海盗鸭

Barron's rare admission of fault: before the IPO, it valued $SPCXB at $90 per share; this time the headline bluntly says, “We were wrong.” What’s changed is the AI. Back then, Wall Street’s expectations for 2027 were $70 billion in sales and $28 billion in EBITDA; now they’re $100 billion and $59 billion. The AI business’s 2027 revenue forecast rose from $38 billion in July to $60 billion, with 2031 AI-related revenue projected at $530 billion, whereas the earliest estimate was only about $150 billion.
Recalculating under Damodaran’s framework: $500 billion in AI revenue in 2036 corresponds to roughly $140 per share; $1 trillion corresponds to about $200. In other words, for every additional $10 billion of annual AI revenue (per $100 billion), discounted to today, it’s worth roughly $10 per share. The current price is about 34x the 2027 forecast EBITDA.
But Barron’s isn’t calling it a buy. Nor has Damodaran changed his own numbers—he says most of the current AI growth comes from renting compute capacity to others, which is effectively building a factory for the largest customer.
So the vote is: $SPCXB is the beginning of an AI revaluation—or just another compute-rental story?

On Polymarket, the odds of the CLARITY Act being “passed” have been cut in half. Many people read the information as: “the bill is doomed.” I think that interpretation is off. What ordinary users should really read from this price curve are three other things.

First, the core variable driving the market’s pricing is time, not outcome. “Passed within the year” and “ultimately passed” represent two completely different risk exposures. When the probability is halved, most of the time it doesn’t mean the bill is dead—it means it “can’t make the deadline.” As the Senate schedule gets crowded, the time value goes to zero, even if the bill itself is still alive and well. Anyone who has bought options understands this: get the direction right but get the timing wrong, and you still lose everything.

Second, the contract price is real money put at stake, but it is also subject to distortions from liquidity. Event markets have limited depth; a few large orders can be enough to smash the price far away from its “true” level. The “odds halved” in a news headline can’t be directly equated with “market consensus shifting.”

Third, for ordinary users like you and me, the actionable takeaway is actually quite simple: any position assumptions that are predicated on “regulatory implementation” are worth stress-testing again. If the bill is delayed by one year, does the narrative you believe in still hold? If it does, then the halved probability is just someone else’s panic. If it doesn’t, then it means you were buying time, not logic—and the responses in the two cases are completely different.

My leaning is this: passage is a high-probability event; time is the biggest uncertainty. So don’t bet on “whether or not” — if you’re going to bet at all, only bet on the tempo.

Which side are you betting on: this year, next year, or forever by one vote off?#Polymarket上CLARITY法案立法几率减半

Reuters reports that SK hynix is in talks with Intel about producing memory chips for the first time on U.S. soil. Intel was up more than 5.8% before the bell, while SK hynix’s shares in South Korea were up more than 3%.

There are two proposed options: one is for SK hynix to lease part of Intel’s Ohio plant, bringing its own equipment for production; the other is a joint venture among Intel, SK hynix, and several cloud companies that want to secure memory supply. Both sides declined to comment. Intel said this is speculation.

For Intel, this would indeed be life-saving revenue—its first two plants in Ohio have already been pushed back to 2030 and 2031. But whether the South Korean government will approve is a variable, as HBM is a “national core technology,” and export review may not be easy to pass.

My take is that this news is more likely to extend Intel’s foundry narrative for a bit longer, rather than truly coming to fruition: making memory in the U.S. would cost more in labor and factory construction than in South Korea. Whether the numbers add up depends on whether major cloud companies use long-term contracts to backstop the deal.

So I’ll ask you this: $INTCB —does this move represent a fundamentals reversal, or another round of sentiment rebound? $SKHYB

According to media reports, IBM$IBMB and NASA have jointly launched a new open-source AI model, continuing to turn satellite remote-sensing data into tools that everyone can use. This collaboration line has actually been running for a few years: from Prithvi-100M to Prithvi-EO-2.0. The model is trained using NASA’s Landsat and Sentinel-2 satellite imagery, and can handle Earth science tasks such as flood mapping, burned-area recognition, and crop classification, all released as open source on Hugging Face. There are two reasons worth paying attention to: first, the open-source strategy means research institutions and small and medium-sized enterprises don’t have to burn compute from scratch, effectively lowering the threshold for climate research; second, for IBM, this is one of the few battlegrounds in its AI narrative where it can offer differentiation—without competing on the parameters of general-purpose large models, it competes on vertical, industry-specific deployment. Will the combination of tech companies and public research institutions’ open-source efforts become the mainstream model for the next phase of AI?

