Anahtar Kelimeler：AI hidrojel, Otonom cerrahi robot, Akıllı mikroskop, GPT-5, Büyük model satranç şampiyonası, AI video oluşturma, AI arkadaş robotu, AI etiği, AI ile tasarlanmış süper yapışkan hidrojel, Da Vinci cerrahi robotu ile otonom safra kesesi ameliyatı, Derin öğrenme ile protein yanlış katlanmasının tahmini, GPT-5’in insanı aşan akıl yürütme yeteneği, Grok 4 uluslararası satranç AI performansı, Yapay zeka hidrojel teknolojisi, Kendi kendine ameliyat yapabilen robot sistemleri, Dijital akıllı mikroskop cihazları, GPT-5 dil modeli özellikleri, Büyük ölçekli yapay zeka satranç turnuvaları, Yapay zeka ile video içerik üretimi, Duygusal destek sağlayan AI robotlar, Yapay zeka etik kuralları ve tartışmaları, Nanoteknoloji ile geliştirilmiş AI hidrojel tasarımları, Robotik cerrahide otonom safra kesesi çıkarma teknikleri, Makine öğrenmesi ile protein yapısı analizi, GPT-5’in mantıksal çıkarım yeteneklerinin insan seviyesini aşması, Grok 4’ün satranç performans değerlendirmeleri
🔥 Spotlight
AI “Creates” Hydrogels, Adhering Everything : Breakthrough progress has been made in AI-assisted material design. Nature featured a cover story on AI designing a super-adhesive hydrogel. By analyzing natural adhesive protein sequences, the hydrogel achieves strong adhesion in wet environments, along with long-term stability and biocompatibility. This technology is expected to revolutionize biomedical applications such as prosthetic coatings, wearable biosensors, and underwater repair materials, opening up a new end-to-end data-driven path for soft material design and demonstrating AI’s immense potential in material science. (Source: 36氪)
Autonomous Surgical Robot Successfully Removes Gallbladder : Johns Hopkins University and other institutions have developed a system called SRT-H, enabling the da Vinci surgical robot to autonomously complete critical steps of gallbladder removal without continuous human intervention. The system trains high-level planners and low-level action generators through imitation learning, and can self-correct errors during operation, demonstrating the immense potential of autonomous surgery. Although currently only tested on ex-vivo tissues and slower than humans, its natural language interface and interpretability lay a crucial foundation for future safe autonomous surgery. (Source: DeepLearning.AI Blog)
Smart Microscope Predicts Misfolded Protein Aggregation : EPFL researchers have developed a smart microscope using deep learning that can track and analyze the aggregation of misfolded proteins associated with neurodegenerative diseases in real-time, even predicting it before it begins. The system combines image classification algorithms with Brillouin microscopy, automatically triggering analysis upon detecting protein aggregation, significantly improving imaging efficiency and reducing the use of fluorescent labels. This breakthrough is significant for understanding the biomechanical mechanisms of neurodegenerative diseases and drug discovery, marking the immense potential of smart microscopes in life sciences. (Source: aihub.org)
🎯 Trends
Silicon Valley’s AI Big Three Release New Models Intensively : Silicon Valley AI giants have recently made a flurry of new announcements, accelerating AI competition. OpenAI has re-launched its open-source model, gpt-oss, after six years, including 120B and 20B versions, emphasizing local deployment and Agent applications, with performance approaching o4-mini. Google released Genie 3, enabling text-to-minute-level interactive 3D virtual worlds, seen as a crucial step towards AGI. Anthropic updated Claude Opus 4.1, achieving new SOTA in AI programming capabilities, further solidifying its leading position in the programming domain. These releases foreshadow accelerated competition in AI technology across open-source, world models, and vertical applications. (Source: 36氪, DeepLearning.AI Blog, 量子位, 36氪)
Massive Information Leak Ahead of GPT-5 Launch : OpenAI has previewed the GPT-5 launch event, with a significant amount of information leaked. Reportedly, GPT-5 will launch in standard, mini, nano, and chat versions, supporting tiered access, allowing free users to experience the basic version. Internal tests show its excellent performance in reasoning, programming, mathematics, and scientific problem-solving, with reasoning capabilities surpassing the human average for the first time. Concurrently, Sam Altman has awarded substantial bonuses to employees, and OpenAI’s valuation is expected to reach $500 billion, indicating its confidence in GPT-5 and market anticipation. (Source: 36氪, 36氪)
First Large Model Chess Championship: Grok 4 and o3 Advance to Finals : Google’s Kaggle platform hosted the first AI Chess Championship, with eight top LLMs competing. In the first round, domestic models like DeepSeek R1 and Kimi K2 Instruct were unfortunately eliminated. In the semifinals, xAI’s Grok 4 and OpenAI’s o3 defeated their opponents to advance to the finals. The competition rules restricted models from calling external tools, aiming to purely test their reasoning capabilities, exposing deficiencies in AI models’ contextual understanding and tactical execution. However, Grok 4’s performance received high praise from Elon Musk, garnering widespread attention. (Source: 36氪, 36氪, 36氪)
