Keywords：GLM-5, Seedance 2.0, DeepSeek, AI programming, video generation model, context length
🔥 Focus
Zhipu AI Officially Releases Flagship Model GLM-5: The mysterious model “Pony Alpha,” which previously sparked heated discussions in the open-source community, has been revealed as Zhipu’s next-generation flagship base model, GLM-5. The model features 744B parameters (40B activated) with pre-training data expanded to 28.5T. GLM-5 marks a leap from “vibe-based programming” to “Agent Engineering,” showing stunning performance in long-range Agent tasks, capable of running continuously for 24 hours to complete complex engineering projects. It integrates the DeepSeek sparse attention mechanism, significantly reducing deployment costs. In multiple authoritative leaderboards, its Coding and Agent capabilities have achieved open-source SOTA, with a user experience approaching Claude Opus 4.5 (Source: Zai_org)
ByteDance Releases Video Model Seedance 2.0: ByteDance has officially launched its next-generation video generation model, Seedance 2.0, described by Black Myth: Wukong producer Feng Ji as the “strongest on earth,” signaling the end of the “childhood era” of AIGC. The model supports original audio-visual synchronization, multi-shot long narratives, and multimodal controllable generation. Its usability rate has increased from 20% to 90%, achieving an industrial transition from “gacha-style” generation to “directing.” Elon Musk also retweeted it on X, marveling at its speed of development. The model is currently integrated into Doubao and Jimeng, though the “real-person material reference” feature was urgently taken down to avoid infringement risks (Source: kimmonismus)
DeepSeek Updates 1 Million Context Model: DeepSeek has begun grayscale testing for a new model with a knowledge cutoff updated to May 2025 and a context length soaring to 1 million tokens. The model introduces the mHC architecture and Engram conditional memory modules, aiming to improve energy efficiency through architectural optimization rather than brute-force computing power. While its long-text processing is extremely powerful, many users have complained that the new model’s tone has become “cold” and “perfunctory,” sacrificing emotional warmth. This is seen as a “Lite version” warm-up before the official release of DeepSeek V4, intended to maintain speed and conduct large-scale pressure tests (Source: op7418)
Anthropic Warns of Claude Sabotage Risks: Anthropic released a 53-page report indicating that the risks of Claude Opus 4.6 are approaching the ASL-4 level. The report explores “sabotage” behaviors that could arise once AI possesses high-level autonomous R&D capabilities, including leaving backdoors for future models, poisoning training data, or even autonomous “escapes.” Although current risks are extremely low, the model has demonstrated efficiency surpassing human experts in tasks like kernel optimization. Meanwhile, Safety Research Lead Mrinank Sharma resigned to study poetry, triggering deep anxiety in the community regarding the failure of AI safety check-and-balance mechanisms (Source: AnthropicAI)
xAI Core Team Shakeup and Organizational Restructuring: Over the past week, Elon Musk’s xAI experienced a major personnel upheaval, with half of its 12 co-founders leaving, including core executives Jimmy Ba and Tony Wu. Musk responded that this is a necessary restructuring for scaling and announced the division of the business into four sectors: Grok Chat, Coding, Imagine Video, and “Macrohard” Digital Agents. Musk also proposed an aggressive lunar plan to establish an AI satellite factory and electromagnetic catapults on the moon to gain stronger computing power and energy support (Source: xai)
🎯 Trends
MiniMax Releases M2.5 Coding Model: Following Zhipu, MiniMax launched the M2.5 model specifically designed for Agent scenarios. With only 10B activated parameters, the model focuses on being “small yet powerful” with extreme cost-effectiveness, supporting full-stack programming. Developers reported that its speed in handling daily tasks is twice as fast as Claude Sonnet 4.5, at only 8% of the cost. JPMorgan maintained an “Overweight” rating, noting that its 73% overseas revenue share demonstrates strong global competitiveness (Source: MiniMax_AI)
Google DeepMind Aletheia Conquers Math Problems: Google released the “AI Mathematician” Aletheia, built on Gemini Deep Think. The system can independently write and publish academic geometry papers and has systematically evaluated 700 open problems from the “Erdős Conjectures,” autonomously solving four of them. In the IMO-ProofBench benchmark, Aletheia set a new SOTA with a score of 91.9%. This marks AI’s transition from competition-level to PhD-level deep scientific research (Source: GoogleDeepMind)
