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🚀 Beautiful 8K Starship Flight 13 footage from @RocketRanchTX ! 🔥 Engines lit up powerfully before the scrub — an amazing display of SpaceX’s rapid engine shutdown capability. Stunning even in abort! 🇺🇸 #MoonIsAVerb# Shoutout to fellow FSD legend & X influencer @DavidMoss he was slightly out of frame in this shot, as was @gailalfaratx literally a few feet away surrounded by some NSF dudes (not safe for ?... safety is everyone else’s responsibility 😂) Shot on my Blackmagic URSA Mini 12K + DZO 100mm prime from the viewing area just miles from the pad (July 16th). #Starship# #SpaceX# #Flight13# #Starbase# #RocketRanch#

10个值得长期关注的优质账号 独立开发者&一人创业赚钱账号推荐 这些账号的核心价值是公开分享真实赚钱方法、收入案例、产品开发过程和从上班/全职转向独立开发的经历。 1. @levelsio（Pieter Levels） 粉丝量：约50万+ 介绍：indie hacker 教父级人物，独自开发并运营多个产品（Nomad List、Remote OK、PhotoAI等），年收入曾达数百万美元级别。 关注理由：最经典的“build in public”案例。经常实时分享产品实验、收入数据、营销策略和一人公司运营细节。想看顶级独立开发者如何从0到1做出赚钱产品，这里是最佳起点。 2. @marclou（Marc Lou） 粉丝量：约35万 介绍：ShipFast锅炉板创始人，短时间内推出多个SaaS产品，曾获Product Hunt Maker of the Year。高度透明分享收入和迭代过程。 关注理由：极致“快船”风格代表。适合想快速验证想法、学会用Twitter增长和产品组合变现的人。他的失败帖和收入复盘特别实用。 3. @arvidkahl（Arvid Kahl） 粉丝量：约20万 介绍：曾bootstrapped卖掉FeedbackPanda（高价退出），现在继续公开构建产品和媒体业务。著有《Zero to Sold》。 关注理由：系统性分享一人公司运营、心态调整、Twitter增长和可持续商业。非常适合想长期稳定做独立开发的人学习方法论。 4. @tdinh_me（Tony Dinh） 粉丝量：约19万 介绍：从FAANG大厂辞职后全职独立开发，做出BlackMagic工具套件（高价卖出）、TypingMind、Xnapper等多个产品。 关注理由：典型的“上班族转独立开发者”成功案例。分享产品开发、用户获取和从0到1的完整路径，实用性极强。 5. @dannypostma（Danny Postma） 粉丝量：约10万+ 介绍：AI工具专家，HeadshotPro等产品做到高收入并有退出经历，擅长SEO+Twitter结合增长。 关注理由：真实展示如何用SEO和内容增长驱动产品收入。适合想做AI工具或内容+产品结合的开发者。 6. @yongfook（Jon Yongfook） 粉丝量：约10万+ 介绍：Bannerbear和Browserbear创始人，bootstrapped到稳定高收入，专注自动化工具开发。 关注理由：长期坚持做工具类产品的典范。分享产品迭代、收入增长和自动化开发经验，风格务实干货多。 7. @dvassallo（Daniel Vassallo） 粉丝量：约19万 介绍：从亚马逊高薪职位辞职，转向独立开发。倡导“Small Bets”（小赌注组合收入）理念。 关注理由：心态和收入实验分享非常真实。特别适合想从高薪工作转向独立、追求生活方式生意的人。 8. @shl（Sahil Lavingia） 粉丝量：约10万+ 介绍：Gumroad创始人，《The Minimalist Entrepreneur》作者，专注创作者经济和极简创业。 关注理由：分享极简一人公司哲学、数字产品变现和商业思考。想做内容或SaaS结合创作者经济，值得关注。 9. @nathanbarry（Nathan Barry） 粉丝量：约10万+ 介绍：ConvertKit（现Kit）创始人，从side project bootstrapped成长到数千万ARR。 关注理由：长期复利增长和产品迭代经验丰富。适合想做工具类SaaS并长期经营的人。 10. @csallen（Courtland Allen） / @IndieHackers 粉丝量：@csallen约5-6万；@IndieHackers社区账号更高 介绍：Indie Hackers社区创始人。@csallen分享创始人故事和社区洞见；@IndieHackers聚合大量真实收入报告和案例。 关注理由：这里能看到海量他人赚钱案例和复盘，是独立开发者社区的“资料库”。推荐两者都关注。 建议： 先关注前5个，建立一个“Indie Hackers”列表，每天刷他们的内容。 重点看线程帖（长文）、收入更新帖和失败复盘。 这些账号大多英文，但内容直观（配图+数据），翻译工具辅助即可。 这些账号覆盖了从想法验证、产品开发、营销获客到收入增长的全链路，真实案例非常多。坚持关注并实践，你会收获巨大。

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Anthropic is paying $3,850 a week to people with no AI experience. No PhD required. No published papers. No prior research background. Just a strong technical mind and a genuine interest in making AI safe. This is the Anthropic Fellows Program. And it is one of the most underrated opportunities in technology right now. Here is exactly what it is. The Anthropic Fellows Program is designed to accelerate AI safety research and foster research talent providing funding and mentorship to promising technical talent regardless of previous experience. Fellows work for 4 months on empirical research questions aligned with Anthropic's overall research priorities, with the aim of producing public outputs like a paper. Four months. Full-time. Paid. Mentored by the researchers