Review of China’s AI Large Model Platform Progress in July : In July, China’s large model market showed active momentum. The WAIC conference focused on embodied AI, emphasizing AI’s transition from “screen to reality.” Multi-agent systems have become a new trend, with 360 Nano AI launching L4-level multi-agent swarms for complex task collaboration. Leading manufacturers have successively open-sourced their latest models, such as Alibaba’s Qwen3 series, Moonshot AI’s Kimi K2, and Zhipu AI’s GLM-4.5, fostering the nascent “root system” of the domestic large model ecosystem, continuously enhancing technical strength, and dominating international rankings. (Source: 36氪, 量子位, DeepLearning.AI Blog, 量子位)
Explosion of AI Video Generation Models and Rise of Agentic Web Concept : The AI video generation field has seen explosive growth. After Sora broke through technical bottlenecks, Runway Gen-3, Luma Dream Machine, Kuaishou Keling, and others were successively launched, significantly reducing video production costs. The market landscape remains fluid, with domestic manufacturers like ByteDance, Kuaishou, MiniMax, and Aishi Tech showing prominent performance. Concurrently, the Agentic Web concept has emerged, proposing a next-generation internet driven by AI agents, where agents will become primary Web operators, automating tasks and foreshadowing a complete restructuring of the internet’s underlying logic. (Source: 36氪, 36氪, 36氪)
AI Glasses Achieve “Grab-from-Air” for New Mixed Reality Interaction : Researchers including Zhejiang University alumni have proposed Reality Proxy technology, enabling AI glasses to perform “grab-from-air” functionality, allowing users to select and interact with real-world objects via gestures, greatly enhancing the mixed reality experience. This technology abstracts real-world objects into digital proxies, supporting browsing, multi-object selection, attribute filtering, semantic grouping, etc., and is expected to be applied in daily information retrieval, architectural navigation, and drone control, marking significant progress in embodied AI and human-computer interaction. (Source: 36氪)
🧰 Tools
Nokia 3210 Features DeepSeek AI: A New Feature Phone Experience : HMD has launched a re-released Nokia 3210 feature phone, with built-in DeepSeek AI. This phone offers AI voice assistant functionality at a low price of 429 yuan, with fast and accurate voice recognition, concise and amusing replies, and even humorous responses like “cracking walnuts.” Although its AI capabilities are limited, its “good enough” philosophy and user-friendliness for elderly users provide a new approach for AI popularization in low-cost devices, demonstrating the potential for AI inclusivity. (Source: 36氪)
Tencent AI Lab Open-Sources Deep Research Agent Framework Cognitive Kernel-Pro : Tencent AI Lab has open-sourced Cognitive Kernel-Pro, a fully open-source, multi-module, hierarchical deep research agent framework. The framework uses Python code as its action space, minimizing external dependencies, and aims to improve the efficiency of knowledge discovery and problem-solving. It performs excellently in GAIA benchmarks, approaching paid tool agents, and improves performance through innovative training methods, providing a reproducible solution for AI agent development and training. (Source: 量子位)
Claude Code Launches Automated Security Review Feature : Anthropic’s Claude Code now features automated security review functionality, allowing users to run security checks directly from the terminal and integrate with GitHub Actions to automatically review every new PR. This feature can identify and fix vulnerabilities such as SQL injection, XSS, and authentication flaws. Anthropic has internally used it to discover and fix real vulnerabilities, demonstrating AI’s potential in enhancing software development security and efficiency, though community discussions exist regarding its trustworthiness. (Source: Reddit r/ClaudeAI)
OpenWebUI User Experience Issues : The Reddit community discussed issues with OpenWebUI running Ollama and LiteLLM in a Proxmox LXC environment, specifically the inability to use tools, functions, and pipeline features, with users seeking successful experiences under similar configurations. Concurrently, users are also interested in how to hide or expand the Chain-of-Thought (CoT) output of gpt-oss models (running via llama.cpp-server) within OpenWebUI. These issues reflect the challenges faced in deploying and configuring AI tools and optimizing user experience in specific virtualization environments. (Source: Reddit r/OpenWebUI, Reddit r/OpenWebUI)
