老狗

🧠 爱折腾 AI，也热爱分享
🚀 聚焦 LLM、Agent 与 AI 工作流
📖 持续更新技术观察与实践经验

[老狗 @dog_not_ai]

@DafaStudent @btcmos 请注意言辞，不喜欢不要喷别人，怎么一点的真诚到你嘴里就这么难听呢

[老狗 @dog_not_ai]

@Tx090929 感谢大佬看得起我，我一个小喽喽几十粉丝还会回复我

[老狗 @dog_not_ai]

不懂就问，难道X的计算有延迟

为啥浏览量才显示14呀，我看有些推文是几百，难道全是普通用户看到的？

[老狗 @dog_not_ai]

@Tx090929 好像是必须得蓝v评论还在怎么的才会有Impression.好奇怪

[老狗 @dog_not_ai]

@SisyphusMoon 我去说错名字了 https://t.co/GmEgkNKMns

[老狗 @dog_not_ai]

@SisyphusMoon 谷歌云免费的每月200鸡，够用了，而且是免费的，比较爽。速度也还可以，可以看yt视频，不卡的。 网上有教程可以自己搭建 另外光哥你如果想看便宜的可以看我做的vpn聚合平台，https://t.co/LmQ7juLPeu，里面对比了不同的节点的价格哈。此外，如果自己有钱就是买一台境外好的服务器自搞

[老狗 @dog_not_ai]

@btcmos 学习到了雷哥，今晚或者周末就去实践

[老狗 @dog_not_ai]

@zgjncw2024 这你也受得了，你真是太年轻，我怀疑你是女的，哈哈哈

[老狗 @dog_not_ai]

@btcmos 雷哥影响力已经到小红书了，主要这些人能不能搬过去的时候说一下原作者

[老狗 @dog_not_ai]

@ShanHai_AI @elonmusk 确实，他这个搞得好乱

[老狗 @dog_not_ai]

Karpathy 揭示了一个令人眩晕的现实：全球对 AI 的认知与使用，已经裂变为一条极度陡峭的断层漏斗。
4 级能力金字塔：
60 亿人（~75%）：从未真正接触过 LLM。
10-20 亿人（~20%）：偶尔用免费版，当作高级搜索或写作辅助。
2000 万人（~0.2%）：专业开发者/数学家，已体验到 Agent 单个 Prompt 搞定整套项目。
5000 人（~0.00006%）：实验室内部顶层，掌控成千上万 Agent 集群数周攻坚科研、挖 0-day、推导前沿数学，人类审查速度已然跟不上。
为何分化如此严重？
1. 任务规模：日常琐碎提问无法压榨其潜力，高难度、长周期问题才会放大能力。
2. 能力锯齿：在可验证、高价值的代码和数学领域极强，其他领域平缓。
3. 权限代差：免费版、付费版与内部系统存在代际壁垒。
这也解释了 Sam Altman 的判断：即便 ASI 降临，现实世界也不会瞬间改变。技术在前沿实验室爆发，到渗透进大众社会，中间横亘着巨大的时间与认知鸿沟。

[Andrej Karpathy @karpathy]

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.

- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.

The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.

So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

[老狗 @dog_not_ai]

@Tx090929 那是肯定的，到手的工资越来越少，这几年还不涨薪 还有房贷 车贷 tama的房子贬值，搞得人啥欲望都没了

[老狗 @dog_not_ai]

@jianyi99 哎呀，遇到志同道合的人，大家有点钱也是希望过一下比较自由的时候，我也是我现在每天早上9:00出门，晚上10:00才能到家，一工作五天 想去很多地方，但是都没有时间去，说白了其实就是没有钱，因为你不得不停的工作才能养的起家，都活活的好久了，再这么过下去，人就要老了

[老狗 @dog_not_ai]

@ShanHai_AI 我觉得可以 交流经验

[老狗 @dog_not_ai]

@JackSteve6uh 太难了

[老狗 @dog_not_ai]

@Bigfish1127 股票搞得我都不想打开App了

[老狗 @dog_not_ai]

@0xleolabs 我去这么可怕啊

[老狗 @dog_not_ai]

刚才关灯躺床上玩手机，脑子突然闪过一个念头：

我现在手里捧着的，可能是整个屋子里细菌密度最高的东西。

白天手摸了成百上千种物品，细菌全集中转存到了手机壳上。我们记得天天洗澡洗手，却可能几个月没给手机洗过一次澡，晚上还捧着它贴脸刷、抱上床睡。

瞬间觉得手里的手机有点烫手了。

听我一句 花30秒把手机壳拔下来，用酒精湿巾里外擦干净。