Group 1: OpenAI and Intel - OpenAI has recruited Intel's CTO Sachin Katti to focus on building computational infrastructure for AGI, leading to Intel CEO Pat Gelsinger taking direct control of the AI department [1] - Katti brings over 20 years of experience in wireless communication and AI infrastructure, having recently been promoted to CTO at Intel [1] - OpenAI plans to invest approximately $1.4 trillion over the next eight years to develop AI infrastructure, making Katti's role significant for OpenAI's autonomous computing strategy, while representing a major loss for Intel [1] Group 2: Meta's Voice Recognition Model - Meta AI's FAIR team has released the Omnilingual ASR voice recognition model suite, capable of supporting over 1,600 languages with a character error rate below 10% for 78% of languages [2] - The framework is community-driven, allowing users to expand the model to new languages with minimal samples, achieving large-scale ASR framework contextual learning [2] - Meta has also open-sourced the Omnilingual ASR Corpus dataset, covering 350 underrepresented languages, and a 70 billion parameter Omnilingual wav2vec 2.0 speech representation model [2] Group 3: SenseNova-SI by SenseTime - SenseTime has launched and open-sourced the SenseNova-SI series of spatial intelligence models, with the 8B model achieving an average score of 60.99 on four core spatial intelligence tasks, outperforming GPT-5 and Gemini-2.5-Pro [3] - The models validate the "scale effect" in spatial intelligence and establish a classification system across six core dimensions, including spatial measurement and reconstruction [3] - The models are integrated into the "Wuneng" embodied intelligence platform, and the spatial intelligence evaluation platform EASI has been open-sourced to enhance three-dimensional structural cognition capabilities [3] Group 4: Doubao-Seed-Code by ByteDance - ByteDance's Volcano Engine has introduced the Doubao-Seed-Code model, with reduced calling prices at 1.20 yuan per million tokens for inputs ranging from 0 to 32k [4] - This model supports visual understanding capabilities for programming, generating code based on UI design drafts, and features a native 256K long context [4] - A Coding Plan package has also been launched, utilizing a training library of 100,000 container images and end-to-end reinforcement learning [4] Group 5: Space Data Centers - Researchers from Zhejiang University and Nanyang Technological University have proposed a complete technical framework for building carbon-neutral data centers in space, leveraging near-infinite solar energy and deep space cooling conditions [5] - Two solutions are suggested: integrating AI accelerators on remote sensing satellites to create "orbital edge data centers" and forming a satellite constellation for "orbital cloud data centers" [5] - An innovative "full lifecycle carbon utilization efficiency" assessment model indicates that long-term carbon efficiency may surpass that of medium carbon intensity ground data centers despite initial carbon emissions from manufacturing and launching [5] Group 6: AI Development Insights - Anthropic researcher Julian Schrittwieser asserts that the belief that AI has peaked is a major misconception, with AI task capabilities doubling every seven months [6] - Predictions indicate that by mid-2026, models will be able to work autonomously for eight hours, with at least one model matching human experts across multiple industries by the end of the year [6] - He emphasizes that the public often misjudges AI development, overlooking the exponential growth trend, and that leading labs show stable and exponential increases in AI capabilities [6] Group 7: AI Adoption and Performance - A McKinsey survey reveals that 88% of organizations use AI in at least one business area, but only 39% report substantial financial returns (EBIT growth) from AI [7] - While 62% of organizations have experimented with AI Agent applications, less than 10% have implemented them in any department, primarily in standardized areas like IT operations and knowledge management [7] - High-performing companies are more ambitious about AI transformation, with 50% planning significant AI-driven changes, compared to only 14% of average companies [7] Group 8: Future of AI and World Models - Fei-Fei Li emphasizes that spatial intelligence is a foundational aspect of human intelligence, predating language, and current large language models (LLMs) lack real-world experience and understanding [8] - She defines world models as needing three capabilities: generative (creating geometrically and physically consistent worlds), multimodal (designed for multiple modalities), and interactive (outputting the next world state based on actions) [8] - Li believes that building world models will face challenges in new training tasks, large-scale data, and new model architectures, with applications in creativity, robotics, and transformative changes in science, healthcare, and education [8] Group 9: Sora's Social Platform Insights - The Sora team reported nearly 2 million weekly active users within 40 days of launch, with 70% of users engaging in content creation, surpassing traditional internet engagement metrics [9] - Sora is positioned as a social creation platform rather than a single-user tool, with algorithms prioritizing content with remix potential over mere consumption time [9] - A points-based system is implemented for flexible monetization, balancing the interests of the platform, creators, and copyright holders, while lowering barriers for user-generated content [9]

