HDT IBI 14: 00 0-8 地点:深圳南山区 扫码报名 P Z Potentials 主題:AI 视频 形式: 晚餐 时间: 12.3周三19:00 人数:6-8 地点: 北京 主題: Al Agents 形式: 晚餐 时间: 12.5周五19:00 සිට 100 105 EQTEUNIP 欢迎软/硬件大厂、创业公司产品/算法、（潜在）创 业者、独立开发者/创作者 带着你最近的收获、新的想法 一起Eat&Nip! Ⅰ创业狂想曲 关于 Z Potentials 近十位上市公司CEO和顶级风投合伙人 鼎力推荐 AI创业心法,20+领军者亲授 开启Al创业新纪元 我们正在招募新一期的实习生 我们正在寻找有创造力的00后创业 ...

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Group 1 - The article discusses the upcoming AI-themed dinner events aimed at fostering collaboration among hardware/software companies, startups, and independent developers [2][4] - The first event focuses on AI video and is scheduled for December 3rd, while the second event centers on AI agents and will take place on December 5th [2] - The events are designed to bring together creative individuals and industry leaders to share insights and ideas in the AI space [8][7] Group 2 - The article highlights the involvement of top CEOs and venture capital partners who endorse the initiative, indicating strong industry support [7] - It emphasizes the importance of innovative thinking among the younger generation, specifically targeting creative entrepreneurs born after 2000 [9] - The initiative aims to provide guidance on AI entrepreneurship through insights from over 20 industry leaders [8]

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China’s Top Companies Focus on AI Agents as Next Battleground https://t.co/xvhJXmcVNK ...

Core Insights - The article emphasizes the growing importance of Reinforcement Learning (RL) and Agents in the context of large models, highlighting a shift from merely generating text to enabling models to perform actions through decision-making processes [1][2]. Group 1: Event Overview - The NeurIPS 2025 event aims to create a relaxed environment for researchers and engineers from leading organizations like OpenAI, DeepMind, and Meta FAIR to discuss RL, decision-making, and the underlying capabilities of large models [1]. - The event will not feature formal presentations but will encourage informal discussions about technology, ideas, and experiences, fostering a collaborative atmosphere [1]. Group 2: Focus on RL and Agents - There is a renewed focus on RL, moving beyond traditional fine-tuning methods to enable models to strengthen through interaction with the environment [2]. - The development of executable Agents requires a robust Action Layer, which is essential for models to perform tasks effectively [2][3]. Group 3: Industry Developments - Platforms like Composio are emerging to build the next generation of AI Agents by creating an Action Layer that integrates various tools and APIs into a unified interface, highlighting the infrastructure needed for operational Agents [3]. - Investment in AI infrastructure is being driven by funds like Hattrick Capital, which have been early supporters of AI advancements, particularly in the areas of Agents and robotics [4].

AI Model & Strategy - Open AI models are essential for building intelligence and enabling customization for specific industry workflows [1] - Open source AI models offer increased visibility and customizability [2] - Synopsis' strategy heavily relies on AI to provide autonomous functionality in engineering workflows [4][5] - The industry anticipates AI agents to power transactions in the agentic economy [5] Agent & Technology - CrowdStrike aims to transform human expertise into AI agents for rapid response to cyber attacks [2] - Nemotron facilitates control over expertise and enables the creation of virtual analysts like Charlotte for security alert management [3] - Agent engineers are being developed with progressively higher levels of autonomy [3] - Open models deployed on GPUs, coupled with stack control, allow for fine-tuning, solving challenges in agentic commerce [6] - Nemotron enables the selection of the optimal balance between reasoning and performance, allowing for fine-tuning to achieve desired outcomes [7] Partnership - Nvidia and CrowdStrike collaborate to prevent AI-based attacks [6] - The industry relies on the partnership with Nvidia for components like Nemotron and Nemo agent kit to accelerate agent development [7]

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Model Performance & Ranking - GLM 4.6 is currently ranked 1 on the LMSYS Chatbot Arena, on par with GPT-4o and Claude 3.5 Sonnet [1] - The GLM family of models has achieved over 100 million downloads [1] Training & Architecture - zAI utilized a single-stage Reinforcement Learning (RL) approach for training GLM 4.6 [1] - zAI developed the "SLIME" RL framework for handling complex agent trajectories [1] - The pre-training data for GLM 4.6 consisted of 15 trillion tokens [1] - zAI filters 15T tokens, moves to repo-level code contexts, and integrates agentic reasoning data [1] - Token-Weighted Loss is used for coding [1] Multimodal Capabilities - GLM 4.5V features native resolution processing to improve UI navigation and video understanding [1] Deployment & Integration - GLM models can be deployed using vLLM, SGLang, and Hugging Face [1] Research & Development - zAI is actively researching models such as GLM-4.5, GLM-4.5V, CogVideoX, and CogAgent [1] - zAI is researching the capabilities of model Agents and integration with Agent frameworks like langchain-chatchat and chatpdf [1]

https://t.co/R25EjNSvL3Egg.Party (@EggDotParty):On the surface, EGG looks like memes and good vibes.But EGG is doing a lot more behind the curtain — from building AI Agents, to powering tokens, to helping creators grow real influence.Come see the whole picture 🥚→ https://t.co/6PFIuky9mR https://t.co/kQm8dCbXX4 ...