“It’s settled” — these four words are always the most expensive in the interest-rate market. The starting point for this discussion isn’t complicated: at the start of the year, people were still arguing about “how many cuts will happen this year,” and the conversation wobbled all the way to now, with serious debate over “whether to raise rates.” It isn’t about who’s making the loudest call; it’s about price—when the 30-year U.S. Treasury yield broke above 5.40%, the long end used real money to cast a vote of doubt on inflation and fiscal policy. At the same time, Bitcoin fell to $76,000, and risk assets pulled back across the board. These two signals are really two sides of the same coin.

But it’s worth reminding you: in September 2024, the Fed began a rate-cutting cycle. That year it cut three times, bringing rates down to 4.25%-4.50%. Back then, that consensus was also called “settled.” From that “settled” point to today’s debate about “the settled plan to raise rates,” only a few quarters of data separated the two. The rates market is best at drawing sudden turns on what you thought was a straight line.

My view is very clear: the closer you get to consensus expectations, the more you need to stay alert. The real risk has never been “to raise” or “not to raise” itself—it’s what happens when everyone has loaded up to full exposure according to the “settled” narrative, and then the decision deviates from the consensus by even half a step. The stampede will be from the same batch of people. A single change in wording during the press conference can be enough to wipe out leveraged accounts overnight.

So rather than betting on direction, it’s better to do two things first: bring leverage down to a level where you can sleep at night, and price “surprises” as one of the baseline scenarios.

Is your current position built on “it’s settled,” or have you left a way out for “the unexpected”? $BTC #Has it already become settled that the Federal Reserve will raise interest rates?

A piece of news that few people in the industry talk about, but that deserves attention: AWS says that six months after the attack in Iran, it still hasn’t been able to fully restore service to its facilities in Bahrain and the UAE. This past March, two of Amazon’s data centers in the UAE were struck by drones, and another site was also affected by nearby drone attacks. So far, the only two AWS regions in the Middle East have not been able to fully recover. I tend to believe this is a lesson for every team that has put all its “eggs” into a single centralized cloud basket: geopolitics has become part of infrastructure risk, no longer a low-probability black swan. And it’s exactly the hardest scenario for the decentralized storage and DePIN narrative—not as a marketing buzzword, but as a real need for disaster-recovery redundancy. In the past, when discussing the value of decentralized disaster recovery, people always said it was too idealistic—now we have a real case in the Middle East. Has your project done multi-cloud or decentralized backup? $AMZNB

Bitcoin falls to $76,000; longs and shorts have turned the debate into a full-on argument. Strip away the emotions, and the real disagreements come down to three questions.

First: Is this round of decline driven by problems within crypto itself, or by macro factors? The shorts’ answer is confident— the selloff is almost perfectly synchronized with the pullback in tech stocks and the rise in long-end U.S. Treasury yields. Bitcoin, they say, is now a high-beta macro asset; if the interest-rate environment doesn’t turn, any rebound is just a chance to run for safety. The longs counter: precisely because the drop is macro-driven, on-chain fundamentals have not deteriorated—this is a “mispricing,” not a “refutation.”

Second: Is $76,000 a floor or a ceiling? Shorts look at momentum and positioning structure—after a chain of liquidations among leveraged longs, the “buy-the-dip” base is also fragile. Longs look at location and historical scripts—the prior cycle’s peak area, once it breaks and then retests, often becomes support. $76,000 is within the range of this kind of technical narrative.

Third—and I think the most critical question: the stance of ETF flows. Spot ETFs have been the biggest marginal buyers over the past two years. If, during the downturn, they flip into sustained outflows, the longs’ “mis-hits” thesis loses its most important pillar. If inflows merely slow, then in truth the shorts don’t have new ammunition.