Core Viewpoint - The article discusses the transformative impact of the AI revolution, comparing it to previous major revolutions like the Industrial Revolution, and suggests that AI may fundamentally reshape society, economy, and human relationships [6][9]. Group 1: Nature of the AI Revolution - The AI revolution is seen as a continuation of technology's role in enhancing human capabilities, shifting from physical to cognitive enhancements [7]. - AI is expected to accelerate the cycle of discovery and innovation, leading to exponential growth in technology and knowledge [8]. Group 2: Impact on Work and Society - The rise of AI may lead to the emergence of a "leisure class," where many professional jobs are replaced by AI, resulting in fewer people needing to work [11][12]. - Education will need to shift from preparing individuals for traditional jobs to teaching them how to live creatively and meaningfully in a world where work is not the primary focus [14]. Group 3: Challenges to Human Creativity - AI's capabilities in creative fields challenge the unique value of human creativity, as it can produce works indistinguishable from those created by humans [15]. Group 4: Economic and Social Structures - The traditional economic model based on work for income is being challenged, leading to discussions about basic income and wealth distribution in a potential "workless society" [17]. - The AI revolution could lead to a "post-scarcity" society, but there are concerns about wealth concentration and inequality [18]. Group 5: Knowledge and Intellectual Property - The concept of intellectual property may need to be redefined in an AI-driven world, where contributions to creative works are increasingly collaborative and difficult to attribute [19]. Group 6: Social Relationships and AI - AI is expected to decentralize social activities and relationships, potentially transforming how humans interact with each other and with AI [21][23]. Group 7: Global Implications - AI has the potential to foster global cooperation and reduce nationalism, but it may also reshape global power dynamics and economic structures [25][26]. Conclusion - The future of AI development depends on responsible practices that consider ethical, social, and ecological impacts, aiming for a better world with reduced conflict and poverty [28][29].

Group 1: Generative AI Developments - OpenRouter platform has launched the anonymous model Polaris Alpha, believed to be a variant of GPT-5.1, with a knowledge base cutoff in October 2024 and a maximum context capacity of 256K and a single output limit of 128K [1] - Polaris Alpha shows smooth performance in desk work and programming tasks, exhibiting typical GPT characteristics and supporting NSFW mode [1] - The model is currently available for free via API, demonstrating good performance in programming mini-games and web design, with GPT-5.1 expected to be officially released in mid-November [1] Group 2: Multi-Modal Intelligence - A new multi-modal paradigm called Cambrian-S has been proposed by researchers including Yann LeCun, focusing on "spatial super-perception" and marking the first step in exploring video spatial super-perception [2] - The research outlines a development path for multi-modal intelligence across four levels: semantic perception, streaming event cognition, 3D spatial cognition, and predictive world modeling, introducing the VSI-SUPER benchmark for spatial super-perception capabilities [2] - Cambrian-S utilizes latent variable frame prediction to manage memory and event segmentation through a "surprise" signal, outperforming Gemini in spatial cognition tasks with smaller models [2] Group 3: AI Programming Tools - Meituan has launched an AI IDE programming tool named CatPaw, featuring code completion, agent Q&A generation, built-in browser preview debugging, and project-level analysis [3] - The core engine of CatPaw is Meituan's self-developed LongCat model, fully compatible with major programming languages like Python, C++, and Java, and currently available for free [3] - Over 80% of weekly active users among Meituan's internal developers utilize CatPaw, with AI-generated code accounting for about 50% of new code submissions, and a Windows version expected to launch soon [3] Group 4: Domestic AI IDE Launch - YunSi Intelligence has introduced Vinsoo, the world's first AI IDE equipped with a cloud-based security agent, surpassing products like Cursor and Codex that utilize Claude [4] - Vinsoo achieves breakthroughs in long-context engineering algorithms, supporting effective context lengths in the millions and allowing up to eight intelligent agents to operate simultaneously [4] - The new Beta 3.0 version supports cloud-based one-click publishing, mobile usage, and team collaboration, led by a founding team of post-00s graduates from top universities in China and the U.S. [4] Group 5: Open Source