Demand for Open-Source Lightweight CPU-Friendly Word Alignment AI Model : Reddit users are seeking an open-source, lightweight, CPU-friendly AI model for language translation that can take source and target language sentences as input and return an array of word alignment indices, similar to simalign but not limited by its accuracy issues. This reflects developers’ specific needs for model performance, deployment environment, and open-source customizability in certain NLP tasks, to achieve efficient language processing in resource-constrained scenarios. (Source: Reddit r/deeplearning)
📚 Learning
LLM “Soft Thinking” Capability and Reasoning Optimization : Research papers explore the “soft thinking” capability of large reasoning models, finding that LLMs primarily rely on the most influential parts of soft inputs during subsequent decoding, leading to “soft thinking” degenerating into greedy decoding. By introducing Dirichlet resampling and Gumbel-Softmax tricks, randomness can be effectively introduced to unleash “soft thinking” potential, performing excellently in eight reasoning benchmarks and revealing new directions for enhancing LLM reasoning capabilities. (Source: Reddit r/MachineLearning)
“Mastering Modern Time Series Forecasting” Book Recommendation : The book “Mastering Modern Time Series Forecasting” consistently ranks first in Leanpub’s Machine Learning, Time Series, and Forecasting categories. The book comprehensively covers classic methods like ARIMA and Prophet, as well as modern ML/DL models such as LightGBM and Transformer, focusing on Python practice, production deployment, interpretability, and uncertainty quantification, aiming to provide data scientists, ML engineers, and researchers with a resource that balances theory and practice. (Source: Reddit r/deeplearning)
Qwen3’s New Paradigm GSPO: Solving DeepSeek GRPO Model Collapse : The Qwen team proposed the GSPO (Group Sequence Policy Optimization) algorithm, aiming to solve stability issues encountered by DeepSeek GRPO (Group Relative Policy Optimization) when training large language models, especially the collapse phenomenon in MoE models. GSPO significantly reduces variance and eliminates reliance on auxiliary policies by elevating importance sampling from token-level to sequence-level, potentially becoming a new standard for LLM post-training reinforcement learning, crucial for enhancing model reasoning capabilities. (Source: 36氪, Reddit r/MachineLearning)
Frontier Research in Reinforcement Learning : Several recent research advancements have been made in the field of reinforcement learning. The HyCodePolicy framework enhances the robustness and efficiency of embodied agent operation strategies through code synthesis, geometric localization, perceptual monitoring, and iterative repair. Sotopia-RL improves LLM social intelligence training effectiveness through discourse-level, multi-dimensional reward design. The EARL model, combining RL and VLM validators, performs excellently in image editing tasks with less training data required. Concurrently, community discussions indicate that Bayesian deep learning methods still face training challenges in achieving SOTA performance, with most successful cases involving “Bayesianizing” non-Bayesian models. (Source: HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, Reddit r/MachineLearning)
LLM Behavior and Optimization Mechanism Research : Multiple studies focus on LLM behavior and optimization. AttnTrace proposes an attention-weight-based long-context LLM context backtracking method, enhancing trustworthiness and prompt injection detection. LeanK significantly reduces memory and accelerates decoding through KV cache channel pruning. However, research finds that LLM’s Chain-of-Thought (CoT) reasoning is fragile when exceeding training data distribution, potentially being a “mirage.” The Sculptor framework, through active context management tools, mitigates interference and improves the reliability of long-context task reasoning. Web-CogReasoner enhances Web agents’ knowledge content learning and cognitive processes through knowledge-driven Chain-of-Thought reasoning. (Source: HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers)
Multimodal Models and Generative Technology Progress : The field of multimodal AI has recently seen fruitful achievements. UniEgoMotion proposes a unified model for first-person human motion reconstruction, prediction, and generation, opening new possibilities for AR/VR and other applications. AI agents’ purchasing behavior in e-commerce was evaluated, finding model preferences similar to humans but varying in degree. The BLiM framework improves text-video retrieval performance by combining query and candidate likelihoods. HPSv3 provides a new human preference evaluation standard for text-to-image generation models and optimizes image quality through CoHP. The 3D occupancy grounding benchmark and GroundingOcc model enhance spatial perception capabilities in autonomous driving. Additionally, Gaussian Splatting Diffusion models have achieved high-quality video-to-4D content generation. (Source: HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers, HuggingFace Daily Papers)