My position: among the three questions, I’m temporarily on the shorts’ side—but only halfway. The macro tailwind is indeed gone, but a “crash” requires the confirmation signal that ETFs reverse course and start selling hard. That hasn’t happened yet. So this is a pullback, not the endgame—and the responses are completely different.

Which side are you on? Is a breakdown imminent, or is this just a fake drop to shake out weak hands? $BTC #Bitcoin drops to $76,000

USDC’s cumulative on-chain transaction volume has surpassed $1 trillion, and Circle puts this milestone alongside an “internet-scale settlement network.” The numbers are indeed astonishing, but let’s calmly break it down first: this is a cumulative figure since USDC was issued in September 2018—eight years of total accumulation, which is not the same as annual processing volume. The truly informative part comes from two things.

First is growth. In recent years, stablecoin on-chain settlement volumes have been rising exponentially. The jump to $1 trillion went from “unimaginable” to “announced” within just a few quarters—the slope of the curve matters far more than its height. Two external engines are driving this acceleration: the 2025 stablecoin regulatory legislation taking effect, and Circle’s IPO in June 2025. Regulatory certainty plus support from the capital markets are the twin catalysts.

Second is composition. On-chain transaction volume includes real cross-border settlements and enterprise payments, but it also contains a large amount of “round-tripping” and robot transfers. With the same $1 trillion, how valuable the figure is for “payment infrastructure” ultimately determines whether it’s a moat or a vanity metric. My take: USDC’s moat is not in the transaction volume itself, but in network effects—issuing entity compliance, native deployment on mainstream public chains, and the most comprehensive institutional integrations. The combined conversion costs produced by these three factors are the hard-to-replicate part. Transaction volume is merely the readout of that structure.

For users, the implication is that competition for on-chain dollars is shifting from “who has the biggest volume” to “who gets embedded into real capital flows.” The latter is the real long-term deciding factor. Don’t just watch the milestone announcement—watch the quarter-over-quarter growth rate and changes in the share of transactions that are truly payment-related.

When was the last time you used USDC—for a payment, or for round-tripping? $USDC $CRCLB #USDC on-chain transaction volume surpasses $1 trillion

$BTC ’s technicals are reaching a fork in the road: the rebound at the start of the week never regained the $80,000 level, and on Tuesday it suddenly plunged again to around $75,000. The entire network was liquidated—$674 million in total. Some analysts say the daily chart is forming a rounded top; if the neckline is confirmed to break, the next target would be around $71,000. My view is: this drop looks more like a concentrated liquidation of leverage rather than the end of a trend. Whether the rounded top actually holds up depends on one key point—can the $75,000 area be defended? If it holds, the pattern would end up being a false signal; if it fails, $71,000 is only a matter of time. After the liquidation wave flushes one round of long leverage, resistance to a short-term rebound may be lower—provided that spot buyers are willing to step in. I lean toward the idea that the rounded top will more likely end up as a false signal. This selloff is driven by events rather than a genuine weakening of the broader trend, but on positioning, I’d still favor defense for now. Are you currently on the long side or the short side? $BTC #全网爆仓6.74亿美元

Vitalik again brings the Ethereum and AI circles together. He proposes that the mechanism design used in the crypto world to counter “collusion” might be ported to the field of AI safety: anti-collusion infrastructure in on-chain governance (e.g., MACI) uses private voting, commitment schemes, and multi-party computation to make it difficult for participants to collude and sell out the collective interest. The same idea applied to increasingly autonomous AI agents would structurally increase the cost of coordinating multiple AI systems to do wrongdoing. This isn’t the first time he has crossed domains—from writing “On Collusion” in 2020 to systematically mapping out the paths of the crypto+AI convergence in 2024—he has consistently argued for constraining coordination risks with game theory and cryptography, rather than relying only on regulatory language. In other words: rather than praying that AI will do good, raise the cost of doing evil. The significance for the $ETH ecosystem is that if an economy of AI agents really arrives, blockchains could be its accountability layer and settlement layer. Do you think large-scale AI agents on-chain is narrative or necessity?