Audio Editing Model - Jieyue Xingchen has released the first open-source LLM-level audio editing model, Step-Audio-EditX, which allows precise control over audio emotions, speaking styles, and paralinguistic features through language commands [5] - The model employs a unified LLM framework and a "dual-codebook" audio tokenizer structure, supporting zero-shot text-to-speech, iterative editing, and bilingual capabilities [5] - With approximately 3 billion parameters, the model can run on a single 32GB GPU, achieving higher accuracy in emotion and style control compared to closed-source models like MiniMax and Doubao [5] Group 6: AI Glasses Launch - Baidu has officially launched the Xiaodu AI glasses Pro, priced at 2299 yuan, with a promotional price of 2199 yuan for Double Eleven, weighing 39 grams and featuring a 12-megapixel wide-angle camera [6] - The glasses integrate multi-modal AI models, offering functionalities such as photography, music recognition, AI translation, object recognition, note-taking, and audio recording, with real-time translation capabilities [6] - Similar to Xiaomi's AI glasses, these are not the more advanced AI+AR glasses currently available [6] Group 7: Robotics Innovation - Galaxy General has introduced the DexNDM, a dexterous hand neural dynamics model that achieves stable, multi-axial rotation operations on various objects, capable of using tools like screwdrivers and hammers [8] - The DexNDM model disassembles hand-object interactions to the joint level, utilizing a training process that allows for stable operations across tasks and forms without requiring successful examples [8] - This technology has been applied to remote operation systems, enabling operators to give high-level commands via VR controllers while DexNDM autonomously manages fine control at the finger level [8] Group 8: Insights on AI Entrepreneurship - A YC partner emphasizes that AI tools cannot replace a founder's sales capabilities, suggesting that AI should first target quick-to-implement entry points in traditional industries rather than aiming for full automation [9] - The core competitive advantage in early-stage entrepreneurship is "learning speed" rather than scale, with a focus on quickly validating ideas with small customers [9] - AI sales development representatives (SDRs) are effective only when there are already well-functioning sales processes, and founders must clarify their target audience and attention acquisition strategies for AI tools to be effective [9]

Core Viewpoint - The gaming industry is experiencing significant growth, with offline gaming events becoming key drivers of economic and cultural influence, showcasing a vibrant ecosystem that connects various sectors and demographics [2][36]. Group 1: Growth of Gaming Events - The number and scale of gaming-themed offline events have significantly increased, with over 400,000 attendees at ChinaJoy and nearly 800 companies participating, including traditional brands entering the youth market [2][7]. - Major gaming exhibitions like Tokyo Game Show and Gamescom have seen substantial participation, with the latter attracting 35.7 million visitors from 128 countries, highlighting the global appeal of gaming [2][4][12]. - The rise of independent games is notable, with the number of independent game exhibitors at BW increasing more than threefold compared to four years ago, reflecting the diverse and dynamic nature of the gaming industry [4][5]. Group 2: Technological Integration - Gaming exhibitions are becoming platforms for showcasing future digital technologies such as AI, XR, and cloud computing, with events like ChinaJoy introducing innovative experiences like smart entertainment robots and brain-machine interfaces [5][27]. - The integration of cutting-edge technologies is driving new productivity in the gaming sector, with companies like NVIDIA presenting advanced rendering technologies and AI solutions at these events [5][27]. Group 3: Cross-Industry Collaboration - Non-gaming companies are leveraging gaming exhibitions to tap into Gen Z culture, with brands like Old Fengxiang and Yadi launching co-branded products to connect with younger consumers [7][27]. - The presence of global brands such as LEGO and Disney at gaming events underscores the economic value of the "gaming plus" cross-industry model, enhancing brand visibility and engagement [7][27]. Group 4: Economic Impact - Gaming events are becoming vital for urban economies, generating significant ancillary spending in areas like food, accommodation, and transportation, with ChinaJoy alone driving approximately 661 million yuan in surrounding service consumption [39][40]. - The gaming industry is projected to reach a global market revenue of $188.8 billion by 2025, with a user base of 3.6 billion gamers, indicating a robust growth trajectory [36][38]. Group 5: Cultural Significance - Gaming is increasingly recognized as a cultural cornerstone for youth, fostering community and identity through unique cultural practices and social interactions at events [40][42]. - Events like ChinaJoy and KPL finals are not only entertainment spectacles but also serve as platforms for cultural expression and community building among young audiences [40][42].

