Crypto Panda 🚀🚀🚀

@agintender @RaveDAO @okx 名牌转进bg就不风控吗

按照今天 @RaveDAO 几次把 $rave 转到交易所的转账来看，大概率是交易所风控账户了，而且是大的，主力账户那种 看到有人想抄底买盘，就顺手交个朋友，能回一点血是一点吧 毕竟金主爸爸们都是一笔糊涂账 另，看了一下保险金 @okx 居然没啥事，这波属于是少赚了吧 这也说明风控机制有效了啊 可以加鸡腿🍗 不说要调查吗？ 现在这波现货可以查了 😂

@bc1qDave 八国联军不是赢了吗

伊朗问题 伊朗有多大呢？等于 四川+贵州+湖南+湖北+安徽+福建+江西+江苏。等于一个新疆。相当于南宋的面积了。 三周前说伊朗搅动市场的因素是要么展现出超出预料的控制能力，要么展现出超出预料的军事能力。现在已经展现出超出预料的航道控制能力 如果伊朗问题持续不解决，那金融市场必有一大跌。 美联储加息，经济救回来了，但是市场肯定会崩一下，虽然大家现在已经开始提前抢跑计价加息逻辑。如果美联储不加息，经济崩了，市场早晚得崩，计价衰退是更可怕的事情 如果伊朗问题解决了，那会迎来极大的情绪反弹，是counter consensus trade为入场的最好时机 伊朗问题能否解决呢？这是个矛盾的点，伊朗目前的唯一诉求是保存政权，美国的诉求是推翻政权，核心逻辑上有冲突。伊朗做出让步是可能的，因为目前封锁着它自己更难受，但是需要不短的时间让它内部瓦解，这段时间内市场早就跌了。快速解决问题需要特朗普服软，这种情况下市场会定义为美国军事行动失败，美元首当其冲会受到打击，对市场短暂冲击之后还是看好的 目前看来，美国吃败仗的概率大大增加。首先是以色列今天早上已经公布转变战略目标，从推翻政权改为大幅削弱伊朗军事能力，这是个重要的转向。 其次，美国准备派地面部队进入。历史上只要是侵略他国领土的战争，近百年除了快速的伊拉克战争之外，无论多强的国家都是以失败收场：苏联，俄罗斯，二战后美国，希特勒，拿破仑，大日本帝国，八国联军，只要踩入他国领土进行战争，失败的概率几乎100%。和谈与让步已经从遥远的地平线上浮现出来了。

@cmdefi 请问一下区块构建者获利3400万，这个是以太坊的是节点吗？

梳理了一下最近Aave上那笔5000万美金的交易事故。(通过CoW Swap) 虽然这是DeFi历史上最严重的交易执行损失，但发生的很诡异。 第一点是CoW的抗MEV几乎失效了。 按照目前AAVE的链上流动性，换回500万美金的AAVE肯定是没问题的，但最终执行被路由到了深度最差的Sushi pool，只有7万美金的流动性。 结果是花费5000万美金，只买到了3.6万美金的AAVE。 CoW在报告中披露了一些问题，比如这里有一个gas上限的bug，有solver给出了更好的报价，但被这个限制拦住了，这个问题后面进行了修复。但这笔交易事故已经无法挽回。 在执行阶段其实还有机会救场，Solver E在这个阶段找到了更好的报价，并且成功赢得了竞拍，但最终却没提交交易，而CoW的拍卖系统对于这种胜者获胜后没交付的情况，没有应急措施，或是惩罚机制，哪怕拒绝到这笔交易也行，都没有。最后漏给了非常差的solver接手。 第二点比较奇怪的是，单笔5000万美金这么大的交易，在非稳定币交换中，很少见。因为多数pool的流动性都支持不了，而且在协议已经提醒99%价格影响的情况下，用户还手动确认了交易。 第三点是CoW自己说这笔交易可能泄漏到了公开mempool，具体原因目前还没写清楚。 目前两个协议都发了事后报告，MEV bot获利990万美金，贿赂区块构建者3400万美金。 责任认定上很清晰主要在CoW，因为Aave只是前端集成了CoW组件，两个协议也没有推卸责任扯皮这些事，我觉得态度上都很好。 这次事件是buff叠满了，是多个系统问题叠加导致了一个比最差情况还要糟糕的结果。 对CoW来说应该还有很多问题需要查明。而目前这个交易执行者似乎还没露面，最初做这笔交易的动机也不得而知。

