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单任务成本约0.2美元 智谱要用云端Agent抢市场
Di Yi Cai Jing· 2025-08-20 14:45
智谱在Agent方面的迭代从去年10月持续至今,初级版本可微信点赞、淘宝购物、携程订票。11月升级后新增会议总结、文档处理、网页搜索与总结等功 能。彼时智谱CEO张鹏对记者表示,智谱对智能体的理解更偏底层技术。 今年3月升级的AutoGLM沉思可以完成在小红书14天养号接商单任务,但沉思主要是本地化运行,暂无虚拟机设备,通过可视化交互图形界面 (GUI)而非 API调用的运作。此次2.0版本除了云端属性,也将可操作应用增至美团、京东、小红书、抖音等几十个高频应用。 关于底层技术路线的变化,采访中智谱AutoGLM 技术负责人刘潇对记者表示,与其他Agent不同的是,智谱相信"模型即Agent",即Agent相当大一部分能力 正直接被模型通过端到端强化学习的方式吸纳。去年智谱Agent方案更多依赖于对人类专家轨迹的学习,虽然当时产品可以点外卖,但只要是没有见过的任 务类型,就无法完成。这推动团队在沉思产品上实现Deep Research(深度研究)与Browser-use Agent(网页智能体)的融合,因为如果不使用Browser-use的 方式,便无法阅读大量数据,也没有办法充分发挥个人所拥有的生产资料和数 ...
AI Agent是2025年最大风口还是泡沫?
3 6 Ke· 2025-07-25 09:56
Core Insights - OpenAI has launched ChatGPT Agent, a versatile AI agent that signifies a shift towards the "model as agent" concept, which is gaining traction among major AI companies [1][2] - The "model as agent" paradigm suggests that large models will evolve from being mere assistants to proactive agents capable of executing tasks independently [2][7] - The competitive landscape for AI agents is changing, with various companies introducing their own models and features to enhance agent capabilities [11][12] Group 1: "Model as Agent" Concept - The "model as agent" concept represents a fundamental shift in AI understanding, moving from a tool-based approach to a collaborative partner mindset [8] - ChatGPT Agent exemplifies this shift by integrating all skills and task executions within a single model, allowing users to observe the AI's operations in real-time [2][10] - The transition to "model as agent" is seen as a pathway to achieving Artificial General Intelligence (AGI) [1][2] Group 2: Competitive Landscape - The AI market has seen significant changes since 2025, with new entrants like DeepSeek offering low-cost, high-performance models [11][12] - Companies such as xAI and Anthropic are competing with their models, like Grok 4 and Claude 4, which set new standards in programming and agent capabilities [3][6] - The "six small tigers" of AI, including companies like MiniMax and Kimi, have experienced varying degrees of market performance and funding challenges [12] Group 3: Industry Trends and Future Directions - The industry consensus is that the application of general AI agents is still in its early stages, focusing on business scenario exploration and technical validation [10] - Multi-agent collaboration models are gaining attention as a way to diversify task handling, with companies like Manus showcasing practical use cases [9][10] - The future of AI agents will likely involve a balance between technology and cost, with a focus on solving core business problems [10][15]