manuel

北京上班，想认识更多有趣有意思的人。向往国外的奔放与自由。当然少不了看人妻 露出 野炮。搬运有侵权 -请私信 删

[北京Hot（不接推广 不卖号） @BeijingHotihuo]

三亚母狗第三季 看了一些评论区的留言 母狗说要么就是她玩过的要么就是不着边的意淫 难道三亚就没什么优质会玩的男的吗？喜欢舔屁眼的母狗在这免费给玩都没有接得住的人？ #三亚 #母狗 #轮奸 #内射 #多人 @lvmaoshetuite @lvmaozhijia @nvpusafuliji

[阿泽（牛马版） @wzlululu]

假期快乐～发一个和腰臀比女主的库存叭 ＃女上 ＃后入 ＃腰臀比 ＃北京

[Athu @athuinvests]

I am honestly disappointed with a lot of investors and popular accounts.

They clearly didn't do their homework on $CBRS and were talking absolute rubbish.

Let me clear this out.

1. Insider selling:

The claim that the CEO sold 99.8% of his shares is flat wrong.

Class A is what you and I trade. Class B is what founders hold, and it only converts to Class A when they sell.

So the CEO shows just 17,659 Class A shares but still holds ~13.9M Class B. Did people actually read the second table?

Since the IPO, insiders sold ~$400M, under 1% of the company. About 80% was pre-planned sales of old options bought at $1-8, and the rest came from VC board members and forced tax sales.

Stake each still holds
- CEO Feldman ~98%
- CFO Komin ~97%
- CTO Lie ~87%
- COO Mallick ~50%, the only outlier

The real short-term scare is the lockup, with ~39M shares (~16%) unlocking on Oct 14 and Oct 28.

These are old shares that can now trade, not new ones. That's pressure on the stock, not dilution.

2. $NVDA competition:

People are saying Nvidia just launched OpenAI's "Ultrafast" mode on Blackwell, so Cerebras is done. That's not the whole picture. Every AI chip trades speed against volume.

Nvidia wins on volume. One GPU holds 288GB of memory, so it serves lots of users at once, the cheapest way to run big models for the masses.

The catch with $NVDA is speed. Its memory sits next to the chip, not on it, so every token has to travel back and forth. To go fast anyway, Nvidia runs each GPU with only a few users, which wastes most of the chip. That's why Ultrafast costs 6x the normal price and still tops out around ~300 tokens/sec.

Cerebras wins on speed per user. The whole model sits on the chip, and data moves thousands of times faster (21 PB/s vs ~8 TB/s on a GPU). Cerebras ran OpenAI's Ultrafast at 750 tokens/sec in August, on a smaller model, and the new CS-4 does 4,400+.

The catch with $CBRS is memory and bandwidth. Each wafer holds 44GB, so big models get split across many wafers that talk to each other slowly, about a sixth of one Nvidia GPU.

That's likely part of why the new tier went to Nvidia. But CS-4 links wafers 6x faster per rack, and more memory is coming. And speed is where a lot of the demand is heading, not just scale. AI agents work for one user or one task at a time, and every second they wait is lost work. Companies will happily pay for that.

That's why $AMZN and $AMD pair Cerebras with their own chips instead of replacing it. Theirs reads the question, and Cerebras writes the answer.

3. OpenAI and concentration:

Yes, OpenAI is the biggest customer, with a $20B+ deal through 2028 and about a third of last quarter's revenue.

One launch on Nvidia doesn't cancel a multi-year contract though. And the list is growing with Amazon, AMD, $META, Mistral, Perplexity, Cognition, $CRWD and more.

Wall Street already expects ~$3B of revenue and the first real profit in 2027, then ~$7.5B of revenue and ~$3B of free cash in 2028, with ~60% gross margins long term.

4. The $450M loss:

$377M was stock comp, and $274M of that was a one-time IPO catch-up. It's non-cash, and without it the business lost only ~$7M.

Stock comp keeps engineers from leaving for Nvidia, OpenAI or Google, and should run ~$100M+ per quarter until ~2028. The cost is dilution from new grants, roughly 1-2% a year, not cash.

Where I land:

Long term, Cerebras owns a specific job in the AI stack that gets more valuable as demand for fast AI grows.

I'd love to see more chip sales, since ~61% of revenue is cloud today, plus the memory and bandwidth upgrades.

The risks are real, but none of those break the story.

- OpenAI is most of the backlog today, but it won't stay the only big customer.

- Nvidia could get "fast enough" with the Groq technology it licensed, but the market is too big for just one winner.

- Dilution is real, and the lockup plus Q3 earnings could bring short-term volatility.

Do your homework before you panic.

Not financial advice.