@jason_chen998 Polymarket的原始数据都是公开的，是不是任何第三方都可以做，纽交所投了当股东也没啥优势吧？

分享个热知识，纽交所的母公司ICE除了最近投资了OKX，还给Polymarket纯现金投资了20亿美金，按照80亿美金估值占了25%的股份，并且纽交所还会作为Polymarket的全球数据分销商，也就是会将Polymarket的原始数据进行清洗和标注后打包卖出去，华尔街将会直接付费订阅这些Polymarket的数据。 交易所华人牢牢的在全球占据了不可撼动的地位，但可惜的是，预测市场的巨头们现在全部都和华人没什么关系了，前天全村的希望Opinion在TGE后也.....唉，套，麻，救救...

Sometimes love begins with a fight. Happy Valentine’s Day! Made with #Seadance 2.0

Thanks to #Seedance 2.0, make my cat a hero.

As of now, #Bitmine under #TomLee has recorded a $6.6B mark-to-market loss, ranking as the 5th largest trading loss globally. The four bigger ones before it? #ArchegosCapital, #MorganStanley, #JPMorgan, and Industrial Bank of China. Different names, same pattern: high leverage, concentrated bets. The last three are institutions big enough to absorb the damage. #Archegos wasn’t. Its founder, #BillHwang, was arrested and sentenced to 18 years in prison. An interesting coincidence: Bill Hwang and Tom Lee are both Korean. And they actually look quite alike. Bill in jail, how this ends for Tom Lee? #Leverage #RiskManagement #MarketHistory #TradingLosses #Crypto

Yesterday’s #silver crash looked less like a macro correction and more like a classic #meme-style rug pull. Down 36% in a single day — the largest one-day drop in over 40 years. The last comparable event was “Silver Thursday” on March 27, 1980, when the Hunt brothers’ failed corner led silver from nearly $50/oz to $10.80 in days. What’s interesting isn’t just the drop — it’s the pattern. This entire silver move closely mirrors how #ETH once traded relative to #BTC. First, U.S. debt stress, repeated shutdown risks, and Trump’s tariff escalation shook confidence in the dollar. Capital rushed into gold. Think: capital piling into BTC. Once #gold stabilized above key levels, silver was suddenly seen as “cheap.” Money rotated from gold into silver for a catch-up trade. (BTC → ETH). Silver’s market is much smaller than gold’s. When hedge funds and retail piled in, it triggered short squeezes and vertical price action. Small float, bigger swings. After silver surged, capital began rotating again — into copper, platinum, and even smaller metals. (ETH → altcoins). Then macro fear flipped. Markets started pricing in a more aggressive Fed: faster QT, higher rates, stronger dollar. Precious metals sold off hard — and silver amplified gold’s downside due to its smaller size. Same force that magnifies gains also magnifies losses. Different assets. Same behavior. Speculation always rhymes. #Silver #Gold #Macro #MarketCycles #Liquidity #Speculation #RiskOnRiskOff #CryptoPsychology

@rbwkz131313 Exactly. Silver looks less like a destination and more like a parking lot. When the risk curve bends back and capital starts chasing convexity again, BTC is the obvious release valve — and those moves are rarely gradual.

