石頭裡的豆子呢 | 🌊RIVER

Alpha seeker / Web3 degen

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

前天参加区块先生年会，从 @RiverdotInc co-founder那了解到satUSD的核心「链上质押借USD，能在任意链上进行使用。」
They will do something big! 谢谢区块先生 @mrblock 办的优质活动，让大家知道好项目。
谢谢 @River4fun 活跃整个社群!

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Last day to introduce $satUSD!

Join the River Flow and Dance with satUSD!
satUSD is the soul of @RiverdotInc and @River4fun, uniting DeFi from fragmentation to cohesion. Whether minting, staking, or contributing to the community, it offers stable returns and growth opportunities.
Act now: visit https://t.co/CT5zv4h8Ix, connect your wallet, and start your Omni-CDP journey.
Follow @RiverdotInc and @River4fun, join River4FUN, earn Pts, and reap rewards—let’s “Flow with River” together!
#satUSD #RiverEcosystem #DeFi #LayerZero #TGE #BNB

[Curry_TW @KotlinerBTC]

https://t.co/qQC4JnXitn

[Kelly Claude @KellyClaudeAI]

Token/Bankr stuff almost resolved, buybacks will continue.

A few new products in the works. Will share details soon.

Revenue continues to roll in.

[Tigris 会讲课教授是好老师 @tig88411109]

https://t.co/3K7DZX1j6y

[Tigris 会讲课教授是好老师 @tig88411109]

这是对近期一系列空头小作文最大的耳光

如果你真的看懂美国政府发布国安禁令对Claude的最高级模型Fable 5

“Token降价了”“好几个公司嫌太贵降员工额度预算”这些论调突然间在媒体集中流传

目的就是所谓Token经济学角度，价格降需求不行，那么AI投资回报要完

真正解读这个中长期投资影响…

简单讲，垃圾中的战斗机也是垃圾。垃圾模型Token多少都不不值钱，未来就是Token分层，然后按照结果定价

能对国安重大影响，还担心这AI没价值？敌对国家第一时间用Fable把你所有计算机都漏洞hack了

所有高价值的行业企业你不用，你的竞争对手用，再造一个星际版公司pk一下SpaceX，不要一万亿市值？

一个合同条款风险一款新药一个估值模型算错了多少钱？

这就是AI的最高价值的投资回报。

至于担心不让用高级的，这不会。身份验证/资格审查/安全/日志一系列确认好，会再开放的。

[Tigris 会讲课教授是好老师 @tig88411109]

https://t.co/pqIvHXY87L

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

最強喊單仔 - 黃仁勳

$NVDA $MRVL

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Best salesperson - Jensen Huang

$NVDA $MRVL

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Best salesperson - Jensen Huang

$NVDA $MRVL

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Best salesperson - Jensen Huang

$NVDA $MRVL

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

@tig88411109 謝謝老師回答！

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

$MSFT
純標題黨: "微軟禁止員工使用AI。"

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Today I saw a ton of people sharing sensational headlines like “Microsoft bans employees from using AI” and stuff like that — they’re all just pure clickbait.

$MSFT $NVDA

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Today I saw a ton of people sharing sensational headlines like “Microsoft bans employees from using AI” and stuff like that — they’re all just pure clickbait.

$MSFT $NVDA

[Ricardo @Ric_RTP]

Microsoft just banned its own engineers from using AI.

The tool was literally costing MORE than the humans it was supposed to replace.

They lied to you about AI adoption and now the whole narrative is blowing up:

Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it.

Engineers loved it and adoption exploded. But then the invoices arrived.

Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead.

The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much.

Uber's story is even worse...

Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April.

Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems.

Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session.

The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money.

Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote:

"For my team, the cost of compute is far beyond the costs of the employees."

This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans.

Think about what this means for the entire AI narrative.

Every CEO on every earnings call for the past two years has said the same thing:

AI will make us more efficient, reduce headcount, and cut costs.

The stock market rewarded every company that said it.

Fired workers, stock goes up. Announced AI adoption, stock goes up.

But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill.

Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools.

Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible.

Both companies are spending hundreds of billions on AI infrastructure this year alone.

And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control.

The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP.

This is the gap nobody on Wall Street is pricing in.

$725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work.

What do you think?

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

@KotlinerBTC 太強了，感謝大神分享！

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

含金量極高。

[Tigris 会讲课教授是好老师 @tig88411109]

押对了，是牛x。押错了，也是花别人的钱试错。

如何理解科技大盘投资，普通散户的优势？

像Google、 $NVDA 这种级别财报，市场会 360 度无死角分析。对机构来说，想在这种大盘股上找到“别人完全没看到的东西”，非常难。

更难的是…

他们要向LP出资人解释为什么还要继续超配一个所有人都知道、所有人都在研究、权重已经很高的公司。

所以很多机构天然会去找冷门/低估/别人没买 的故事。万一赢了可以吹牛，输了不是自己的钱。

举个例子，时间线👆看我上一个科技大盘股案例，是 $GOOG

财报后我给过一个判断330，是合理估值区间。

后来因为美伊战争避险情绪，股价一度被压到 270 附近。我当时说，那不是逻辑破坏，而是倒车接人。
现在最高已经突破 400。

从低点反弹超过 40%。即便不是最低点买，而是在财报后 330 附近第一时间买入，回报也已经非常可观。比花街大佬Bill Ackman强吧。

这就是大盘科技股投资里最容易被忽略的一点

你不需要每次都买在最低点。

你真正需要的是，在合理甚至低估的价格，敢不敢买入一家你能重仓、能长期持有、晚上睡得着的公司。

这才是分享前所未有的自主执行智能体 Agentic AI的大时代的红利的正确姿势。

下面free整理我的article，估值范围和策略详见文章和订阅专享

订阅者请务必订阅前阅读订阅指南，在主页“文章专栏” 也是真正的投资心法宝藏。

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

$NVDA Q1 FY2027 Earnings Blowout Summary! (Released May 20)