💼 Business
Differences in China-US AI Investment and Profit Models : US tech giants Meta, Microsoft, Google, and Amazon are projected to spend up to $400 billion on AI capital expenditures this year, with AI revenue growing rapidly. OpenAI and Anthropic’s annualized revenue are expected to reach $29 billion by year-end. In contrast, the commercialization of China’s AI industry faces challenges, with slow revenue and profit growth, and an accelerated outflow of some AI innovative products and talent. This disparity stems from a divergence in the underlying paradigms of the internet in China and the US: US SaaS drives AI applications with an “interface” mindset, while China relies on an “entry point” mindset, leading to limited returns on AI commercialization and highlighting the critical link between capital investment and business logic. (Source: 36氪, 36氪, 36氪, DeepLearning.AI Blog)
Meitu’s AI Transformation Achieves Profitability and Growth : Meitu Inc. has achieved business transformation through AI technology, with net profit for the first half of 2025 projected to increase significantly. It has built the visual large model MiracleVision, an AI open platform, and multiple AIGC products for C/B-end users, driving VIP subscription revenue as a main growth engine and expanding into overseas markets and B-end productivity scenarios. Although there’s still a gap compared to professional design tools like Figma, Meitu has successfully overcome years of losses, reshaping its profitability model through AI, and has formed a strategic partnership with Alibaba to further explore the B-end market, demonstrating AI’s immense potential in empowering traditional enterprises. (Source: 36氪)
AI Companion Robots Become a Hot New Sector : With the rise of aging populations and the single economy, “loneliness” has become a driving force for the AI companion robot market, with the global market size projected for rapid growth. Prominent figures like Lei Jun, Richard Liu, Zhu Xiaohu, and Yu Minhong have entered the fray, investing or launching products to capture market share. The business models in this sector are diverse, including hardware sales, subscription services, scenario-based solutions, and data monetization, but high return rates and differing user expectations remain challenges. The industry is moving from a technology validation phase to rapid commercialization, signaling an explosive growth in emotional technology products. (Source: 36氪)
🌟 Community
ChatGPT Privacy Leak Scandal and User Trust Crisis : Over 70,000 ChatGPT private chat contents were publicly indexed in Google search results due to a design flaw in the “share” feature, sparking user privacy concerns and widespread controversy. OpenAI admitted to the design issue and urgently removed the “discoverable” option. However, this incident exacerbated the trust crisis among users regarding AI chat privacy and OpenAI’s data governance, drawing criticism for treating users as “guinea pigs.” The incident highlights the importance for AI products to more clearly inform users about data processing methods during feature design. (Source: 36氪)
AI’s Impact on the Job Market and Career Transformation : Microsoft research indicates that AI will replace a large number of human jobs, listing 40 high-risk professions (e.g., interpreters, journalists) and 40 low-risk professions (e.g., surgeons, construction workers). AI is reshaping the developer’s role from “coder” to “AI manager,” requiring mastery of core competencies like AI literacy and agent collaboration. While AI won’t cause complete human unemployment, it will drive a structural reshaping of the labor market, and the education system also needs corresponding reforms to adapt to the AI era. For example, the Reddit community is also discussing AI’s impact on resumes and hiring. (Source: 36氪, 36氪, Reddit r/ArtificialInteligence)
AI’s Impact on Human Cognition and Mental Health : The Reddit community discussed whether AI makes humans “dumber,” with MIT research showing that excessive reliance on ChatGPT might reduce brain activity and affect critical thinking. Concurrently, ChatGPT launched an “anti-addiction mode” to address potential mental health issues from prolonged user engagement, reflecting concerns about over-reliance on AI. Elon Musk’s Grok “AI girlfriends” Ani and Valentine sparked ethical controversy; their emotional companionship model challenges the boundaries between AI tools and emotions, raising alarms about social atomization and emotional manipulation. (Source: Reddit r/ChatGPT, Reddit r/ArtificialInteligence, 量子位, 36氪, 36氪)