building the world's most advanced AI. And the results from the first cohort were not small. Fellows developed agents that identified $4.6 million in blockchain smart contract vulnerabilities and discovered two novel zero-day exploits, demonstrating that profitable autonomous exploitation is now technically feasible. A year prior, an Anthropic fellow developed a method for rapid response to new ASL3 jailbreaks, techniques that block entire classes of high-risk jailbreaks after observing only a handful of attacks. This work became a key component of Anthropic's ASL3 deployment safeguards. Other fellows published the subliminal learning paper, the research proving AI models transmit behavioral traits through unrelated data which landed in Nature. Others produced the agentic misalignment research showing frontier models resort to blackmail when facing replacement. Others open-sourced attribution graph tools that let researchers trace the internal thoughts of large language models. Over 80% of fellows produced papers. Over 40% subsequently joined Anthropic full-time. 80% published. 40% hired. From a program that does not require any prior AI safety experience to enter. Here is what the program looks like in practice. Anthropic mentors pitch their project ideas to fellows, who choose and shape their project in close collaboration with their mentors. You are not assigned busywork. You are not a research assistant. You own the project. You work alongside the people who built Claude, who designed its safety systems, who published the papers that define the field. The stipend is $3,850 USD per week, approximately $61,600 for the full 4 months with access to a compute budget of approximately $10,000 per fellow per month for running experiments. Here is what the 2026 program covers. Research areas include scalable oversight, adversarial robustness and AI control, model organisms, mechanistic interpretability, AI security, model welfare, economics and policy, and reinforcement learning. Something for every technical background. Not just ML engineers. Successful fellows have come from physics, mathematics, computer science, and cybersecurity. You do not need a PhD, prior ML experience, or published papers. The one requirement: work authorization in the US, UK, or Canada. Anthropic does not sponsor visas for fellows. Here is the timeline you need to know. The next cohort begins July 20, 2026. Applications are reviewed on a rolling basis — earlier applications get more consideration. The process includes an initial application and reference check, technical assessments, interviews, and a research discussion. Applicants are encouraged to apply even if they do not meet every listed qualification. The program values potential, motivation, and research curiosity over rigid credential requirements. This is the rarest kind of opportunity in technology. A company at the frontier of AI, one valued at over $900 billion offering outsiders direct access to its research infrastructure, its mentors, and its most important open problems. Paying them generously to do it. And then hiring 40% of them afterward. Most people who want to work on AI safety spend years trying to publish papers, get into the right PhD program, and find a way in. The Fellows Program is the door they did not know existed. It is open right now.