[像素诗人 @xssr_sf]

舞蹈生，身体就是就软、还很听话。
她就那样跪进我双腿之间，先低头把脸埋进去，舌头从后穴慢慢舔到鸡巴，湿、热、一点不急。
舔够了，再自己坐上来。腰一沉，整根吃进去，又深又紧，像是故意要把我绞住。
她换着姿势迎我，每一次坐下都又准又狠，水声和喘息叠在一起。
我忍不住了，掐着她的腰往上一顶，抽出时已经全射了。
她立刻张开嘴，把那些全接进去，唇边还亮着一点白。

【拍了一个多小时兄弟们看���够】

[Shay Boloor @StockSavvyShay]

TOP 5 POSITIONS IN MY GROWTH PORTFOLIO

1. $SITM supplying precision timing chips that keep faster AI networks synchronized
2. $AEHR testing powerful AI chips before they reach deployment
3. $CRDO moving data faster between chips & servers inside AI data centers
4. $RKLB creating a vertically integrated space platform across rockets, satellites, components & defense
5. $FPS delivering customized power equipment faster to get AI data centers online sooner

[𝐀𝐠𝐫𝐢𝐩𝐩𝐚 𝐈𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭𝐬 @Agrippa_Inv]

$BLLN: I think I found my next >20 bagger

Many of you know that I’m a very concentrated investor.

I went very heavy into $HIMS at $6-12 and then shortly thereafter into $IREN sub $5, with an average price of about $7.50.

Today, I’m still pretty much all-in $IREN since I think the stock has yet to reach its full potential, with plenty of gains still to be had.

That said, I’m always on the lookout for my next big “bet,” which prompted me to launch our Radar Report series on Substack and X.

The goal of the series is to explore stocks that are still flying under the radar and figure out whether any of them have a realistic chance of becoming major multibaggers.

The stocks I’ve deep dived on so far as part of the series:

$GROY / $REAX / $PGY / $SLDE / $BLLN

I might end up investing in each one of those in the future given their potential, but the one I’m most excited about is $BLLN, the most recent company we covered in a new Radar Report released yesterday.

There are certain companies that eventually become almost synonymous with the industry they dominate. Electric cars make people think of $TSLA, smartphones of $AAPL, while $NVDA has become the defining name in AI hardware.

I think early cancer detection could eventually have a name attached to it as well, and from everything I have seen so far, BillionToOne has a serious chance of becoming that company.

Before I explain why, this is not one of those biotech moonshots that spends hundreds of millions of dollars every year hoping that one experimental drug eventually makes it through clinical trials.

$BLLN is already a profitable diagnostics company with an established prenatal business, 22 consecutive quarters of revenue growth and another major business in oncology that is still in the early stages of scaling.

The technology behind all of this came from founders Oguzhan Atay and David Tsao, both of whom distinguished themselves at Princeton before pursuing doctoral work at Stanford and Rice. What they eventually built is surprisingly elegant for something that solves such a difficult problem.

Genetic testing requires DNA to be copied before it can be properly analyzed, yet that copying process distorts the original quantities because some fragments get duplicated more than others.

$BLLN figured out a way to measure that distortion and mathematically subtract it afterward, allowing the company to count incredibly small quantities of DNA with a level of precision that conventional methods struggle to achieve.

That sounds more complicated than it actually is in practice, and we break the mechanism down much more clearly in the full report.

In any case, the same basic idea is now being applied across several completely different markets.

$BLLN started in prenatal testing because it offered the quickest route to an established business.

Its UNITY platform can use an ordinary blood draw from the mother to screen the baby for genetic conditions that competing prenatal tests either cannot detect directly or struggle to detect with the same approach, which helped the company build its way to roughly 20% of pregnancies that actually undergo prenatal screening in the US.

The company then took essentially the same technology into oncology, because tumor DNA floating through a cancer patient’s bloodstream presents a very similar problem. The signal is tiny, surrounded by an enormous amount of normal DNA, yet finding and accurately measuring that signal can tell an oncologist which mutations are driving the cancer and whether a treatment is actually working.

The next step is MRD, or minimal residual disease, where $BLLN wants to detect microscopic traces of cancer left behind after surgery before they grow large enough to become visible on a scan. That product is expected to launch around the end of this year and moves the company one step closer to the market I find most interesting of all.

Early cancer detection.

Cancer would be a very different problem if a routine blood test could find a tumor while it was still at stage 1, when it is small, localized and in many cases still removable through surgery. The problem today is that these tumors shed almost no DNA into the bloodstream, while a screening test used on millions of healthy people also needs to avoid false alarms with extraordinary accuracy.

Nobody has properly solved both sides of that equation yet...

There is obviously a lot more to the story than what I’ve laid out here. In the full Radar Report, I go much deeper into the technology, business model, competitive landscape, regulatory environment, risks, valuation and the different markets $BLLN is ultimately trying to attack.

After spending the last few weeks researching the company from pretty much every angle I could think of, I genuinely believe this could become a >$100B company over time. At a market cap of ~$5B today, the potential upside for shareholders is enormous if that thesis proves right.

I’m not personally invested yet, since most of my capital remains concentrated in $IREN and I still think there is a major re-rating ahead there. But once that happens, $BLLN is currently the company I’m most seriously considering for my next major position.

