腾讯研究院AI速递 20250613

Group 1: Meta's Developments - Meta has open-sourced the V-JEPA 2 world model, capable of understanding the physical world and trained on 1 million hours of video data, enabling zero-shot planning and robot control [1] - The model requires only 62 hours of training to generate planning control models, achieving top-tier performance in behavior classification and prediction with success rates between 65% and 80% [1] - Meta has released three benchmarks for physical understanding, highlighting the gap between AI and human physical reasoning capabilities, with plans to develop hierarchical and multimodal JEPA models in the future [1] Group 2: Meta's Talent Acquisition - Meta CEO Mark Zuckerberg is forming a "superintelligence" team, successfully recruiting Google DeepMind's chief researcher Jack Rae and other top AI talents [2] - Jack Rae is known for the "compression is intelligence" concept and has contributed to significant model developments during his 7 years at DeepMind [2] - Meta is offering compensation packages in the seven to nine-figure range to attract AI talent and plans to establish a team of about 50 people, potentially acquiring Scale AI and its team for billions [2] Group 3: Manus AI Chat Mode - Manus has updated its interface and launched a free Chat mode, replacing previous standard and high-investment modes with Agent (workflow) and Chat (quick Q&A) modes [3] - The new features allow for the creation of Slides (PPT), images, videos, and web pages, enhancing task execution and content generation [3] - Testing indicates that the Chat mode is responsive and can display reference sources, with the AI product outperforming competitors in task planning, hallucination control, and content richness [3] Group 4: Quark's College Admission Model - Quark has launched the first college admission large model, integrating official data to provide free personalized planning for 13.35 million candidates, addressing information asymmetry [4][5] - The model can handle multi-dimensional admission consultations, analyzing schools, majors, and admission probabilities while offering gradient suggestions that consider personal interests and family expectations [5] - It generates comprehensive admission reports, including "reach, stable, and safety" strategy recommendations and historical admission data, along with intelligent selection features and expert guidance [5] Group 5: Xiamen University's AI Assistant - Xiamen University has implemented an AI assistant via WeChat to address frequent campus inquiries, utilizing DeepSeek and mixed models for instant responses [6] - The AI system can be deployed by simply uploading existing knowledge files, capable of handling both simple and complex queries, including software installation guidance [6] - Integrated within WeChat, the system requires no new software downloads and can be set up within half a day, ensuring data is restricted to campus use with controlled permissions [6] Group 6: Disney and NBC's Lawsuit Against Midjourney - Disney and NBC Universal have sued Midjourney for copyright infringement, alleging that it allows users to generate images of iconic characters from franchises like "Star Wars" and "Frozen" [7] - Midjourney has built its training data through web scraping, projecting $300 million in revenue for 2024, with its founder admitting the inability to track image sources and ignoring copyright holders' cease-and-desist requests [7] - The companies are seeking financial compensation and a court injunction, emphasizing that "piracy is piracy" and that AI companies do not lessen the nature of infringement, signaling a warning to the entire AI industry [7] Group 7: OpenWBT by Galaxy General and Tsinghua University - Galaxy General and Tsinghua University have released OpenWBT, the first open-source humanoid robot full-body remote control system, supporting multiple models and cross-virtual-real operations [8] - The system can be deployed within hours using only a VR headset and a laptop to remotely control robots for full-body movements, compatible with various models [8] - Utilizing "Real-world-Ready Skill Space" technology, it breaks down control into walking, posture adjustment, and hand reach as atomic skills, addressing the challenge of transferring from simulation to reality [8] Group 8: NVIDIA's Quantum Computing CUDA - Jensen Huang announced the release of CUDA-Q, a quantum computing-specific version, predicting that quantum computing will be applicable within a few years, enhancing development speed by 1300 times on the GB200 [9] - NVIDIA anticipates that the number of quantum bits will follow Moore's Law, with future supercomputers integrating quantum processing units alongside GPUs, enabling quantum simulation and quantum-classical hybrid computing [9] - Huang showcased the core of the "physical AI" strategy, including tools for intelligent agents, autonomous driving systems, and humanoid robots, claiming a market opportunity of $50 trillion in this field [9] Group 9: a16z on SEO to GEO Transition - The search landscape is shifting from traditional browsers to language model platforms, with the $80 billion SEO market being replaced by the new paradigm of "Generative Engine Optimization (GEO)" [10] - The focus of competition is moving from click-through rates to "model citation rates," requiring brands to be "encoded into the AI layer," with "no-prompt awareness" becoming a key metric [10] - Winners in GEO will build action infrastructures, becoming core channels and controlling budget allocations, with the ultimate brand question being "Will the model remember you?" [10] Group 10: AI Pricing Trends - Traditional seat and fixed pricing models are being replaced by hybrid pricing, with 41% of companies adopting this approach, balancing revenue predictability with actual value [11] - AI pricing strategies are diversifying, including pay-per-use, package deals, and platform fees plus usage, requiring companies to choose the best model based on their circumstances [11] - Outcome-based pricing is becoming a trend, necessitating consistency, attribution, measurability, and predictability, as AI pricing evolves towards charging based on customer outcomes [11]