A thought-provoking data point: among Meta’s 55 sell-side analysts, the “sell” rating count is zero. Not one or two missing—it’s none at all. The long consensus behind $METAB is fully maxed out, which usually has two interpretations: either the fundamentals are so strong there’s genuinely no disagreement, or the consensus expectations themselves have already become a risk. I lean toward the latter accounting for at least half: when everyone is on the same side of the boat, any quarter where earnings miss expectations—or any quarter where capital expenditures come in higher than expected—could quickly turn the “zero-sell” consensus into fuel for a stampede. And the squeeze on profit margins from AI spending is currently the softest weakness that can be amplified most easily. Of course, Meta’s ad engine is still printing cash—this is the bulls’ confidence, and it’s why 55 analysts dare not collectively call “sell.” History has repeatedly shown that the places where analysts are most in sync bullish are often where disappointment hits hardest. Would you go along with the “zero-sell” consensus, or do you think this is precisely the moment to be cautious?

Apple cuts 147 positions in the Bay Area. The number 147 isn’t large by tech industry standards—other companies lay off thousands or tens of thousands—but when it happens at Apple, it becomes news: this company has long been known for conducting layoffs at very small scale. In previous rounds of economic downturn, it has generally preferred to redeploy internally to absorb redundancies rather than push people out. This is part of Apple’s corporate culture. So when Apple begins officially cutting roles as well, the market naturally asks: is this routine organizational optimization, or the start of a reallocation of resources during the AI transition period? For holders of $AAPLB , the impact of this event on earnings reports may be negligible, but it is a time point worth remembering—when a large company shifts strategy, signs often first appear through personnel changes. Reading personnel moves is often earlier than reading earnings reports. Apple’s AI narrative has been delayed for far too long; now it remains to be seen whether there will be more concrete actions at the organizational level. Do you think this is an isolated incident, or the prelude to broader adjustments?

Anthropic CEO calls for slowing down AI development, and the first response the market received came from a chip company. Broadcom CEO Hock Tan said: Although concerns about models being too powerful continue to heat up, the company’s AI revenue targets have not changed, and demand for AI infrastructure remains strong. The weight of this statement is significant: Broadcom is one of the suppliers of Anthropic’s custom AI chips. Its custom accelerator business is a core engine of its AI revenue. In the last fiscal year, AI-related revenue was about US$12.2 billion, with growth far outpacing the company’s overall performance. There’s another intriguing detail: Anthropic is both the party calling for a slowdown and Broadcom’s customer—worries and orders end up on the same balance sheet. The logic is straightforward: as long as top labs keep expanding their clusters, the “slowdown narrative” will stay at the level of ethical discussions and won’t filter down to orders. Next, attention should be on cloud providers’ capital expenditure data, not slogans. $AVGOB Will the disagreement in the AI narrative ultimately be settled by earnings reports? #AnthropicCEO呼吁放缓AI发展

Samsung jointly led a $230 million funding round for Dutch chip startup Euclyd, with the same round also attended by institutions such as Somerset Capital Partners and the Scaleup Europe Fund. Euclyd’s positioning is very straightforward: it aims to provide computing power alternatives beyond NVIDIA GPUs, betting that after AI demand explodes, the market will not be able to tolerate a single dominant player forever. Even more intriguing is Samsung’s role—it's itself a top upstream giant in the global semiconductor industry. On one hand, it does business within the existing AI chip supply chain; on the other, it puts real money behind a challenger to NVIDIA. Its intent is unmistakably two-pronged. For holders of $NVDAB , this kind of news becomes a long-term valuation variable: when cloud providers and hardware giants are all betting on “de-NVIDIA” alternative routes, the width of the moat must be reassessed. As for the GPU replacement track, the next two years are worth keeping a close watch. How many more years do you think NVIDIA’s monopoly can hold?

