最新资讯
reddit.com OpenAI 称 Astra 仅满足 10% 安全任务标准 dev.to FreeToken:在自有 GPU 上运行前沿 MoE 模型及其内存需求 dev.to 当 AI Agent 说“完成”时,究竟完成了什么? dev.to 部署 Underdog Bark 3.0 Pro:逐字转写、自定义后端与分块设置 dev.to 为艰难对话构建 AI:五个 Agent、一条安全正则与一位盲评监督者 techcrunch.com Palo Alto Networks 洽谈以 5 亿美元收购 AI Agent 安全初创公司 Clutch theinformation.com 黄仁勋被要求就涉华间谍指控向国会作简报 www.infoq.com Edera 推出 Object Capability Bounded Authority,试图将凭证与 AI Agent 工作负载隔离 wechat 这波杀疯了!旗舰级模型不限量、1个月视频额度免费领 bloomberg.com AI 抛售蔓延至信用市场,软银领跌亚洲美元债 dev.to 如何在专用 GPU 服务器上用 OpenAI 兼容 API 部署 LLM dev.to 审计 153 份 Claude Code 与 Codex 会话记录:User-Agent 与 URL 中的邮箱泄露
多元动态
登录 注册
智能体 x.com · @latentspacepod

Latent.Space 播客对话 Richard Socher:Recursive 与递归自我改进 AI

原文 我的收藏

Latent.Space 发布与 Richard Socher 的访谈节目,主题围绕其新实验室 Recursive 的 50 亿美元融资、面向 AI 研究的开放式自我改进系统、Eureka Machine、智能的十个空间、DecaNLP 与 AI 同行评审问题等。节目附有从超级智能、对齐与安全到算力上限、Agent 路线图的完整时间轴,但正文未提供可验证的技术细节。

AI推荐理由 Latent.Space 播客对 Richard Socher 的访谈,涉及新实验室 Recursive 的 50 亿美元融资、Eureka Machine、递归自我改进、AI 同行评审等议题,并附完整时间轴,信息密度较高;但正文仅为节目预告与章节列表,未给出可验证的技术细节或数据,融资规模等说法来自节目自述,需保留不确定性。

62 浏览 2,550 点赞 11 评论 7 转发 4

正文

🆕 Humanity’s Last Invention — with [@RichardSocher](https://x.com/RichardSocher)! [youtube.com/watch?v=eDFXtS…](https://www.youtube.com/watch?v=eDFXtSg3zB8)g [@recursive\_si](https://x.com/recursive_si) is the latest neolab to burst on the scene with a $5B fundraise and one of the most impressive cofounder lists ever assembled to tackle open ended, self-improving AI for AI research. We dive into the Eureka Machine, Richard's 10 Spaces of Intelligence (so much left until AGI!), DecaNLP vs [@alecrad](https://x.com/alecrad) and why AI peer review is broken, and why this may just be the last invention that humanity has to do on our own. Timestamps 00:00:00 The Eureka Machine and Superintelligence 00:02:23 AI Optimism, Slow Takeoff, and Regulation 00:07:56 AI Safety, Reward Hacking, and Anthropic’s Constitution 00:11:49 Alignment, Personalization, and Open Source AI 00:15:46 Why Richard Started Recursive 00:20:03 Recursive Self-Improvement and the Founding Team 00:22:55 Are Today’s LLMs Enough? 00:29:03 DecaNLP, GPT, and the Rejected Idea Ahead of Its Time 00:34:38 Open-Endedness and Evolutionary AI 00:36:38 What Happens When AI Chooses Its Own Goals? 00:41:16 Superintelligence for Science 00:42:40 GPUs, Compute, and the Limits of AI Takeoff 00:45:07 Recursive’s Results: AI Beating Humans and Their Agents 00:49:14 Reward Engineering and Auto Research 00:53:12 The AI Economist and Simulating Entire Economies 00:58:07 LLM Simulations, Personas, and Mode Collapse 01:03:38 Recursive’s Roadmap, Agents, Search, and Finance 01:09:13 The Upper Bounds and Spaces of Intelligence 01:30:21 Goals, High Agency, and Advice for Builders

来源报道 · 1 篇 · 以下链接均前往原始媒体

← 返回精选动态 原文

更多内容