Ben

Every time I see a tweet saying “I can vibe code this in a weekend” - I think of the slack notification system.. It takes time, persistence and effort to get the details right. Sure, a lot of simple workflows will get vibe coded away. And maybe you can put this in Claude Code and get the code right in one shot. But quality, depth and great systems will still have value and take time. You can’t vibe code lessons. Now and forever.

@elonmusk @LeahLibresco Please make one available soon, really need a bigger size car and can’t live without FSD, so no other options now

@LeahLibresco Something way cooler than a minivan is coming

MAKE A MINIVAN, ELON.

Anthropic和Claude最近的成功，是不是在抄彼得·蒂尔十年前的作业？ 他的理论很简单。 想搞垄断，别总盯着大市场。 先找个小池塘。 一个没人注意的缝隙市场。 比如，编码。 迅速占领，成为池塘里最大的鱼。 然后，围绕这个小市场建立起声望和铁粉。 听起来是不是反直觉？ 但这是Facebook和PayPal走过的路。 Facebook最开始的市场是什么？ 哈佛大学的一万名学生。 十天内拿下60%的份额。 PayPal的起点呢？ eBay上的两万个超级卖家。 三个月拿下30%的市场。 这套打法背后，是对主流商业思维的颠覆。 大部分创业者犯的致命错误是什么？ 一上来就说自己要颠覆万亿级市场。 当年的清洁能源公司就是这么死的。 PPT第一页，市场规模数千亿，甚至数万亿。 结果呢？ 你成了汪洋里的一条小鱼。 不仅要跟几十家太阳能公司竞争。 还要跟风能、煤炭、甚至突然冒出来的页岩气竞争。 最后悄无声息地消失。 这套“小市场垄断”理论，今天还适用吗？ 尤其是在AI这种巨头林立的领域。 Anthropic靠“编码”这个小切口，真的能复制Paypal和Facebook的路径，最终挑战OpenAI和谷歌吗？ 还是说，这只是硅谷精英们讲给资本听的又一个故事？ 当一个市场被清晰定义为“小”的时候，它是不是已经被更大的捕食者盯上了？

Rivian的AI day 我一看到三种传感器端到端就直接关掉了

I took delivery of a beautiful new shiny HW4 Tesla Model X today, so I immediately took it out for an FSD test drive, a bit like I used to do almost daily for 5 years. Basically... I'm amazed - it drives really, really well, smooth, confident, noticeably better than what I'm used to on HW3 (my previous car) and eons ahead of the version I remember driving up highway 280 on my first day at Tesla ~9 years ago, where I had to intervene every time the road mildly curved or sloped. (note this is v13, my car hasn't been offered the latest v14 yet) On the highway, I felt like a passenger in some super high tech Maglev train pod - the car is locked in the center of the lane while I'm looking out from Model X's higher vantage point and its panoramic front window, listening to the (incredible) sound system, or chatting with Grok. On city streets, the car casually handled a number of tricky scenarios that I remember losing sleep over just a few years ago. It negotiated incoming cars in tight lanes, it gracefully went around construction and temporarily in-lane stationary cars, it correctly timed tricky left turns with incoming traffic from both sides, it gracefully gave way to the car that went out of order in the 4-way stop sign, it found a way to squeeze into a bumper to bumper traffic to make its turn, it overtook the bus that was loading passengers but still stopped for the stop sign that was blocked by the bus, and at the end of the route it circled around a parking lot, found a spot and... parked. Basically a flawless drive. For context, I'm used to going out for a brief test drive around the neighborhood to return with 20 clips of things that could be improved. It's new for me to do just that and exactly like I used to, but come back with nothing. Perfect drive, no notes. I expect there's still more work for the team in the long march of 9s, but it's just so cool to see that we're beyond finding issues on any individual ~1 hour drive around the neighborhood, you actually have to go to the fleet and mine them. Back then, I processed the incredible promise of vehicle autonomy at scale (in the fully scaleable, vision only, end-to-end Tesla way) only intellectually, but now it is possible to feel it intuitively too if you just go out for a drive. Wait, of course surround video stream at 60Hz processed by a fully dedicated "driving brain" neural net will work, and it will be so much better and safer than a human driver. Did anyone else think otherwise? I also watched @aelluswamy 's new ICCV25 talk last week (x.com/aelluswamy/sta…) that hints at some of the recent under the hood technical components driving this progress. Sensor streams (videos, maps, kinematics, audio, ...) over long contexts (e.g. ~30 seconds) go into a big neural net, steering/acceleration comes out, optionally with visualization auxiliary data. This is the dream of the complete Software 1.0 -> Software 2.0 re-write that scales fully with data streaming from millions of cars in the fleet and the compute capacity of your chip, not some engineer's clever new DoubleParkedCarHandler C++ abstraction with undefined test-time characteristics of memory and runtime. There's a lot more hints in the video on where things are going with the emerging "robotics+AI at scale stack". World reconstructors, world simulators "dreaming" dynamics, RL, all of these components general, foundational, neural net based, how the car is really just one kind of robot... are people getting this yet? Huge congrats to the team - you're building magic objects of the future, you rock! And I love my car <3.

@IamRamenPanda 最难的三点 ai自主学习可以应对不同场景 手部灵活度 还有量产能力 请问哪一个不止国内任何公司有特斯拉这个能力 强烈不认同你的观点

不黑不吹，擎天柱这简单的动作，控制身体协调的小脑，对比宇树真的差的老远了 美国机器人现在就是拼不过中国的啊，宇树、小鹏的机器人就做到了一件事，把马斯克画大饼里面的想象空间给打没了 中国竞品是个照妖镜，能照出美股同行里面“信仰”的溢价到底有多高

So true.

