Y11
4小时前
有些公司可能正用更直接的方式快速盈利,而你却在第十次重构代码时,连一分钱的收入都还没有? 别再纠结于代码的完美了,先把产品推出去。 创业初期,我们总容易陷入“准备过度”的陷阱。 就像学游泳,与其反复研究动作要领,不如先跳进水里试试。代码重构和系统优化固然重要,但它们应该是为产品目标服务的工具,而不是拖延产品上线的借口。 想想那些成功的企业,没有谁一开始就做到尽善尽美。 他们都是在一次次“试错-调整-迭代”中找到正确的方向。第一个版本可能有很多缺陷,但它能帮你验证想法,收集反馈,这才是最宝贵的资产。 记住,产品的价值不在于它有多完美,而在于它能否为用户解决问题。与其在0到1的阶段追求100分,不如先拿到一个60分的版本,然后用用户的反馈把它变成80分、90分。 毕竟,没有用户验证的完美,只是自嗨。 行动永远比空想更有力量。现在就放下对“完美”的执念,把你的产品推出去。 哪怕只是一个最小可行产品,也能让你在真实的市场中找到前进的方向。因为只有走出去,你才能知道下一步该往哪走。 别让“准备”变成“停滞”。 代码会不断优化,功能会持续迭代,但只有产品真正触达用户,你的努力才有意义。现在,就去“造船”吧,哪怕它一开始只是一艘小舢板,也能带你驶向更远的地方。
Y11
4小时前
Y11
4小时前
独立创业这条路,似乎有点跑偏了。 现在太多人陷入了一个怪圈:无休止地堆砌功能代码,空谈一个模糊的未来上线日期,耗费时间去迎合单一潜在客户,结果却在原地打转,最后还抱怨说,“看Pieter Levels多轻松啊,他就是有‘流量’”。 我把话说简单点:你的目标,就是做到月入1000元。 这不是“为了上线而上线”,也不是模棱两可的“验证市场”。 目标就是实实在在的月入1000美元。 你做的每一件事,都应该围绕这个目标展开。 每月收费至少50美元,在网站上放上微信支付链接,然后(最关键的一步),让人们对你的产品产生真正的兴趣。 如果你自己都不对产品感到兴奋,那你肯定吸引不到客户。 靠AI写几篇推广文,或者在公开频道每周发点产品更新,这些都成不了月入1000元的“捷径”。 真正的问题在于:你的产品有什么能让人眼前一亮、记住并为之兴奋的东西? 从0到1000元的月收入,需要“突破临界点”的勇气和努力,这很难。 我给点实在建议: 真心热爱你的产品。如果做不到,就换个方向。 用你独特的经验写别人写不了的内容,别依赖AI。你的经历、你的思考,这才是最有价值的。 在网站上加点免费工具,给用户一个分享的理由。 想个让人记住的“小噱头”。比如有人记得“Moto Meter”,谁在乎它是不是有点“傻”,关键是让人印象深刻。 别再纠结“上线”、“加功能”或者“找到一个客户”这些表面目标了。 真正的目标,是月入1000元。然后是1万元,5万元,以此类推。一步一步来,目标清晰,路才能走得稳。
Y11
5小时前
在科技行业,谷歌始终展现出其在技术领域的深厚积累与创新能力。 无论是备受关注的Gemini系列大模型,还是Gemma开源模型,以及支撑其技术落地的JAX、Keras和TPU生态系统,都体现了这家公司在人工智能领域持续深耕的战略定力。都值得大家学习看一看这几个框架和基础知识。 从技术角度看,谷歌的优势在于对底层架构的深刻理解和长期投入。 TPU作为专为机器学习优化的芯片,从第一代到最新的第五代,不断提升算力与能效比,为大模型训练提供了强大的硬件支撑。 而JAX和Keras则构成了完整的软件生态,前者在高性能计算与自动微分领域表现突出,后者作为深度学习框架,降低了模型开发的门槛,让更多开发者能够参与到AI创新中。 这种软硬结合的技术体系,正是谷歌能够持续推出高质量模型的核心竞争力。 在开源领域,Gemma系列模型的推出展现了谷歌开放技术的决心。 通过提供不同规模的开源模型,谷歌不仅降低了AI技术的使用门槛,也为整个行业的创新提供了基础。 Gemini作为面向多模态的大模型,在语言、图像、音频等领域的融合能力,代表了当前AI技术发展的前沿方向。 谷歌通过持续迭代模型能力,不断拓展AI的应用边界,这种技术驱动的发展模式,为行业树立了标杆。 当然,技术只是创新的基础,真正的价值在于如何解决实际问题。 谷歌在推进技术落地的过程中,始终以用户需求为导向,从搜索、云服务到智能助手,不断将技术转化为实际产品。 这种技术与产品的结合能力,让谷歌能够在激烈的市场竞争中保持领先地位。 对于科技行业的从业者而言,谷歌的发展路径提供了重要启示:技术创新需要长期投入,需要构建完整的生态体系,更需要开放合作的心态。 无论是大模型的研发,还是底层技术的积累,都需要沉下心来,一步一个脚印地突破。 谷歌用多年的实践证明,唯有以技术为根,以创新为翼,才能在快速变化的科技浪潮中屹立不倒。未来,随着AI技术的不断发展,谷歌在技术研发上的积累,必将带来更多改变世界的创新成果。
sitin
5小时前
Google 出了个 Genkit Extension,给 Gemini CLI 装了“Genkit 大脑”。 装上以后,命令行不止会跑命令,它能读懂你的 Genkit 项目结构、最佳实践、MCP 工具,在终端里帮你写、跑、调、优一整套。 它到底改变了啥?三句话说完: 1.懂行:内置 Genkit 知识 + MCP 工具,明白“flow、trace、SDK 使用规范”。 2.省事:在终端里直接生成代码、跑 flow、看 trace、定位问题,少翻文档。 3.可扩:和 Gemini CLI 的扩展体系打通,能连 Figma、Postman、Stripe、Firebase 这些常用工具,形成你自己的“AI 命令行工作台”。 装完能干啥? 列出并执行 flow:list_flows 看清项目里有哪些 flow,run_flow 直接在终端跑; 查问题看链路:get_trace 把 OpenTelemetry 的执行链路过一遍,哪里慢、哪步错,一眼看到底。 这不是“拍脑袋生成代码”,而是按 Genkit 规范来,尽量给出可直接落地的模板和修复建议。 和我们日常开发怎么配合? 你用 Genkit 写多模型/多模态/Tool 调用那套,Developer UI 做可视化; CLI 侧装上这个扩展,补齐“终端里的智能助理”:问它“帮我写个 flow……”,它给出贴标准的代码;跑不顺,trace 一键看;需要文档,命令行直接调出对应段落。 给团队的三步上手法: 1.把 CLI 跑起来:装 Gemini CLI → 安装 Genkit Extension → 在一个现有 Genkit 项目里试 list_flows / run_flow / get_trace。 2.定一条“从写到上”闭环:让新人把“新增一个 flow → 本地跑通 → 用 trace 校验 → 开 PR”的动作,全在终端里完成一次,减少来回切页面。 3.接入常用工具扩展:把设计(Figma)、接口(Postman/Stripe)、部署(Firebase/GCP)相关扩展串进来,形成你团队自己的“命令行工作流”。 一句话总结: 以前我们要翻文档 + 手配 SDK + 人肉看日志;现在把这些活塞给 CLI 的“Genkit 大脑”,速度更快、调试更顺、质量更稳,你把时间留给业务和创意就好
Byron Wan
7小时前