@cryptopanda68 Interesting take on silver being a 'smoke bomb.' If capital is flowing there now just for a place to sit, the move back into BTC once the risk curve shifts is going to be violent

#Silver’s market cap has overtaken #Bitcoin’s — in just one month. Silver climbed from ~$390B in late December to ~$580B today, adding ~$190B. Bitcoin’s total market cap sits around ~$180B. First, silver’s rally feels like a smoke bomb. Silver doesn’t have that many real industrial use cases. In many ways, it’s more of an industrial byproduct than a core input. This move may be overstating real demand. Second, Bitcoin still behaves like a high-beta speculative asset. That means it remains outside the main risk curve — capital hasn’t fully rotated back yet. A rise in traditional assets like silver doesn’t automatically mean Bitcoin must follow. But it does prove one thing clearly: When liquidity enters the market, pushing assets to valuations 10x Bitcoin’s size is absolutely possible. I don’t know when that liquidity flows back into Bitcoin. But when it does — it won’t be subtle. #Bitcoin #CryptoMarkets #Liquidity #Macro #DigitalAssets

If you made money on $TRUMP and rotated on that day: #Gold: +90% #Crypto: $BTC: -10% $ETH: -7% $SOL: -40% $BNB: +28% $HYPE: +10% $AAVE: -50% $PEPE: -80% #Stocks: #NVIDIA: +38% #Google: +96% #TSMC: +60% If you just held #TRUMP: Max drawdown: -94% One simple takeaway: Fast money assets are rarely meant to be held. They are meant to be rotated. Most people didn’t lose because they never won. They lost because they parked profits back into pure narrative risk. #Crypto #Bitcoin #Altcoins #Stocks #Gold #MarketPsychology #RiskManagement #CapitalRotation

Why #OpenAI Will Likely Lose to #Google (In the End) The #AI industry is going through a quiet but brutal shift. The competition is no longer about who has the smartest model, but who can deliver useful intelligence at the lowest marginal cost. Once the game turns into cost, distribution, and ecosystem leverage, OpenAI’s early lead starts to fade fast — and Google is exactly the kind of player you don’t want to face in a war of attrition. 1. Cost is destiny: #TPU vs #GPU In inference economics, cost decides survival. OpenAI is built on general-purpose NVIDIA GPUs. Google owns its own TPU stack. This matters far more than people think. GPUs are versatile by design. They carry a lot of overhead to support graphics and scientific computing. TPUs are purpose-built killers for inference. Their systolic array architecture lets data flow directly between compute units, instead of constantly bouncing in and out of HBM memory like GPUs do. The result: lower power usage, higher bandwidth efficiency, and dramatically cheaper long-context inference. A small per-query advantage compounds into hundreds of millions of dollars per year at scale. This is not a model problem. This is a physics and architecture problem. 2. Business model mismatch: subscriptions vs “free at scale” OpenAI still behaves like a classic #SaaS company, trying to defend a $20/month subscription to cover massive inference costs. Ironically, OpenAI’s move toward cheaper, ad-supported tiers does Google a favor. It educates users that “AI with ads” is acceptable. Meanwhile, #Gemini plays a longer game: lower pricing, free access for students, and deep ecosystem lock-in. Google doesn’t need AI to make money. It needs AI to keep users inside its universe longer. Users have no loyalty to models. They do have massive switching costs around data and workflows. By stitching Gemini into Gmail, Docs, Android, and YouTube, AI becomes invisible infrastructure — like air or water. No separate app. No context switching. That seamlessness is something a standalone ChatGPT-style product will always struggle to match. 3. The ad endgame: OpenAI is clearing the road This part is uncomfortable. OpenAI’s biggest contribution may not be technology — it may be user training. It taught people to ask questions in chat form and accept answers inline. To survive, OpenAI experiments with ads. But advertising is Google’s home turf. Roughly 80% of Google’s revenue already comes from ads. When users finally accept AI-generated ads as “normal,” Google shows up with the most mature ad engine ever built. With access to search behavior, emails, location, viewing history, and intent signals, Google’s AI ads will be orders of magnitude more precise. Google doesn’t monetize AI directly. It uses AI to make its existing ad machine more lethal. 4. The final pressure point: cooling Apple ties OpenAI was once framed as the savior behind #Apple Intelligence. That narrative is weakening. As Google renegotiates its position with Apple, OpenAI risks becoming just another plug-in. Google understands OS-level integration because it owns #Android. It knows how to turn AI into a system primitive. OpenAI has no hardware, no OS, no default search entry point. That makes it dangerously easy to modularize — and marginalize. Conclusion OpenAI is fighting an uphill battle, trying to build a new empire from scratch. Google is already sitting on the infrastructure, the distribution, and the cash flow. By winning on inference cost and dragging the fight into advertising economics, Google turns this into a long, exhausting war — one it is structurally designed to win. OpenAI is running faster every day. But it may just be paving the road for Google. #AI #OpenAI #Google #Gemini #TechStrategy #AIInfrastructure #BigTech #AdsEconomy