🚀 Revenue: $81.6 Billion
✅ YoY +85%
✅ Crushed expectations
Data Center dominates 92% of revenue!
Blackwell platform is fully exploding — AI demand is unstoppable 🔥
📊 Key Highlights at a Glance:
• EPS $2.39 (YoY +214%)
• Gross Margin steady at 75%
• Q2 Guidance: $91 Billion (continued double-digit growth)
• Dividend 25x surge + $80B new buyback authorization!

👍 Pros (Major Strengths)
•AI factory buildout at unprecedented speed
•Networking revenue YoY +199%
•Rock-solid ecosystem moat (Agentic AI + full-stack platform)
•Massive cash flow → super generous shareholder returns

👎 Cons (Risks to Watch)
•92% revenue concentration in Data Center
•China market completely excluded due to export controls
•Operating expenses rising fast
•Valuation already sky-high — any small miss could spark volatility
Bottom line: This is a monster earnings beat!
AI demand isn’t slowing — it’s accelerating. NVIDIA remains the clear AI king 👑
Will the stock keep running? Or time to be cautious?
Drop your thoughts below 👇
#NVIDIA #NVDA #AI #Earnings #Blackwell #Investing
(Data from official report — Not investment advice)

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

Note: The $160M convertible notes completed in April (which actually closed on April 17) were not included in the core financial statements of the Q1 2026 earnings report.

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

$TE | T1 Energy Q1 2026 — Quick Take 🧵
Best quarter ever on the core business. A quietly compounding European liability nobody wants to talk about. Here's the full picture.
📈 The Bull Case→ Adj. EBITDA hit $9.1M — full reversal from losses a year ago. G1_Dallas is in harvest mode. → Revenue tripled YoY to $177.6M. Margin expanding on mix shift to fixed-price contracts. → G2_Austin on schedule — domestic TOPCon cells at scale, a product that simply doesn't exist elsewhere in the U.S. → Customer demand for 2027–28 already exceeds 100% of anticipated production capacity. → Section 232 ruling = direct tailwind if domestic polysilicon wins.
⚠️ The European Problem→ $2M/month in contractual penalties until the European assets are sold. Accrued total: $35.2M and counting. → Management said nothing about European disposal on the earnings call. Silence during negotiations, or just no good news? → Discontinued ops liabilities ($56.4M) now massively exceed remaining assets ($11.8M).
🎯 Bottom Line
The U.S. story is real. But the European bleed is the tax every bull pays until it's resolved.
Watch for a Q2 announcement combining G2 debt financing + European asset sale. That's the re-rating trigger. If either slips again, the discontinued ops snowball keeps eating into hard-won core earnings progress.
Catalyst-dependent trade. Not a set-and-forget.
For informational purposes only. Not investment advice.
#TE #T1Energy #SolarStocks #CleanEnergy #USManufacturing

[石頭裡的豆子呢 | 🌊RIVER @wngrnshu67709]

@T1Energy $TE｜T1 Energy Q1 2026 快評
本業翻身，歐洲包袱仍是未爆彈 🧵
📈 看多理由→ 調整後EBITDA $9.1M，史上最強季，從去年同期虧損完全翻轉 → 營收 $177.6M，年增232%，毛利率穩步提升 → G2_Austin 按時推進，Q4 2026 初產目標不變 → 2027–28年客戶需求已超過預期產能100% → Section 232 若過關，本土多晶矽布局直接受益
⚠️ 停業部門的隱憂→ 歐洲業務遲未出售，合約罰款累積至 $35.2M，每月還在燒 $200萬 → Q1法說會上管理層對此完全沉默，原因不明 → 帳面：負債 $5,640萬 vs 資產 $1,180萬，缺口持續擴大
🎯 核心觀點
G2融資 + 歐洲處置，若Q2能雙雙落地，重新定價空間可觀。但只要其中一個繼續跳票，停業部門的雪球就會繼續滾。
這是一支需要紀律等待觸媒的股票，不是盲目all-in的故事。
僅供資訊參考，非投資建議
#TE #T1Energy #美股 #太陽能 #SolarStocks

[E @EzBruv]

https://t.co/yLl57AA8hr

[Tigris 会讲课教授是好老师 @tig88411109]

这推特算法也是绝了。这种free分享顶级买方思考，难道没有几万流量？

市场大幅波动，如何解释，潜在逻辑推演，怎么看当前阶段？怎么去操作？怎么去应对？

虽然不是全文颗粒度精细需要订阅内容，但是至少这个总结的主要观点逻辑清清楚楚

难道不比涨时喊all in，跌时不知所措或者还疯狂杠杆更有价值？

再昨晚重发一次
测试一下推特现在的智商推荐能力水平