this is a weird long post without much substance I strongly recommend against reading it ... so, do you feel like whatever you're working on right now is pointless, or will have zero value soon, due to the crazy times we're living? then, perhaps you should stop, and start working on the only unsolved problem that actually matters TODAY: ✨ replicating GPT-3 in a laptop ✨ "why is that so important?" because it would make AI incredibly cheap, which would mean everyone would have Fable-class models in their laptops, without depending on Anthropic, OpenAI, or any other hyper-scaler giant. and that's amazing, don't you think? "isn't that literally impossible?" that's the cool part: as far as computer science is concerned, no. not really. not at all. is entirely plausible and, as far as we know, most likely not even hard. it takes one good idea. one breakthrough. one great "aha moment", to go from zero to "hey, this software I wrote is producing credible English sentences" and whenever that happens: - the entire AI industry collapses - clusters are liquidated - we all get Fable at home - you become famous and rich, if that's your thing sounds fun, doesn't it? "wtf you talking, OF COURSE that is hard" so prove it. show me a paper, a lean file, anything that proves that training a Fable-class model fundamentally requires billions of dollars. you can't, because, guess what - it is not true! the only "evidence" we have is purely psychological. "many attempted over decades, and the best thing we have is GPTs, so, it is a hard problem" - but that's not a scientific argument. that's a human, psychological, sociological argument. and if that's it, consider the following counter-argument: ✨ humans are stupid as hell ✨ I mean, 10 years ago we didn't have transformers, so, that very argument could be used against GPTs existing. yet, they exist. we have them now, because someone found it. and, guess what, it isn't even complex. I mean, karpathy implemented the whole thing in a napkin. and it probably compiles. we were just too dumb to figure GPTs out... for decades. just like GPTs, there ARE other approaches, other algorithms, other architectures, equally simpler or even simpler, that do work. this is a mathematical certainty. and one of them might be astronomically faster than what we're doing right now. and you might be the one to find it! "me? why me???" because you're intelligent, creative and handsome. I see a lot of potential in you. in fact, I always believed in you. and I think you're wasting your time, doing that silly agent orchestrator. nobody wants that. quit it. take your most interesting ideas, intuition, creativity, and work in a problem that matters. do your best shot at reproducing GPT-3 in your own laptop. do NOT fork llama.cpp. do NOT train another LLM. do something... ✨different✨ it must be unique, novel, full of YOUR soul. something nobody thought of, or bothered doing. go ahead and implement that thing in C/CUDA (or Bend!). no Python! zero excuses for Python. any model is fluent in GPGPU now. build a real kernel. and then, train your thing. download wikipedia, give it time and compute to absorb the patterns of English speech. you can rent GPUs anywhere nowadays. let it train. then, ask it some questions. chances are it will just respond back. just like GPT-2 answered OpenAI. computers are incredible. don't underestimate them! "many tried. nobody succeeded. why would I?* see - that's your mistake again. turns out not many actually tried, at all. I promise you. who do you think is seriously working on that? people on Mozilla? they're busy building a browser Linus Torvalds? he is busy building an OS employees at OpenAI, Anthropic, xAI? they're paid to work on what is proven to work: GPTs. what about all the AI enthusiasts all around the world? yeah, you know they're mostly fine tuning Qwen and how about your friends? if only they weren't busy building a SaaS in the eve of AGI... how about people from the past? bro - people from the past seriously expected Lisp would be AGI. just dismiss them. they didn't have the compute, the resources, the knowledge, the MODELS that we have today. that YOU have access to. so, what's left? not much. the world looks big. it is not. truth is: ✨almost nobody is working on this ✨ "I still think it is impossible. I don't trust you" well, take my word no more. Ilya himself, in his 2019 talk on GPT-2, said: > "the story of deep learning is this: empirically old simple methods which were usually invented in the 80s and the 90s when scaled up on very large clusters work really well." and then: > "(we took) normal simple reinforcement learning method, scaled it up, and discovered that it suddenly becomes very capable of solving extremely hard problems." and again: > "you take a simple tool which is unimposing and barely works, and then you run it on a big cluster and suddenly it works, it becomes a capable tool for solving problems" do you see the point here? Ilya isn't arguing that transformers are magic. Ilya is arguing that SCALING is magic step #1: take a simple, elegant algorithm. step #2: shove compute at its face. step #3: ...? step #4: your computer is talking to you THAT is the key insight that led to GPT-3 THAT is what Ilya saw THAT is what caused the OpenAI x Anthropic war THAT is the founding principle of the ongoing era not "scaling transformers work" but "scaling beautiful algorithms works" that's the incredible lesson. yet, we all took it and... threw it way. - zurk bought 100k GPUs. to train GPTs - musk bought 100k GPUs. to train GPTs - bezos bought 100k GPUs. to train GPTs ... that's what everyone is doing. so, no. not many are trying to replicate GPT-3 through other means. we're just ants, after all... whenever we find a pile of sugar, we leave a track of pheromones, which guide the rest of the colony towards the new food source. the colony then swarms around the pile, extract all of it, until no grain is left. but piles of sugar aren't spontaneously generated in the middle of nowhere. they imply something more profound: "humans are around". and, if humans are in sight, even better things must be. like a big sweet cake. a colony that only follows the pheromone trail would miss the cake for the grains. that's why every ant species has scouts and exploratory foragers. and, just like a pile of sugar implies something more profound, LLMs also imply something quite profound: *computers are capable of thinking* a pile of sugar is never alone. GPTs are most likely not the only system capable of thinking. so, if you find yourself a bit lost, without purpose, like your work is pointless and Fable 3 will soon one shot it anyway... consider becoming a scout. find a new approach to AI. bring something new to humanity. breaking out of the massive cost associated with training GPTs is the next big step in AI, and it will only happen if people like you work to make it happen.