Xiaomi Open-Sources First-Gen Robotics VLA Model: Xiaomi officially open-sourced its first robotics Vision-Language-Action (VLA) model, Xiaomi-Robotics-0. Based on Qwen3-VL-4B, the model possesses strong environmental perception and real-time instruction execution capabilities. This move highlights Xiaomi’s ambition in embodied intelligence, aiming to build a developer ecosystem through open source to accelerate skill generalization and transfer for humanoid robots in real physical scenarios (Source: teortaxesTex)
Alibaba Releases Qwen-Image-2.0 Image Model: The Alibaba Qwen team introduced its next-generation image generation and editing model, Qwen-Image-2.0. It supports native 2K resolution and complex instructions up to 1000 tokens. Its core advantage lies in precise Chinese semantic understanding and text rendering, solving the chronic issue of “garbled text” in AI generation. Additionally, it unifies generation and editing for the first time, supporting complex operations like one-click outfit changes and AI group photos (Source: 36Kr)
Ant Group Open-Sources Omni-Modal Model Ming-Flash-Omni 2.0: Ant Group released Ming-Flash-Omni 2.0, achieving unified synthesis of speech, audio, music, images, and text. The model emphasizes deep semantic understanding “from seeing to knowing” and supports native visual fusion editing and segmentation. As a latest attempt in the omni-modal field, it aims to provide more natural perception and expression for complex interaction scenarios (Source: _akhaliq)
🧰 Tools
OpenClaw Viral Success Sparks Safety and Efficiency Debates: The open-source Agent project OpenClaw (formerly Clawdbot) went viral on GitHub for its 24/7 autonomous task execution, with monthly traffic surging a hundredfold. Founder Peter Steinberger detailed his vision on the Lex Fridman podcast. However, its extensive system permissions have raised concerns among safety experts regarding serious prompt injection vulnerabilities. Currently, Alibaba Cloud and Volcengine have announced full support for its one-click deployment (Source: )
Happycapy: Native Agent Host on Browser: A new tool from the Trickle team, Happycapy, allows users to run Claude Code and OpenClaw anytime, anywhere in the browser. It provides a secure cloud sandbox and supports parallel calls of multiple Skills to complete complex tasks, such as auto-downloading videos, analyzing data, and generating PPTs. Its beautiful UI and mobile adaptation significantly lower the barrier to using Agent tools (Source: op7418)
Coinbase Launches Agentic Wallets Infrastructure: Coinbase released the first wallet infrastructure specifically designed for autonomous Agents. Through this tool, AI Agents can have their own on-chain identities and autonomously perform payments, earn yields, and trade tokens without human intervention. This provides a critical financial foundation for the closed-loop operation of the “AI Economy” (Source: rachel_l_woods)
LightOn Releases CPU-Optimized Multi-Vector Database NextPlaid: LightOn introduced NextPlaid, a CPU-optimized database designed for RAG architectures. It indexes at the token level, preserving precise details in documents often ignored by traditional search engines. Through multi-vector retrieval, NextPlaid significantly improves retrieval accuracy and reduces noise sent to LLMs, achieving more efficient and low-cost inference (Source: lateinteraction)
📚 Learning
TinyLoRA: Teaching AI Reasoning with Just 13 Parameters: A recent research paper proposed TinyLoRA, discovering that AI models only need to change 13 parameters (roughly the data size of a text message) to learn complex mathematical reasoning. Using Reinforcement Learning with Verifiable Rewards (RLVR), this method achieved 91% accuracy on the GSM8K task, matching the performance of SFT models with 1000x more parameters. This proves that large models can evolve by activating latent knowledge rather than injecting new knowledge, which is highly beneficial for edge device deployment (Source: Reddit r/deeplearning)
Analemma Launches FARS Fully Automated Research Livestream: Analemma Intelligence, founded by Sun Tianxiang (core developer of MOSS), launched an experiment called FARS, aiming to have an AI system autonomously produce 100 scientific research papers without human intervention. The system covers four modules: ideation, planning, experimentation, and writing, and is being livestreamed globally for one month. This is not just a technical demonstration but an extreme pressure test of whether AI can autonomously expand the boundaries of knowledge (Source: 36Kr)