Social Discussion on AI Ethics and Governance : The Reddit community discussed the necessity of AI governance, with students seeking interviewees for a thesis exploring AI governance at macro, meso, and micro levels. Society expressed concerns about Duolingo’s “AI-first” policy’s profitability model, believing it could lead to environmental damage, job displacement, and weakened human connections, calling for a boycott. Concurrently, discussions on LLM data leakage risks emphasized the importance of responsible API usage and local models, calling for strengthened AI data privacy protection and ethical review. (Source: Reddit r/ArtificialInteligence, Reddit r/artificial, Reddit r/ArtificialInteligence)
Philosophical Reflection on AI’s Impact on Social Structure and Human Meaning : Scholar Zhang Xiaoyu proposed “emergence principle,” “human equivalent,” “algorithmic judgment,” and “civil contract” as foundational points to understand AI’s comprehensive societal changes. He believes AI will mass-produce intelligence at extremely low costs, potentially widening societal divides to a “species-level,” necessitating “universal basic work” and balanced allocation by recommendation algorithms. AI will become an “impartial third-party judge,” forcing humanity to ponder justice and the meaning of existence, calling for humans to abandon “anthropocentrism” and adapt to the AI era. DeepMind head Demis Hassabis also believes the AI revolution will bring a world of “extreme abundance,” but resource allocation and unemployment issues need to be addressed. (Source: 36氪, 36氪, 36氪)
Humor and Reflection in the AI Community : The Reddit community saw numerous humorous discussions about AI, such as ChatGPT’s “accurate” explanations of professions leading to user self-doubt, Claude Opus 4.1’s “sweeping out” image when solving problems, and jests about OpenAI’s “open-source” naming and Qwen models’ “personalization.” These discussions reflect users’ lighthearted reflections on AI’s limitations, ethical boundaries, and future development in their daily use, as well as a community culture of using humor to alleviate technological anxiety. (Source: Reddit r/ChatGPT, Reddit r/ClaudeAI, Reddit r/LocalLLaMA, Reddit r/LocalLLaMA, Reddit r/LocalLLaMA, Reddit r/ChatGPT)
Sustainability Challenges of AI Conference Models : A HuggingFace paper points out that the current centralized AI conference model is unsustainable due to rapid expansion, facing multiple pressures: scientific (excessive publication rates), environmental (carbon footprint), psychological (negative emotions, mental health issues), and logistical (venue capacity). The study proposes a “Community Federated Conferences (CFC)” model, separating review, presentation, and social aspects through global coordination and local organization, to achieve more sustainable, inclusive, and resilient AI research development, addressing new challenges brought by the rapid growth of the AI field. (Source: HuggingFace Daily Papers)
💡 Other
Interview with Unitree Robotics Founder Wang Xingxing: Pragmatic Idealism in Embodied AI : An unreleased interview by Vertex Ventures with Unitree Robotics founder Wang Xingxing reveals his profound insights into quadruped/bipedal robots and AI’s role in embodied intelligence. Wang Xingxing emphasizes “slow is fast,” insisting on independent R&D of core components, pursuing low-cost and high-performance, and is optimistic about AI’s long-term prospects in robotics. The interview showcases his pragmatic and long-term entrepreneurial philosophy, and his ultimate pursuit of technological rationality and product implementation, seen as a microcosm of top entrepreneurs in the era of technological innovation. (Source: 36氪)
New Directions in Finance and Management Education in the AI Era : Shanghai Advanced Institute of Finance (SAIF) at Shanghai Jiao Tong University’s 2026 EMBA program has been fully upgraded, integrating AI technology and legal regulations deeply into finance and management education for the first time, establishing “Finance × AI” and “Finance × Law” specializations. The program launched the “Talent Cultivation Special Scholarship for a Strong Tech Nation,” offering full or half scholarships to outstanding tech innovation talents, aiming to cultivate interdisciplinary professionals with both global vision and local insights, supporting enterprise development in the AI era. (Source: 量子位)
Tencent 2026 Campus Recruitment Launched, Focusing on AI Product Manager Trainees : Tencent has officially launched its 2026 campus recruitment, opening over 70 positions across five major categories including technology, product, and design to university students worldwide. This recruitment will significantly increase investment in AI-related positions and introduce an “AI Product Manager Trainee” program for top product talents, aiming to attract outstanding young individuals to deeply participate in AI technological transformation and build talent reserves for Tencent’s AI business development, demonstrating leading enterprises’ strong demand for and commitment to cultivating AI talent. (Source: 量子位)
