鹭羽 发自 凹非寺 量子位 | 公众号 QbitAI 首个 能跨领域精准预测人类认知的基础模型诞生！ 不仅可以完全预判你的行为，还能知道你是如何思考、以及为什么思考。 Centaur现在就像一名专业的心理学家，只需传统模型Llama的0.15%参数，就可以完美模拟人类在 160项 心理学实验中的行为，理解人类如 何学习、决策甚至犯错。 不仅仅受限于单一领域，而是真正的多任务全能选手，性能全面超越传统的特定领域认知模型。 这是一项最新登上 Nature 的突破性研究，来自德国的研究团队只用了5天训练时间就开发出人类认知的通用计算模型—— Centaur 。 更惊人的是，其神经表征竟与真人fMRI （功能性磁共振成像） 扫描结果高度吻合。 AI，正在成为最懂人类的 "读心者" 。 Centaur：心理学与AI的跨界突破 在心理学领域，建立一个 统一的认知理论 ，可以识别和描述所有人类认知、行为和情感，是所有心理学家孜孜不倦的追求。 认知的统一理论是唯一能将我们日益增长的丰富知识，置于理智掌控之下的方法。 那么首先需要构建一个能够预测和模拟人类行为的 通用计算模型 ，它不是AlphaGo这种专为某一个领域而生的模型 ...

Core Insights - The emergence of "Agentic AI" is gaining attention in the tech industry, with predictions that 2025 will be the "Year of AI Agents" [1][9] - Concerns have been raised about the actual capabilities and applicability of Agentic AI, with many projects potentially falling into the trap of concept capitalization rather than delivering real value [1][2] Group 1: Current State of Agentic AI - Gartner predicts that by the end of 2027, over 40% of Agentic AI projects will be canceled due to rising costs, unclear business value, or insufficient risk control [1][10] - A survey by Gartner revealed that 19% of organizations have made significant investments in Agentic AI, while 42% have made conservative investments, and 31% are uncertain or waiting [2] Group 2: Misrepresentation and Challenges - There is a trend of "agent washing," where existing AI tools are rebranded as Agentic AI without providing true agent capabilities; only about 130 out of thousands of vendors actually offer genuine agent functions [2][3] - Most current Agentic AI solutions lack clear business value or return on investment (ROI), as they are not mature enough to achieve complex business goals [3][4] Group 3: Performance Evaluation - Research from Carnegie Mellon University indicates that AI agents have significant gaps in their ability to replace human workers in real-world tasks, with the best-performing model, Gemini 2.5 Pro, achieving only a 30.3% success rate in task completion [6][7] - In a separate evaluation for customer relationship management (CRM) scenarios, leading models showed limited performance, with single-turn interactions averaging a 58% success rate, dropping to around 35% in multi-turn interactions [8] Group 4: Industry Reactions and Future Outlook - Companies like Klarna have experienced setbacks with AI tools, leading to a return to human employees for customer service due to quality issues [9] - Despite current challenges, Gartner remains optimistic about the long-term potential of Agentic AI, forecasting that by 2028, at least 15% of daily work decisions will be made by AI agents [10]