猿来如此
张赫这里没有高深的理论，只有和你一样关心科技和生活的普通人。每一期，我用最简单的语言聊聊新技术、行业故事，还有那些让人会心一笑的小发现。关注《猿来如此》，和我一起，慢慢变好。
| Publishes | Daily | Episodes | 73 | Founded | 3 years ago |
|---|---|---|---|---|---|
| Language |  ZH-CN | Number of Listeners | Category | Technology |
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本期播客介绍了 MiniMax-M2.1 模型在编程能力方面的重大突破，重点阐述了该模型如何超越传统的 SWE-Bench 评估标准。开发者通过构建覆盖十余种主流编程语言的大规模多语言训练系统，显著提升了模型在复杂企业级开发中的表现。除了修复漏洞，该模型在自动化测试生成、代码性能优化以及代码评审等多样化任务中也展现出卓越实力。为了确保在不同开发工具下的通用性，模型特别强化了长指令遵循和对各种智能体架构的适应能力。展望未来，研发团队计划通过强化学习规模化和构建编程世界模型，进一步优化开发者的交互体... more
本期播客汇总了 Hacker News 社区成员在 2025 年分享的各类副业项目及其盈利情况。文中展示了多元化的商业模式，涵盖了从在线传真服务和数据库客户端等实用工具，到线下美食俱乐部及手工定制唱片等创意产品。许多开发者分享了他们如何利用 AI 技术、SEO 优化或开源社区赞助来实现每月超过 500 美元的营收目标。除了成功的经验，讨论还涉及了获客挑战、定价策略以及平衡全职工作与个人项目之间的个人感悟。这组资料生动勾勒出当代独立开发者如何通过解决细分痛点，将技术热情转化为可持续的商业价值。
本期播客来自 OpenRouter 和 a16z 的实证研究，基于对该平台超过 100 万亿个代币的大型语言模型（LLM）交互数据进行分析。研究指出，自从 o1 等推理模型发布以来，LLM 的使用范式已发生重大转变，向着多步骤、复杂化的代理式推理工作流程演进，体现在工具调用和更长的序列长度上。在应用类别方面，编程已成为最主要的专业工作负载，而创意角色扮演则在开源模型的使用量中占据了最大份额。报告观察到一个结构性的多模型生态系统，开源模型生态正在迅速扩张并变得多元化，尤其在亚洲地区和中国开发者的推... more
本期播客概述了关于人工智能现状与未来发展方向的深刻对话。讨论的核心在于当前 大型语言模型 (LLM) 在评估中的优异表现与其对经济影响的滞后之间存在的费解脱节，并认为随着数据的限制，单纯依靠 规模化 (scaling) 的时代正走向终结。对话重点强调需要重新回归 研究时代 (age of research)，以解决模型在 泛化能力 (generalization) 和 样本效率 (sample efficiency) 方面的根本缺陷，这是目前 AI 与人类学习能力相比的不足之处。通过借鉴人类 情... more
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猿来如此 launched 3 years ago and published 73 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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