我做了一个 AI 产业链资料站:AI产业链地图(aichainmap.com)。
· Serenity 7,400 多条推文中英对照,新推几分钟内翻好
· 1,152 家公司、697 个概念的产业链词条
· 173 篇机构深度报告的中文解读,30 门公司课
· 10,000+ 份 AI 相关研报,用 AI 对话查,回答带出处
双十一新人立减 ¥100,¥599 → ¥499,11 月 16 日 24:00 前领券。
aichainmap.com/join?src=x-pi…
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我做了一个能拆开的 3D 数据中心:从园区大门一路走到一颗 GPU 上,机柜能拉出托盘,GPU 能一层一层分开。录了 90 秒,带你走一遍。
aichainmap.com/explore/?src=…
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研报里天天写 HBM、CoWoS、液冷、光模块,可这些东西,我一个都没见过。
所以我干了件有点轴的事:把一整座 AI 数据中心做成了 3D,搬到了网页上。
从 1.6 公里宽的园区点进去,一路能走到一颗 GPU 上,机柜、托盘、芯片,都能拆开看。
网址在评论里。
把巴菲特 1956 到 2025 年的信整理成了中文知识库,98 篇全文,每句原话都注明出自哪封信,概念、公司、人物之间能互相跳转。这是介绍视频。
learnbuffett.com
Replying to @ziqiu886
他讲本分的话我收了 288 条,读下来大概是:做对的事情,把事情做对,明知是错的就不做;只拿来要求自己,其中一条是不赚人便宜。历年原话按年份排在网站的「本分」专题里,网站介绍在这:xitter.gq/binbinmath/status/2110…
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Replying to @0427SMtieshou
他自己公开说过的茅台买卖有 18 则,最早是 2013 年 1 月确认开始持有,最近一次是 9 月 28 日那 3 万股。每条都附了他的原话,我整理在一个网站里,介绍在这:xitter.gq/binbinmath/status/2110…
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Replying to @santoulang
那位网友的原帖已经删了,段永平 10 月 10 日的回复原文是「你是觉得我弱智吗?」。他这些年说过的话和公开的买卖,我整理成了一个能对着原文查的网站,介绍在这:xitter.gq/binbinmath/status/2110…
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Replying to @wufantouzi
他今年几乎天天在雪球回帖。我把他 2006 年以来公开说过的一万多条原话,还有他提过的买卖和期权记录,整理成了一个能对着原文查的网站,介绍在这:xitter.gq/binbinmath/status/2110…
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Replying to @lili103103
他那条原帖正文只有「买了点」三个字,3 万股、3692.5 万是截图里的成交记录。我把他这些年说过的话和公开的买卖整理到了一个网站里,写了篇介绍:xitter.gq/binbinmath/status/2110…
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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.
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把 Serenity 全量 6200+ 推做成了可查的多空地图:786 家公司逐个标看多/看空 + AI 观点摘要 + 注意力榜,点名即见她的态度 👉 aichainmap.com/serenity/ #AI #Semiconductors @aleabitoreddit
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