If I eventually make that move, I’ll start covering the company on an ongoing basis, both publicly here on X and in considerably more depth for subscribers.

The full Radar Report, BLLN: Genomic’s Disruptive Dark Horse, is available to all X subscribers and Advanced+ subscribers on Substack.

Links to the full report in the comments below.

Wishing you all a great weekend! ✌️

[0411骚母狗DCM @xiao90610]

我早上拉稀了三次的臭屁眼子，都喷水了，母狗都舔的津津有味，还把舌头伸进屁眼子里猛嗦，还是她自己主动要舔，然后大臭脚昨晚都没洗，她也给我一顿舔，太恶心了，卧槽他妈的！

[Ba @Krismmmmm0571]

舔过我的屁眼现在又会去亲谁的嘴呢
#淫妻 #绿帽 #ntr #红杏 #前任

[唔与 @zhuohahaaiai]

舔的整条鸡巴都苏苏麻麻的，屁眼都给进攻了

[总有吊毛想害朕 @dngyun045937867]

冷知识：其实X上面很多人翻墙都是买的高价会员app。他们压根就不会用机场，不知道ss 不知道clash，甚至不知道全局模式，规则模式。只会买高价会员，然后点一键连接！

[胖虎博主合集 @jingxuanbozhu1]

"明天给我妈说，骚逼被你操烂了"
外表清纯内心却超级反差，嘴上说着舔屁眼太恶心了，舔起来格外认真，真实内心早就沦为一条下贱母狗了，被扒开牛仔裤强势插入，猛操一顿直接骚穴各种喷水，���头和床都被骚货的淫水打湿。

[精液成瘾🙄 @GokkunLover8]

FC2-PPV-4915321 非常色气的骚母狗舔屌毒龙

[CLASSIC HD VIDEOS @classichdvideos]

主动求男友扣逼，还去舔屁眼玩毒龙。全程都让男友使劲扣自己，就连男友都没忍住说她恶心

感谢关注
坚持每天更新好视频

[五道口WUDAOKOU |X联盟 @wdknews]

英国移动 1英镑的电话卡 又可以下单了，无需实名，带���码，带流量，可以接打电话，上网，收发短信

实体卡可以直邮国内，无需转运
esim当天买，当天用
买完可直接写入 xesim使用

永久零月租
收短信免费
可以接打电话，收发短信，上网
可以注册 chatgpt,gemini, claude
落地IP是英国
可以注册访问 各类AI工具

可以注册 monzo uk 拿 50英镑开户奖励
可以注册 yongder bank 免费获得 海外地址证明
可以注册 zopa bank 拿 20英镑 开户奖励

英国移动 1英镑的电话卡，��网直达链接
https://t.co/HzCPk00PuW
付款可以使用，微信，支付宝，applepay, 加密货币

号码可以注册 tiktok,gmail,paypal, telegram ,youtube,whatsapp

外贸可以用，ai可以用
注册交易所，银行，U卡都可以用。

实体卡无需转运，下单后 ，写国内地址
可以收到。
esim 当天买 ，当天就能用
激活可使用 红茶移动 1D卡

详情可查看这里
https://t.co/CQvzYZdisC

其他信息，稍后评论区补全
需要问什么，直接说就行。
英国电话卡，不用实名，可以接打电话，上网，收发短信。

[KK的AI笔记 @ainotes_KK]

中国移动 CMLink 推出了一款英国电话卡，只需要 1 英镑，不需要实名。英国号码，有流量，支持接打电话、收发短信和上网。

而且它是实体卡，可以直接邮寄到国内，不需要转运，也不需要解决 eSIM 设备或小白卡的问题。我买的就是实体卡，如果搞不定 eSIM 设备，推荐大家直接入手实体卡。

这张卡最大的特点非常牛逼：
• 永久 0 月租，免费接收短信
• 可以打电话、上网、收发短信
• 支持注册 ChatGPT、Claude 等海外 AI 工具与软件

需要解决海外手机号注册 AI 问题的朋友可以试一试，既便宜又能完美解决问题

另外还给大家备注一下，购买的这个 1 英镑的费用，也是直接返还到你的手机卡话费里面的，所以相当于是 0 元购

链接：https://t.co/7YNTFK8z2K

[大鸭梨 @0451dayali]

肌肉男内射 拔出JB 精液顺着肥逼流出 终于射出了第二发，后续视频刷锅 ，超近视角

3P刷锅 轮流内射肥B ， 每人两发被榨干 ，和男大学生一起轮流 内射（CUT4）
#3p #刷锅 #男大 #内射 #射精 #情侣单男 #多人轮奸

[黑主调教 @EarpHollie]

这就是你作为女大学生的工作嘛？
这样的反差母狗背着家人，朋友，同学及男朋友过来扮演母狗，
作为母狗过来舔屁眼不是应该的事情嘛

不过这头母狗长的还挺好看，真下贱
#偷情 #反差女大 #调教 #反差 #控制 #母狗

[姜庚 @wheniiileave]

#毒龙 #舔屁眼