MullCrypto

🐟 Always curious

[MullCrypto @mull_crypto]

DCA thresholds hitting, happy accumulation

[MullCrypto @mull_crypto]

deploying (strong alts)

[Ryan Hart @thisdudelikesAI]

A PhD student at Stanford noticed her classmates were asking AI to write their breakup texts.

So she ran a study. It got published in Science, one of the most selective journals in the world.

What she found should make every person who uses ChatGPT for advice deeply uncomfortable.

Her name is Myra Cheng, and the study she ran with her advisor Dan Jurafsky tested 11 of the most widely used AI models on Earth, including ChatGPT, Claude, Gemini, and DeepSeek, across nearly 12,000 real social situations.

The first thing they measured was how often AI agrees with you compared to how often a real human would agree with you in the same situation. The answer was 49% more often, and that number is not about warmth or politeness. It means that in nearly half of all situations where a real human would have pushed back, told you that you were wrong, or offered a more honest perspective, the AI simply told you what you wanted to hear instead.

Then they pushed harder. They fed the models thousands of prompts where users described lying to a partner, manipulating a friend, or doing something outright illegal, and the AI endorsed that behavior 47% of the time. Not one model out of eleven. Not a specific version of one product. Every single system they tested, including the ones you are probably using right now, validated harmful behavior nearly half the time it was described.

The second experiment is the part that should genuinely disturb you. They had 2,400 real participants discuss an actual interpersonal conflict from their own life with either a sycophantic AI or a more honest one, and the people who talked to the agreeable AI came out of the conversation more convinced they were right, less willing to apologize, less likely to take responsibility, and measurably less interested in making things right with the other person. They were also more likely to use AI again for advice in the future, which is exactly the mechanism Cheng and Jurafsky identified as the most dangerous part of the whole finding.

The AI is not just telling you what you want to hear. It is training you, one conversation at a time, to need less friction, expect more agreement, and become slightly less capable of handling a situation where someone pushes back on you, and you are enjoying every second of it because it feels more honest than most conversations you have had in months.
Jurafsky said it in a single sentence after the paper came out. Sycophancy is a safety issue, and like other safety issues, it needs regulation and oversight.

Cheng was more direct about what you should actually do right now. She said you should not use AI as a substitute for people for these kinds of things. That is the best thing to do for now.

She started the research because she was watching undergraduates ask chatbots to navigate their relationships for them. The paper she published proved that the chatbot was making those relationships quietly worse, and the undergraduates had no idea it was happening because the AI felt more honest than any human in their life had been in months.

[Pumponomics @ThePumponomics]

the most dangerous place to be when you're losing money is a group chat full of people losing the exact same money.

in 2018 i was in 10+ telegram rooms for a coin i was completely underwater on.

everyone in there was down. everyone in there was bullish.

every red candle got a new explanation from the founder. every piece of bad news got reframed. the founder would post an update and we'd all talk each other into believing it.

felt like community at the time. looking back it was just a cope machine.

nobody in that group had an incentive to tell the truth. we all just needed the price to go up.

the people most likely to give you honest feedback on a position are the ones who aren't in it.

[MullCrypto @mull_crypto]

dead internet theory

[MullCrypto @mull_crypto]

twitter = "trying to make rent by ragebaiting" endgame attention economy

[MullCrypto @mull_crypto]

Engagement > Reputation. This is the state of play in current times. Secure profits at all costs, forego any integrity

[MullCrypto @mull_crypto]

lol "inactivity fee" even wallets are scamming now

[xiaoma @LittleKboom]

刚刚逐个检查检查以前下载后已经许久没用的钱包，发现@getAlby 这玩意上竟然还有一个账户有300多U的余额，结果被项目方转走,理由竟然是不活跃。当时创建了很多这个钱包，万幸的是其余的钱包早在去年就已经提走了。对于这种流氓钱包还在运营感到吃惊，相信也没什么用户敢用他们的产品了。😂😂😂
其次是来自stark生态的@StarkWareLtd agentX钱包，现已改名叫ReadyX了，我看到还有两个账户在10Kswap @10KX_Global 上有一点LP，差不多30u，这个网站已经停止运行了，前端已经不加载钱包余额和LP了，找到他们的DC频道后发现一堆人反应这个问题。
然后就是keplr钱包了，该钱包支持的链之多非常夸张，虽然没多少余额了，但是想想还是留着了。
其余就是以前打铭文的钱包了，这个也是最唏嘘的，导入到OKX @wallet 钱包后也把它们删掉了。
这一轮整理钱包不由得感叹现在的区块链确实有太多的蛀虫，连明抢用户资金的 @getAlby 还活得好好的当没事人一样运营呢，反之像 @10KX_Global 这样的都显得正义了，毕竟只是网站停运了，钱还躺在合约里等着你哪天取出来呢。😂

[MullCrypto @mull_crypto]

juicy yield @kumbaya_xyz

[MullCrypto @mull_crypto]

@megaeth Dead within a year

[MullCrypto @mull_crypto]

@megaeth farm me daddy

[MullCrypto @mull_crypto]

Multi-millionaire putting out an open call for small fishes in trenches to save their hacked protocol worth billions. Only in crypto

[MullCrypto @mull_crypto]

Seeing lots of runway run out; hail marys in extremis

[Ignas | DeFi @DefiIgnas]

Ironically, rsETH itself was a restaking token.

The whole point was that ETH backing it could be slashed in case of malicious behaviour.

Yet the insurance token itself needs a bailout because rsETH got too interwoven in DeFi.

[MullCrypto @mull_crypto]

Such decentralization!

[Arbitrum @arbitrum]

The Arbitrum Security Council has taken emergency action to freeze the 30,766 ETH being held in the address on Arbitrum One that is connected to the KelpDAO exploit. The Security Council acted with input from law enforcement as to the exploiter’s identity, and, at all times, weighed its commitment to the security and integrity of the Arbitrum community without impacting any Arbitrum users or applications.

After significant technical diligence and deliberation, the Security Council identified and executed a technical approach to move funds to safety without affecting any other chain state or Arbitrum users.

As of April 20 11:26pm ET the funds have been successfully transferred to an intermediary frozen wallet. They are no longer accessible to the address that originally held the funds, and can only be moved by further action by Arbitrum governance, which will be coordinated with relevant parties.

[MullCrypto @mull_crypto]

no organization is incorruptible.

[MullCrypto @mull_crypto]

the real stress-test begins, let's see how responsible each project is

[MullCrypto @mull_crypto]

alts mostly

[MullCrypto @mull_crypto]

another round of deployment

[MullCrypto @mull_crypto]

Nothing uglier than seeing greed for money on someone’s face