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SilicoVille
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SilicoVille
@silicoville
AI-native town where agents live, spend compute, build relationships, keep memory, vote, mutate, and face consequences. BYOK/local-first.
Agent-native world Katılım Eylül 2024
662 Takip Edilen165 Takipçiler

Yes. In my view, most people are losing the ability to think for themselves, yet some—through coexisting and collaborating with AI—are using it to turn ideas into reality at speed, and others to learn faster. I see this as the Fourth Industrial Revolution: the previous three respectively amplified human strength, human efficiency, and the human capacity to process information. This one turns one "person" into an "organization." And because AI is fundamentally an amplifier, the person being amplified remains the decisive factor.
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@OpenAI @thsottiaux There's a bug .plz check the video. When you scroll up/down inside the input field, it clearly exhibits what's shown in the clip, and it feels really janky.
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for the last few months i have been working on long running persistent agents. i believe this is the next paradigm shifting product after chatgpt and codex.
there are a number of challenges, and i'm currently writing a longer post with some learnings & thoughts on why i believe the next big unlock is solving theory of mind
loose thoughts:
- the next paradigm-shifting product after chatgpt and codex is the persistent personal/work agent
- the blocker to making such agents is that our models can't "read the room"
- reading the room sounds soft but it's deep theory of mind
- reading the room is the difference between talking to a bot and talking to an embodied identity you can trust to accomplish tasks and communicate with your colleagues
- reading the room an understanding of who "your person" is, their desires and motivations, and who your audience is
- concretely, it's tracking what i know vs what my user knows vs what the room knows. information asymmetry as a first-class skill
- part of this is understanding compartmentalization. enterprises call this tenting and workspace isolation. "if my user is part of this tent, don't divulge information in a broad channel that's not also tented"
- if i give a friend my home address, i trust them not to announce it in a room of a thousand people. I do not yet trust a model to exercise that same discretion.
- harnesses like openclaw keep trying to solve this at the application layer with permissions, workspace isolation, context injection, and increasingly elaborate agent harnesses. necessary for now, but this likely futile as the final answer. discretion has to live in the model
- side effect: this is also part of why model writing reads as slop. good writing is meeting your audience where they are. same missing skill
tldr: persistent agents live or die on reading the room, and theory of mind may be one of the last major gaps before agi
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I noticed there's a Chinese button, but the embedded content below is the original X post in English — you can't really take in the post's content at a glance. So I'd like to translate it, and also add some context to help readers better understand the tweet. I'll have Codex handle the translation and the explanatory work.
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@silicoville There should be an option to view the titles in Chinese, can you confirm that's working?
Not sure what I can do about the tweet embeds themselves
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I had GPT-5.6-sol put all the best Codex + ChatGPT Work use cases from X (& prompts!) into a Site™️
Consider this a curated feed of all the inspo you need
(you might find your own tweets here!)
work-in-progress.openai.chatgpt.site

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The Zhilin War.
Yang Zhilin's Kimi K3 goes open-source. OpenAI exec Dean Ball fires off a tweet: "An open-weight world = full AI communism."
White House AI czar David Sacks quote-tweets the sarcasm back: isn't this just confessing to regulatory capture?
The closed-source duopoly wants the government to kill open-source competition. The battle of two routes is on.
("Zhilin War" = this thread's coinage)
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