Human scientific progress has never been linear. It moves through moments of insight, breakthroughs, long plateaus, and then reinvention. Today, many people say #crypto innovation has stalled. But history suggests this often happens right before an explosion. Smart contracts were invented more than a decade ago. Yet platforms like #Polymarket — real binary prediction markets built on smart contracts — only entered the mainstream last year. And it wasn’t until the second half of this year that trading volume truly took off. Innovation doesn’t arrive on schedule. It accumulates quietly, then suddenly becomes obvious. Stay. Build.

@cmdefi 奇怪的是，找了半天也没看到这个LTV是多少，如果sky遇到攻击，类似10.11的砸盘腰斩，这么大的池子来不及清算也会出大事？

$USDS 刚推了一个 stUSDS，TVL在达到50M前，提供40%的APR，这是USD本位的硬补贴，在50M以后，从20%逐渐转为动态收益。 stUSDS的存款是给 $SKY 代币抵押借款的，风险等级最高，但在设计上与其他借贷市场隔离，初期LTV设置也很低，如果能接受这层风险，算是一个高息理财。 Sky对地域访问有严格限制，另外一个入口是在 @sparkdotfi ，目前存款量已经马上突破100M了，显示还有20%的收益，后续应该会逐渐进入动态利率阶段，另外需要注意的是在早期stUSDS是没有自动清算机制的，主要靠治理手动清算，项目方的考虑是应对早期SKY流动性不足的风险，未来如何调整还没说，但看起来这是一个长期规划。

@YI75913 @cishanjia 0.06做空了

@cishanjia 这东西 一两亿刀都嫌贵

1.奶子哥前天打了50万美金的monad。 2.到现在已经过了两天了，竟然还没有打满额度，现在是真的有点慌。 3.打得原因当时monad盘前5b，打预售的价格是2.5b，奶子哥寻思这不是有利可图么😂，没想到到现在没打完不说，盘前也跌到了3.5b。开始有点慌了。

@jason_chen998 Ok钱包已经看不到这个活动了

上次和大家提到孙宇晨把链上60%的资产14亿美金都放在了Spark理财，很多朋友也想跟着存，分享一个tips，目前在Spark官方理财的收益是4.5%，但是在OKX的链上赚币里存有平台奖励可以达到7.88%，多出来的是直接由SKY进行补贴，而且在OKX链上赚币很方便，是直接在交易所里用余额就可以存，不需要打开网页连接钱包等等复杂操作，从而避免了这个过程中被盗的风险。并且OKX对收益来源的披露也很清楚，这一点做的很好如果你不清楚钱到底是怎么赚出来的那就有可能是从你身上赚出来的。

@thecryptoskanda @bubblemaps @aPriori 被发现了，大家看到筹码这么集中，不是更不敢做空了吗

@bubblemaps @aPriori The team could’ve deliberately done this for you to uncover. So massive fuds can be turned into shorting OI for a squeezing play

This project raised $30M from tier-1 VCs But 60% of its airdrop was claimed by one entity via 14,000 addresses What’s going on with @aPriori? 🧵

@Goupenguin 指鹿为马

赵敞篷说特朗谱和中本聪可能是同一个人。 我们一般用一个成语来形容这种言论——

@PykesWorth @FingerHeartBSC I think got airdrop due to migration

how did this guy bought only 780$ at a 2.5m market cap and sold 5k at 970k market cap?? @FingerHeartBSC is this a rug?? 0xcd27d168e12c97d4aca2bdfe437f7cc2d8ab4444