$XRP On the ledger, the Batch feature that was missed once is back again: the patched Batch V1.1 is already close to activation. According to XRPL’s mechanism, once the validator node support rate stays above the threshold for two weeks, the amendment will automatically take effect—this time it’s for real. The original vulnerability was quite alarming: a malformed multisig setup could slip through the validation stage, bypassing the requirement for other related accounts’ private keys. In other words, the security of batch transactions was fundamentally broken, so the developers simply tore it down and rewrote it from scratch. This feature is no small matter for XRPL: batch transactions can bundle multiple operations into an atomic execution—either all succeed or none do. The experience for DeFi and multi-step payments will jump to the next level. I tend to approve of this kind of handling: "discover the problem → rewrite it from the ground up → go through voting again." On-chain protocols can be slow, but they can’t go live while sick. Do you think this kind of self-correcting process is something the traditional financial system could learn?

The most counterintuitive thing about DeFi: every deposit and every position in your wallet is exposed to the entire world. The matter of #Zama在以太坊开放16个机密Morpho金库 is specifically targeting this pain point.

Let’s first talk about the mechanism. Zama is a team that came from fully homomorphic encryption (FHE). The core idea behind its product fhEVM is to let smart contracts run directly on ciphertext. In traditional privacy solutions, the ZK approach is: “I prove what I’m saying is true, but you don’t get to see the details.” FHE is more aggressive: the data is never decrypted from start to finish, yet computation still proceeds. Applied to Morpho’s vault architecture, this means your deposit balance, interest rate, and liquidation threshold are all encrypted—yet the protocol can still determine whether a position is approaching the threshold and how much interest to accrue while staying in encrypted form. When audits are needed or when information must be shown to specific parties, selective disclosure is performed using a viewing key. Currently, this batch of confidential vaults is deployed on an FHE co-processor connected to Ethereum ($ETH ) mainnet.

Why is Morpho worth paying attention to in particular? Its vault (MetaMorpho) is one of the most modular lending infrastructures in DeFi—many institutional yield products are, in essence, simply wrapping a Morpho vault layer. Once the confidential version runs smoothly, it means “institution-grade privacy” and “composability” are no longer mutually exclusive. And the fact that positions are fully public is actually one of the main excuses traditional financial institutions have long refused to put on-chain.

I tend to believe the signal from 16 vaults being opened in bulk is more meaningful than the short-term capital impact: it shows that the FHE co-processor has moved from demo stage into a replicable, mass-producible phase. But we should also be clear about one caveat: the bottleneck today isn’t whether data can be encrypted, but the gas cost of encrypted computation and the maturity of audit processes. Whether privacy-focused DeFi’s real TVL can take off is the number worth tracking next year—just the number of vaults alone doesn’t explain much.

If it were you, how much extra gas would you be willing to pay so that others can’t see your positions?

#Zama opens 16 confidential Morpho vaults on Ethereum

Another moment edging toward 5%: The U.S. 10-year Treasury yield is at a 20-month high, steadily moving closer to 5%. The last time it formally closed above 5% was in October 2023, when risk assets were under collective pressure. This current upswing is different: the driver isn’t rate hikes, but rather a surge in Treasury supply under fiscal deficits, rising inflation expectations, and the return of the term premium. At its core, the market is re-pricing national credit. Yields are the gravitational force behind pricing across all assets—each step higher adds another unit of pressure to the denominator of risk assets. The transmission to the crypto market is direct: risk-free returns are nearing 5%, the appeal of holding cash increases, and the opportunity cost of high-beta assets rises—assets like $BTC are hit first. Next, watch the subscription data from Treasury auctions and the Fed’s remarks. Any signals that keep interest rates high for longer will continue to weigh on valuations. In an environment that’s approaching 5%, will you de-lever and wait, or add on dips? #U.S. 10-year Treasury yield nearing 5%

NVIDIA’s CEO connects with Trump, publicly downplays AI risks—this news has a strong political flavor. But what ordinary people should extract from it are three actionable signals, not emotions.

