POP

当日记本发，不求流量

[POP @InfoEchoes]

https://t.co/yGuMyKy6Jf

[POP @InfoEchoes]

人是一种运行了成千上万年的Harness。而它会生老病死，所以我觉得AI它在某一个阶段也会演化出来类似的机制，或者说它不演化���来类似机制，就没法更进一步。

如果这样一个系统跨越了灾变，见证了沧海桑田，它的目的将不再是人类赋予的某个具体任务，在宏大的时间尺度上，它的目的就是维持秩序本身。

[POP @InfoEchoes]

劳动，在这个角度上是智能体（人或 AI）将内在的信息结构映射到外部物质结构上的过程。

[POP @InfoEchoes]

@0xAstra 传统SaaS找FDE吗？我们最近在给一个传统上市软件公司做FDE咨询

[Ash Jogalekar @curiouswavefn]

As a scientist, AI has made me feel the most intellectually alive and excited I have felt since I was a graduate student and postdoc more than 20 years ago. Every day I can start with an idea in the morning, and by lunchtime, I see a testable, rational, well-thought-out hypothesis forming in front of my eyes. And every day, the possibilities seem endless, like mountains beyond mountains. What a time to be alive.

Here's a case in point. I'm collaborating with a professor, an experimentalist, who is trying to solve a thorny problem in his field. There's one particular molecule that he is using in his experiments that seems to result in radically different crystal structures compared to similar molecules. What's happening here? He has come up with a few different hypotheses that could explain the differences but is not a theoretician and needs to tease them apart.

On Thursday, I started an investigation using AI at his bequest. The AI immediately confirmed the hypotheses that he had in mind and added a few of its own.

Then it started its exploration. The investigation was carried out in three different phases, each of increasing difficulty; the first one using classical physics, and the second and third using quantum mechanical techniques of increasing rigor. This tiered strategy is the right one.

By Thursday evening, I had the glimpse of an answer. Most of the hypotheses had been examined and rejected. Two stood out, although the AI identified one as more a mechanism through which the other one operated rather than a root cause. It immediately pivoted to the higher-level, more rigorous calculation.

Every time I interacted with the AI, it was more like a dialogue between a professor and a bright student or scientific collaborator than a mandate issued to a tool. The feeling was very much of a process where the AI and I were solving a problem together. I steered the conversation several times, pushed back, suggested course-corrections, acknowledged my own wrong ideas as well as the AI's and went back and forth. The AI was successful in keeping multiple requests in its memory, stacking them by priority while never losing the conversation thread.

By late Friday morning, there had collected enough data from the more rigorous calculation to corroborate the suspicion that it was really just one hypothesis that was the root cause. It then moved on to the next step, which was to come up with a distinct set of novel molecules that would confirm the hypothesis beyond any reasonable doubt. In addition, it launched an even more rigorous calculation at a higher level of theory.

By the end of Friday, roughly 48 hours later, using this multi-layered approach of increasing rigor, backed up by references, and made useful and actionable by testable experiments, the AI had arrived at a solid, rigorous conclusion.

Now imagine doing this every day, about any topic under the scientific sun, in any scientific field, so that your intellectual labor is multiplied a million-fold.

Mountains beyond mountains. What a time to be alive.

[POP @InfoEchoes]

@ZenoRho 策子天天抄你文案哈哈哈

[POP @InfoEchoes]

不彻底摆脱资源类的路径依赖的话，基本这辈子平台级的机会无缘了。

���成可期，大成无望。

[jietang @jietang]

@elonmusk @teortaxesTex won’t take that long

[POP @InfoEchoes]

希望大家少熬点夜。我做了一个 7×24 小时本地运行、能手机远程看进展和授权的 Auto Research harness，先开源出来，欢迎 PR
https://t.co/Lq0I2xNGcb

1. 7×24 小时持续 AutoResearch

AutoBCI 会在本机持续推进研究循环:排队候选方向、运行受控实验、复盘结果、沉淀下一步。它适合有长期调参、评估漂移和结果复盘压力的团队,不是一次性脚本。

2. 随叫随到:微信汇报,也能接收远程任务

Hermes、OpenClaw、ClawBot、微信或 webhook 只负责传话和��报告:查状态、发报告、记录论文链接、触发白名单命令。你可以在通勤、散步或临时看到一篇论文时,随时把灵感交给它,也可以随时调整下一步研究方向。手机不是远程桌面,也不能变成任意 shell;科研真源仍在本机 Program、ledger、events 和 artifacts 里。

3. Research Tree:把多轮实验变成经验

每一次尝试都应该留下来:为什么选这条方向,跑了什么命令,改了什么文件,结果是不是可信,为什么下一轮要继续或放弃。上下文足够多时,AutoBCI 才会真正变强,因为它不是只记对话,而是在积累可复盘的研究证据。Research Tree 让它能跨轮次学习、进化和迭代,把前后几次实验的结论变成下一次实验的经验。

[POP @InfoEchoes]

当你在Auto research一天烧了8亿token准备大展拳脚时，你的Kaggle对手be like

[POP @InfoEchoes]

意识到了一个问题，就是我写的一些帖子，过于的学���化，过于的抽象化，而不是像Building Public，要说我做了什么，怎么做，遇到什么坑，然后有效利他的内容比较容易爆

[POP @InfoEchoes]

度过风暴的唯一方式是进入风暴的中���。

[POP @InfoEchoes]

https://t.co/Qv8M81ODYK

[POP @InfoEchoes]

需要在战争中学习战争，逻辑推理太有限了

[POP @InfoEchoes]

我觉得不同公司的 Agent 不同水平智能体，可能在某种程度上��会出现像基因争夺自然资源那样的竞争在不同的生态位下面。

而最后最大的闭源模型，就如同那些大型的恐龙或者，反正那些大的动物不如水龙兽活得久，或者鳄鱼活得久一样。

生物的多样性是非常重要的。生物的分布性也是非常重要的。有的灭绝是指在水里，有的大灭绝是在地面上的，有的大灭绝是天上来的。

如果 Agent 或者说以后的人��智能，硅基生命想要在火星生存的话，它可能不能是一种单一的形式，量产的形式。应该是各种不同的方式，就像生物多样性一样。

而我们现在并没有，再有雏形，就比方说分布式的一些计算。当然随着 Scaling law 不确定这是不是一个，它是不是会一直持续。边缘的那些小智能体，也会拥有相当高的智能水平。但是如果要活下去的话，在自然界的情况下，它并不一定需要单个生命拥有这么高的智能水平。

[POP @InfoEchoes]

@Spleap17598 @sixsixjay 之前出过赛题，主观的比赛就是主办方分分蛋糕

[POP @InfoEchoes]

@SeanchenZ 刚提完离职，心态转变是极大的，和一个月前的自己根本不是一个人

不能寄望于一个 big other ，���望于确定性，寄望于体制，寄望于大佬，铁饭碗只是一个叙事，更大的海啸近在眼前

在生存层，长期来看并不确定。在机会层，它会提供一种虚假的信念导致懒惰。需要接受变化，接受中间态不确定的情况