Core Insights - The article discusses the revolutionary approach of Training-Free GRPO, which allows for cost-effective reinforcement learning without modifying model parameters, aligning with Richard Sutton's vision of intelligent agents learning from their own experiences rather than solely from human data [4][8][28]. Cost and Efficiency - Traditional reinforcement learning (RL) methods can cost around $10,000 for training a 32B model, while Training-Free GRPO reduces this cost to approximately $8 to $18 for optimizing a 671B model [25]. - The Training-Free GRPO method enables significant cost savings and efficiency improvements, making reinforcement learning accessible to smaller teams and individual developers [28][25]. Methodology - The Training-Free GRPO process involves four key steps: 1. Multi-path exploration to generate various solution paths for a problem [14]. 2. Providing minimal sample rewards to guide the model's learning direction [15]. 3. Semantic advantage extraction through self-reflection on different answers [16]. 4. Optimizing the experience library based on validated strategies [17][20]. Performance Improvement - Using only 100 training samples, the Training-Free GRPO can enhance performance on the AIME leaderboard, achieving a Mean@32 score increase from 68.6 to 72.6 [19]. - In web search scenarios, the method achieved a 4.6% improvement in Pass@1 metrics without updating model parameters [22][23]. Application Scenarios - Training-Free GRPO is particularly suitable for long-tail niche applications, rapid iteration scenarios, and teams with limited budgets, such as individual developers and small enterprises [26]. Conclusion - The introduction of Training-Free GRPO marks a new era in reinforcement learning, making it feasible for a broader range of developers and applications, thus democratizing access to advanced AI capabilities [28].

Group 1: Generative AI Developments - Grok 4 has upgraded its context window to 2 million tokens, which is twice that of Gemini 2.5 Pro and five times that of GPT-5, with reasoning mode completion rate increasing from 77.5% to 94.1% [1] - The upgraded Grok Imagine can generate high-quality outputs that are indistinguishable from reality, accurately depicting scenes from Western classical literature, with x.ai capturing 26.4% of API calls on OpenRouter [1] - The 2 million token context capability allows processing of approximately 1.5 million English words or 6,000 pages of text, equivalent to two volumes of "War and Peace" [1] Group 2: New Model Releases - OpenAI has released the compact version of GPT-5-Codex Mini, which has a usage rate approximately four times that of GPT-5-Codex, and ChatGPT Plus users see a 50% increase in rate limits [2] - The code reveals traces of three new models in the GPT-5.1 series, including flagship model GPT-5.1, reasoning model GPT-5.1 Reasoning, and research-grade GPT-5.1 Pro [2] - New models are expected to be released by the end of November, with one model possibly being tested under the name Polaris Alpha, showing strong performance in creative writing and benchmark tests [2] Group 3: AI in Entertainment - Utopai Studios has partnered with LG and a Middle Eastern sovereign fund to establish a joint venture, Utopai East, with a capital scale of several billion dollars [4] - Utopai employs a "decoupled planning and rendering" architecture, addressing long-range consistency issues in traditional models, enabling stable character identity and scene consistency across multiple shots [4] - This architecture reduces the creative iteration cycle from weeks to days, facilitating a significant leap from short film generation to industrial-level feature film production [4] Group 4: Financial Technology Innovations - The new version of Google Finance integrates the Gemini multimodal AI model's "deep search" feature, capable of scanning hundreds of documents in minutes to generate comprehensive analysis reports [5] - For the first time, it incorporates predictive market data from platforms like Kalshi and Polymarket, providing investors with an unprecedented "market sentiment barometer" [5] - The redesigned "earnings season experience" interface supports real-time transcription, AI-generated news summaries, and historical data comparisons, currently available for beta testing [5] Group 5: Advances in Antibody Design - The RFdiffusion model developed by David Baker's team can rapidly generate new antibody designs with near-atomic precision, targeting specific viral epitopes [6] - This model has successfully designed antibodies against influenza, Clostridium difficile toxin, COVID-19, and RSV, with cryo-electron microscopy validating the designs [6] - RFdiffusion can create new antibody design diagrams in hours, potentially transforming human responses to infectious diseases, with the team founding Xaira Therapeutics [6] Group 6: Space Exploration Updates - The U.S. has simplified the Artemis lunar lander plan, reducing the number of onboard devices and cutting the number of refueling launches from 15-30 to fewer than 10 [8] - China's space agency has announced breakthroughs in key technologies for a new generation of crewed launch vehicles, with demonstration flights imminent [8] - The Long March 10 rocket is 92.5 meters tall with a launch thrust of approximately 2,678 tons, capable of carrying at least 27 tons to