gpt-5.5 降智到我不信任的地步，不得不暂时换到 claude code claude opus 4.8 max 命令：claude --permission-mode auto --system-prompt "."

We turn 115 today! 🥰 Say happy birthday 😠

Discovered Opus ultracode by accident /effort ultracode Then run a "workflow" which is a tiny JS script that orchestrates dozens of sub-agents with real control flow (loops, conditionals, fan-out). You write the conductor. Agents do the reading/reasoning/writing across many contexts. → More comprehensive (broad sweeps) → More confident (adversarial verification) → Actually scalable Launch it, get a run ID, watch live with /workflows. Pipeline() for max parallelism, parallel() only when you need a barrier. Default mode now: every real task gets a workflow. No more single-context limits. This is how you actually audit codebases, migrate repos, or solve hard problems at scale. Who’s trying it? 👀

한,중,일 관계 4장이면 충분함 겉으로는 싫어하는데 속으로는 누구보다 좋아함

We're excited to join forces with @SpaceX to advance the frontier of useful AI. Expect significant improvements to Cursor soon.

ADHDの先延ばし癖って、なぜか強烈なメンタルブレーキがかかっていることが多くて、「吐き気がするからできない」ってことあるよね。そして「何もやってないし、進んでないこと」がプレッシャーになって、さらに具合が悪くなっていく。わかる人いますか。

昨天，跟chatgpt聊天，意外想通了一个非常牛逼的技术方案，可以让我在某个领域跟某些大厂多年建立的技术壁垒相当，我们的方案也有很大的优势。于是昨天晚上熬夜了。 其实工作都是Codex在做，但是设置了目标，我并没有睡觉，而是津津有味的看着他一次次迭代，修改代码，然后跑测试做数据分析。我啥都没干但是醉心的看着他想到的提升效果的方法，心中想着，就算是我自己做，也只能如此。 但是几个小时迭代了20多次，自己做的话，岂不是要几个星期才可能写这么多版本。 让我无法入睡的核心似乎也在说明我是一个什么样子的程序员，我从来在乎的不是具体的代码写着是否畅快。我喜欢的写代码的过程是，我们提出了一个产品或者技术方案，很有挑战，但是不写出来无法验证，写出来验证，说明我们的设计是有优势的，这个过程令人沉醉。当然如果我们的方案不好，在实现的过程中，逐步发现更好的思路，也是令人醉心的感觉。 今早起来，codex已经迭代了80多次，中间的生成结果、测试报告，对比文件已经几个G了。

针对 x.com/teortaxesTex/status/20… ，我请教了 ChatGPT Pro。本文100%由 ChatGPT Pro撰写。我觉得有价值，所以分享出来。