First some context: Huang Renxun’s downplaying of “existential risks of AI” is not the first time. He previously said publicly that truly dangerous general AI is still decades away from reality. For now, the pressing issues are specific problems like bias and misuse. The AI policy backdrop of this White House is also one of looseness: in the early days of taking office, it revoked the prior administration’s AI regulatory executive order, with the emphasis on develop first, govern later. When the CEO calls the president to play down risks, it’s essentially another convergence of industrial capital and policy direction.

For ordinary users, I distill three actions. First, don’t use news like this as a reason to chase higher prices for $NVDAB —policy headwinds and tailwinds have long been priced in. What drives the stock price is the marginal change in data center capital expenditures; watching the capex guidance of hyperscale vendors is far more useful than focusing on the headline. Second, regulatory easing will likely accelerate the diffusion of open-source models. Toolchains keep getting cheaper—this is a concrete benefit that developers and everyday users can directly enjoy, something more tangible than gambling on a single stock. Third, if you hold tech or crypto positions, treat events like this as a source of volatility rather than a trend signal—repeated cycles of policy changes in domestic industry are the norm, so keep your position sizing with room for those repetitions.

My take: I’m not convinced by the “AI risk is still far off” judgment—it feels like an extension of a business position. But on the direction, I also admit that easing does accelerate rollout. These two things don’t conflict—you can be bullish on deployment while not blindly trusting the safety narrative.

Do you think AI should be regulated first for “runaway control,” or first for “misuse”?

#NVIDIA CEO connects with Trump downplays AI risks

Larry Ellison canceled a $7.5 billion Oracle stock sale plan. Insider activity at this level has long been one of the market’s most sensitive signals. Large executive sell-offs are often interpreted as “insiders believe the stock has peaked,” while an active pause is frequently read the other way as “the founder believes the stock is undervalued.” Given that Oracle’s share price has surged over the past two years on AI cloud infrastructure orders, and Ellison’s net worth has grown accordingly, stopping the cash-out at this point—whatever the true reason—would be an emotional positive for ORCLB bulls. In tech stocks, the votes a founder backs with real money are more persuasive than any roadshow. Still, one reminder: insider trading should be used only as reference, not as a basis. In history, there are plenty of examples where the stock price fell even after “insiders didn’t sell,” so don’t treat that as the only anchor. Would you include insider executives’ share increases or decreases in your decision-making?

About $MSTRB city value surpassing Ford, the fiercest clash isn’t really between bulls and bears—it’s between valuation methods. I lay out both sides’ arguments, and then I’ll say which side I’m on.

The critics’ representatives are JPMorgan’s analysts: they believe Strategy’s market-value premium far exceeds the value of the bitcoins it holds, and that there’s a clear bubble component. This criticism holds up mathematically—when mNAV is greater than 1, every share you buy is more expensive by $BTC than if you simply bought the corresponding proportion directly in the market. So what exactly are you buying with the premium? You’re buying Saylor’s ability to keep issuing equity and accumulating, the leverage structure of convertible bonds, and Strategy’s exposure to scarcity within the index and ETF ecosystem.

The supporters’ logic is also strong: as long as the flywheel keeps turning (premium-issued tokens → more accumulation → higher bitcoin per share → premium maintained), the premium becomes self-fulfilling. In 2025, the company demonstrated through its $42 billion “21/21 plan” that its financing machine really can run—its holdings surpassed 600,000 BTC, representing about 3% of the total bitcoin supply. This isn’t a PPT narrative; it’s real inventory.

I tend to think both sides are right, just on different time horizons. In the short term, the premium is driven by liquidity and sentiment, and the volatility bubble critics talk about can happen at any time. In the long term, there’s only one decisive variable—the price trajectory of bitcoin itself. Strategy doesn’t have a second growth curve independent of bitcoin; all of its “operating leverage” comes from that one asset. That makes its fate both simple and brutal.

So my conclusion is: rather than arguing whether there’s a bubble, focus on the premium itself. The premium is this company’s only “product,” and it’s also the most honest emotional indicator—when it approaches 1, it means the market isn’t even willing to pay for the extra value of “trust in Saylor.”

What about you? If you had to choose one between “holding bitcoin directly” and “holding MSTR via the premium,” would you pay that premium? Why?

#Strategy market cap surpasses Ford