lunar transfer orbit, with the Dream Chaser 1 spacecraft set for its first flight in 2026 [8] Group 7: AI Industry Insights - Six AI leaders, including Yann LeCun and Fei-Fei Li, debated the authenticity of the AI revolution, with Huang Renxun asserting that AI is a productivity driver requiring significant investment [9] - LeCun argued that current large language models cannot lead to human-level intelligence without fundamental breakthroughs [9] - Predictions on achieving "human-level AI" vary, with Hinton suggesting it could happen within 20 years, while Li emphasized the vast potential in frontier fields yet to be explored [9] Group 8: AI Model Performance Evaluation - Kimi K2 Thinking scored 67 in the Artificial Analysis intelligence index, ranking second among all open-source models, only behind GPT-5 [10] - The model achieved a 93% score in the τ²-Bench Telecom benchmark, setting a new record for open-source models [10] - With a total parameter count of 1 trillion and 32 billion active parameters, Kimi K2 was evaluated using 1.4 million tokens, approximately 2.5 times that of DeepSeek V3.2, showcasing its extensive capabilities [10] Group 9: Training Large Language Models - HuggingFace released a comprehensive technical blog exceeding 200 pages, detailing the end-to-end experience of training advanced LLMs, specifically the SmolLM3 model with 3 billion parameters [11] - The blog covers the entire process from decision-making to implementation, including training compass, ablation study design, model architecture, data management, and infrastructure [11] - It emphasizes that data quality has a far greater impact than architecture choice, and training LLMs is a "learn-as-you-go" process, requiring sufficient computational power and rapid iteration [11]

Group 1: Core Insights - The article highlights the top 50 keywords in AI for the week, providing a comprehensive overview of the latest developments in the industry [2][3][4]. Group 2: Computing Power - Key developments in computing power include collaborations between Cambricon and NeuWare, OpenAI and AWS, and the introduction of space AI servers by NVIDIA and Google's space AI initiatives [3][4]. Group 3: Models - Significant model advancements include the release of Composer-1 by Cursor, linear attention by Kimi, and the preview of Gemini 3 Pro by Google, among others [3][4]. Group 4: Applications - Various applications are emerging, such as OpenAI's Bug agent, Canva's creative operating system, and AI smart glasses by Rokid, showcasing the diverse use cases of AI technology [3][4]. Group 5: Opinions - Notable opinions expressed include Elon Musk's views on intelligence elevation, Stanford University's insights on speech therapy, and discussions on AI's impact on labor by Geoffrey Hinton [4].

Group 1 - The article discusses the controversial use of predictive AI in decision-making processes, particularly in educational institutions and healthcare, highlighting the potential for both beneficial and harmful outcomes [1][3][12] - It presents a case study of St. Mary's College, where the administration suggested expelling underperforming students to artificially inflate retention rates, raising ethical concerns about the treatment of students [1][3] - The EAB Navigate tool is mentioned as an example of predictive AI that can identify at-risk students, but it also risks reinforcing biases against marginalized groups by suggesting easier majors for them [1][3][12] Group 2 - Predictive AI systems are widely used across various sectors, including healthcare, employment, and public welfare, often without individuals being aware of their involvement in automated decision-making [6][12][30] - The article emphasizes that while predictive AI can improve efficiency, it often relies on historical data that may not accurately reflect current realities, leading to flawed predictions [12][20][42] - The use of algorithms in decision-making can lead to significant consequences for individuals, particularly in criminal justice, where risk assessment tools may disproportionately affect marginalized communities [10][11][39][43] Group 3 - The article highlights the limitations of predictive AI, including its inability to account for causal relationships and the dynamic nature of human behavior, which can lead to unintended consequences [19][21][23] - It discusses the phenomenon of "gaming the system," where individuals manipulate their behavior to meet the opaque criteria set by AI systems, often without understanding the underlying factors [24][26][30] - Over-reliance on automated systems can result in a lack of accountability and transparency, as seen in the Netherlands' welfare fraud detection algorithm, which led to wrongful accusations without recourse for those affected [28][29][31] Group 4 - The article argues that predictive AI can exacerbate existing social inequalities, particularly in healthcare, where models may prioritize patients based on financial metrics rather than actual health needs [39][41][42] - It points out that the training data for AI systems often reflects historical biases, leading to discriminatory outcomes, such as lower healthcare quality for Black patients compared to white patients [41][42][43] - The need for high-quality, representative data is emphasized, as relying on existing data can perpetuate systemic biases and fail to address the needs of underrepresented groups [20][42][43]

