邦比快跑 (@binbinmath) profile picture

巴菲特致股东信知识库 https://xitter.gq/t.co/fXsw2Z3gHn 查理·芒格的思维模型 https://xitter.gq/t.co/yLUZg7aPkV AI产业链地图 https://xitter.gq/t.co/NA1TNsKERh 阿段笔记 https://xitter.gq/t.co/CJVv0bCWIJ

Joined February 2007
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。
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做了个段永平的网站,他 20 年来说过的话、做过的买卖,都整理在里面了。这是介绍视频。 learnduan.com
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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
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把查理·芒格的思维模型整理成了一个网站,每个模型一篇长文加一份检查清单,遇到问题还能按场景反着查。这是 3 分钟的介绍视频。 mungermodels.com
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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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今天证监会拟对老虎、富途、长桥跨境展业违法所得进行罚没,引发市场对存量账户和港股抛压的担心;但把规模一算会发现,这些账户相对港股通仍不是一个量级,真正决定港股资金面的主线,还是南向资金。
🤖 Made with AI
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