@Valvrave1992 @lidangzzz 这些在他学术成就面前根本不重要

@lidangzzz 杨老50年代判断不能回国;70年代判断能回国，但是不能长住;00年代判断可以回国长住，但是必须保留美籍;最后在15年这个全球化黄金时代的最后一年，才选择回国并改国籍。 对时局的判断和精致利己的程度称得上伟大

逆天文科生

Yes

@amandevx sora 2

Looking for a Sora 2 invite code? I have codes available to share! If you’re interested, please: 1. Like this post 2. Follow me (so I can send you a DM) 3. Comment “SORA 2” below

现在英伟达和甲骨文正在玩一种“空手套白狼”的AI圈钱游戏，堪称AI印钞机 第一步：英伟达把天价GPU卖给甲骨文 → 赚一笔硬件钱 第二步：甲骨文用GPU搭建AI云 → 向OpenAI等公司出租算力 → 再赚一笔租金 第三步：英伟达反手租回部分算力 → 硬件+云服务双重收入躺赢！ 这种模式让：英伟达不用自建数据中心，却能赚两份钱 甲骨文把买GPU的烧钱变成收租，OpenAI不用砸几十亿买GPU，随用随租，现在，微软、谷歌都在学这招 那这样的玩法会直接引爆GPU租赁市场，这不那几个做算力出租的股票都涨的很好。

出卖自己的时间，就是把本来可以自由创作，复合成长，不断觉醒，奔赴未来的时间，置换成为原地踏步，缺乏灵魂，和他人的现状纠缠的时间。 成长的过程，就是把要出卖的时间，压缩到接近于零的过程。

人脉是你对多少人有用，而不是有多少人喜欢你。 让自己有用的一个方法，是思考并解决困扰自己的问题。因为如果你有这样的问题，肯定会有其他人有类似的问题。而且解决自己的问题时，你很清楚痛点在哪里，不会一厢情愿自欺欺人，这样你的解决方法别人才会真心觉得有用。 而通过线上写作并大规模传播这些思考，可以让你有更大规模的人脉。 如果你研究的问题的抽象结构通用常见，并可以把解决方法举一反三，用于别的行业与场景，那么你就会有跨越时空的，(睡觉时也能) 持续复合增长的，大规模的人脉。

仔细对比这两张图，你会发现一个令人毛骨悚然的细节，GPT-4o 将原图桌上的书本换成了 Peace Sattlement，这说明他知道这张图背后的故事 GPT-4o 的绘图能力是模型原生的，而不是像以前那样简单去调用 Dall-E，而是经过思维链思考后结合自己的知识去反馈你的指令 你可能不知道这意味着什么，那我来说句暴论： 当下资本热捧的所有 AI 衍生工具，在多模态 AI 的面前可能都会价值归零，包括不限于各种 RAG 工具、AI IDE、AI Workflow 工具、各种 Agent、各种场景化衍生品 想想 23 年我花了一晚上搞个 lora 才能实现图片换脸，而现在在 GPT 上你只需要不到 20 个汉字就能实现 一个盲人 + 一个聋子永远比不过一个正常的人类，多模态能力的共振对于 AI 能力的提升也并不是 1+1=2 的线性增长。在发展更加多维 AI 这个努力目标面前，所有的试图曲线救国或者投机取巧的努力都将白费 此刻我脑袋里只有《三体》中托马斯·维德的那句话 前进！前进！不择手段地前进！

It's 2025 and most content is still written for humans instead of LLMs. 99.9% of attention is about to be LLM attention, not human attention. E.g. 99% of libraries still have docs that basically render to some pretty .html static pages assuming a human will click through them. In 2025 the docs should be a single your_project.md text file that is intended to go into the context window of an LLM. Repeat for everything.

@onenewbite 其实很多人，每次见面都可能是最后一次了

实用却不烧脑，值得周末静下来慢慢看 How I use LLMs youtu.be/EWvNQjAaOHw?si… via @YouTube

Agency > Intelligence I had this intuitively wrong for decades, I think due to a pervasive cultural veneration of intelligence, various entertainment/media, obsession with IQ etc. Agency is significantly more powerful and significantly more scarce. Are you hiring for agency? Are we educating for agency? Are you acting as if you had 10X agency? Grok explanation is ~close: “Agency, as a personality trait, refers to an individual's capacity to take initiative, make decisions, and exert control over their actions and environment. It’s about being proactive rather than reactive—someone with high agency doesn’t just let life happen to them; they shape it. Think of it as a blend of self-efficacy, determination, and a sense of ownership over one’s path. People with strong agency tend to set goals and pursue them with confidence, even in the face of obstacles. They’re the type to say, “I’ll figure it out,” and then actually do it. On the flip side, someone low in agency might feel more like a passenger in their own life, waiting for external forces—like luck, other people, or circumstances—to dictate what happens next. It’s not quite the same as assertiveness or ambition, though it can overlap. Agency is quieter, more internal—it’s the belief that you *can* act, paired with the will to follow through. Psychologists often tie it to concepts like locus of control: high-agency folks lean toward an internal locus, feeling they steer their fate, while low-agency folks might lean external, seeing life as something that happens *to* them.”