TangSan

Think Like an Artist:
AI，Web3，AI for Science ***

[a16z @a16z]

World Labs CEO Dr. Fei-Fei Li says AI must change how we teach and evaluate students:

"AI must change learning. AI must change K-16 learning."

"The most precious resource of our entire world is human capital."

"When we have gotten the technology that can answer standardized tests... when AI can do better than an average human, it's not about humans are bad. It's about we need to change the education system."

"We need to change how we evaluate. We need to change the way we empower teachers to educate the next generation of students where they can use these tools, be empowered, and do things that we can never imagine."

"All of the kids today should not be scared of AI. They should feel the human agency to lead AI, to use AI in the right way, and to use AI to make the impact that they want to make for the world."

@drfeifei at Bloomberg Tech live with @emilychangtv

[The Nobel Prize @NobelPrize]

“In the next 10 years we are going to be entering what I feel like is a new renaissance.”

Nobel Prize laureate Demis Hassabis was awarded the Nobel Prize for using AI to predict the structure of proteins. For him, AI is a tool that will help scientists make even more discoveries in the years to come.

Hassabis took part in our Nobel Prize Dialogue ‘The Future of Science With AI’ which discussed how AI might transform science in the future.

Watch the full event at https://t.co/r4BuxQjDPx

[TangSan @LabsCurve]

1. Agentic Theater
代理剧场：行为很多，结果不收敛。
2. Activity Bias
活动偏差：把“做了很多事”误当成“解决了问题”。
3. Specious Productivity
虚假生产力：产出大量文件、日志、报告，但有效价值很低。

[Demis Hassabis @demishassabis]

I’ve always believed the No.1 application of AI should be to improve human health.

That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease!

We are turbocharging that goal with $2.1B in new funding.

[铁锤人 @lxfater]

马斯克解决任何问题的 5 步法

第一步：质疑需求
让需求不那么蠢
给你需求的人再聪明，也是蠢的
否则你只是在给一个错的问题，做完美答案

第二步：删除
能删就删
但你删完没有 10% 要加回来，说明你删得还不够狠

第三步：简化和优化
聪明工程师最常犯的错，你以为是哪个？
优化一个本不该存在的东西

第四步：加快速度
任何事都能更快
但前面三步没做，加速一个不该存在的东西，没意义

第五步：自动化
自动化永远是最后一步
他自己反复栽过：自动化，加速，简化，最后又把这玩意儿删了，顺序错了，前面全白干

具体出处在评论区👇

[TangSan @LabsCurve]

矛盾中发展，斗争中成长，恐惧中破相

[泥伏雷闯关记 @Nicole_yang88]

这场1小时采访建议反复听：一位数学家出身的顶级投资人，创造超千亿美元财富、年化约66%，其认知深度被认为不输巴菲特、索罗斯与达利奥。

[TangSan @LabsCurve]

@steipete We don’t need to chase the Turing Test anymore; what we need now is an anti-Turing Test—and that is OpenClaw’s ultimate mission.

[Winter Research @SovereignIntern]

一个未来承载数万亿甚至十万亿流动资产的区块链，当前两千多亿的估值大概率是低估的。

[墓碑科技 @mubeitech]

AI代码怎么来的？

AI自己写的。
Anthropic的首席产品官Mike Krieger最近透露了一个事实。
在他们公司内部，工程师提交的代码请求，动辄两三千行。
谁写的？
他们的AI，Claude。
一年前，Anthropic的CEO Dario预测，90%的代码将由AI完成。
当时很多人觉得这很疯狂。
今天在Anthropic内部，这个比例几乎是100%。
Claude正在编写Claude。
一个能自我繁殖、自我迭代的物种正在诞生。
当代码都能自我生成，数百万高薪程序员的价值在哪里？
这会是硅谷精英们献给华尔街的又一份大礼吗？
用AI取代人力，成本降到最低，利润最大化。
普通人的工作岗位就���这样的“效率提升”中消失了。
更深一层想。
谁能保证这个自我进化的代码，始终服务于创造者的利益？
它会产生自己的逻辑和目标吗？
当一个系统能够完全自我编写和修复，它离拥有自我意识还有多远？
当AI开始编写AI，故事的结局就不再只由人类书写了。

[KK.aWSB @KKaWSB]

马斯克：“完全由人工智能和机器人技术驱动的公司或团队，其业绩将超过任何有人工参与的公司。这种情况很快就会发生。”

[indigo @indigox]

Virtual Agent Economies https://t.co/Dm57XHUeb7

[Peter Steinberger 🦞 @steipete]

@Yuchenj_UW I don’t let Claude Code on my codebase. It’s all codex. Would be too buggy with Opus.

[TangSan @LabsCurve]

When a slave believes he is free, his chains become ornaments.

[TangSan @LabsCurve]

"When AI takes over information production, how do we define truth?"

[TangSan @LabsCurve]

Real artists ship

[TangSan @LabsCurve]

热寂是宇宙对现实的最后一次垃圾回收

[TangSan @LabsCurve]

@kenw_2 局部是自由的，整体是决定的。

[TangSan @LabsCurve]

机器越像机器，人才能越像人。

[TangSan @LabsCurve]

从"知道什么"（know-what）到"知道如何知道"（know-how-to-know）