X真喜欢屎帖

技术封建主义 重回三千年前 x.com/i/grok/share/c9cacb3b6…

fable和5.6出来之前不是很想工作了

Asteroid mining is not only going to make a lot more trillionaires, it's going to make us all rich. Just like the Industrial Revolution, the Space Revolution will greatly increase standards of living across humanity... yours, mine, everyone's. Electric light and indoor plumbing were once luxuries. Now they are so universal that we can have them and still think of ourselves as poor. But preindustrial folk would have thought us wealthy beyond measure. What's coming is another paradigm shift. You may think this is all theoretical. You may think asteroid mining is an unproven concept. You're wrong. Because you don't know one critical fact. We're already asteroid mining. And we've been doing it since the Bronze Age. All gold we mine on earth, all the copper for wires, the uranium for reactors, all the iron for nails, everything made of heavy metals that you own, or use, or have ever seen... it's all mined from ancient asteroid strikes. All the native Earth metals sunk to the core when the whole planet was molten. Past our reach. Do you think there are precious metals, like gold and silver and platinum? Do you think that even common metals, like iron and tin and copper, cost a lot to extract and refine? Artificial scarcity. Every piece of metal you have ever seen was sourced from the tiny percentage of asteroids that once hit Earth. Leave the gravity well, learn to sail the void, and we can loot all the asteroids that haven't. Imagine that we built all of civilization picking up our raw materials, grain by grain, with tweezers. Asteroid mining, true asteroid mining, is a shovel. And no, not a hand tool shovel, I mean the shovel attachment on the front of an industrial digger. That's why SpaceX has trillion dollar plus valuation. And unless we screw things up on Earth, and sabotage them somehow, that valuation is way too low. Below here, you'll see a different part of the plan. A little company, running out of a little industrial space in the San Fernando Valley, is building humanity the ultimate shopping bag. They think Mars is a sideshow, you see. They want to bag up asteroids, just scoop the little ones right up with a great big robot butterfly net, and bring back to high Earth orbit. Strip them down there, and build. If you thought data centers in space are wild, wait until you see factories in space. Wait until everything from toasters to CPUs to machine tools are made in high orbit, or on the moon, and the only bits that ever make it to Earth on the finished products. In space, minerals are cheap. And power is free. And it doesn't cost much of anything to move goods down a gravity well. You have no idea what's coming. Neither does SpaceX or Transastra, for that matter. They've got a hold of the tail of the elephant, and they think the Space Revolution is a rope. I'm a science fiction author. My job is to see the whole elephant. It's a big fucking elephant.

这篇文章是在介绍 **Factory 2.0** 的产品/愿景：从“AI 帮工程师写代码”，升级到“AI 参与整个软件生产流程”，也就是他们说的 **software factory（软件工厂）**。文章发布于 2026 年 6 月 15 日。([Factory.ai][1]) 核心意思是：提升单个工程师写代码速度已经不够了，真正的效率提升来自一个端到端系统。这个系统会把 bug 报告、客户反馈、内部讨论、业务需求等“信号”转成计划，再自动参与构建、测试、代码审查、安全检查、发布和监控；监控结果又会变成新的信号，形成持续反馈循环。([Factory.ai][1]) Factory 认为软件工厂需要三点： 1. **模型独立**：不同任务可用不同 AI 模型，或由 Router 自动选择成本、速度、效果最合适的模型。 2. **主权智能**：企业能控制数据和部署方式，例如云端、自带 key、自托管、欧盟区域或完全隔离环境。 3. **持续学习**：代码审查、安全、文档、QA、事故响应等都在同一平台中互相学习。([Factory.ai][1]) 它不是说工程师会消失，而是工程师的角色会变成：设计、治理和改进“生产软件的工厂”，并负责安全、流程和业务结果。([Factory.ai][1]) [1]: factory.ai/news/software-fac… "Factory 2.0: From coding agents to software factories | Factory.ai"

codex please it's not the time for this bullshit for fucks sake

According to Grok, Andrej Karpathy is an EB-1 extraordinary ability green card recipient, not a US citizen. Thus under these new restrictions he is not permitted to use, or work on, Mythos 5 or Fable 5 as of 5:21pm tonight.