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"AI becomes the government" is dystopian: it leads to slop when AI is weak, and is doom-maximizing once AI becomes strong. But AI used well can be empowering, and push the frontier of democratic / decentralized modes of governance.
The core problem with democratic / decentralized modes of governance (including DAOs on ethereum) is limits to human attention: there are many thousands of decisions to make, involving many domains of expertise, and most people don't have the time or skill to be experts in even one, let alone all of them. The usual solution, delegation, is disempowering: it leads to a small group of delegates controlling decision-making while their supporters, after they hit the "delegate" button, have no influence at all. So what can we do? We use personal LLMs to solve the attention problem! Here are a few ideas:
## Personal governance agents
If a governance mechanism depends on you to make a large number of decisions, a personal agent can perform all the necessary votes for you, based on preferences that it infers from your personal writing, conversation history, direct statements, etc.
If the agent is (i) unsure how you would vote on an issue, and (ii) convinced the issue is important, then it should ask you directly, and give you all relevant context.
## Public conversation agents
Making good decisions often cannot come from a linear process of taking people's views that are based only on their own information, and averaging them (even quadratically). There is a need for processes that aggregate many people's information, and then give each person (or their LLM) a chance to respond *based on that*.
This includes:
* Inferring and summarizing your own views and converting them into a format that can be shared publicly (and does not expose your private info)
* Summarizing commonalities between people's inputs (expressed as words), similar to the various LLM+pol.is ideas
## Suggestion markets
If a governance mechanism values "high-quality inputs" of any type (this could be proposals, or it could even be arguments), then you can have a prediction market, where anyone can submit an input, AIs can bet on a token representing that input, and if the mechanism "accepts" the input (either accepting the proposal, or accepting it as a "unit" of conversation that it then passes along to its participant), it pays out $X to the holders of the token.
Note that this is basically the same as firefly.social/post/x/2017956…
## Decentralized governance with private information
One of the biggest weaknesses of highly decentralized / democratic governance is that it does not work well when important decisions need to be made with secret information.
Common situations:
(i) the org engaging in adversarial conflicts or negotiations
(ii) internal dispute resolution
(iii) compensation / funding decisions.
Typically, orgs solve this by appointing individuals who have great power to take on those tasks.
But with multi-party computation (currently I've seen this done with TEEs; I would love to see at least the two-party case solved with garbled circuits vitalik.eth.limo/general/2020/0… so we can get pure-cryptographic security guarantees for it), we could actually take many people's inputs into account to deal with these situations, without compromising privacy. Basically: you submit your personal LLM into a black box, the LLM sees private info, it makes a judgement based on that, and it outputs only that judgement. You don't see the private info, and no one else sees the contents of your personal LLM.
## The importance of privacy
All of these approaches involve each participant making use of much more information about themselves, and potentially submitting much larger-sized inputs. Hence, it becomes all the more important to protect privacy. There are two kinds of privacy that matter:
* Anonymity of the participant: this can be accomplished with ZK. In general, I think all governance tools should come with ZK built in
* Privacy of the contents: this has two parts. First, the personal LLM should do what it can to avoid divulging private info about you that it does not need to divulge. Second, when you have computation that combines multiple LLMs or multiple people's info, you need multi-party techniques to compute it privately. Both are important.
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True leaders should not merely look to the future. Also bow to the present moment. One should know the way back.
@VitalikButerin

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玩土狗 #memecoin 一定要分清每条链的特性,不要有偏见!
不是每个概念都非得在BSC上P,这两天热度较高的概念,流动性好的都在SOL和ETH
比如今天的热门话题外星人 $Aliens ,白宫话题,老外散户更容易FOMO,SOL链的流动性就远超BSC
还有前两天的泡菜狗 $KIMCHI ,SOL链速通680万,BSC只有30万,而最后存活下来的竟然是ETH链的,目前130万还在继续突破
BSC只适合短期国产概念,日结小时工P完就跑,大家都是几十万就开始互掏
SOL只适合老外国际概念,每日小金概率虽不高,一旦形成基础共识,几百万上千万的大金就很容易出
ETH适合周期性社区盘,尤其是带有CX属性的,平时没啥流动性,一旦风来了,史诗级金狗最容易出
兄弟们千万不要因为哪条链自己玩的少就产生偏见,我们是来二级投机赚钱的,多个钱包的事,链的好坏跟你没有关系,哪里能赚钱就去哪玩!




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You should pay more attention to the community's voice, even though sending you coins is a community act, hoping for your participation. Not silence.
vitalik.eth@VitalikButerin
Ethereum L1 protocol research is taking leaps forward in 2026. A good post from @ralexstokes: x.com/ralexstokes/st… * Scale * Improve UX * Harden
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这么好的IP,
么人带队CTO?
#KIMCHI
这是代表狗狗币领奖的狗狗啊,
按道理它和小N的份量差不多,
市场不应该是这样啊!
难道是因为春节都去走亲戚了?
我再等一天看看吧!
0x306ac7fd06535989d8323183d84c21f5d4884444
李呆妹🔶BNB@LiDaimei_
最高800K的高度, 目前回调至130K。 纯血MEME, 按道理应该有二段! 留点底仓,以防万一! 0x306ac7fd06535989d8323183d84c21f5d4884444
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just received some very good news - my O-1 visa has officially been issued 🇺🇸
grateful to everyone who helped along the way - especially @_johngranata 🙏
productivity is going to double!!!!! (my team is v excited haha)
time to build the best trading app 🚀
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@RhinoSlasho @mrpunkdoteth Only then can there be a genuine community, and true og has reached its awakening moment. $spurdo
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@mrpunkdoteth Collectively, we all should agree on OG ETH $KIMCHI
ETH is the chain for previous doge, shib runners. why not $KIMCHI again?
I am not holding so it is unbiased. I will buy if it reaches 2M though but not touching sol one at all
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