally [2][4] - His significant contributions include foundational work in machine learning and artificial intelligence, with a remarkable citation record that reflects his influence in the field [5][6] Group 2: Other Top Cited Scientists - Geoffrey Hinton ranks second globally, with a total citation count of 952,643 and over 577,970 citations in the last five years, recognized for his pivotal role in deep neural networks [8][9][10] - Kaiming He, known for developing deep residual networks (ResNets), ranks fifth with a total citation count of 733,529, and 617,328 citations in the last five years [13][14][15] - Ilya Sutskever, co-founder of OpenAI, has a total citation count of 670,000, with 500,000 citations in the last five years, contributing significantly to advancements in AI [16][18] Group 3: Citation Ranking Methodology - The AD Scientific Index ranks scientists based on total citation counts and citations over the last five years, evaluating their academic performance and impact [26][29] - The ranking system incorporates various metrics, including H-index and i10-index, to provide a comprehensive assessment of researchers' contributions [31][32]

Core Viewpoint - The article discusses the introduction of GUAVA, a novel framework developed by researchers from Tsinghua University and IDEA, which enables the creation of upper-body 3D avatars from a single image in just 0.1 seconds, without the need for multi-view videos or individual training [1][5][36]. Summary by Sections Introduction - GUAVA is recognized for its ability to create realistic and expressive upper-body avatars, which is valuable in fields such as film, gaming, and virtual meetings [4]. Challenges and Innovations - Creating avatars from a single image has been a significant challenge, particularly in achieving real-time rendering and ease of creation. GUAVA addresses these challenges by allowing inference reconstruction in seconds and supporting real-time animation [5][6]. Methodology - GUAVA introduces the Expressive Human Model (EHM) to enhance facial expression capture, overcoming limitations of existing models [12][36]. - The framework employs a two-branch model for avatar reconstruction, combining a "template Gaussian" and a "UV Gaussian" to maintain geometric structure while capturing detailed textures [14][15]. - Real-time animation is achieved by deforming the Ubody Gaussian based on new pose parameters, followed by optimization through a neural refiner to enhance rendering quality [16][17]. Experimental Results - The dataset for experiments included over 620,000 frames, focusing on upper-body videos, with evaluations based on ID consistency, efficiency, and viewpoint control [18][20]. - GUAVA outperformed existing 2D and 3D methods in rendering quality and efficiency, achieving approximately 50 FPS and a reconstruction time of around 0.1 seconds [22][23]. - In self-reenactment scenarios, GUAVA showed superior performance across all metrics compared to 2D methods, while also maintaining ID consistency in cross-reenactment scenarios [22][25]. Conclusion - GUAVA represents a significant advancement in the field of 3D avatar reconstruction, demonstrating improved rendering quality and efficiency over existing methods, with a reconstruction time of approximately 0.1 seconds and support for real-time animation [36][37].

Child Development & Education - Early childhood experiences significantly impact future potential [4] - Opportunities in arts, science, math, and writing can spark passion and future careers [5] - Encouraging curiosity and exploration in children is crucial for development [3][11] Creativity & Innovation - Creativity evolves throughout life, adapting to different stages and challenges [6][7] - Engaging in creative activities is linked to higher life satisfaction [7] - Even seemingly uncreative jobs require unique forms of creativity [10] Job Market & Career Trends - Computer science fields are projected to grow by 26% from 2023 to 2033 [9] - Creative thinking is increasingly valued in various professions [8][9] - Diverse career paths benefit from creative problem-solving skills [10]

Core Insights - The article discusses the acceptance of 10 papers from a laboratory at the 20th ICCV International Conference on Computer Vision, highlighting advancements in 3D vision and related technologies [25]. Paper Summaries Paper 1: Domain-aware Category-level Geometry Learning Segmentation for 3D Point Clouds - This paper addresses domain generalization in 3D scene segmentation, proposing a framework that couples geometric embedding with semantic learning to enhance model generalization [1]. Paper 2: Hierarchical Variational Test-Time Prompt Generation for Zero-Shot Generalization - The authors introduce a hierarchical variational method for dynamic prompt generation during inference, significantly improving the zero-shot generalization capabilities of visual language models [3]. Paper 3: Knowledge-Guided Part Segmentation - A new framework is proposed that utilizes structural knowledge to enhance the segmentation of fine-grained object parts, improving understanding of complex structures [5][6]. Paper 4: TopicGeo: An Efficient Unified Framework for Geolocation - TopicGeo presents a unified framework for geolocation that improves computational efficiency and accuracy by directly matching query images with reference images [9]. Paper 5: Vision-Language Interactive Relation Mining for Open-Vocabulary Scene Graph Generation - This paper explores a model that enhances the understanding of relationships in open-vocabulary scene graph generation through multimodal interaction learning [11]. Paper 6: VGMamba: Attribute-to-Location Clue Reasoning for Quantity-Agnostic 3D Visual Grounding - The authors propose a mechanism that combines attribute and spatial information to improve the accuracy of 3D visual grounding tasks [13]. Paper 7: Meta-Learning Dynamic Center Distance: Hard Sample Mining for Learning with Noisy Labels - A new metric called Dynamic Center Distance is introduced to enhance the learning process in the presence of noisy labels by focusing on hard samples [15]. Paper 8: Learning Separable Fine-Grained Representation via Dendrogram Construction from Coarse Labels for Fine-grained Visual Recognition - The paper presents a method for learning fine-grained representations from coarse labels without predefined category numbers, enhancing adaptability to dynamic semantic structures [17]. Paper 9: Category-Specific Selective Feature Enhancement for Long-Tailed Multi-Label Image Classification - This research addresses the issue of label imbalance in multi-label image classification by enhancing feature sensitivity for underrepresented categories [19]. Paper 10: Partially Matching Submap Helps: Uncertainty Modeling and Propagation for Text to Point Cloud Localization - The authors redefine the task of text to point cloud localization by allowing partial spatial matches, improving the model's ability to handle real-world ambiguities [21].