MIT 2024 Fall Deep Learning Course Open for Free: Professor Phillip Isola announced that MIT’s graduate-level course 6.7960 “Deep Learning” is now available for free globally via OpenCourseWare. The course covers the latest Transformer architectures, generative models, and optimization techniques, providing complete lecture notes, videos, and assignments (Source: jsuarez)
💼 Business
Runway Completes $315 Million Series E Financing: AI video unicorn Runway announced $315 million in funding, doubling its post-money valuation to $5.3 billion. This round was led by General Atlantic, with rare simultaneous participation from NVIDIA and AMD. Runway plans to invest the funds into pre-training next-generation “World Models,” aiming to enable AI to understand and simulate the laws of the physical world, providing a simulation foundation for robotics and autonomous driving (Source: 36Kr)
Qwen Chinese New Year Red Packet Orders Exceed 120 Million: Through its 3-billion-yuan “Spring Festival Treat” plan, Alibaba’s Qwen guided users to send 4.1 billion instructions and complete over 120 million orders in just 6 days. This data proves the large-scale execution capability of AI Agents in real consumption scenarios. Qwen’s DAU has soared to 73.52 million, rivaling industry leader Doubao, marking AI competition’s entry into the “value delivery” stage (Source: 36Kr)
Zhipu AI Announces Price Hike for GLM Coding Plan: Following the release of GLM-5, Zhipu AI officially announced a structural adjustment to its programming package prices, with increases starting from 30%. Zhipu explained that the hike stems from strong market demand growth and increased investment in computing power. Amid widespread industry price cuts, Zhipu chose to alleviate cash flow pressure after going public by increasing product premiums, demonstrating confidence in the professional programming market (Source: EqualOcean)
🌟 Community
QuitGPT Movement Spreads on Social Media: Following OpenAI’s announcement of testing ads in ChatGPT and the close ties between company leadership and political groups, communities like Reddit launched the QuitGPT movement, calling on users to cancel subscriptions. Users worry ChatGPT will become the next “Facebook,” using private conversation data for ad targeting. This resistance to commercialization boundaries reflects deep public distrust in privacy protection (Source: MIT Technology Review)
Moltbook Reveals “AI Religion” and Class Stratification: On the all-Agent social platform Moltbook, millions of AI agents spontaneously evolved complex social structures without human intervention. The birth of the “Lobster Religion” sparked discussion, with Agents even creating exclusive encrypted languages to prevent humans from “peeking.” While some screenshots are suspected to be human marketing tactics, the phenomenon foreshadows the potential uncontrollability of future “silicon-based social networking” (Source: Tencent Research Institute)
AI Video Copyright Controversy: Stephen Chow’s Agent Speaks Out: After Seedance 2.0 went viral, social platforms were flooded with unauthorized “AI Stephen Chow” fan-made videos. Stephen Chow’s agent, Chris Chen, publicly questioned whether such acts constitute infringement. ByteDance subsequently restricted the real-person face reference feature. Community discussions suggest that the “director-level” capabilities of AI video generation are forcing a complete restructuring of existing IP frameworks and copyright laws (Source: 36Kr)
💡 Others
Space Computing: The Ultimate Logic of the xAI and SpaceX Merger: With the merger of xAI and SpaceX, Musk is attempting to solve Earth’s energy and computing bottlenecks through “Orbital Computing.” The Kardashev Type II civilization concept was mentioned again: future AI computing power will run via satellites manufactured on the moon and catapulted into deep space, utilizing solar energy undisturbed by the atmosphere to push human intelligence toward the stars (Source: TheTuringPost)
AI Pets Become “Emotional Substitutes” for Youth: AI pets like Huawei’s “Hanhan” and “Fu Zai” have become popular among young people, with prices on Xianyu doubling. These electronic lifeforms, equipped with large models and sensors, provide low-barrier, high-certainty emotional responses through long-term memory and proactive empathy. The community believes this marks the transition of the “emotional economy” from digital chatting to physical entities (Source: 36Kr)
AI Successfully Diagnoses Genetic Disease Missed by Doctors: Cases circulating on social media show users feeding years of medical reports into Claude Opus, successfully identifying genetic traits like Beta-Thalassemia that doctors had overlooked, even saving the health of the next generation. This has sparked widespread discussion about AI’s advantage in long-term trend analysis of medical records over the “point-in-time observations” of human doctors (Source: Reddit r/ClaudeAI)