Group 1: Generative AI Developments - Google plans to release the Gemini 3 Pro preview version to select developers and enterprise users in November, with a formal launch expected in December. The model features a context window of up to 1 million tokens, making it suitable for handling long documents and complex data pipelines, particularly for AI researchers and teams with high context capacity requirements [1] - Apple is nearing an agreement to pay approximately $1 billion annually to Google for the Gemini model to enhance the new version of Siri with summarization and task planning capabilities. The Gemini model will operate on Apple's private cloud servers, ensuring user data does not interact with Google's systems. The model boasts 1.2 trillion parameters, significantly surpassing Apple's existing model with 150 billion parameters [2] - The Kimi-k2 thinking model, recently launched by Moon's Dark Side, excels in deep reasoning and can solve complex problems through multi-turn tool invocation. It demonstrates strong performance in programming, capable of generating a complete web project in 3 minutes, although it still has room for improvement in solving 2025 IMO math competition problems [3] Group 2: AI Model Innovations - iFlytek has released the new X1.5 deep reasoning model, trained on a fully domestic computing platform, featuring a total of 293 billion parameters with only 30 billion activated for reasoning. This model achieved first place in the AIME 2025 math competition, with deep reasoning training efficiency improved from 25% to 84% and reasoning speed doubled compared to its predecessor [4] - Tencent Cloud's CodeBuddy has become the first AI programming tool in China to support the Skills standardized interface, allowing developers to add diverse skill packages to the AI. Skills encapsulate specialized knowledge into reusable modules, enabling efficient execution of tasks by the AI [5] Group 3: Autonomous Vehicle Collaborations - Gaode has announced a partnership with Xiaopeng Motors to jointly provide Robotaxi services globally, marking a significant application of Gaode's spatial intelligence capabilities. The TrafficVLM model enables "beyond-visual-range" capabilities, allowing for the detection of sudden accidents and congestion predictions several kilometers away, thus enhancing preemptive warning systems [6] Group 4: Consumer Technology Innovations - A former Meta engineer has launched the Stream Ring, a smart ring equipped with a microphone and touchpad, supporting voice transcription, AI assistant interaction, and music control. Priced from $249, it has secured $13 million in funding and offers an app that provides unlimited note support without a subscription [7] - FutureHouse has introduced Kosmos, a next-generation AI scientist capable of completing the workload equivalent to six months of research in a single day. It can analyze 1,500 papers and execute 42,000 lines of analysis code, with 79.4% of research conclusions verified as accurate in fields like neuroscience and materials science [8] Group 5: AI and Programming Perspectives - Amjad Masad, founder of Replit, argues that syntax is counterintuitive for humans, suggesting that English will become the programming language, with user identity shifting from humans to AI agents. He notes that AI's long-term reasoning capabilities have advanced from minutes to hours, emphasizing the importance of reinforcement learning and "verification loops" in model training [9]

Core Viewpoint - The article outlines an internship opportunity at Tencent Research Institute, focusing on legal research in the fields of digital economy and artificial intelligence, emphasizing the importance of understanding legal and ethical issues in these rapidly evolving sectors [1][3]. Group 1: Job Description - The internship involves tracking, analyzing, and interpreting global legal and ethical issues, legislative trends, and industry governance practices related to the digital economy and AI [3]. - Responsibilities include supporting research on AI governance and safety, conducting surveys and interviews, and assisting in writing research articles and reports [3]. Group 2: Requirements - Candidates should be graduate students (not recent graduates) with backgrounds in internet law, digital law, AI law, technology ethics, or AI governance, with interdisciplinary backgrounds preferred [4]. - Strong interest in the internet technology industry and familiarity with legal policies, safety, and governance issues in the internet and AI sectors are essential [4]. - Proficiency in using generative AI products, data analysis skills, and good PPT creation abilities are required [4]. - Candidates must possess strong logical thinking, theoretical knowledge, and writing skills, along with excellent English proficiency [4]. Group 3: Internship Details - The internship is a full-time position for at least six months, with an immediate start date [4]. - The work location is in Shenzhen or Beijing [5]. Group 4: Opportunities - Interns will participate in significant research projects related to AI safety and governance [7]. - The position offers exposure to the latest developments in the internet industry and access to research resources from both domestic and international academic and industry circles [7].