On a June night in 2024, Nvidia CEO Jensen Huang held court with several of his company’s major Asian customers at a bar in Taipei. Next to him was Huang Xiaole (黄小乐) aka Alice Huang, an executive of Megaspeed, a shady Singapore-based data center company. Nvidia’s compliance team has looked into Megaspeed and determined it’s “wholly owned and operated by a company based and headquartered outside China, with no China shareholder.” Megaspeed was created in 2023 when 🇨🇳 7Road, a gaming company with ties to 🇨🇳 state-backed investors, split off its overseas operation in Singapore and renamed it Megaspeed, which in early 2024 set up Speedmatrix, a subsidiary in Malaysia that quickly snapped up ~$2B worth of Nvidia’s most advanced chips. Most of those chips came from Aivres, the US subsidiary of 🇨🇳 Inspur, a major tech company added to the 🇺🇸 Entity List in 2023 for supporting 🇨🇳 military 👉🏻 Nvidia is barred from selling its technology to Inspur without a special license. But since Aivres is based in California and records sales as a US company, it can buy Nvidia chips freely. Megaspeed has funneled those chips to data centers in Malaysia and Indonesia that appear to remotely serve customers in China. That is not necessarily illegal, but it can be found unlawful if it is done on behalf of a 🇨🇳 company. US officials have also been scrutinizing whether Megaspeed diverted some of those chips on to China, in violation of US law. Megaspeed is also facing scrutiny from Singaporean police. Megaspeed listed Alice Huang as its managing director for its first 8 months, and its current director James Tan is from Singapore but is based in Shanghai. It’s not clear when Jensen Huang and Alice Huang, who are not related, first met. She was mingling with a crowd of tech executives just after midnight at the Taipei bar in early June 2024 when she offered to ask Jensen Huang to join them. “I bet you guys I can get Jensen here,” she said, and shortly afterwards Jensen Huang arrived in his trademark black leather jacket and drank a whiskey shot with the group. Jensen Huang and Alice Huang were photographed together again in May, exiting a restaurant in Taipei with an Nvidia aide after a business dinner with other AI suppliers. Alice Huang spent much of her career in China, including working as a TV reporter for 🇨🇳 state media and as a private banker. Huang left Megaspeed in recent months. It’s unclear when and why she left and what she’s doing now. Both she and 🇨🇳 7Road, the Chinese company that Megaspeed split off from, have close ties to a web of wealthy investors and tech companies with data center projects in China. The owners of 7Road include 🇨🇳 central government and several local governments. Before joining Megaspeed, Ms. Huang was executive director for a Shanghai-based fund that had invested in 7Road and had ties to state-backed firms. Reporters looking into Megaspeed’s opaque operation have tracked business listings that led to a Malaysian data center and shopping mall, a near-empty office in Singapore and a dilapidated storefront outside Kuala Lumpur. It’s not clear where Megaspeed’s billions of dollars came from. But a few weeks after the gathering in Taipei last year, Megaspeed began receiving a steady supply of multimillion dollar shipments of some of Nvidia’s most advanced chips. Over the next 3 months, Megaspeed bought a billion $ of Nvidia technology. Within the next 9 months, it secured roughly a billion $ more. The bulk of those advanced Nvidia chips were purchased from 🇨🇳 Inspur’s US subsidiary Aivres. The shipments went to Megaspeed’s Malaysian subsidiary Speedmatrix. The registered address for Speedmatrix on the shipping records led to a dilapidated storefront outside Kuala Lumpur, where the sign out front advertised a construction company. No one was inside when a reporter visited the address in late Sep. Employees at the law firm next door said they rarely saw people in the office. 1/2